Initial.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ad2b37d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "import codecs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "f3c2d832",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_rows', 500)\n",
    "pd.set_option('display.max_columns', 30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "32ab821c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9a889e5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as mlp\n",
    "\n",
    "plt.style.use('dark_background')\n",
    "\n",
    "mlp.rcParams['lines.linewidth'] = 2\n",
    "\n",
    "mlp.rcParams['xtick.major.size'] = 15\n",
    "mlp.rcParams['xtick.major.width'] = 2\n",
    "mlp.rcParams['xtick.labelsize'] = 15\n",
    "mlp.rcParams['xtick.color'] = '#4DFC2D'\n",
    "\n",
    "mlp.rcParams['ytick.major.size'] = 15\n",
    "mlp.rcParams['ytick.major.width'] = 2\n",
    "mlp.rcParams['ytick.labelsize'] = 15\n",
    "mlp.rcParams['ytick.color'] = '#4DFC2D'\n",
    "\n",
    "mlp.rcParams['axes.labelsize'] = 20\n",
    "mlp.rcParams['axes.titlesize'] = 20\n",
    "mlp.rcParams['axes.titlecolor'] = '#ED6919'\n",
    "mlp.rcParams['axes.labelcolor'] = '#ED6919'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2633e798",
   "metadata": {},
   "source": [
    "<!-- # df = pd.read_excel('../descr/descriptions/description.xlsx')\n",
    "\n",
    "# df.head() -->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "089fe674",
   "metadata": {},
   "outputs": [],
   "source": [
    "def column_to_snake_case(name):\n",
    "    return name.lower().replace(' ', '_')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f824d768",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>ушная_бирка_животного</th>\n",
       "      <th>номер_матери</th>\n",
       "      <th>код_отца</th>\n",
       "      <th>отец_матери</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>570034283</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>533487712</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>897733157</td>\n",
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       "      <td>-</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>584322510</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>887578050</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
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      ],
      "text/plain": [
       "  номер_животного ушная_бирка_животного  номер_матери    код_отца отец_матери\n",
       "0               1             570034283           0.0  -           -         \n",
       "1               2             533487712           0.0  -           -         \n",
       "2               3             897733157           0.0  -           -         \n",
       "3               4             584322510           0.0  -           -         \n",
       "4               6             887578050           0.0  -           -         "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f = codecs.open('../data/Предки.csv', 'r', 'cp1251')\n",
    "ancestors = pd.read_csv(f, sep=';', encoding='utf-8')\n",
    "\n",
    "ancestors.columns = pd.Series(ancestors.columns).apply(column_to_snake_case)\n",
    "\n",
    "ancestors.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c0f0fbd8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25499, 5)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ancestors.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f257a05a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "номер_животного          0\n",
       "ушная_бирка_животного    1\n",
       "номер_матери             1\n",
       "код_отца                 1\n",
       "отец_матери              1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ancestors.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6937a9f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>ушная_бирка_животного</th>\n",
       "      <th>номер_матери</th>\n",
       "      <th>код_отца</th>\n",
       "      <th>отец_матери</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>25494</th>\n",
       "      <td>912270</td>\n",
       "      <td>912270</td>\n",
       "      <td>612166.0</td>\n",
       "      <td>777H10771</td>\n",
       "      <td>STEVIE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25495</th>\n",
       "      <td>912271</td>\n",
       "      <td>912271</td>\n",
       "      <td>407078.0</td>\n",
       "      <td>1H11917</td>\n",
       "      <td>ICEMAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25496</th>\n",
       "      <td>912272</td>\n",
       "      <td>912272</td>\n",
       "      <td>803014.0</td>\n",
       "      <td>777H10574</td>\n",
       "      <td>29H16387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25497</th>\n",
       "      <td>912273</td>\n",
       "      <td>912273</td>\n",
       "      <td>803140.0</td>\n",
       "      <td>777H10690</td>\n",
       "      <td>777H10473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25498</th>\n",
       "      <td>Итого:25498</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      номер_животного ушная_бирка_животного  номер_матери    код_отца  \\\n",
       "25494          912270                912270      612166.0  777H10771    \n",
       "25495          912271                912271      407078.0  1H11917      \n",
       "25496          912272                912272      803014.0  777H10574    \n",
       "25497          912273                912273      803140.0  777H10690    \n",
       "25498     Итого:25498                   NaN           NaN         NaN   \n",
       "\n",
       "      отец_матери  \n",
       "25494  STEVIE      \n",
       "25495  ICEMAN      \n",
       "25496  29H16387    \n",
       "25497  777H10473   \n",
       "25498         NaN  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ancestors.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a11f89e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ancestors = ancestors.iloc[:-1]\n",
    "\n",
    "ancestors.isna().sum().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "464ee1e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-             3229\n",
       "1H13456        849\n",
       "777H10915      840\n",
       "ICEMAN         716\n",
       "1H15057        709\n",
       "501H15000      628\n",
       "EDEN           571\n",
       "1H11673        561\n",
       "YUENGLIN       540\n",
       "LOVEBOAT       539\n",
       "777H10778      522\n",
       "1H11978        514\n",
       "SAMPSON        475\n",
       "KAMPMAN        469\n",
       "501H15074      444\n",
       "1H12902        441\n",
       "777H10690      392\n",
       "777H11079      391\n",
       "1H11913        390\n",
       "CLAYK          377\n",
       "1H12490        347\n",
       "ALMOND         346\n",
       "PILOT          345\n",
       "COUNTRY        317\n",
       "STEVIE         310\n",
       "1H11917        303\n",
       "TOUCH          301\n",
       "1H14138        297\n",
       "200H528        297\n",
       "TAK            295\n",
       "501H14018      288\n",
       "777H10574      272\n",
       "BALANCE        270\n",
       "INDY           268\n",
       "200H10181      257\n",
       "1H15184        242\n",
       "777H10771      224\n",
       "777H10777      198\n",
       "1H15185        193\n",
       "DISTANCE       192\n",
       "BUILDER        189\n",
       "200H10021      183\n",
       "1H11372        179\n",
       "1H15132        179\n",
       "DONNIE         167\n",
       "1H13162        159\n",
       "1H13878        154\n",
       "ROXETTE        145\n",
       "200H10233      142\n",
       "777H11243      140\n",
       "1H11344        139\n",
       "FLYNS          137\n",
       "29H16387       133\n",
       "SHATL          132\n",
       "29H18091       127\n",
       "EDENS          126\n",
       "1H13411        126\n",
       "200H3859       126\n",
       "200H10591      123\n",
       "1H13471        122\n",
       "29H16384       116\n",
       "777H10755      112\n",
       "200H10686      112\n",
       "AMSTRNGS       108\n",
       "777H10376      107\n",
       "FLOLESS        104\n",
       "LOTTIE         102\n",
       "777H10473      100\n",
       "FIGHTER        100\n",
       "FEIM            96\n",
       "CHAPEL          96\n",
       "200H10446       95\n",
       "LARIATS         95\n",
       "777H10532       91\n",
       "OSOFINE         90\n",
       "DEKART          86\n",
       "GILLETTE        82\n",
       "DOWRY           82\n",
       "WYN             81\n",
       "PADLOCK         81\n",
       "29H16650        80\n",
       "777H6540        80\n",
       "ANSVER          77\n",
       "501H12658       75\n",
       "777H10649       68\n",
       "EMERALDS        60\n",
       "777H10787       59\n",
       "CALGARY         57\n",
       "777H528         49\n",
       "200H10533       48\n",
       "ESQUIRE         47\n",
       "777H10622       43\n",
       "ALABAMA         43\n",
       "GALAXY          42\n",
       "TRINITY         42\n",
       "PLUTON          40\n",
       "DOLMAN          35\n",
       "TOMAH           32\n",
       "29H18019        30\n",
       "BALANS          30\n",
       "LOCKLYN         28\n",
       "11H11531        27\n",
       "11H11718        26\n",
       "MONTREAL        21\n",
       "OSOFINES        20\n",
       "CHAPELS         19\n",
       "HOLDING         19\n",
       "EMERALD         18\n",
       "CHARMAN         18\n",
       "TREIDER         18\n",
       "LEWELLYN        18\n",
       "11H11298        17\n",
       "200H10861       16\n",
       "4MOCT           15\n",
       "NETWORT         15\n",
       "200H10690       12\n",
       "777H10225       12\n",
       "777H10314       12\n",
       "501H15132       11\n",
       "NETWORTH        11\n",
       "GRAYTON          9\n",
       "11H11591         8\n",
       "BRIAR            8\n",
       "RELANT           8\n",
       "NATWORT          5\n",
       "BULL             5\n",
       "REMOTE           4\n",
       "FORTUNA          4\n",
       "LAURIN           4\n",
       "ERIC             3\n",
       "DELKAMPO         3\n",
       "BONJOVI          3\n",
       "KLEIK            2\n",
       "LAMANSCH         2\n",
       "BOJAK            2\n",
       "MODEL            2\n",
       "11H11461         2\n",
       "11H11648         2\n",
       "WORMONT          2\n",
       "ROSS             2\n",
       "LADDY            1\n",
       "SCHKODA          1\n",
       "ALFA             1\n",
       "TYSON            1\n",
       "11H11694         1\n",
       "Name: код_отца, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ancestors.код_отца.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "df8e878c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-             9734\n",
       "ICEMAN         988\n",
       "EDEN           661\n",
       "YUENGLIN       643\n",
       "777H10778      530\n",
       "KAMPMAN        515\n",
       "SAMPSON        503\n",
       "LOVEBOAT       486\n",
       "ALMOND         376\n",
       "PILOT          368\n",
       "777H10690      357\n",
       "COUNTRY        346\n",
       "STEVIE         292\n",
       "777H10574      269\n",
       "TAK            266\n",
       "1H11978        250\n",
       "BALANCE        247\n",
       "777H10771      246\n",
       "200H528        240\n",
       "FLYNS          240\n",
       "INDY           238\n",
       "DISTANCE       233\n",
       "TOUCH          232\n",
       "BUILDER        228\n",
       "CLAYK          225\n",
       "777H10376      200\n",
       "1H11673        194\n",
       "777H10777      192\n",
       "EDENS          191\n",
       "FLOLESS        187\n",
       "200H10181      180\n",
       "777H10473      179\n",
       "AMSTRNGS       177\n",
       "777H10915      164\n",
       "777H10755      159\n",
       "DONNIE         155\n",
       "777H6540       148\n",
       "LARIATS        144\n",
       "777H10532      139\n",
       "200H10021      136\n",
       "29H18091       127\n",
       "1H12902        124\n",
       "1H11917        123\n",
       "CHAPEL         122\n",
       "FIGHTER        120\n",
       "EMERALDS       111\n",
       "OSOFINE        109\n",
       "1H12490        108\n",
       "29H16387       103\n",
       "501H12658      103\n",
       "200H10233      102\n",
       "ROXETTE        100\n",
       "DOWRY           97\n",
       "200H3859        97\n",
       "777H10649       96\n",
       "777H11079       95\n",
       "29H16384        94\n",
       "LOTTIE          94\n",
       "1H13162         92\n",
       "SHATL           91\n",
       "PADLOCK         89\n",
       "777H10787       88\n",
       "200H10446       85\n",
       "WYN             84\n",
       "777H528         84\n",
       "GILLETTE        82\n",
       "200H10591       76\n",
       "DEKART          72\n",
       "29H16650        71\n",
       "1H11344         69\n",
       "200H10686       65\n",
       "777H10622       62\n",
       "DOLMAN          58\n",
       "ALABAMA         56\n",
       "GALAXY          56\n",
       "ESQUIRE         47\n",
       "OSOFINES        47\n",
       "4MOCT           47\n",
       "200H10533       45\n",
       "CALGARY         43\n",
       "CHARMAN         42\n",
       "1H11372         39\n",
       "CHAPELS         38\n",
       "TRINITY         35\n",
       "777H11243       34\n",
       "11H11531        31\n",
       "BALANS          31\n",
       "29H18019        30\n",
       "RELANT          29\n",
       "LOCKLYN         27\n",
       "EMERALD         26\n",
       "200H10861       26\n",
       "TOMAH           23\n",
       "GRAYTON         21\n",
       "TREIDER         20\n",
       "11H11718        19\n",
       "BRIAR           19\n",
       "777H10314       18\n",
       "HOLDING         18\n",
       "200H10690       18\n",
       "NATWORT         17\n",
       "11H11298        16\n",
       "PLUTON          16\n",
       "777H10225       15\n",
       "LEWELLYN        15\n",
       "NETWORT         13\n",
       "11H11591        13\n",
       "NETWORTH        13\n",
       "MONTREAL        12\n",
       "LAURIN          11\n",
       "LAMANSCH         9\n",
       "BONJOVI          7\n",
       "11H11233         7\n",
       "REMOTE           6\n",
       "1H13471          6\n",
       "ROSS             5\n",
       "KLEIK            5\n",
       "BOJAK            5\n",
       "LADDY            5\n",
       "BULL             4\n",
       "ERIC             4\n",
       "FORTUNA          4\n",
       "11H11648         4\n",
       "MODEL            4\n",
       "11H11450         4\n",
       "11H11461         4\n",
       "KALGARI          3\n",
       "CYCLER           3\n",
       "11H11114         3\n",
       "11H11302         3\n",
       "11H10930         2\n",
       "11H11201         2\n",
       "WORMONT          2\n",
       "REGENT           2\n",
       "TYSON            2\n",
       "DELKAMPO         2\n",
       "11H11694         2\n",
       "1H11913          2\n",
       "ALFA             2\n",
       "11H11331         1\n",
       "11H10316         1\n",
       "11H9508          1\n",
       "11H10846         1\n",
       "11H10660         1\n",
       "11H10676         1\n",
       "11H11087         1\n",
       "11H11419         1\n",
       "Name: отец_матери, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ancestors.отец_матери.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e4dc7094",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>ушная_бирка_животного</th>\n",
       "      <th>пол</th>\n",
       "      <th>номер_лактации</th>\n",
       "      <th>результат_отела</th>\n",
       "      <th>легкость_отела</th>\n",
       "      <th>дата_рождения</th>\n",
       "      <th>дней_в_сухостое_предыдущей_лактации</th>\n",
       "      <th>дней_стельности_при_событии</th>\n",
       "      <th>номер_группы_животного</th>\n",
       "      <th>предыдущий_номер_группы_животного</th>\n",
       "      <th>событие</th>\n",
       "      <th>дни_доения_при_событии</th>\n",
       "      <th>дата_события</th>\n",
       "      <th>примечание_события</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>146</td>\n",
       "      <td>598621616</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>29.03.2010</td>\n",
       "      <td>62</td>\n",
       "      <td>277</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>РАСЧКОП</td>\n",
       "      <td>336</td>\n",
       "      <td>28.03.2019</td>\n",
       "      <td>КАН</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>146</td>\n",
       "      <td>598621616</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>29.03.2010</td>\n",
       "      <td>62</td>\n",
       "      <td>277</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>349</td>\n",
       "      <td>10.04.2019</td>\n",
       "      <td>КОГЛАВАК</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>146</td>\n",
       "      <td>598621616</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>29.03.2010</td>\n",
       "      <td>62</td>\n",
       "      <td>277</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>349</td>\n",
       "      <td>10.04.2019</td>\n",
       "      <td>ЛЕПТО</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>291</td>\n",
       "      <td>530073354</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>30.07.2009</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>448</td>\n",
       "      <td>08.04.2019</td>\n",
       "      <td>F001T023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>291</td>\n",
       "      <td>530073354</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>30.07.2009</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>ПРОДАНА</td>\n",
       "      <td>458</td>\n",
       "      <td>18.04.2019</td>\n",
       "      <td>ПРОДАНА ; Прочее ; УВЗ8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   номер_животного ушная_бирка_животного пол  номер_лактации результат_отела  \\\n",
       "0              146             598621616   F               6              FA   \n",
       "1              146             598621616   F               6              FA   \n",
       "2              146             598621616   F               6              FA   \n",
       "3              291             530073354   F               6              MA   \n",
       "4              291             530073354   F               6              MA   \n",
       "\n",
       "   легкость_отела дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "0               1    29.03.2010                                   62   \n",
       "1               1    29.03.2010                                   62   \n",
       "2               1    29.03.2010                                   62   \n",
       "3               1    30.07.2009                                   68   \n",
       "4               1    30.07.2009                                   68   \n",
       "\n",
       "   дней_стельности_при_событии  номер_группы_животного  \\\n",
       "0                          277                      18   \n",
       "1                          277                      18   \n",
       "2                          277                      18   \n",
       "3                            0                      23   \n",
       "4                            0                      23   \n",
       "\n",
       "   предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "0                                 18  РАСЧКОП                     336   \n",
       "1                                 18   ВАКЦИН                     349   \n",
       "2                                 18   ВАКЦИН                     349   \n",
       "3                                 23  ПЕРЕВОД                     448   \n",
       "4                                 23  ПРОДАНА                     458   \n",
       "\n",
       "  дата_события       примечание_события  \n",
       "0   28.03.2019                      КАН  \n",
       "1   10.04.2019                 КОГЛАВАК  \n",
       "2   10.04.2019                    ЛЕПТО  \n",
       "3   08.04.2019                 F001T023  \n",
       "4   18.04.2019  ПРОДАНА ; Прочее ; УВЗ8  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert .csv from Win-1251 to utf-8\n",
    "f = codecs.open('../data/dump_19_22.csv', 'r', 'cp1251')\n",
    "df = pd.read_csv(f, sep=';', encoding='utf-8')\n",
    "\n",
    "df.columns = pd.Series(df.columns).apply(lambda x: x.lower().replace(' ', '_'))\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "67001e4a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "номер_животного                         int64\n",
       "ушная_бирка_животного                  object\n",
       "пол                                    object\n",
       "номер_лактации                          int64\n",
       "результат_отела                        object\n",
       "легкость_отела                          int64\n",
       "дата_рождения                          object\n",
       "дней_в_сухостое_предыдущей_лактации     int64\n",
       "дней_стельности_при_событии             int64\n",
       "номер_группы_животного                  int64\n",
       "предыдущий_номер_группы_животного       int64\n",
       "событие                                object\n",
       "дни_доения_при_событии                  int64\n",
       "дата_события                           object\n",
       "примечание_события                     object\n",
       "dtype: object"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "32e341cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "df.дата_рождения = df.дата_рождения.apply(lambda x: datetime.strptime(x,\"%d.%m.%Y\"))\n",
    "df.дата_события = df.дата_события.apply(lambda x: datetime.strptime(x,\"%d.%m.%Y\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e35ae588",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "номер_животного                                 int64\n",
       "ушная_бирка_животного                          object\n",
       "пол                                            object\n",
       "номер_лактации                                  int64\n",
       "результат_отела                                object\n",
       "легкость_отела                                  int64\n",
       "дата_рождения                          datetime64[ns]\n",
       "дней_в_сухостое_предыдущей_лактации             int64\n",
       "дней_стельности_при_событии                     int64\n",
       "номер_группы_животного                          int64\n",
       "предыдущий_номер_группы_животного               int64\n",
       "событие                                        object\n",
       "дни_доения_при_событии                          int64\n",
       "дата_события                           datetime64[ns]\n",
       "примечание_события                             object\n",
       "dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "761b1f98",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15322"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.номер_животного.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "dad9564f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "номер_животного                             0\n",
       "ушная_бирка_животного                       0\n",
       "пол                                         0\n",
       "номер_лактации                              0\n",
       "результат_отела                        260950\n",
       "легкость_отела                              0\n",
       "дата_рождения                               0\n",
       "дней_в_сухостое_предыдущей_лактации         0\n",
       "дней_стельности_при_событии                 0\n",
       "номер_группы_животного                      0\n",
       "предыдущий_номер_группы_животного           0\n",
       "событие                                     0\n",
       "дни_доения_при_событии                      0\n",
       "дата_события                                0\n",
       "примечание_события                          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "34f86466",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "FA      206135\n",
       "MA       97163\n",
       "FD       12018\n",
       "MD        9822\n",
       "MAMA      3505\n",
       "FAFA      1811\n",
       "FDMD       217\n",
       "FAFD       177\n",
       "FDFD       127\n",
       "MAFD       117\n",
       "MAMD       116\n",
       "FDFA        74\n",
       "MDMD        67\n",
       "FDMA         8\n",
       "Name: результат_отела, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.результат_отела.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c256eac7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    564740\n",
       "0     22251\n",
       "2      5316\n",
       "Name: живых_потомков, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Попробуем заменить разреженную колонку с результатом отела на количество живых потомков \n",
    "from collections import Counter\n",
    "\n",
    "df.результат_отела = df.результат_отела.fillna(\n",
    "        df.результат_отела.value_counts().index[0]\n",
    ")\n",
    "\n",
    "df['живых_потомков'] = df.результат_отела.apply(lambda x: Counter(x)['A'])\n",
    "\n",
    "df.живых_потомков.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d59e7367",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16, 8))\n",
    "\n",
    "fig.add_subplot(1, 2, 1)\n",
    "sns.countplot(y=df.результат_отела)\n",
    "plt.xticks(rotation=45)\n",
    "\n",
    "fig.add_subplot(1, 2, 2)\n",
    "sns.countplot(y=df.живых_потомков)\n",
    "plt.xticks(rotation=45)\n",
    "\n",
    "\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "4b9946fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d0051da9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>номер_лактации</th>\n",
       "      <th>легкость_отела</th>\n",
       "      <th>дней_в_сухостое_предыдущей_лактации</th>\n",
       "      <th>дней_стельности_при_событии</th>\n",
       "      <th>номер_группы_животного</th>\n",
       "      <th>предыдущий_номер_группы_животного</th>\n",
       "      <th>дни_доения_при_событии</th>\n",
       "      <th>живых_потомков</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>592307.000000</td>\n",
       "      <td>592307.000000</td>\n",
       "      <td>592307.000000</td>\n",
       "      <td>592307.000000</td>\n",
       "      <td>592307.000000</td>\n",
       "      <td>592307.000000</td>\n",
       "      <td>592307.000000</td>\n",
       "      <td>592307.000000</td>\n",
       "      <td>592307.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>561959.241464</td>\n",
       "      <td>1.128155</td>\n",
       "      <td>0.734476</td>\n",
       "      <td>19.105364</td>\n",
       "      <td>84.225510</td>\n",
       "      <td>19.055809</td>\n",
       "      <td>18.280589</td>\n",
       "      <td>209.465411</td>\n",
       "      <td>0.971408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>350585.858440</td>\n",
       "      <td>1.331666</td>\n",
       "      <td>0.729751</td>\n",
       "      <td>28.571645</td>\n",
       "      <td>105.591151</td>\n",
       "      <td>12.715732</td>\n",
       "      <td>13.531659</td>\n",
       "      <td>185.204920</td>\n",
       "      <td>0.213833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>142.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>23144.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>707166.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>163.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>812077.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>171.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>339.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>912273.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>192.000000</td>\n",
       "      <td>327.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>1430.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       номер_животного  номер_лактации  легкость_отела  \\\n",
       "count    592307.000000   592307.000000   592307.000000   \n",
       "mean     561959.241464        1.128155        0.734476   \n",
       "std      350585.858440        1.331666        0.729751   \n",
       "min         142.000000        0.000000        0.000000   \n",
       "25%       23144.000000        0.000000        0.000000   \n",
       "50%      707166.000000        1.000000        1.000000   \n",
       "75%      812077.000000        2.000000        1.000000   \n",
       "max      912273.000000        8.000000        5.000000   \n",
       "\n",
       "       дней_в_сухостое_предыдущей_лактации  дней_стельности_при_событии  \\\n",
       "count                        592307.000000                592307.000000   \n",
       "mean                             19.105364                    84.225510   \n",
       "std                              28.571645                   105.591151   \n",
       "min                               0.000000                     0.000000   \n",
       "25%                               0.000000                     0.000000   \n",
       "50%                               0.000000                     0.000000   \n",
       "75%                              56.000000                   171.000000   \n",
       "max                             192.000000                   327.000000   \n",
       "\n",
       "       номер_группы_животного  предыдущий_номер_группы_животного  \\\n",
       "count           592307.000000                      592307.000000   \n",
       "mean                19.055809                          18.280589   \n",
       "std                 12.715732                          13.531659   \n",
       "min                  0.000000                           0.000000   \n",
       "25%                  8.000000                           6.000000   \n",
       "50%                 18.000000                          17.000000   \n",
       "75%                 30.000000                          30.000000   \n",
       "max                 50.000000                          50.000000   \n",
       "\n",
       "       дни_доения_при_событии  живых_потомков  \n",
       "count           592307.000000   592307.000000  \n",
       "mean               209.465411        0.971408  \n",
       "std                185.204920        0.213833  \n",
       "min                  0.000000        0.000000  \n",
       "25%                 52.000000        1.000000  \n",
       "50%                163.000000        1.000000  \n",
       "75%                339.000000        1.000000  \n",
       "max               1430.000000        2.000000  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d291ccab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['РАСЧКОП', 'ВАКЦИН', 'ПЕРЕВОД', 'ПРОДАНА', 'МАСТИТ', 'ЗДОРОВА',\n",
       "       'ХРОМОТА', 'СУХОСТ', 'ВАКВИРУС', 'ЯЛОВАЯ', 'ОСЕМЕН', 'БОЛЕЗНЬ',\n",
       "       'НЕОСЕМ', 'СТЕЛН', 'ПРОФОТ', 'ОТЕЛ', 'ПАРЕЗ', 'МЕТРИТ', 'КЕТОЗ',\n",
       "       'ПОСЛЕД', 'ПАЛА', 'АБОРТ', 'ВЕС', 'СТЕЛНДО', 'НА_СХЕМУ',\n",
       "       'СО_СХЕМЫ', 'SOLD', 'WEIGHT', 'METR', 'DRY', 'MOVE', 'FOOTRIM',\n",
       "       'WELL', 'POT', 'ILLMISC', 'MAST', 'BRED', 'LAME', 'RP', 'FRESH',\n",
       "       'OPEN', 'DNB', 'NULSCM', 'ABORT', 'ДЕФЕКТ', 'СУХ2', 'TOSCM',\n",
       "       'KETOS'], dtype=object)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.событие.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "56dab649",
   "metadata": {},
   "outputs": [],
   "source": [
    "dict_transl = {\n",
    "    \"ABORT\": \"АБОРТ\",\n",
    "    \"BRED\": \"ОСЕМЕН\",\n",
    "    \"DNB\": \"НЕОСЕМ\",\n",
    "    \"DRY\": \"СУХОСТ\",\n",
    "    \"FOOTRIM\": \"РАСЧКОП\",\n",
    "    \"FRESH\": \"ОТЕЛ\",\n",
    "    \"ILLMISC\": \"БОЛЕЗНЬ\",\n",
    "    \"KETOS\": \"КЕТОЗ\",\n",
    "    \"LAME\": \"ХРОМОТА\",\n",
    "    \"MAST\": \"МАСТИТ\",\n",
    "    \"METR\": \"МЕТРИТ\",\n",
    "    \"MOVE\": \"ПЕРЕВОД\",\n",
    "    \"NULSCM\": \"СО_СХЕМЫ\",\n",
    "    \"OPEN\": \"ЯЛОВАЯ\",\n",
    "    \"POT\": \"ПРОФОТ\",\n",
    "    \"RP\": \"ПОСЛЕД\",\n",
    "    \"SOLD\": \"ПРОДАНА\",\n",
    "    \"TOSCM\": \"НА_СХЕМУ\",\n",
    "    \"WEIGHT\": \"ВЕС\",\n",
    "    \"WELL\": \"ЗДОРОВА\"\n",
    "}\n",
    "\n",
    "def convert_event(event):\n",
    "    if event in dict_transl:\n",
    "        return dict_transl[event]\n",
    "    return event"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "2e93ccb9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ВАКЦИН      122450\n",
       "ПЕРЕВОД     114399\n",
       "ВЕС          79855\n",
       "ВАКВИРУС     32081\n",
       "НА_СХЕМУ     32040\n",
       "СТЕЛН        31982\n",
       "РАСЧКОП      31215\n",
       "ОСЕМЕН       28497\n",
       "ЗДОРОВА      25375\n",
       "ХРОМОТА      11826\n",
       "ОТЕЛ         11292\n",
       "ЯЛОВАЯ       10862\n",
       "БОЛЕЗНЬ       9813\n",
       "ПРОФОТ        8728\n",
       "ПРОДАНА       8705\n",
       "МАСТИТ        8368\n",
       "СУХОСТ        6908\n",
       "МЕТРИТ        6447\n",
       "СУХ2          3503\n",
       "НЕОСЕМ        2322\n",
       "ПОСЛЕД        1585\n",
       "КЕТОЗ         1494\n",
       "АБОРТ         1343\n",
       "ПАЛА           776\n",
       "ПАРЕЗ          227\n",
       "СО_СХЕМЫ       147\n",
       "ДЕФЕКТ          34\n",
       "СТЕЛНДО         33\n",
       "Name: событие, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.событие = df.событие.apply(convert_event)\n",
    "\n",
    "df.событие.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a630f274",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(225621, 16) 2767\n"
     ]
    }
   ],
   "source": [
    "# Будем работать только с маститом\n",
    "mast_ind = df[df.событие == 'МАСТИТ'].номер_животного.unique()\n",
    "\n",
    "df = df[df.номер_животного.isin(mast_ind)]\n",
    "\n",
    "print(df.shape, df.номер_животного.nunique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "8bc9c6f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>ушная_бирка_животного</th>\n",
       "      <th>пол</th>\n",
       "      <th>номер_лактации</th>\n",
       "      <th>результат_отела</th>\n",
       "      <th>легкость_отела</th>\n",
       "      <th>дата_рождения</th>\n",
       "      <th>дней_в_сухостое_предыдущей_лактации</th>\n",
       "      <th>дней_стельности_при_событии</th>\n",
       "      <th>номер_группы_животного</th>\n",
       "      <th>предыдущий_номер_группы_животного</th>\n",
       "      <th>событие</th>\n",
       "      <th>дни_доения_при_событии</th>\n",
       "      <th>дата_события</th>\n",
       "      <th>примечание_события</th>\n",
       "      <th>живых_потомков</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>321</td>\n",
       "      <td>896820302</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>213</td>\n",
       "      <td>2019-03-15</td>\n",
       "      <td>МВ</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>321</td>\n",
       "      <td>896820302</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>215</td>\n",
       "      <td>2019-03-17</td>\n",
       "      <td>ТМ6_34</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>321</td>\n",
       "      <td>896820302</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>216</td>\n",
       "      <td>2019-03-18</td>\n",
       "      <td>F006T003</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>321</td>\n",
       "      <td>896820302</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>221</td>\n",
       "      <td>2019-03-23</td>\n",
       "      <td>КМ4_134</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>321</td>\n",
       "      <td>896820302</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ЗДОРОВА</td>\n",
       "      <td>230</td>\n",
       "      <td>2019-04-01</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592273</th>\n",
       "      <td>912242</td>\n",
       "      <td>912242</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-29</td>\n",
       "      <td>0</td>\n",
       "      <td>259</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>306</td>\n",
       "      <td>2022-08-31</td>\n",
       "      <td>СКОУ</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592274</th>\n",
       "      <td>912242</td>\n",
       "      <td>912242</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-29</td>\n",
       "      <td>0</td>\n",
       "      <td>259</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>СУХ2</td>\n",
       "      <td>306</td>\n",
       "      <td>2022-08-31</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592279</th>\n",
       "      <td>912253</td>\n",
       "      <td>912253</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-30</td>\n",
       "      <td>0</td>\n",
       "      <td>266</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>СУХОСТ</td>\n",
       "      <td>280</td>\n",
       "      <td>2022-07-30</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592280</th>\n",
       "      <td>912253</td>\n",
       "      <td>912253</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-30</td>\n",
       "      <td>0</td>\n",
       "      <td>266</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>280</td>\n",
       "      <td>2022-07-30</td>\n",
       "      <td>F017T045</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592281</th>\n",
       "      <td>912253</td>\n",
       "      <td>912253</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-30</td>\n",
       "      <td>0</td>\n",
       "      <td>266</td>\n",
       "      <td>45</td>\n",
       "      <td>17</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>325</td>\n",
       "      <td>2022-09-13</td>\n",
       "      <td>СКОУ</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>225621 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        номер_животного ушная_бирка_животного пол  номер_лактации  \\\n",
       "5                   321             896820302   F               6   \n",
       "6                   321             896820302   F               6   \n",
       "7                   321             896820302   F               6   \n",
       "8                   321             896820302   F               6   \n",
       "9                   321             896820302   F               6   \n",
       "...                 ...                   ...  ..             ...   \n",
       "592273           912242                912242   F               1   \n",
       "592274           912242                912242   F               1   \n",
       "592279           912253                912253   F               1   \n",
       "592280           912253                912253   F               1   \n",
       "592281           912253                912253   F               1   \n",
       "\n",
       "       результат_отела  легкость_отела дата_рождения  \\\n",
       "5                   FA               3    2009-09-11   \n",
       "6                   FA               3    2009-09-11   \n",
       "7                   FA               3    2009-09-11   \n",
       "8                   FA               3    2009-09-11   \n",
       "9                   FA               3    2009-09-11   \n",
       "...                ...             ...           ...   \n",
       "592273              FA               1    2019-12-29   \n",
       "592274              FA               1    2019-12-29   \n",
       "592279              FA               1    2019-12-30   \n",
       "592280              FA               1    2019-12-30   \n",
       "592281              FA               1    2019-12-30   \n",
       "\n",
       "        дней_в_сухостое_предыдущей_лактации  дней_стельности_при_событии  \\\n",
       "5                                        62                          291   \n",
       "6                                        62                          291   \n",
       "7                                        62                          291   \n",
       "8                                        62                          291   \n",
       "9                                        62                          291   \n",
       "...                                     ...                          ...   \n",
       "592273                                    0                          259   \n",
       "592274                                    0                          259   \n",
       "592279                                    0                          266   \n",
       "592280                                    0                          266   \n",
       "592281                                    0                          266   \n",
       "\n",
       "        номер_группы_животного  предыдущий_номер_группы_животного  событие  \\\n",
       "5                           18                                 18   МАСТИТ   \n",
       "6                           18                                 18   МАСТИТ   \n",
       "7                           18                                 18  ПЕРЕВОД   \n",
       "8                           18                                 18   МАСТИТ   \n",
       "9                           18                                 18  ЗДОРОВА   \n",
       "...                        ...                                ...      ...   \n",
       "592273                      17                                 17   ВАКЦИН   \n",
       "592274                      17                                 17     СУХ2   \n",
       "592279                       3                                 17   СУХОСТ   \n",
       "592280                      17                                 17  ПЕРЕВОД   \n",
       "592281                      45                                 17   ВАКЦИН   \n",
       "\n",
       "        дни_доения_при_событии дата_события примечание_события  живых_потомков  \n",
       "5                          213   2019-03-15                 МВ               1  \n",
       "6                          215   2019-03-17             ТМ6_34               1  \n",
       "7                          216   2019-03-18           F006T003               1  \n",
       "8                          221   2019-03-23            КМ4_134               1  \n",
       "9                          230   2019-04-01             МАСТИТ               1  \n",
       "...                        ...          ...                ...             ...  \n",
       "592273                     306   2022-08-31               СКОУ               1  \n",
       "592274                     306   2022-08-31                  -               1  \n",
       "592279                     280   2022-07-30                  -               1  \n",
       "592280                     280   2022-07-30           F017T045               1  \n",
       "592281                     325   2022-09-13               СКОУ               1  \n",
       "\n",
       "[225621 rows x 16 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "686f7239",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2    1758\n",
       "1     861\n",
       "3     148\n",
       "Name: ушная_бирка_животного, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Проверим, для всех ли животных совпадают порядковый номер и значение на бирке\n",
    "\n",
    "df.groupby('номер_животного').ушная_бирка_животного \\\n",
    "                             .nunique().value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "152c563c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Тем не менее, избавимся от колонки с номером бирки, так как одного идентификатора достаточно\n",
    "df = df.drop('ушная_бирка_животного', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "504d3676",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F    225621\n",
       "Name: пол, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Пока рассмотрим только коров\n",
    "\n",
    "df.пол.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12de19d6",
   "metadata": {},
   "source": [
    "Комментарии - работа с полом "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "e18ca55e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.пол = df.пол.apply(lambda x: 1 if x == 'F' else 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3ae12e4",
   "metadata": {},
   "source": [
    "<!-- # Группы среди быков\n",
    "\n",
    "df[df.пол == 'M'].номер_группы_животного.value_counts() -->\n",
    "\n",
    "<!-- # # Группы, содержащие и быков, и коров\n",
    "# groups_in_common = np.intersect1d(\n",
    "#    df[df.пол == 'M'].номер_группы_животного,  df[df.пол == 'F'].номер_группы_животного\n",
    "# )\n",
    "\n",
    "# groups_in_common -->\n",
    "\n",
    "<!-- df[df.номер_группы_животного.isin(groups_in_common)].пол.value_counts() -->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "0ad89caf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>пол</th>\n",
       "      <th>номер_лактации</th>\n",
       "      <th>результат_отела</th>\n",
       "      <th>легкость_отела</th>\n",
       "      <th>дата_рождения</th>\n",
       "      <th>дней_в_сухостое_предыдущей_лактации</th>\n",
       "      <th>дней_стельности_при_событии</th>\n",
       "      <th>номер_группы_животного</th>\n",
       "      <th>предыдущий_номер_группы_животного</th>\n",
       "      <th>событие</th>\n",
       "      <th>дни_доения_при_событии</th>\n",
       "      <th>дата_события</th>\n",
       "      <th>примечание_события</th>\n",
       "      <th>живых_потомков</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>213</td>\n",
       "      <td>2019-03-15</td>\n",
       "      <td>МВ</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>215</td>\n",
       "      <td>2019-03-17</td>\n",
       "      <td>ТМ6_34</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>216</td>\n",
       "      <td>2019-03-18</td>\n",
       "      <td>F006T003</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>221</td>\n",
       "      <td>2019-03-23</td>\n",
       "      <td>КМ4_134</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ЗДОРОВА</td>\n",
       "      <td>230</td>\n",
       "      <td>2019-04-01</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "5              321    1               6              FA               3   \n",
       "6              321    1               6              FA               3   \n",
       "7              321    1               6              FA               3   \n",
       "8              321    1               6              FA               3   \n",
       "9              321    1               6              FA               3   \n",
       "\n",
       "  дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "5    2009-09-11                                   62   \n",
       "6    2009-09-11                                   62   \n",
       "7    2009-09-11                                   62   \n",
       "8    2009-09-11                                   62   \n",
       "9    2009-09-11                                   62   \n",
       "\n",
       "   дней_стельности_при_событии  номер_группы_животного  \\\n",
       "5                          291                      18   \n",
       "6                          291                      18   \n",
       "7                          291                      18   \n",
       "8                          291                      18   \n",
       "9                          291                      18   \n",
       "\n",
       "   предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "5                                 18   МАСТИТ                     213   \n",
       "6                                 18   МАСТИТ                     215   \n",
       "7                                 18  ПЕРЕВОД                     216   \n",
       "8                                 18   МАСТИТ                     221   \n",
       "9                                 18  ЗДОРОВА                     230   \n",
       "\n",
       "  дата_события примечание_события  живых_потомков  \n",
       "5   2019-03-15                 МВ               1  \n",
       "6   2019-03-17             ТМ6_34               1  \n",
       "7   2019-03-18           F006T003               1  \n",
       "8   2019-03-23            КМ4_134               1  \n",
       "9   2019-04-01             МАСТИТ               1  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67f58bc9",
   "metadata": {},
   "source": [
    "Считаем, что мастит не был вылечен, если не было соответствующей записи о выздоровлении и корова умерла / была продана по причине мастита"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "61d22c09",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ПРОДАНА ; Прочее ; УВЗ8             757\n",
       "ПРОДАНА ; Агалактия ; УВЗ9          259\n",
       "ПРОДАНА ; Травмы ; УВЗ5             240\n",
       "ПРОДАНА ; Болезни ЖКТ ; УВЗ3        192\n",
       "ПРОДАНА ; Причина 12 ; УВЗ12         95\n",
       "ПРОДАНА ; МясоКомбинат ; УВЗ13       65\n",
       "ПРОДАНА ; Послеродовое ; УВЗ2        51\n",
       "ПРОДАНА ; Пневмония ; УВЗ1           40\n",
       "ПРОДАНА ; Копыта ; УВЗ4              38\n",
       "ПРОДАНА ; Мастит ; УВЗ7              28\n",
       "ПРОДАНА ; Болезни печени ; УВЗ11     12\n",
       "SOLD ; Прочее ; УВЗ8                  7\n",
       "ПРОДАНА ; Прочее ; УВЗ3               3\n",
       "ПРОДАНА ; Прочее ; УВЗ2               2\n",
       "ПРОДАНА ; Прочее ; УВЗ5               2\n",
       "ПРОДАНА ; Прочее ; УВЗ7               2\n",
       "ПРОДАНА ; Травмы ; УВЗ8               1\n",
       "SOLD ; Болезни ЖКТ ; УВЗ3             1\n",
       "ПРОДАНА ; Репродукция ; УВЗ6          1\n",
       "ПРОДАНА ; Прочее ; УВЗ4               1\n",
       "ПРОДАНА ; Травмы ; УВЗ3               1\n",
       "УВЗ5                                  1\n",
       "Name: примечание_события, dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.событие == 'ПРОДАНА'].примечание_события.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "149d2770",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(28, 15)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sold_mastit = df[df.примечание_события == 'ПРОДАНА ; Мастит ; УВЗ7']\n",
    "\n",
    "sold_mastit.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "63af96ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2166"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cured = df[(df.событие == 'ЗДОРОВА') & (df.примечание_события == 'МАСТИТ')].номер_животного.unique()\n",
    "\n",
    "cured.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "a5fa17ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cured = df[(df.событие == 'ЗДОРОВА') & (df.примечание_события == 'МАСТИТ')]\n",
    "not_cured = df[(df.событие.isin(['ПРОДАНА', 'ПАЛА'])) & ~(df.событие.isin(cured.номер_животного))] \n",
    "\n",
    "df['вылечена'] = df.номер_животного.apply(lambda x: 1 if x in cured.номер_животного else 0)\n",
    "\n",
    "sns.barplot(x=[0, 1], y=[not_cured.номер_животного.unique().size, \n",
    "                         cured.номер_животного.unique().size])\n",
    "\n",
    "plt.title('Успешное лечение мастита')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "4e9466ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    225319\n",
       "1       302\n",
       "Name: вылечена, dtype: int64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.вылечена.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "c9883f37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(df.легкость_отела)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "2dea7eb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>пол</th>\n",
       "      <th>номер_лактации</th>\n",
       "      <th>результат_отела</th>\n",
       "      <th>легкость_отела</th>\n",
       "      <th>дата_рождения</th>\n",
       "      <th>дней_в_сухостое_предыдущей_лактации</th>\n",
       "      <th>дней_стельности_при_событии</th>\n",
       "      <th>номер_группы_животного</th>\n",
       "      <th>предыдущий_номер_группы_животного</th>\n",
       "      <th>событие</th>\n",
       "      <th>дни_доения_при_событии</th>\n",
       "      <th>дата_события</th>\n",
       "      <th>примечание_события</th>\n",
       "      <th>живых_потомков</th>\n",
       "      <th>вылечена</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>592273</th>\n",
       "      <td>912242</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-29</td>\n",
       "      <td>0</td>\n",
       "      <td>259</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>306</td>\n",
       "      <td>2022-08-31</td>\n",
       "      <td>СКОУ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592274</th>\n",
       "      <td>912242</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-29</td>\n",
       "      <td>0</td>\n",
       "      <td>259</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>СУХ2</td>\n",
       "      <td>306</td>\n",
       "      <td>2022-08-31</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592279</th>\n",
       "      <td>912253</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-30</td>\n",
       "      <td>0</td>\n",
       "      <td>266</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>СУХОСТ</td>\n",
       "      <td>280</td>\n",
       "      <td>2022-07-30</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592280</th>\n",
       "      <td>912253</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-30</td>\n",
       "      <td>0</td>\n",
       "      <td>266</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>280</td>\n",
       "      <td>2022-07-30</td>\n",
       "      <td>F017T045</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592281</th>\n",
       "      <td>912253</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-30</td>\n",
       "      <td>0</td>\n",
       "      <td>266</td>\n",
       "      <td>45</td>\n",
       "      <td>17</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>325</td>\n",
       "      <td>2022-09-13</td>\n",
       "      <td>СКОУ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "592273           912242    1               1              FA               1   \n",
       "592274           912242    1               1              FA               1   \n",
       "592279           912253    1               1              FA               1   \n",
       "592280           912253    1               1              FA               1   \n",
       "592281           912253    1               1              FA               1   \n",
       "\n",
       "       дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "592273    2019-12-29                                    0   \n",
       "592274    2019-12-29                                    0   \n",
       "592279    2019-12-30                                    0   \n",
       "592280    2019-12-30                                    0   \n",
       "592281    2019-12-30                                    0   \n",
       "\n",
       "        дней_стельности_при_событии  номер_группы_животного  \\\n",
       "592273                          259                      17   \n",
       "592274                          259                      17   \n",
       "592279                          266                       3   \n",
       "592280                          266                      17   \n",
       "592281                          266                      45   \n",
       "\n",
       "        предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "592273                                 17   ВАКЦИН                     306   \n",
       "592274                                 17     СУХ2                     306   \n",
       "592279                                 17   СУХОСТ                     280   \n",
       "592280                                 17  ПЕРЕВОД                     280   \n",
       "592281                                 17   ВАКЦИН                     325   \n",
       "\n",
       "       дата_события примечание_события  живых_потомков  вылечена  \n",
       "592273   2022-08-31               СКОУ               1         0  \n",
       "592274   2022-08-31                  -               1         0  \n",
       "592279   2022-07-30                  -               1         0  \n",
       "592280   2022-07-30           F017T045               1         0  \n",
       "592281   2022-09-13               СКОУ               1         0  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "14f4b89a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "weights = df[df.событие == 'ВЕС'].примечание_события.astype(int)\n",
    "\n",
    "sns.distplot(weights, bins=np.linspace(weights.min(), weights.max()), hist=False)\n",
    "\n",
    "plt.xlabel('Вес коровы')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "d9ac54a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# TODO: boxplots with mean weights\n",
    "df[(df.вылечена == 1) & (df.событие == 'ВЕС')].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b0bfe52",
   "metadata": {},
   "source": [
    "Для вылеченных коров будет всего 7 значений веса\n",
    "\n",
    "Тогда в сравнении распределений веса для выздоровевших/невыздоровевших коров нет смысла"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "b284b1b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['возраст'] = (df.дата_события  - df.дата_рождения).dt.days / 365.25\n",
    "\n",
    "df.возраст.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "86b75c29",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.возраст.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "1fa9de98",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(df.возраст, kde=True)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "f132db3d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_unique = df.\n",
    "first_ages = df.groupby('номер_животного').возраст.first()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "e0a9e96c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 4))\n",
    "\n",
    "df_unique = df.drop_duplicates('номер_животного')\n",
    "\n",
    "# sns.violinplot(x=df.вылечена, y=df.возраст)\n",
    "sns.violinplot(x=df_unique.вылечена, y=df_unique.номер_животного.map(first_ages))\n",
    "\n",
    "plt.title('Возраст, в котором в первый раз заболели')\n",
    "plt.ylabel('Средний возраст')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "3845f7c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "225621"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "9d7eeceb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x=df.вылечена, y=df.номер_лактации)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fdd77e04",
   "metadata": {},
   "source": [
    "Проведем промежуточные итоги - вычислим, есть ли статистически значимая разница между возрастами и номерами лактации для вылечившихся и невылечившихся коров\n",
    "\n",
    "Конечно есть некие условности, как, например, независимость наблюдений между и внутри выборок, но пренебрежем этим"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "d231259e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import ttest_ind, mannwhitneyu, bootstrap\n",
    "\n",
    "def get_p_values(a, b, variable_name):\n",
    "    print(f'\\t\\t==={variable_name}===')\n",
    "    \n",
    "    print('Ttest output:\\t', ttest_ind(a, b, alternative='two-sided').pvalue)\n",
    "    print('Mann-Whitney-Wilcoxon:\\t', mannwhitneyu(a, b, alternative='two-sided').pvalue)\n",
    "\n",
    "def bootstrap_confint(a, b):\n",
    "    bs = bootstrap(\n",
    "        data=(b,),\n",
    "        statistic=np.mean,\n",
    "        confidence_level=0.95,\n",
    "        n_resamples=1000\n",
    "    )\n",
    "    print('Bootstrap confint:\\t', \n",
    "          a.mean() < bs.confidence_interval.low or a.mean() > bs.confidence_interval.high)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "dd6306f7",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t\t===Возраст===\n",
      "Ttest output:\t 0.08914954175610681\n",
      "Mann-Whitney-Wilcoxon:\t 0.10758514149938096\n",
      "Bootstrap confint:\t False\n",
      "_____________\n",
      "\t\t===Номер лактации===\n",
      "Ttest output:\t 0.06135989418305116\n",
      "Mann-Whitney-Wilcoxon:\t 0.03785726660974472\n",
      "Bootstrap confint:\t False\n"
     ]
    }
   ],
   "source": [
    "A = df_unique[df_unique.вылечена == 0]\n",
    "B = df_unique[df_unique.вылечена == 1]\n",
    "\n",
    "A['первый_возраст'] = A.номер_животного.map(first_ages)\n",
    "B['первый_возраст'] = B.номер_животного.map(first_ages)\n",
    "\n",
    "\n",
    "get_p_values(A.первый_возраст, B.первый_возраст, 'Возраст')\n",
    "bootstrap_confint(A.возраст, B.возраст)\n",
    "print(\"_____________\")\n",
    "get_p_values(A.номер_лактации, B.номер_лактации, 'Номер лактации')\n",
    "bootstrap_confint(A.номер_лактации, B.номер_лактации)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "50fbfe33",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t\t===Возраст===\n",
      "Ttest output:\t 7.327883688636958e-50\n",
      "Mann-Whitney-Wilcoxon:\t 8.381190586230363e-53\n",
      "Bootstrap confint:\t True\n",
      "_____________\n",
      "\t\t===Номер лактации===\n",
      "Ttest output:\t 7.148059164757116e-49\n",
      "Mann-Whitney-Wilcoxon:\t 1.8648575179565476e-49\n",
      "Bootstrap confint:\t True\n"
     ]
    }
   ],
   "source": [
    "A = df[df.вылечена == 0]\n",
    "B = df[df.вылечена == 1]\n",
    "\n",
    "get_p_values(A.возраст, B.возраст, 'Возраст')\n",
    "bootstrap_confint(A.возраст, B.возраст)\n",
    "print(\"_____________\")\n",
    "get_p_values(A.номер_лактации, B.номер_лактации, 'Номер лактации')\n",
    "bootstrap_confint(A.номер_лактации, B.номер_лактации)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10148436",
   "metadata": {},
   "source": [
    "Все три теста показывают значения **p-value** меньшее, чем *0.05*, поэтому мы можем быть на *95%* уверены, что распределения возраста и номера текущей лактации различаются для коров с разными статусами `вылечена`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "e381ef4a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>пол</th>\n",
       "      <th>номер_лактации</th>\n",
       "      <th>результат_отела</th>\n",
       "      <th>легкость_отела</th>\n",
       "      <th>дата_рождения</th>\n",
       "      <th>дней_в_сухостое_предыдущей_лактации</th>\n",
       "      <th>дней_стельности_при_событии</th>\n",
       "      <th>номер_группы_животного</th>\n",
       "      <th>предыдущий_номер_группы_животного</th>\n",
       "      <th>событие</th>\n",
       "      <th>дни_доения_при_событии</th>\n",
       "      <th>дата_события</th>\n",
       "      <th>примечание_события</th>\n",
       "      <th>живых_потомков</th>\n",
       "      <th>вылечена</th>\n",
       "      <th>возраст</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>213</td>\n",
       "      <td>2019-03-15</td>\n",
       "      <td>МВ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.505818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>215</td>\n",
       "      <td>2019-03-17</td>\n",
       "      <td>ТМ6_34</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.511294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>216</td>\n",
       "      <td>2019-03-18</td>\n",
       "      <td>F006T003</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.514031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>221</td>\n",
       "      <td>2019-03-23</td>\n",
       "      <td>КМ4_134</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.527721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ЗДОРОВА</td>\n",
       "      <td>230</td>\n",
       "      <td>2019-04-01</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.552361</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "5              321    1               6              FA               3   \n",
       "6              321    1               6              FA               3   \n",
       "7              321    1               6              FA               3   \n",
       "8              321    1               6              FA               3   \n",
       "9              321    1               6              FA               3   \n",
       "\n",
       "  дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "5    2009-09-11                                   62   \n",
       "6    2009-09-11                                   62   \n",
       "7    2009-09-11                                   62   \n",
       "8    2009-09-11                                   62   \n",
       "9    2009-09-11                                   62   \n",
       "\n",
       "   дней_стельности_при_событии  номер_группы_животного  \\\n",
       "5                          291                      18   \n",
       "6                          291                      18   \n",
       "7                          291                      18   \n",
       "8                          291                      18   \n",
       "9                          291                      18   \n",
       "\n",
       "   предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "5                                 18   МАСТИТ                     213   \n",
       "6                                 18   МАСТИТ                     215   \n",
       "7                                 18  ПЕРЕВОД                     216   \n",
       "8                                 18   МАСТИТ                     221   \n",
       "9                                 18  ЗДОРОВА                     230   \n",
       "\n",
       "  дата_события примечание_события  живых_потомков  вылечена   возраст  \n",
       "5   2019-03-15                 МВ               1         0  9.505818  \n",
       "6   2019-03-17             ТМ6_34               1         0  9.511294  \n",
       "7   2019-03-18           F006T003               1         0  9.514031  \n",
       "8   2019-03-23            КМ4_134               1         0  9.527721  \n",
       "9   2019-04-01             МАСТИТ               1         0  9.552361  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "f29c3b8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5              МВ\n",
       "6          ТМ6_34\n",
       "8         КМ4_134\n",
       "89          КМ3_4\n",
       "92         КМ5_34\n",
       "           ...   \n",
       "591826      КМ1_1\n",
       "591869      ТМ2_3\n",
       "592067      КМ6_3\n",
       "592101      КМ1_4\n",
       "592127    КМ1_1_4\n",
       "Name: примечание_события, Length: 8368, dtype: object"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.событие == 'МАСТИТ'].примечание_события"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d14ae508",
   "metadata": {},
   "source": [
    "Странное значение колонки с примечаниями - **КМ1_1_4**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "ed7d6c10",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    212294\n",
       "1     12981\n",
       "2       346\n",
       "Name: примечание_события, dtype: int64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.примечание_события.apply(lambda x: Counter(x)['_']).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "f9eb3790",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>пол</th>\n",
       "      <th>номер_лактации</th>\n",
       "      <th>результат_отела</th>\n",
       "      <th>легкость_отела</th>\n",
       "      <th>дата_рождения</th>\n",
       "      <th>дней_в_сухостое_предыдущей_лактации</th>\n",
       "      <th>дней_стельности_при_событии</th>\n",
       "      <th>номер_группы_животного</th>\n",
       "      <th>предыдущий_номер_группы_животного</th>\n",
       "      <th>событие</th>\n",
       "      <th>дни_доения_при_событии</th>\n",
       "      <th>дата_события</th>\n",
       "      <th>примечание_события</th>\n",
       "      <th>живых_потомков</th>\n",
       "      <th>вылечена</th>\n",
       "      <th>возраст</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>506015</th>\n",
       "      <td>908179</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-08-28</td>\n",
       "      <td>0</td>\n",
       "      <td>261</td>\n",
       "      <td>6</td>\n",
       "      <td>17</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>274</td>\n",
       "      <td>2022-03-06</td>\n",
       "      <td>F006T007</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.521561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>391650</th>\n",
       "      <td>810063</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-10-13</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>8</td>\n",
       "      <td>2021-06-23</td>\n",
       "      <td>F021T002</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.694045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169589</th>\n",
       "      <td>506077</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2015-06-17</td>\n",
       "      <td>48</td>\n",
       "      <td>67</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>125</td>\n",
       "      <td>2020-03-24</td>\n",
       "      <td>F003T043</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.769336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109681</th>\n",
       "      <td>610150</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-10-29</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>10</td>\n",
       "      <td>2019-12-20</td>\n",
       "      <td>F021T002</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.140315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74633</th>\n",
       "      <td>712188</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2017-12-26</td>\n",
       "      <td>0</td>\n",
       "      <td>280</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>605</td>\n",
       "      <td>2019-08-23</td>\n",
       "      <td>F028T047</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1.656400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95986</th>\n",
       "      <td>810001</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>FA</td>\n",
       "      <td>0</td>\n",
       "      <td>2018-10-01</td>\n",
       "      <td>0</td>\n",
       "      <td>139</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>375</td>\n",
       "      <td>2019-10-11</td>\n",
       "      <td>F029T030</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1.026694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78264</th>\n",
       "      <td>809080</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>FA</td>\n",
       "      <td>0</td>\n",
       "      <td>2018-09-14</td>\n",
       "      <td>0</td>\n",
       "      <td>197</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>348</td>\n",
       "      <td>2019-08-28</td>\n",
       "      <td>F034T029</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.952772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>349142</th>\n",
       "      <td>607156</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-07-28</td>\n",
       "      <td>57</td>\n",
       "      <td>178</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>192</td>\n",
       "      <td>2021-03-29</td>\n",
       "      <td>F004T003</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.668036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131271</th>\n",
       "      <td>502131</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2015-02-20</td>\n",
       "      <td>53</td>\n",
       "      <td>284</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>378</td>\n",
       "      <td>2020-01-20</td>\n",
       "      <td>F017T018</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.914442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370848</th>\n",
       "      <td>908085</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-08-15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>6</td>\n",
       "      <td>2021-05-14</td>\n",
       "      <td>F021T002</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1.746749</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "506015           908179    1               1              FA               1   \n",
       "391650           810063    1               2              MA               1   \n",
       "169589           506077    1               3              MA               1   \n",
       "109681           610150    1               2              FA               1   \n",
       "74633            712188    1               0              FA               1   \n",
       "95986            810001    1               0              FA               0   \n",
       "78264            809080    1               0              FA               0   \n",
       "349142           607156    1               3              FA               1   \n",
       "131271           502131    1               3              FA               3   \n",
       "370848           908085    1               1              MA               1   \n",
       "\n",
       "       дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "506015    2019-08-28                                    0   \n",
       "391650    2018-10-13                                   61   \n",
       "169589    2015-06-17                                   48   \n",
       "109681    2016-10-29                                   68   \n",
       "74633     2017-12-26                                    0   \n",
       "95986     2018-10-01                                    0   \n",
       "78264     2018-09-14                                    0   \n",
       "349142    2016-07-28                                   57   \n",
       "131271    2015-02-20                                   53   \n",
       "370848    2019-08-15                                    0   \n",
       "\n",
       "        дней_стельности_при_событии  номер_группы_животного  \\\n",
       "506015                          261                       6   \n",
       "391650                            0                       4   \n",
       "169589                           67                       6   \n",
       "109681                            0                      43   \n",
       "74633                           280                      18   \n",
       "95986                           139                      11   \n",
       "78264                           197                      11   \n",
       "349142                          178                       5   \n",
       "131271                          284                      18   \n",
       "370848                            0                       9   \n",
       "\n",
       "        предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "506015                                 17  ПЕРЕВОД                     274   \n",
       "391650                                  3  ПЕРЕВОД                       8   \n",
       "169589                                  6  ПЕРЕВОД                     125   \n",
       "109681                                  2  ПЕРЕВОД                      10   \n",
       "74633                                  18  ПЕРЕВОД                     605   \n",
       "95986                                  11  ПЕРЕВОД                     375   \n",
       "78264                                  11  ПЕРЕВОД                     348   \n",
       "349142                                  3  ПЕРЕВОД                     192   \n",
       "131271                                 18  ПЕРЕВОД                     378   \n",
       "370848                                  2  ПЕРЕВОД                       6   \n",
       "\n",
       "       дата_события примечание_события  живых_потомков  вылечена   возраст  \n",
       "506015   2022-03-06           F006T007               1         0  2.521561  \n",
       "391650   2021-06-23           F021T002               1         0  2.694045  \n",
       "169589   2020-03-24           F003T043               1         0  4.769336  \n",
       "109681   2019-12-20           F021T002               1         0  3.140315  \n",
       "74633    2019-08-23           F028T047               1         0  1.656400  \n",
       "95986    2019-10-11           F029T030               1         0  1.026694  \n",
       "78264    2019-08-28           F034T029               1         0  0.952772  \n",
       "349142   2021-03-29           F004T003               1         0  4.668036  \n",
       "131271   2020-01-20           F017T018               1         0  4.914442  \n",
       "370848   2021-05-14           F021T002               1         0  1.746749  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.событие == 'ПЕРЕВОД'].sample(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b2c73d3",
   "metadata": {},
   "source": [
    "Сколько раз коровы выздоравливали от мастита"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "9bd115c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1     1166\n",
       "2      567\n",
       "3      229\n",
       "4      105\n",
       "5       52\n",
       "6       19\n",
       "7       12\n",
       "8        9\n",
       "10       4\n",
       "11       2\n",
       "9        1\n",
       "Name: возраст, dtype: int64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df.событие == 'ЗДОРОВА') & (df.примечание_события == 'МАСТИТ')] \\\n",
    "    .groupby('номер_животного').возраст.count().value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d59acad",
   "metadata": {},
   "source": [
    "Графики общего количества коров и числа заболевших маститом"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "090f94de",
   "metadata": {},
   "outputs": [],
   "source": [
    "f = codecs.open('../data/dump_19_22.csv', 'r', 'cp1251')\n",
    "total_df = pd.read_csv(f, sep=';', encoding='utf-8')\n",
    "\n",
    "total_df.columns = pd.Series(total_df.columns).apply(lambda x: x.lower().replace(' ', '_'))\n",
    "\n",
    "total_df.дата_рождения = total_df.дата_рождения.apply(lambda x: datetime.strptime(x,\"%d.%m.%Y\"))\n",
    "total_df.дата_события = total_df.дата_события.apply(lambda x: datetime.strptime(x,\"%d.%m.%Y\"))\n",
    "\n",
    "total_df['год'] = total_df.дата_события.dt.year\n",
    "\n",
    "total_df['год_месяц'] = total_df.дата_события.dt.to_period('M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "8fa06ebd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>пол</th>\n",
       "      <th>номер_лактации</th>\n",
       "      <th>результат_отела</th>\n",
       "      <th>легкость_отела</th>\n",
       "      <th>дата_рождения</th>\n",
       "      <th>дней_в_сухостое_предыдущей_лактации</th>\n",
       "      <th>дней_стельности_при_событии</th>\n",
       "      <th>номер_группы_животного</th>\n",
       "      <th>предыдущий_номер_группы_животного</th>\n",
       "      <th>событие</th>\n",
       "      <th>дни_доения_при_событии</th>\n",
       "      <th>дата_события</th>\n",
       "      <th>примечание_события</th>\n",
       "      <th>живых_потомков</th>\n",
       "      <th>вылечена</th>\n",
       "      <th>возраст</th>\n",
       "      <th>месяц</th>\n",
       "      <th>год</th>\n",
       "      <th>год_месяц</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>213</td>\n",
       "      <td>2019-03-15</td>\n",
       "      <td>МВ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.505818</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>1540</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-07-18</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>43</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>173</td>\n",
       "      <td>2019-04-03</td>\n",
       "      <td>КМ3_4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8.709103</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>1978</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-11-12</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>219</td>\n",
       "      <td>2019-03-12</td>\n",
       "      <td>КМ5_12</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8.328542</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>2215</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-03-27</td>\n",
       "      <td>70</td>\n",
       "      <td>281</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>431</td>\n",
       "      <td>2019-04-14</td>\n",
       "      <td>КМ3_4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.048597</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>2389</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-03-30</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>41</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>294</td>\n",
       "      <td>2019-03-12</td>\n",
       "      <td>КМ5_12</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8.950034</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>591821</th>\n",
       "      <td>912007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>280</td>\n",
       "      <td>2022-08-04</td>\n",
       "      <td>КМ1_4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.674880</td>\n",
       "      <td>8</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>591826</th>\n",
       "      <td>912008</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-01</td>\n",
       "      <td>0</td>\n",
       "      <td>234</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>321</td>\n",
       "      <td>2022-08-19</td>\n",
       "      <td>КМ1_1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.715948</td>\n",
       "      <td>8</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>591869</th>\n",
       "      <td>912023</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-03</td>\n",
       "      <td>0</td>\n",
       "      <td>179</td>\n",
       "      <td>3</td>\n",
       "      <td>43</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>324</td>\n",
       "      <td>2022-08-01</td>\n",
       "      <td>ТМ2_3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.661191</td>\n",
       "      <td>8</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592067</th>\n",
       "      <td>912105</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-13</td>\n",
       "      <td>0</td>\n",
       "      <td>119</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>270</td>\n",
       "      <td>2022-08-27</td>\n",
       "      <td>КМ6_3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.704997</td>\n",
       "      <td>8</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592101</th>\n",
       "      <td>912128</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-16</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>4</td>\n",
       "      <td>2022-08-14</td>\n",
       "      <td>КМ1_4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.661191</td>\n",
       "      <td>8</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3636 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "5                   321    1               6              FA               3   \n",
       "89                 1540    1               6              FA               1   \n",
       "125                1978    1               6              FA               1   \n",
       "162                2215    1               5              MA               1   \n",
       "178                2389    1               6              FA               1   \n",
       "...                 ...  ...             ...             ...             ...   \n",
       "591821           912007    1               1              MA               1   \n",
       "591826           912008    1               1              FA               1   \n",
       "591869           912023    1               1              FA               1   \n",
       "592067           912105    1               1              MA               1   \n",
       "592101           912128    1               2              FA               1   \n",
       "\n",
       "       дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "5         2009-09-11                                   62   \n",
       "89        2010-07-18                                   56   \n",
       "125       2010-11-12                                   58   \n",
       "162       2010-03-27                                   70   \n",
       "178       2010-03-30                                   59   \n",
       "...              ...                                  ...   \n",
       "591821    2019-12-01                                    0   \n",
       "591826    2019-12-01                                    0   \n",
       "591869    2019-12-03                                    0   \n",
       "592067    2019-12-13                                    0   \n",
       "592101    2019-12-16                                   62   \n",
       "\n",
       "        дней_стельности_при_событии  номер_группы_животного  \\\n",
       "5                               291                      18   \n",
       "89                                0                      43   \n",
       "125                               0                      41   \n",
       "162                             281                      18   \n",
       "178                               0                      41   \n",
       "...                             ...                     ...   \n",
       "591821                            0                       3   \n",
       "591826                          234                       3   \n",
       "591869                          179                       3   \n",
       "592067                          119                       3   \n",
       "592101                            0                      21   \n",
       "\n",
       "        предыдущий_номер_группы_животного событие  дни_доения_при_событии  \\\n",
       "5                                      18  МАСТИТ                     213   \n",
       "89                                     43  МАСТИТ                     173   \n",
       "125                                     1  МАСТИТ                     219   \n",
       "162                                    18  МАСТИТ                     431   \n",
       "178                                    41  МАСТИТ                     294   \n",
       "...                                   ...     ...                     ...   \n",
       "591821                                  3  МАСТИТ                     280   \n",
       "591826                                  5  МАСТИТ                     321   \n",
       "591869                                 43  МАСТИТ                     324   \n",
       "592067                                  3  МАСТИТ                     270   \n",
       "592101                                  2  МАСТИТ                       4   \n",
       "\n",
       "       дата_события примечание_события  живых_потомков  вылечена   возраст  \\\n",
       "5        2019-03-15                 МВ               1         0  9.505818   \n",
       "89       2019-04-03              КМ3_4               1         0  8.709103   \n",
       "125      2019-03-12             КМ5_12               1         0  8.328542   \n",
       "162      2019-04-14              КМ3_4               1         0  9.048597   \n",
       "178      2019-03-12             КМ5_12               1         0  8.950034   \n",
       "...             ...                ...             ...       ...       ...   \n",
       "591821   2022-08-04              КМ1_4               1         0  2.674880   \n",
       "591826   2022-08-19              КМ1_1               1         0  2.715948   \n",
       "591869   2022-08-01              ТМ2_3               1         0  2.661191   \n",
       "592067   2022-08-27              КМ6_3               1         0  2.704997   \n",
       "592101   2022-08-14              КМ1_4               1         0  2.661191   \n",
       "\n",
       "        месяц   год год_месяц  \n",
       "5           3  2019   2019-03  \n",
       "89          4  2019   2019-04  \n",
       "125         3  2019   2019-03  \n",
       "162         4  2019   2019-04  \n",
       "178         3  2019   2019-03  \n",
       "...       ...   ...       ...  \n",
       "591821      8  2022   2022-08  \n",
       "591826      8  2022   2022-08  \n",
       "591869      8  2022   2022-08  \n",
       "592067      8  2022   2022-08  \n",
       "592101      8  2022   2022-08  \n",
       "\n",
       "[3636 rows x 20 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['месяц'] = df.дата_события.dt.month\n",
    "df['год'] = df.дата_события.dt.year\n",
    "\n",
    "df['год_месяц'] = df.дата_события.dt.to_period('M')\n",
    "\n",
    "df[df.событие == 'МАСТИТ'] \\\n",
    "    .drop_duplicates(['номер_животного', 'год'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "dd1cb0a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import plotly.express as px\n",
    "plt.figure(figsize=(12, 8))\n",
    "\n",
    "year_unique = df[df.событие == 'МАСТИТ'] \\\n",
    "              .drop_duplicates(['номер_животного', 'год']).copy()\n",
    "year_stats = year_unique.groupby('год').номер_животного.count()\n",
    "\n",
    "year_unique_total = total_df.drop_duplicates(['номер_животного', 'год']).copy()\n",
    "year_stats_total = year_unique_total.groupby('год').номер_животного.count()\n",
    "\n",
    "sns.lineplot(x=year_stats.index, y=year_stats)\n",
    "sns.pointplot(x=year_stats_total.index, y=year_stats_total)\n",
    "\n",
    "plt.legend(['Больных коров', 'Всего коров'])\n",
    "plt.xlabel('Всего больных коров')\n",
    "plt.title('Изменение числа больных коров')\n",
    "# plt.xticks(year_stats.index)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "b858677e",
   "metadata": {},
   "outputs": [],
   "source": [
    "month_year_unique = total_df[total_df.событие == 'МАСТИТ'] \\\n",
    "              .drop_duplicates(['номер_животного', 'год']).copy()\n",
    "month_year_stats = month_year_unique.groupby(['год_месяц']).номер_животного.count()\n",
    "\n",
    "month_year_unique_total = total_df.drop_duplicates(['номер_животного', 'год_месяц']).copy()\n",
    "month_year_stats_total = month_year_unique_total.groupby(['год_месяц']).номер_животного.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "30a16773",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import plotly.express as px\n",
    "\n",
    "# px.line(x=range(month_year_stats.size), y=month_year_stats.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "9226f32b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PeriodIndex(['2019-03', '2019-04', '2019-05', '2019-06', '2019-07', '2019-08',\n",
       "             '2019-09', '2019-10', '2019-11', '2019-12', '2020-01', '2020-02',\n",
       "             '2020-03', '2020-04', '2020-05', '2020-06', '2020-07', '2020-08',\n",
       "             '2020-09', '2020-10', '2020-11', '2020-12', '2021-01', '2021-02',\n",
       "             '2021-03', '2021-04', '2021-05', '2021-06', '2021-07', '2021-08',\n",
       "             '2021-09', '2021-10', '2021-11', '2021-12', '2022-01', '2022-02',\n",
       "             '2022-03', '2022-04', '2022-05', '2022-06', '2022-07', '2022-08',\n",
       "             '2022-09'],\n",
       "            dtype='period[M]', name='год_месяц')"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "month_year_stats.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "8c6bf1be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>ушная_бирка_животного</th>\n",
       "      <th>пол</th>\n",
       "      <th>номер_лактации</th>\n",
       "      <th>результат_отела</th>\n",
       "      <th>легкость_отела</th>\n",
       "      <th>дата_рождения</th>\n",
       "      <th>дней_в_сухостое_предыдущей_лактации</th>\n",
       "      <th>дней_стельности_при_событии</th>\n",
       "      <th>номер_группы_животного</th>\n",
       "      <th>предыдущий_номер_группы_животного</th>\n",
       "      <th>событие</th>\n",
       "      <th>дни_доения_при_событии</th>\n",
       "      <th>дата_события</th>\n",
       "      <th>примечание_события</th>\n",
       "      <th>год</th>\n",
       "      <th>год_месяц</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>146</td>\n",
       "      <td>598621616</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-03-29</td>\n",
       "      <td>62</td>\n",
       "      <td>277</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>РАСЧКОП</td>\n",
       "      <td>336</td>\n",
       "      <td>2019-03-28</td>\n",
       "      <td>КАН</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>146</td>\n",
       "      <td>598621616</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-03-29</td>\n",
       "      <td>62</td>\n",
       "      <td>277</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>349</td>\n",
       "      <td>2019-04-10</td>\n",
       "      <td>КОГЛАВАК</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>146</td>\n",
       "      <td>598621616</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-03-29</td>\n",
       "      <td>62</td>\n",
       "      <td>277</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>349</td>\n",
       "      <td>2019-04-10</td>\n",
       "      <td>ЛЕПТО</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>291</td>\n",
       "      <td>530073354</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2009-07-30</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>448</td>\n",
       "      <td>2019-04-08</td>\n",
       "      <td>F001T023</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>291</td>\n",
       "      <td>530073354</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2009-07-30</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>ПРОДАНА</td>\n",
       "      <td>458</td>\n",
       "      <td>2019-04-18</td>\n",
       "      <td>ПРОДАНА ; Прочее ; УВЗ8</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   номер_животного ушная_бирка_животного пол  номер_лактации результат_отела  \\\n",
       "0              146             598621616   F               6              FA   \n",
       "1              146             598621616   F               6              FA   \n",
       "2              146             598621616   F               6              FA   \n",
       "3              291             530073354   F               6              MA   \n",
       "4              291             530073354   F               6              MA   \n",
       "\n",
       "   легкость_отела дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "0               1    2010-03-29                                   62   \n",
       "1               1    2010-03-29                                   62   \n",
       "2               1    2010-03-29                                   62   \n",
       "3               1    2009-07-30                                   68   \n",
       "4               1    2009-07-30                                   68   \n",
       "\n",
       "   дней_стельности_при_событии  номер_группы_животного  \\\n",
       "0                          277                      18   \n",
       "1                          277                      18   \n",
       "2                          277                      18   \n",
       "3                            0                      23   \n",
       "4                            0                      23   \n",
       "\n",
       "   предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "0                                 18  РАСЧКОП                     336   \n",
       "1                                 18   ВАКЦИН                     349   \n",
       "2                                 18   ВАКЦИН                     349   \n",
       "3                                 23  ПЕРЕВОД                     448   \n",
       "4                                 23  ПРОДАНА                     458   \n",
       "\n",
       "  дата_события       примечание_события   год год_месяц  \n",
       "0   2019-03-28                      КАН  2019   2019-03  \n",
       "1   2019-04-10                 КОГЛАВАК  2019   2019-04  \n",
       "2   2019-04-10                    ЛЕПТО  2019   2019-04  \n",
       "3   2019-04-08                 F001T023  2019   2019-04  \n",
       "4   2019-04-18  ПРОДАНА ; Прочее ; УВЗ8  2019   2019-04  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "0799dc50",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 8))\n",
    "\n",
    "sns.lineplot(x=month_year_stats.index.to_timestamp(), y=month_year_stats.values)\n",
    "sns.lineplot(x=month_year_stats.index.to_timestamp(), y=month_year_stats_total.values)\n",
    "\n",
    "\n",
    "# ax.set_xticklabels(labels=month_year_stats.reset_index().год_месяц.values\n",
    "plt.legend(['Больных коров', 'Всего коров'])\n",
    "plt.xlabel('Всего больных коров')\n",
    "plt.title('Изменение числа больных коров')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "4e19318f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QtwBTWpjiv8fFVW6pjckRI1coRUdnIybvUhdup5evgnerZs7aZGHEweLuVkjIE+P38Kq3lhaJZXiULUILOz5sBHWsfCV3zv2xpfjlbiGW3y7/T77wjyrtnYwwLcgMu5+U4LKKLacV7maIIJHK0N3NGGZVVAdXVLFFvboqzBX8rMuD7MPxyrns3VVsf6/OnfTyr6OHu/LrrIw5aGVvhBKxDE9ebouPfFkpuEcVLaAqtt9HZrJvpjS34cFGwEV4hno7LRTJADwvkuKzy/nIF0rRzlG93Q66vsbqvjZws+Dhiyv5+OJKPlzMeVjT37pW1x93OBs5Qhn2xZZiT0wJxvib4tUAdh58RaXmLq7GUFFnDqHuFd9/5e+zqtQILqf8XACYKvF1uYa8gjIZjiUKsTO6BC7mPPTy0M/7CiGk6aFgmBBCtMCUz8GC9pbIF0qx/LZ6OW72JspvwSY8YJx/+YfYrGq2B+6ILkFivgR5ZTJsVFE4q4JEVr790sW8fPukiYoFR2czbp0LW/33uBi5Qik+7mSB9k7KgQAHqj9Q19YnHS3gYs7D55fza+yLuyaiCAIeB3/0tYGVsfIndGtjDlo76Haj1M89rVAkkuEbFUWz5GWVSrEvthQu5jx8390SirM153OY/Fmg/OdlfvvybeaH4qsPyAHg6cvVVcW/C29LHr7pqtk24b0xpSgSSfFWK3Ol3NovO1vCSsDF7iclTA/nG2kixOSI0c3VGCMVCiiN9DNBDzcBYnPFuC6XL8xBeb9uADgUV/PXVx1Xcy7MjDjIU7eptA6v8W4bcwz2McH+2BJsfVT+396YEgzwKs9H15T8VuKPL+YhuUCCZaFWrGJvz4ukOP9MCG8rvlJqQgcnI7zS3BQ5pVIcTVC+UdLLQ4BB3uybGG+EmMHPmo9LKUKmwnddrqFKsH35v0sZLQoTQnSEtkkTQogWVOTmfn89H9ml6n1y2zDIBuZ8Du5niZFVKoWDKReDvAVwNuPhUopQqYiQvEKRDJ23K2/rVGXFnUKE2BthVktzDPY2waUUIVKLyq/nZ81DFxdjLLmpXAVaEzlCGWadzMHmIbY4Oc4eF5PL8DhHDKlMBg8LHjo5G8PWhAv3dWm1voa8tk7GOBpfyvRorc5/j0vQ1tEIs0PMcWeKE849EyKlQAIbEy68LXno5maM/x4XV5l3ra35fn45j9laXJ1PL+UhyI6PWS3N0cNNgHPPhCiTyOBtxUM/TwGmHM/BledleKu1Gd5pbQ5PSz7+F1mEKDV6OJ9MFCIuV4z32log2N4IUS9EcLfgYbC3AKeShPC0VP9jQVapFJ9eyseqvtYIm+CAA3GlyC4t7zPc0dkYT3LE+E4hXeC9c7nYO9IOGwba4HiiEDG5Yvjb8DDMxwQFZVK8K9dfd3xzE3zU3gKBdkY4llCKYxq2/pr5MheXyynfdv5qgCn4XA7+eaBeCy1dXaOdoxG+7mKJxHwxPpRrO7UgLA/tnIzwZWdLXEstY3ZbaCq/TIa553Oxb6Qd1vS3xuiD2cz3dEFYHo6Ntcf33a3Q11OAe5kiuJtzMaqZKaQyYN75XJXFt44nlmLzYFscTShFQr4ELe35GORtguxSKT6+yN5uX9tryBfQsjTmoIebAG0cjZCQJ8aF5NpV2CaEkJpQMEwIIVqSXCBh2tOo42BcKcY3N8VwXxNYCzgoEcsQmyvG2ogi/C+qSK2KtOoQS4GpJ3LwaoApJgeaYpC3CcyNOMgqkSKpQIKfbhVUmXOsiYspZei56wXmtjFHX08BuroaQySVIa1IikspQpVbc2urSCTFF1fUD14/uZSPM0+FmBlsht4exrA25iJHKEVKgQSr7xVq5euvzv0XIpWtr1TJK5Nh6P4svN3aHGP8TTA9yAxSmQwphRJse1zC3LTo6S5AUr4EP9woUGpVVJVisQxjDmVhUVcrhLoZo6urMZLyxVhxpxBrIoowTsMWW9ujS5BcKMH7bS0wupkJTPgcJBdIsCq8EL/dLVTKDb2TIcKAvS+woL0FenkIMNhbwKyGr7hTwMo97uJijEKRDJ9czMOmh5oHsL/0Lt9yLJXJkFUqRVxu+c/6jhq2tOvyGpbGHKwfZAMAePN0LqtNVoFIhjdP5+LYWHusG2CD3rtfaFQwTN6llDL8FVGE99paYG5bc/xxr/x9KalAUv7972CBAV4C9HAzRkGZDOeeCfHrnUKEV7F9+Wh8KTY/LMZH7S0w0FsAsRQ4HF+CxdcLlFJCansN+QJahSIpUgulWBVe/nOpSWV1QgjRBAfQ2uctQgghhBDSSEwONMXqfjas4laEENKYUM4wIYQQQgghhJAmh4JhQgghhBBCCCFNDgXDhBBCCCGEEEKaHMoZJoQQQgghhBDS5DT5atIZGRlISkoy9DQIIYQQQgghhOiAt7c3nJyclB5v8sFwUlISOnXqZOhpEEIIIYQQQgjRgVu3bql8nHKGCSGEEEIIIYQ0ORQME0IIIYQQQghpcigYJoQQQgghhBDS5DT5nGFCCCGEEEJI02Zra4v58+fDx8cHHA7H0NMhtSCTyZCYmIiVK1ciJydHrddQMEwIIYQQQghp0ubPn4/bt2/j+++/h0QiMfR0SC3weDwMHz4c8+fPxzfffKPWa2ibNCGEEEIIIaRJ8/HxwbFjxygQbsAkEgmOHj0KHx8ftV9DwTAhhBBCCCGkSeNwOBQINwISiUSjbe4UDBNCCCGEEEIIaXIoZ5gQQgghhBBCDEwsFiMqKoo5Pnr0KL766isDzqjxo2CYEEIIIYQQQgBMWfotHH29dXLuzIQkbPvs2yqfLykpQbt27XRybaKaWtukOTzA/xNH9H0UgGFFLTEgsQVa/uKqNM7/M0cMSAjEsIKW6H7eD1ZtTJTGWAQJ0PWUL4blt8TApy0Q+K2Tylmocy5CCCGEEEII0RZHX294BrfQyX91CbKXL1+OqKgoREZG4tVXX2Ue7927N3JzcxEeHo7U1FQsWLAAAJCQkAB7e3ul8xQUFDB/7tChA86fPw8A+Oabb5jXVnjllVewadMmAMCBAwcwbdo0AMCcOXOwdetWpXNv2rQJr7zyCgBgzZo1TEVnLy8vnDlzBhEREThz5gw8PT2Z8X/99RcuXryI6OhoDB8+HAAgEAiwceNGREZG4u7du+jTpw8AYMaMGcjIyMC9e/cQExODSZMmafhdVKZWMNx2gwd859oj/tcXuDE0EY++SIOkRMoa4/+pIwK+dELszy9wc0wixIVSdDvpC4Fz5eKzkQ0X3U76AjLg5rgkPPkhA34fOiLwW2eNz0UIIYTUFzw+HxZ2tuALBIaeCiGEkAbK1NQU4eHhCA8Px7lz59ClSxcAwLhx49C2bVu0adMGAwYMwM8//wwXFxcA5e2EwsLC0K5dO6xdu1Znc5szZw4WLVqE0NBQLFiwAPPmzaty7Ndffw0ej4fvvvsOALB69Wps3rwZbdq0wbZt27Bq1SpmrI+PD3r37o3hw4dj7dq1EAgEeO+99wAArVu3xuTJk/Hvv/9C8PL3686dO9G2bVt8/vnnmDBhQp2/rhqjS8fBFnCbaIOw9jEofCRUOYYr4MD/E0fELMtE4posAEDOtWL0j2sBn/fsEb0oHQDg/ZY9uKZc3B6fBHGBFC8A8K24CFzkjLifMyEukKp9LkIIIcTQvNuEoNfUiQjp3xt8IyNIpVLEXLuJS9t249Glq4aeHiGEEA1lJiQZ7Nzy26S7du2KPXv2wNPTE6Ghodi+fTukUikyMjIQFhaGTp064fDhwzA1NUVpaanK850/fx5SqRRRUVF48803UVpaygTcQHnwnZqayoz/8MMPMXXqVBQVFSmtEmdkZGDRokU4f/48xo4di5ycHJXXnDlzJgYOHMis/gJAt27dMG7cOADAli1bsHz5cua5Xbt2QSaTITY2FvHx8WjRogVCQ0Pxxx9/AACio6ORlJSEgIAAAMDEiRPRq1cv+Pj4MKvQdVFjMOw10xYvzhdWGQgDgG13MxhZ85C6O495TFIsQ/qRfDgNtmQCWKchlsg8VQBxQeWq8vOdeQhe6gr73uZIP1Kg9rkIIYQQQwp9bQLGfv4R6zEul4vAHl0R2KMrLm7diYPLVhpmcoQQQmqlupxefbp+/TqMjIzg4OBQbasgNzc3PH/+XOVzffv2RVZWFjZv3oxp06Zh3bp1rIC7Q4cOWLFiBTP+t99+wy+//IL+/fvj119/xa+//so6X6tWrZCVlQU3N7cq52NnZ4cPP/wQK1aswIwZM1SOkclkKv9ccVzd17tz507MmzcP/v7+OHLkCFq0aFHlWHXUuE3aprMZip4IEfK7G4ZkB2NYfkt03O0FgWtlHG0RKIBULENhDDtgLnwshEULAWtcYTR7TMkzEcRFUlgECjQ6l7yR4la1/o8QQgjRVFDP7kqBsKJeUyei55RXqx1DCCGEqBIYGAg+n4+srCxcvHgREydOBJfLhYODA3r16oWbN2+Cy+Vi3LhxuHLlSrXnys7OhrGxsdrXzsrKUhrfqVMnDB06FO3atcPChQvh4+Oj8rW//vor/vrrL7i5uWHgwIEAgKtXrzL5vVOmTMHly5eZ8RMmTACHw4Gfnx/8/PwQHR2NixcvYsqUKQCA5s2bw8vLC9HR0azrFBQUqMyJ1lSNK8MCFz48Z9giP7IUd6c8A9+Ci6ClLui01xuXu8cBAIxteZAUSgF2GjFEORLwzbngGHEgE8lgZMuDKFe5mbUoRwIjW55G5yKEEEIMZcCcmWqN6zd7Gq7s3AupWPl3HyGEECJPfgszj8fDrFmzIJPJsH//fnTr1g0RERGQyWT45JNPkJ6ejm3btiEmJgZ79+5Veb4jR45AKpWisLAQixYtqvH67733HsaMGQMzMzN8/vnnsLS0BAAYGxtj3bp1mDVrFlOka+PGjejXr1+V53rrrbdw6NAhdOrUCe+//z42btyIjz/+GJmZmZg1axYzLjo6GmFhYXB2dsbbb78NoVCINWvWYO3atYiMjIRYLMbMmTNRVlYGoHybdGhoKAQCgdJW7trgAKg2shxe3BLSMhnO+EVDlF3+y9yupxl6nG+Ga4Pi8eJcEZp/7gi/jxxx0vEh67Ves23R5n8eOGISBZkYGF4SgoefpCLhjyzWuAFJLZC8OQePv05X+1zacuvWLXTq1El7JySEENKoOXh74vMju9Qev/7dBZQ/TAgh9dzmzZsxffp0Q0+jSdm0aROOHDlSZTBfW6r+LquK+WrcJi3KkSD/vpAJhAEg+3IxJEIpLILK2x2V5UjAt+Qqnc3IhgdxkZQJXkU5EhjZ8JSuYWTNZVaM1T0XIYQQYgh2bsqtBasd767ZeEIIIYToR43bpAseC8EVKMfMHA4AafmicmG0EFw+B+b+xih6UsaMsQgUoPBxZe5vYbSQyQ2uYOJhBL4Fj8klVvdchBBCiCGIhJr9Luo3u7wv452jJ1FaUKiLKRFCCCENjvx2aUOpcWU4/WgBrFqZwNi+ckXXvpc5uMZc5EeWl/HOuVoMUZ4EbuOtmTE8Uw6cR1gh42RlY+eMEwVwHGQBnkXlZd1etYakWIqssCKNzkUIIYQYQsqjJygtLFJ7vI2LM8Z9uRDfnD2MiYu/hHebEB3OjhBCCCHqqnFl+Om6bPjNtUengz6IXZpRXkDrJxdknilA9pViAIBUKEPs8kwEfOkEUY4EhdFC+M13AIcLJKyuzA9O+l8WfOfao9MeL8T+nAkzX2MELnJC3MoXTLsldc9FCCGEGEJZSQluHzqG0NcmaPQ6Y1MTdB4zAp3HjEBqTByu7zmAO0dOoiSffaPXytEBXV8ZhcAeXWFsZoq8jEzcPXoSkafOQ1xWVsXZCSGEEKKpGoNhcYEUVwcmIGSlG9pv84K0TIb0Q/l4sIDdzyp2WSY4XMD/UycY2/OQe6cE14YkoCyjMslXlCvFtUEJaLXKDZ0P+ECUK0H871mI/i5d43MRQgghhnLqrw3oMHIoTC0tqhxTUliIxHtRaN6lI/hGRqznXJs3w9jPF2DEh3MRceocru85gITwSHQZNxLjvlwIvlxLC7cAfwSFdsOQ9+Zgw9yFSI9L0NnXRQghhDQlNQbDAFAcV4abIxNrHBfzUyZifsqsdkzhIyGuDaz5F7k65yKEEEIMwdLBHgIz0yqff/4kFls/WYT0uARY2Nmi46hh6Dp+NBy9PVnjjEwE6DhqKDqOGorc9AzYODtVeU57Dze8vf4P/DZxFvIz6PcjIYQQUldqBcOEEEIIqTRywTxweZW1NB5fuY689EyUFhbiwflLiLsdzjxXmJ2DC/9sw4V/tqFZp/boNn40Wg3ow1r9BVBtIFzBysEe/V6figNLf9PeF0MIIaReEIvFiIqKAofDgUQiwdy5c3Ht2jVDT6tRo2CYEEII0UBgj65oEdqVOU6LS8CG9xZCKpFU86pycbfuIu7WXZjb2qDjyKHoOn40nHy9Nbp+x1HDcOS3NRBrWNWaEEJIzaYs/RaOGr4vqyszIQnbPvu2yudLSkrQrl07AMCgQYPw008/oU+fPjqZCylXYzVpQgghhJTj8ngYtXAe67HDv/yhViAsrygnF2Gbt2PZqEn4c+Y7eB4do/ZrTS0tYO/hptH1CCGEqMfR1xuewS108p8mQbaVlRVycnKY448//hiRkZG4d+8efvrpJwCAn58fjh8/jtu3b+PixYsIDAwEAGzatAnx8fEIDw9HeHg4unXrBoFAgI0bNyIyMhJ3795VGWT37t0bhw8fBgD06tUL169fh5WVFQBg+fLliIqKQmRkJF599VVmfFhYGPbt24cHDx7gr7/+AofDAQBMmjQJkZGRiIqKwtKlS5lriMVihIeHIyYmBv/9958GfzO6QSvDhBBCiJq6jBsFF38/5jj66g08vlS3LWzxd+4h6mwY3AKbq/2aig8bhBBCGg9TU1OEh4fDxMQErq6u6NevHwBgyJAhGDNmDLp06YKSkhLY2toCAP7++2+8/fbbiI2NRefOnbFmzRr0798fQHnwvHfvXubcH330EQCgdevWCAwMxKlTpxAQEAChil1GISEh+P333zFs2DDk5+dj3LhxaNu2Ldq0aQMHBwfcunULFy9eBAB07twZwcHBSEpKwokTJzBu3DhcvXoVy5YtQ4cOHZCTk4NTp05h9OjROHjwILP6bWJigoSEBNjY2CA3N1eX39ZqUTBMCCGEqMHEwhyD33uDOZZKJDi04g+tnDv1SazaY4XFxchOeV7zQEIIIRrLTEgy2Lnlt0l37doVmzdvRkhICAYMGIBNmzahpKQEAJCTkwNzc3N0794du3fvZl4vEAiqPHdoaCj++KP8d1Z0dDSSkpIQEBCAqKgo1jg3NzccP34cv/zyC1JTU5nXbt++HVKpFBkZGQgLC0OnTp2Qn5+PmzdvIiGhvDjy9u3bERoaCpFIhAsXLuDFixcAgG3btqFXr144ePAgE/B7eHjgwIEDBg2EAQqGCSGEaIGZtRU6jxkB/64dYWxqgtzUdNw5fAJPrt2ETCYz9PS0ov8b02Fpb8cc39h/GGkxcVo598OwK8h/kQUrB/sax945chJlJaVauS4hhBC26nJ69en69etwcHCAo6MjOByO0u9SLpeL3NxcJniuibo7ilq0aIFJkyZh+fLl2Lp1K168eFHtaxXnJZPJqh1fEfDzeDycPn0a3bp1M2iRMMoZJoQQUiedRg/D16cPYuTCeQgK7YZmHdqhw4ghmPO/lfhg+wZYOzsaeop1Zufuil7TJjHHpUVFOLl6ndbOLxGLcez3v2ocV5Sbh/Mbt2jtuoQQQuqnwMBA8Hg8ZGVl4dSpU3j99ddhalre0s/W1hYFBQVISEjA+PHjmde0bt26yvNdvHgRU6ZMAQA0b94cXl5eiI6OVhp37tw5HD58GD/++CN+//135rUTJ04El8uFg4MDevXqhZs3bwIo3ybt4+MDDoeDiRMn4vLly7hx4wZ69+4Ne3t7cLlcTJ48GWFhYazrSCQSFBcXw8HBoW7fqDqiYJgQQkittR0yAJN++BrGpiYqn/dsGYS31/0BE0sLPc9Mu4Z98A6rFdK59VtQkJWt1WvcOnAUB3/+vcpiXAVZ2fj7rfnITknV6nUJIYTUDxVbiMPDw7Fz507MmDEDUqkUJ0+exKFDh3D79m2Eh4dj4cKFAIApU6Zg9uzZuHfvHh48eIDRo0dXee41a9aAx+MhMjISO3fuxMyZM1FWVlbl+C1btsDe3h5Dhw7F/v37ERkZiYiICJw7dw6ffPIJ0tPTAQDXrl3D0qVLcf/+fSQkJGD//v1IS0vD559/jvPnzyMiIgJ3797FoUOHWF/j/fv3UVRUhBMnTmjxO6g5DoDGsX+tlm7duoVOnToZehqEENLg8Ph8fHX6gFpbe0/+uQ6n1m7Uw6y0z7tNCN7fWrkKnJOahqUjJ+mstZG9pwe6TxyLNoP7w9bFmXl82+ff4u6Rkzq5JiGENHWbN2/G9OnTDT2NBqV3795YuHAhRo4caeipsKj6u6wq5qOcYUIIqefcgwLQcdQw2Lm7QlQqRNytcNw9ehLC4mKDzqtlv15qBcIA0HX8GJz+36YGmT88+uMPWMdHV/6l0x6/Wc+ScXjFH7i2az8+P1pZGMW1eTOdXZMQQghpiigYJoSQesrUyhJTln6LoJ7dWY+3GzoQwz98F3t/+Bnhx04ZaHaAV8sgtcdaOzvC2skRuekZOpyR9rUdMgDebUKY46TIB7h3/LRerv3iaTKK8/Nh9rLHo1dIsF6uSwghhKgjLCxMKRe4oaGcYUIIqYf4xsZ4c82vSoFwBVNLC0xd9h3aDO6v55lV4vJ5Go3n8BrWrxy+QIDhH77LeuzQz6v0urr9LOoh82ePli3A4Tas7yEhhDQUMpkMPJ5mv9dI/cPj8TT6PU2/VQkhpB7qOn4Ua0WyKmM//wg8IyM9zEhZelyC2mNLCgqRn/FCh7PRvl5TX4WdmytzfO/kWSTei9TrHJ4+eMT82cTcHE4+Xnq9PiGENBWJiYkYPnw4BcQNGI/Hw/Dhw5GYmKj2a2ibNCGE1EPdJoxVa5ylvR1aD+xrkO3S906exahPPoCJuXmNY28fOgaJWKyHWWmHhb0t+r8xgzkWl5Xh6Mo1ep+H/MowAHi1CkZ6fKLe50EIIY3dypUrMX/+fLzyyitq9+Ql9YtMJkNiYiJWrlyp9msoGCaEkHrGxMIcLv5+ao/3advKIMGwsKgY59ZvwbAP3q52XHFePsL+3a6nWWnH4HffhIlFZZB/aesuZCc/1/s8nt5/xDr2DAnGrYPH9D4PQghp7HJycvDNN98YehpEzygYJoSQekbTbc88I8O9lZ9d/y/MbKzQZ8ZrKp8vyMrGhrkfIyc1Tc8zqz0Xfz90fWUUc1yYnYMz6/81yFwKXmQhJzUNtq4uAMpXhknjIzA3Q9vB/eHczBdSsQRPHzzCg3MXG9RuCkIIaYgoGCaEkHqmOC8fRbl5MLexVmv8i6RkHc+oeodX/IGg0G5wbuar9NymDz7Ds/sPVbyq/hq5YB64cjljJ9esR2lBocHm8zTqIRMMuwU0B9/YGOKyMoPNh2hXv9nT0f/N6UrpBvkvsnBw2UrcO3HGQDMjhJDGjwpoEUJIPSOTSnH7kHpbYSUiMe4cPq7jGVXP2NQEDt6eKp9z8PLQ82zqJrBHV7QI7cocp8Ul4PqegwacEVg3E3hGfLi1aG7A2RBtGrlgHobPf0dl3r2Vgz2m/bwYncYMN8DMCCGkaaBgmBBC6qGLW3aiOD+/xnFXdu5FQVa2HmZUNY+WQeDxVW808ggK1PNsao/L42HUwnmsxw7/8gekEomBZlROMW/YK0T9/s6k/vJqFYw+M1WnF8h75cuP1d4lQgghRDMUDBNCSD2Um5aOwyv+qHZM+LFTOPxL9WP0wadNK9axVCpl/uweHKDv6dRal3GjWIXLoq/ewONL1ww4o3LJDx+zvqeeIZQ33Bj0mDRerXFGJgJ0GjNCx7MhhJCmiYJhQgipp1qEdqvyucLsHGz99BtIxYZdtQQA33atmT+LhELE3brLHLu3CGgQLSpMLMwx+L03mGOpRIJDNdyM0BdhUTEy5NopeVEw3Cg079JRJ2MJIYSoj4JhQgiph+w93NGqf2/mOC0uAVd37mOOLexsmaJKhsThcODdJoQ5fnb/EZIiHzDHJubmsG8AecP935gOS3s75vjG/sNIi4kz4IzYnsrlDTv5esPUytKAsyHaYGQqUHussamJDmdCCCFNFwXDhBBSD/WeMZlV0fjCP9sQdzucNca3Qxt9T0uJo48XK58xMSIKKY+iWWPqe96wnbsrek2bxByXFhXh5Op1BpyRsqdR7Ircni1bGGgmumduYw3nZr6wcXYy9FR0KjctQ4Ox6TqcCSGENF3UWokQQuoZcxtrdBpdWUE2LyMTd4+egrmtDWucX/u2uHvkpJ5nx6aYL5x4LwppMfGsx9yDAup1e5hhH7wDvrExc3xu/RaDFyVTpNieyjMkGE+u3TLQbHQjoFsn9JnxGgJ7VFbzTo2Jw+X/duPGvsOQyeVNNwZ3Dh2Hm0LBtqrcPmTYivGEENJY0cowIYTUMz0mvcLaFnlp2y5IRCLkZ2QiKzmFedy3veFXhn3k8oWB8mA4KzkFJfkFzGP1eWXYu00I2g0dyBznpKYhbMsOA85ItdQncazewo2tonSfmVPw1t+rWIEwALg2b4YJ33yGmb/9CC6fV8WrG6Yb+4+ofdOlobUoI4SQhoKCYUIIqUeMTAToMbmyymxpURGu7T7AHMffiWD+7NLM1+AtV3zaVq4MZyY+RVFOLgAg5fET5nH3ehYMC8zN4OznA3sPd4z+ZD7ruaMr/4JYKDTMxKohEYuR8qjye+rVqqUBZ6NdLXp2w8gFc6sdE9KvN4bNe1tPM9KPkvx87PjqB8hkshrHjvtyIdqPGKyHWRFCSNNCwTAhDZSplRUsHexZeaWk4es4ahgs7GyZ4+t7DqK0oJA5Trh7jzXekKvDZtZWcPbzYY4TI6KYPyfL5Q2b21jXi2JfrgHNMGXZd/j+0gl8cnA7vji+B96tK4PKpMgHuHf8tAFnWD35IlpWjg6wdnY04Gy0p9/r09Qa133SOAjMzXQ8G/1q3qWjymrreemZeP4klvXYpMVfIaRfL31NjRBCmgTKGSakAeEbG6Pr+FHo9uo4uDTzBQCUFhbh9uHjCNu8HdnJzw08Q1IXHC4XfWa8xhxLRGJc2rKTNSb+bgTr2Ld9G9w/d1Ev81Pk3TqEdZx4rzIYViyi5R4UiJzUNL3MS5WWfUIxbcUPMBJUXcH39NoNaq3SGcpThbxhr5BgRKWHGWg22mHj4oxmHdupNVZgZoaQfr1x53DjyJ81tbJCt1fHMMdFuXlYPeNtlBUVIy8jExweFzN+/REhfcsDYB6fj2k/L8b69xYi5nrjyhcnhBBDoZVhQhoIEwtzvLNhNcZ+voAJhCseD508Hgt2b1b7QyWpn1r1783KDQw/fhq56eyKs5mJT1l5hn7t2+prekrkt0gD7GA4+aFCRelgw22Vtvf0wLSfqw+EAaDn1Il6mlHtKFaU9mrV8PsNa7q6be3UOFbDASD0tfEQmFWudF/etgsZ8YnITc+ATCaDVCzBloVfI+b6bWYM39gYs35fxmpnRgghpPYoGCakgZj84yKl4EOeiYU5Zq1aDhsXZz3OimhTn5lTWMcX/t2mclyC3Oqwe1AAjE1NdTqvqsgXzyrJL0B6XAJznJn0DMLiEubYvUWAXucmr+eUCTAyqbmna2D3LgadZ02yniajOD+fOfYMafjBcFlJSc2D5DSWitLGpibo+doE5lhYXIxL/+1RGicuK8PG9z9BUsR95jGBmSneWPMLXAP89TJXQghpzCgYJqQBcGnejNkqVx1TSwv0mPyKHmZEtM2vQ1tW/urjy9eR+iRO5Vj5rdI8Pp/1On3h8nnwkgvGEiPvs7YYy6RSpMrlPLoHGS7I7DBiiNpj63ORIplMhuQHj5ljz5ZBKvNNG5L0uESl3Q/V6fv6VHQeO7LBf91dXhnNapV2bfcBlMjd6JBXVlKCde8uYOUQm1lZ4a2/f4eDt6eup0oIIY0aBcOENAAdRw5Vf+yoYTqcCdEVpVXhf1SvCgP1o4iWW0BzVvsn+S3SFeSLaFk7OcLSwV4vc5PHFwhgZm2l9ngbZycdzqbu5LdKm1iYw9HHy4CzqTupRILI0+fVHm9uY42J33+BD7ZvUOpx3VDw+Hz0mTGZORaLRAjbXH07r5L8fPw95wNkJj1jHrO0t8Pb61bRbiBCCKkDCoYJaQBs3dSvxGvlYA+ekZEOZ0O0zdnPBy37hDLHyQ+jEXPjdpXjn0fHorSoiDk2RN6w4pb9JBXBcMpDxSJa+l8dlohEkIjFao+X39pdHykV0WrgLZbMbaxZP/tVUSxs5tkyCPO2/o3JPy6ClaODrqanEx1GDGEFsLcOHkV+RmaNryvIysb/3nyfVYjO1tUFb69bBQt722peSQghpCoUDBPSAIhK1e97KpVIINXgwz8xvN5yFaSB6leFgfK/Y/kcQq/WLcHl67fFlq9cvrBUIkFS5AOlMckKFaU9DNBvWCaVsgoQ1eTJtZs6nE3dNaYiWjw+HzN++wn2Hu7MY6qqecffuYc/ps3Bzf1HlJ7rOHIoPjuyE31fn9ogbgJyuFz0fX0qcyyVSHB+Y/X/3uXlpKbhf3M+YBXRc/Txwlv/+x2mVpZanSshhDQFFAwT0gDE3bqjwdjwet0ehrBZOTqgw8jKnNbslFREnDpX4+vk84YFZqZ6DzTlV4afR8eqLISUHpcAcVkZc+xugGAYAC5vVy5MpEpeRiaizlzQ7WTqqOBFFnLT0pljz5AgA86mbsYv+pRVAb8kvwB/znoXB5b+hnMbNuPY72vx64QZ+HPmO0iKuI+di5Zg5eTZrBtBQHnLpREfvoeP929DcG/Vq8wcDketImq61mpAHzj5ejPHEafOIetZskbnyEx8ir/fmo+S/ALmMbfA5nhjzS8GK6ZHCCENFQXDhDQA4SfOoignV62xV3bu1e1kiFb1nDIBfLkVrbDN2yGVSGp8XcKde6xjfW6VtnF2Ym3zTIxQ3iINABKxGKkxlUXADLEyDACPLl7BzQPKq4ryxCIRdny1WKMt1YYivzrsFti8QayIKuozcwo6jx3BHEvEYvy74Esk3LmHS9t24ejKv3B2/b9IefyE9bpn9x/ij2lz8N8X3yM/8wXrOUdvT8xe/TPe+OtXJpe6eddOeH3Vciy9E4alty5gybUzGP/Np3CWa0+nT/1nT2cdn9uwpVbneR4dg/XvLmBt6/dp0wqvr1oOvrFxneZICCFNCQXDhDQAYqEQu75dCmkNbUWizobh/tkwPc2K1JXAzAzdJoxljovz8lVuBVUlKeohxCIRc+zbQX9FtKrrL6xIfqu0nbsrTK3UL2alTbu++Qk39h5S+VxGQhL+nvMBnly7pedZ1c6zB4+YP/ONjOAW2NyAs9Fcyz6hGP7hu6zH9v/0K2Kuq/f9l8lkuHP4OJaOnIhzG7ew/h0AQFBoN3y8bxvm79iIt9etQsu+PZkbTiYW5ug2fgwW7N6M9sMHaecLUlNg9y6sftuPLl3F8+iYWp8vMSIK/8z/lLX7onnXjpi2YrHe0yYIIaShomCYkAbi/rkw/DP/s2pXrhLvRdIW6Qaky/hRrDy/Kzv3qt13VSwUstrs+LZro7d2M95KwXBklWNTHrFX9jwM1GJJJpUiLT6B9ditA0ex9o15WDZqEuJuhxtkXrXRkPOG3QKbY8qy78DlVn78uLRtF67t2q/xuYRFxTj62xr8PHYKHoZdYT3HM+LDs2XVW8h5RnxM+uFrVu67rvV7g70qfHb95jqf88m1W9jy8SLW74WQvr0wafFXsLC1QdcJYzD4vTfRd9aUBnfThJDGxMrRAQPmzMTMlUvx+qrlGD7/Hdh7ehh6WgQA39ATIISo79n9R+DxK//Z5jxPg5WTI3gvVwF6TZuES9t2Q6KwUkLqHy6fh15TJzLHIqEQl//brdE54u/eY1ZpzW2s4eTng/S4hBpeVXfyAUReeiZynqdVOTblkWJF6cBqK2XrUrMObZk/S0Ri7F3ys0bF6eqL5IePIZVKmYDSKyQYV2p4TX1gaW+H1/9YDoGZGfPY48vXcejnVXU674ukZ9gwdyGCenbH6E8+ULvdFI/PR/85M7H+nY/qdH11eLcJgX+n9sxxwt0IJMjl/dfF/XNh2LnoR7z24yLmsQ4jhqDt0IHg8SpXiEd8VH7dXd/+hIyEJK1cmxBSs0HvzMaAN2eCZ1T5+a1l357oN3s6ru05gP1LfmkQKTqNFa0ME9KAyBebAYDjf/wPN/YeZI6tnRzRaTT1GW4I2g4ZAFvXypZZtw8fR2FWjkbniL/D/jCtj7xhY1MT1gpTVfnCFZ4/iWP9kjfUyjCHw4Gv3Pfn2cNHDTIQBoDSwiJWMNMQVob5AgFmrVrO+plPi43Hlo+/UitHXh2PLl3Fz2On4NbBY2q/Jii0G6ycHLVy/eoo5gprY1VY3p3Dx7FvyQrWY/KBcAXf9m0wd/P/WEW8CCG6M2TeHAx+9w1WICyv2/gxmLTkaz3PisijYJiQBqSZ3MoCAMTdDsf5f7axgo2+r08FV8WHIFK/9J05hfmzVCpF2L/bNT5H4r1IVh65nx7yhj1bBrF2J1SXLwyUb+eWD9wMVVHauZkvzG2smeN4hQJkDc0zuX7DTr7eMLG0MOBsajbp+y/g3bqyJ3Jhdg42zPsYpYVF1bxKcxKxGGlyRdvUYefmqtU5KHLx90PLvj2Z4+fRMXh06arWr3Nlx148uHCpxnHmNtaY+P2XWr8+IYTNzsMN/d+YUeO49sMGKX2+I/pDwTAhDYj8ynBWcgpy09KRnfwc4cdPM487eHqgzeD+hpieEp6REaycHKn/pYKAbp1Zq6sPzl9CZuJTjc9Tkl+AtNh45ti3ve6DYZ+27BzL6vKFKyQ/rNwq7eTrDYG5WTWjdUPxexN/+57e56BNinnD1eXHGtqgt19Hu2GVxarEIhH++fBzZCc/18n1FAtq1ThergCVLvSbPY11XNsK0upw9FZvi7hP21asYl6EEO3rNn40qz5CdbpPHKfj2ZCqUDBMSANh6WDP2toWd6uy4I/ih6v+b0zXWzElVVwD/DHph6+x5NppfHP2EH64cgof7vwHnceMoFVrlK/ey7uwaVutzyWfd2jr6sLahqoLPu0qi2eJSoVKBbJUUcwbNkQhH/l8YalUigQ1gvj67Nn9R6zj+hoMtx3cH4Pfe5P12O5vl2otX1YVTc5dnJ+PNB3m2du5u6LtkAHM8YtnyWr1Ea8NWzcXjbY/B3bvqpN5EELKebdpVfOglxS7NBD9oWC4keALBLB2djTIigvRD/kP8wBY1W/T4xIQeeYCc+zavBmC+4TqaWZsbQb3x/wdG9Fp9DAYCQTM4x7BgZi4+EvM+n1ZveqLyuFyYe/pARd/P71sNXUPCkBA107McUJ4ZI15t9VR3O6ryxZLHA4HPnK/3J8+eKhW0Y9kxSJaLfSfN+zXoXJXRWp0LEoLCvU+B216/iSWtaJZH/OGPUOCMekHdi7cuQ2bcfuQ+jm9tZHy+AmSIu6rNTbqzAWIhbrLHe8zcworreD8pm1ay5FWJF+YTB3GZqY6mQchpLxoniY3p2ihwHComnQD59OmFXpNn4SQfr2YX7jxd+7h8vY9iDh51sCzI9qknC98l3V8bv1mtB7Qhznu/8YMPDhfc/6YNrm3CMCUn76tslAEAAT37oHRn3ygVOxF34xMBOg1dRK6vTqGWU2ViMW4f+4izm/cyurlqk195HKFAeDCP7VfFQaA+LvKRbTuHjlZp3NWxdHHC2bWlX2Ck2rIF66g2EtV39sz7T3cYe1cWSQp/u49vV5fFyQiEVIexzB5uF4h9SsYtnF2wut/LIeRSeUNsaizYTj2+1q9XH/fjyvw7qa/IKgh4PNt1wYmlhY6uTliaW+HzmNHMMf5mS9wW4PiXpoqeJGl0fj8zBc6mgkhTZO5jTU6jByKLuNGwsXfT6PXvkh6pqNZkZrQynADFvraeMzb+jfaDOrHuvPs16Etpq/4ARMXf2nQrbJEu/zk8oWzU1KV2tk8e/AI0VdvMMferVuieZeOepsfAPSZNaXaQLhCl1dGwcLeVg8zUs3E0gLvblqDYR+8zdpWzOPz0WZQP8zb8jdra6O22Lq6oM2gfsxxRkJSnW9Y5GdkIis5hTnWZd6wcr6wesGwsKiYlROt7yJafh3bso4bevGsCvJFtKydHfVSFVkdxqameH31z7BysGceS3n0BP99/p3e+qAnP4zG/+a8j6wa8pKdfL0xfcUP4PK1vyrTa9pE1u6YsM07dJqfXJSbh0eXr6k1ViwSIeIU3TAnRBUOh4PmXTth+Px3MPbzj9D39amwcXGuduzU5d9j0dlDGP3JBxoHwgBwY9/huk6b1BKtDDdQgd27YOznC6od03nMCGQ9S8GZv//Rz6SIzljY28KlmS9zrLgqXOHsun8R2L0Lc9z/jRl66+lqbGqC1gP7qjWWb2SEdkMG4tK2XTqelWqTFn9V7Uoaz4iP1378BunxCUh9olll2ur0mjaJdeMqbPN2rQQH8XciYO/hDgBweVk1uSg3r87nVaSY05So5lZUoHyrdEX/V2c/H/AFAp1uT5Wn2HKqMawMA8pFtLxCgnH/XJiBZlOOw+FgytJvWFvh8zNfYMO8hSgrKdHrXJIi7mPpiFcR3LsHgnp2h8DcDAVZ2Xj28DHGf/Uxs6244vfp3sXLtXZtE0sLdJ/4CnNcnJ+Pa7v2a+38VbmwaRuCQrvVOO72wWMat3IjpCnwalWe3uHs58N6fNj7b+Pu0VPY+8NylJWUwuplK8su40Yyv39VKSsthbGJSbXXfPEsBfdOnNHG9EktUDDcQPV7Y3rNgwD0nj4ZF/7drrcPnUQ35PMdAXa+sOLjifeimKCledeO8GrdEk8jH+h8jpb29uBrkAvs36UDru89qPder06+3mjVv3eN43hGfPSaOgk7Fy3RynVNrSzR5ZWRzHFBVjZuHzqulXMn3L3H6i/t0661TrbI+7arXBnOSEhCUU6u2q9NeRSNdkMHAihfgXdt3oy1sqlLfnL59hkJSY0mCFDcyu8ZEqTXYJjL4yGge2c4enlCKpEgMSIKbYcMQEi/yn9folIhNs77BHnpmXqblzypRIL75y7i/rmLrMdL8grw+qplTJ5e91fHIjPpKS5u3qGV6/aY+ApMLMyZ4yvb90JYXKyVc1cn9uYdHFj6G8Z89mGVY2Ju3MaBZb/pfC6ENDSeIcF4e/1qlekVXB4PHUcNhXtQAHJS09CiR9cq83xFQiGizlzA9b2HkPokFq+vWl7trq3i3DydV7UnVaNguAGydXWBv5r9yMysrRDcuwcidVS9kuiH4t933C3VK8MAcGbdv3jjz8p83P5vTMem9z/V2dwqiDS84RLStxe+CzuO6CvXEXUuDA/DrtSYt2fv6YGWfUNhZm2Fouxc3D93ETmpadW+RpF8i5eatB0yALu/XwqpuO4Fb7q/Oo5V4ObStl1a++WXEM6ujOzXvq3Wg2FzG2tWMRBNi34lK1Sd9ggK1EswbOXkCAcvD+Y47o7qG0kNUWbiU5QUFML0ZeE3fRbR6jJuJAa9+wZsnJ2qHbf9q8U6y7+vi0cXr+DQz6tYQePIBfOQ9Sylzv92jEwE6Dn1Vea4rKRUr7tgLm3bhbS4BPSd+RoCeyhXjD65Zr3eb0IS0hBM/P6LGusMuDZvBtfmzVQ+lxoTh+t7DuLOkZMoyc9nHl8z+z20GzIQ3SaMgUfLFuBwuZBJpExNBa9WwegwYgjuHDmhvS+GqI2CYT1zDWiGzmNGwsHbAxKRGIn3onDrwBG1tjQam5rAt10bdJRbAVKHnY5brRDdk1/ZyklNQ3ZKapVjH128gufRMUz7mpC+veDSvBnSYrS33VeV/MwXyEhI0qh6osDMFK0H9kXrgX0hEYkRe/M2os5exP3zF1nFYCzt7TDhm8/Qsm9P1utHffw+Is9cwN7Fy1Gcl694egDlq5BuLQLg07YVfNqEIKhXD7XnZ2xqAlNLS41WQFXhGxsjdMoE5lhYXIyrO7W3ZTIjIQkFWdmwtLcDoJu8Ya/WIaxjdfOFKyi2V3IP1k9FaT+F70XCHd219NE3mUyGZw8eMdXJPVsGgcPh6Dwvd8BbszB07pwax534c129LuR4adsuOPp4ocek8u3MXC4XU5Z+hz9nvq1Wy7CqdB47kvm3CADX9x6s83uIpmKu30LM9VuwsLdFcK9QTPz+C+a5ln166rS1FSENkV/HdlUGudUpLSpC+PHTuLH3cJU3eKViCe4cOcEKdv06tMV7//zFHI9YMBcPLlxCaWGR5pMndULBsJ4Ym5pi0g9fsYrnAECr/r0xZO6bOPrbGqU7xzw+H16tW6J55w7w79oR3q1DNNqGWqGstLROcyeGZW5rw3qDlu8vXJWz6zdj2s+LmeP+b0zHtk+/0cn85F3ZsRdjP/+oVq/lGfER2KMrAnt0xbivFiIp4j7unw1D3J1wTF32PWt1rwKXx0Pbwf3h7OeD1TPeRmlBISzsbeHTphV82rSCd5sQeLYMYlW01ZSplUWdP8h2GDmEVUzoxr7DrLvG2pAQHslUE/cICoSxqQnKSrT3b18pX1jDYLg4Lx/ZKamwc3cFoL/2Sn4KLckaS/GsCk+jHjLBsKmlBRx9vJCRkKSz63mGBKsVCItKS5X6n9dHB5b+BjsPNybPVmBmitl/rMDvU2bXams3l89Dn5mvMccSkRhh/27X2nw1VZiVg1sHj2LYB28zAXqrAb1x5NfVBpsTIfVR884dNBqf/PAxruzYh3snztSqHkL8nXu4c+QEOowYAgCwcrDHoHdm49DPqzQ+F6kbCob1gMPlYtbvSxHQrbPK540EAoz57EPIACSGR8C/c0c079IRvu3b1LhdQx3Vbakl9Z/ih/mq8oXlRZw6hyFz58DR2xMA0HZwf5xYvQ5Zz5J1MUXGi6c1n19UKsSOr3+AnbsrQvr1ZlrDyONyufBt15qVo1od1+bN8MG29eAZ8astZFEbH+/bhis79+Hc+s0ozNY815TD4aDPDLkPx2IxLm7RTl6ivIS7EUwwzDPiw7t1iFaLp8n/XRTn5yMjPlHjc6Q8fsIEw24B/uDyeVrZgl4d+X8/2c9TNd5WX98prkR4hgTrNBgOnTxerXFGJiZoM7ifztp8aYtUIsGWhV9h3pa/mZuO1s6OmP3HCqye8bbGH3LbDR0EOzdX5vjOkRPITUvX6pw1JZNKcf/cRXSbMAYA4ODpAdcAf6Q+iTXovAipT4xqKHKlaOun37C6JNTG4V9Wo2Wfnkx9gdDXJuDm/iNIi42v03mJZqi1kh60Hdy/ykBY3phP5+PDnf9g5IK5aBHatdpAWN3V3pgbt5Feiw+tpP7QJF+4gkwqZa3KcHk89H19SjWvqDsLO1vWVjxVMpOeYe2b7+PeiTM4t2ELVk15A98PGIV9P/6CmOu3IRGLa319J1/vGgNhqUSC5EfRKNGgpyjf2Bi9p03CF8f3YMi8OTB5mZ+pruA+oayt45Gnzim1xdIGxRVPbW6V5vJ5rOrbSRH3a7UVN1luqzTf2BjOfr7VjK47M2sr1q6KxrYqDKioKK3jvOHg3uqnGQRrkJJgSMKiYmx4byEKsrKZx9yDAjBl2bfgcNX/mMThcNBv9jTmWCqV4tzG+rE6HnXmAutYvic9IQTITVP/97JEJNZKn+6CF1k4+dd65pjH52PsF9V3iiHaR8GwHnSbOFatcdX1BC4tKsLDsCs4+PPvWPHKNHzXdwSe13BXtzg/H/uWrKh2DKn/5PsL56ZnsHrKVufO4eOsFYlOo4frrA8ph8PBpB++gpWjA/NYwt0IHF35F67s2Ivzm7bh77c/xLKRE5F4j13sKS89E1e278HaN+fh2z7DseOrxbh//qJWCrwU5ebhYdgVHFu1Fmtefw9fdhuI316difXvfFTjFmKRwg0ngZkZBs6ZhS9P7EW/2dNgbKreXeS+M9k3Ic7/s02zL0JNz6NjUFpUmWuk2E6oLtwDA1hbzTXdIl0h5SE7b9gjWLf9hhVvCDTGYDg/8wVrO69nyyCdXk++QrI2xxpaTmoaNs77mPW+E9K3F0Z89J7a52jZtyerBV7UmQt1XjnSltibd1CSX8Act6JgmBCWeyfOQiwSqTU26lwYhEXaqQ5/+b/drJVg/07tmc4LRD9q3CbtMd0G7TZ6Kj0e+W4Kkv6uvIvq/5kjfN6yg7EDH7m3S3B//nPkR7A/TFoECRDyuxvsuppBlCvB043ZiP4+A5Cyz63OuRoSn9atah6kQFxWhsR7UYi5cRsxN27j2YNHStsJ186ei4mLv0LLPqFKr89NS8e6dz7S6XY5onvmNtZwC/BnjjXZ8i4Ri3Hhn/+Yaql8IyP0mTFZJ/koPadORFDP7sxxYXYONi/8SuM7p8V5+bh18BhuHTwGY1NTDP/wXbW3ZQLlH2gfX7mOpIj7SLwXVeUH0cSIKPz1xlxM+OYz1vcXAITFJbiyfTfOrPsX3SaMRb/Z02BuY808b2ZlheHz30XPqRNx5u9/cH3PQUgUfoHaurrANcAfjj5erIDsyfVbdSrMUx2pRIKkiPtMn2mv1i21tg25rvnCFZIVimh5BAXi1oGjtZ5XTRRTDBpr0aCn9x+ilXN5OyP3Fs3BMzJS+pnUloKsbFireVNNfqW1IXga9RD/ffk9ZvxS2U6tz4zX8CIpGdd211zwrt9sdsvDcxs2a32OtSURi/Eg7DI6jhwKoDy1xMHbEy+Snhl4ZoTUD4XZObix9xBTUK8qErEYFzZp76a2VCzBvh9/wbsb/2QeG7lgHh6GXdFLOzaiQc7w1QHxkJRURq3F8ZUtQfw/dUTAl054+GkaCqNL4TffEd1O+uJCmxgI08u3PRrZcNHtpC8KHglxc1wSzP2MEfyzK8DlIHpRukbnakg4HA44PPUX4DMSn2LfkhVICI+ssTdwUW4eNs77GE6+3ug4cij6vzmDee7JtVuUc9AI+Cqs7qmTLyzvxr5DGDBnJizsbAEAXcePwdl1/6pVvVxd7kEBGP7hu6zHtn+1uM5biMpKSvDg/CWNguHNC79Su6fy08gH+OWVafBt1xrNOrUHX2CMnJRURJw+z7R4uvDPNlzfcwC9p09Gr+mTYGJeudJl5WCPcV8sQJ8Zr+HUX+tx58hJuAX6Y8i8t5hiPIq0+QtUlfi7EUwwLDAzhUdQoNI22tqQD4YlYnGtz1nwIgv5mS+YHQTuQbpdGZZfHS/Iym60NwefRj1kemfzjY3hFuCvs3ZG906cQe/pk9Ube/yMTuagS5GnzuHoyr8wfP47zGNjv/gIWckpeHLtZpWv8+/cgVX/IPrqDSQr7IQwtKgzYUwwDJQX8Dy/casBZ0RI/XJw+e+wdXWpMh1EIhJjx9fabxcXd+suwo+fZlaErZ0dMfDt16nQnZ6oHaXl3ipB7o3K/8oyy1cbuAIO/D9xRMyyTCSuycKLs0W4MzEJMhng815l9VTvt+zBNeXi9vgkvDhTiKS/s/FkcTqazXcA35Kr0bkaEplMptGd1/vnwhBz/VaNgbC8jIQkHFu1lrUK5hmi261yRD+adWrHOta0GFpZSSkubt3JHAvMTNFz6kStzK38fGaYtnwxq8p52JYdeHzpmlbOH3vrjtpBdWbiUzyrRZCWEB6JM3//gxN//I0b+w4r9TouLSzCyTXr8ePQ8bjw739K/ZTt3F0x6Yev8cXxPZi3ZV2VgbBMKoVUottiUQkK24C1tVXaR6541vMnsbWqnFlBfnXYLdBfo5xMTQjMzOAeVFmxujFuka6gWERLl3nDV7bvVauneGpMXLXBY312bsNm3DxwhDnm8fmY/ssSODerOse9/xvsVeGz6+vPqnCF6KvXWekhrQf0NeBsCKl/JCIR9i75WelxsUiEu0dP4vcps3H36CmdXPvwL3+wVoJ7TZ2oUatKUnt1/hRi290MRtY8pO6uXGmSFMuQfiQfToMtmcechlgi81QBxAWVq8vPd+aBZ8aFfW9zjc7V0Mj/Uq1x7H71xyp69vAx82dnPx+1cxpJ/dVMLl84LyNTrWrNiq7s2MsqGBU6eTwE5mZamd/YLz6Co48Xc5z8MBpHf1ujlXMD5duHwjarV3n5/D/bdNpftSgnF4dX/IGfhk/Atd0HlIp92bq6gG9cdeszDpeL6b8ugamV7t7LkqIesnKefDvUvYiWjYszbJydKq9Ryy3SFeS3iQvMzJiK59rm3SYEPH7l5qdGHQwrrFJ4huguGM5KTsF/X3xf7b+13PQMbPrgM533O9alPd8tQ6zczUdTSwu88ecvsLC3VRrrEdyCVSQzKeJ+veziICoV4vHlyhuVXq2CYePibMAZEVL/VOyuqnBg6W/4sttAbPvsW52lOQHl9VNOr93IHPOMqJiWvqgdDPd/EoDhpSHo+yAA3m9WNpO3CBRAKpahMIZ9p7jwsRAWLQSscYXR7DElz0QQF0lhESjQ6FyKRopb1fo/fbi+56BarRXuHDlRp2Ib8h+IuDwe3AL108eT6IaplRVc5fOFNdwiXaG0oBBXduyVO68luk8cV+f5tR8+CJ1GD2eOhcXF2PLJ11rPVQz7978abyhd2rYLN/Ye0up1q5KXnok93y/DslGTcefICUil0ppf9JKZlRU6jhqms7mJhUIkP6i8Kebbrk21hfnUoa184QopCnnDutoq7dexLeu4MQfDpYVFrK4Buq4oXVZcrPLnSlhcjKu79uP3ybN13sZN1yRiMf6Z/znrd7Kduytm/b4MfAH784jSqnA9yhVWFKlQVTqkXy/DTETHjE1N4OLvB2c/H/CNjQ09HZUs7G3RecwI9JnxGjqNGQ5zWxtDT4kACO5VWf9EKpXi7tGTGu3WrIuLW3ay3ssDunZC60H99HLtpqzGnGFhmhiPF6Uh91YJODzAbaINWv/lDp4ZB/G/Z8HYlgdJoVSpCJYoRwK+ORccIw5kIhmMbHkQ5SpvERTlSGBkywMAtc/V0JTkF+Cf+Z/hg/82VLkl8MGFy9j17dI6XUf+QzAAeLZsoVS5l1SPw+HAMyQIVo6OKCspRuK9+3XaEloXfh3agCv381LbYBgALm3did7TJjEVgXtPn4xL23bX+g3e3sMdr3z9Ceux/T/+opNiLDKZDDu/XoK4W+HoOeVVVgXixIgoXNqyE/dOntX6dWuS9SwZ/33+Hc5t3Ir3Nv0JM2vrml8EoM2gfrgkt3Vd2+Lv3mMCWHMbazj5+SA9LqHW59N2MKyqiFb4Me1vO5PfIl5SUIjUmDitX6M+eXb/EZz9fAAAjj5eMLEwR2lhUfUvqqXQKa+yjnd/txRpMfFIjYlrVAVfSvLzsf69BXh/23qmiJ5Pm1Z47cdFeHLtJrzbhMDcxoaVX5gWG4+HFy4baso1enTxCsQiEZPa0mpAH1z+b7eBZ6U9du6u6Dd7OtoPH8y0pywpKMTtQ8dwbsOWWtWy4Bsbo82gfug4aihsXJwhKhUi5uZtXNu1v1a7tUwsLTDm0/loN2wQK8VIXFaGO0dO4uDylVqrVEw0wzMyQvOunZjjp5EPtFpjpSYSsRgHlv6Kt/6uLHQ6+uP38fjSNYN9Fm0KagyGM08VIvNU5RbLjBOF4Ao4aP6FE+JXZQEAVO6EqrhpLP9kVePkh6h7LjmH+bX/cLboVq1fqhGvVi1ZgbBUIoVIKERSRBSu7tyH++cu1nlLWfLDaEilUiaAorxhzXR5ZRT6zprK2rZZWliEmweO4OSf63T2wbIqzWrRX7gqhdk5uL73IHq+/BBraW+HLmNHsFaM1cXj8zF1+fesYlJ3j57ErYPHaj0/ddw+dAy3Dx2DjYszTK0sUZyXx2opYyhpMXEoyslTOxiWr0ytC/F3ItDv9cpep37t29YtGJbLF85Nz0BOat16JOc8T0NxXj7MrK0AgJXXqy18Y2PW6mhCeARkGqzgN0RP7z9Ex1HlxZG4XC48glsg9uYdrV/H0ceLlRefeC8K1/cc1Pp16osXT5Pxz/zP8Na6VUzg0mZQP7SpYrXmwr//1evt4aWFRYi5foup/u/Xvg0s7GxRmJ1j4JnVnWfLIMz530rmvaWCqaUFek55Fa0H9sXaN+ZpVEjP0ccLb/z5Cxy8PFiPuwcFoNe0STjxx984u/5ftc9nYmGOdzf+CfcWyu97fGNjdBk3Em6B/vjr9bmN6sZSQ9GsYzsIzCrTyB5evKL3OTy5dgsRp84x7zE2Ls4YMGcmjv3+l97n0lTUKmc4dW8ejO35MPMxQlmOpLwAlsKZjGx4EBdJIXuZVifKkcDIhqd0LiNrLrNirO65GhoOh4PQ1yYwx2KRCN8PGIUvuvTD/+Z8gKizYVr55VlWUoIMue0Vuu432ZiM+exDvPrt50r5iyYW5ug1dSLe+3etTnM9VWnWoTJfOP9FVp37VV745z9IRJX/iPrMmgIuX/nfZE2GznuLFWhkJadgz+LldZqbJnLT0pH6JLZeBMIViuX6d9akRIOxtZF4L5K1dduvDnnDxqamrNZTdV0VriC/Ouyhg23SniFBMJLbytqYt0hXUKzwraut0orV3S9t26WT69Qn8XfuYdc3P6k1NrhPzzqnJuhalNxWaS6Pp7I9Y0NjYmGO11f/rBQIy7N2csTsP1eAZ1R1bQd55rY2eHvdKqVAuAKXy8WwD95GDw06Hgz74B2VgbA8z5ZBGDz3TbXPSbQnSG6LNAA8unjVIPM49PMqCIsrV4J7z5gMBx3V1yB1LKAlkwGF0UJw+RyY+7NzMiwCBSh8XLkFszBayOQGVzDxMALfgsfkEqt7roYmoFtnVkW4yFPnUPAiSyfXeia3VdrJ11trhZIas7ZDBjArplVxC/DHeIVtwbpkamUJtxbNmWNtFGPJTUvHnSMnmGM7N1d0GD5Yo3MEdOuMvq9PZY4lIjG2fLyoyW/pun/uotpjo86F6XAm5cG2fFs1+T7HmvIMCWIVodJWMJwi13LG1MoSdh5uWjlvBcX+wk0hGH4eHcMqnqaLIlomFuboOLoy5z0vPRORZ85r/Tr10YMLl1jf36q07t8bLfv21MOMau/BhcusyvatBvQx3GS0pOOoobByqLnriIOnB9oPHwy+sTG4vOpvBveaNkmtAmND585hCpbyjIxgYmEOCztb2Dg7wcHLAy7+fuVF1rp3Rqcxw2s4W7nOY0bA2NRUrbFEe4J7VaY85KZn4Hl0jEHmkZuWjrPrKncc8I2MMPazjwwyl6ZA7T7D8lzHWUOYKUZJkgjCVDFEeRK4jbdGzI/lKzU8Uw6cR1ghaX0285qMEwVotsABPAtueV4wALdXrSEpliIrrHz7ac7VYrXO1dCETpnAOtblnfTkh4/QSe7DikdQYJ1yTZuCXtMmqTWu9cC+sHF2Qm56ho5nVF74SFv5wvLObdyCjqOHMefuN3s6bh8+odYWUgt7W0z+cRHrseN/rFVq69IU3dx/GAPmzGRy1KoiLC6uU8V4dSXcjWBWdG1dXWDj4qxWET9F2s4XrqCYN+zeIgDZyc+1cm4AaCYXDJeVlCrVU2iMJCIRnj+OYVaEdbEy3Gn0cFZ6xNVd+yAV67ZdWH3RceQQVn5ndbpPHKfRDTJ9K8zOQfzdCPi/TMVp3rUTTCwtlNrKNSTth6l/Y3fS4i8xafGXzLFELIZULIFEIoZUIoFULIFUIoGFnXLlcFVMrSzxw9XTrBuHdWVqaQHf9m0QfeW61s5Jqufo48XaBfDokmFWhStc+Pc/dBo9jOnY0SK0K0L69cZ9Hd9Qb4pqXBnuuMsLzT52gNMQCzgNt0S7fzzgPtEGT37IAGSAVChD7PJMNP/MCT7v2MGhnzk67PQChwskrK5c/Uz6XxakQhk67fGCQ39zeL1hi8BFTohb+YJpt6TuuRoSBy8P1p2mpMgHStvZtOnpff212GgMbJyd4N26pVpjuTweQvr31vGMytW1v3BVMhOfIvJ05UqOk683WqnxNXE4HEz+YRHrzvuTazdx4Z//tDKvhq4wOwf/ff4daxu6IolIjP8+/w5FObk6n0/C3QjWcW23SssHw2UlpUh5HF3NaPWpKqKlLVweD95y806KvK/UBquxeip3Y8rG2QlWjg5aOzeHw2FtBxWXlTXqXGFFfh3a1TyIGdtWdxPRkii5FX2+kRGrgm5DZOVU+591Hp8PIxMBTMzNYWZlBQs7W1g5OtS4cqx4Dm2z1uK/X1Kz+rJFuoJEJML+pb+xHhv96QdMIVSiPTUGw4VPhPCaaYeOu7zRcYcXLIJMED7jGRL/rAxOY5dlIuanDPh/6oTOB33At+Lh2pAElGVUfgAR5UpxbVACODwOOh/wQeA3zoj/PQvR37JXK9Q5V0PSYxI7l+Tyf7rNr3oeHcv64OfZsoVOr6cJgbkZfNq0gl+HtrBycjT0dABA41YGui5+VEG+v3BBVrZGBT9qIr/1BgD6vzGjxtf0mjYJLUK7suZUU6/Rpub+uTD8b877SIq4r/RcYkQU1s55X2+rRfF377GOfeUqK6uLw+GwguFnDx5pbRUw62kySosqC9K5B2svGHYLbM5avWwKW6QrPFO6Gaq9uhGBoV1ZNRXCj59pFEWX1KXuqjBQvlW2vucN3z/Lfi9q1b+PYSaiJfL5lY3FuK8+xqvffl5jjjHRjoqickD5zb6Y67cNOJty0Veus1aC7dxc1frMRjRT462sx1+l4/FXNW+vi/kpEzE/VV/QpvCRENcG1lzVVJ1zNQQCMzN0HjuCOc7PfIGIk+d0ek2xUIi02HjmzdOjHgTDVo4OGPTubLQfVtnqQCqVIvrKdZxauxFPIx8YZF7Wzo7oMfkVjV5ToodtZCYW5qxfftre5v48OgYPL15hdix4BAcisEfXKrdjeQS3wLD577Ae2/HVYp3lvTdkcbfDsWrqm3AN8IdbYHnO9/PoJ0h9ot+2PnnpmchKfg77l7m4frXIG3by9YaZVWUxGm1tkQbK22U9fxzDrKBpc2W4KfUXVvQ0iv1e6hUSjAfnL2nl3D1fY9dV0PWN3frmRXKK2mOzk5/X+xuFuekZSIp8wOyMahHaDUYmAohKG2Z9lidXb8Klma9aYxPCI5H88DG4PB64fB54PD7zZy6PBx6fDx6fh4BundXuUZwQHon0uASIy8ogLhNBXFYGUVkZJGVlEAnLIBaJIBVLMHLhPJipWYzTSGCMLq+MQpdXRiEhPBJXtu9B5OnzTWaniz4JzMxYOzribofXm1ZGB5atRGD3rsyKcN9ZU3Dr4LEG38u9PtH+vg7C6Dh6GEwsKlcoru3ar5c3seQHj5lgysHTA6ZWVijJz9f5dVVx8PLAuxvXwNqZvRLM5XIR1LM7mnfthK2fLGJVt9Q1Rx8v9J01FR00yAEDygN4bX2wrI5vuzas7VnxOsj5PrtuM2v7fv83p6sMhgVmZpi6/HvW9+nCv//h8WXKY6pO6pNYpD6JNegcEu5GMMGwi78fzKytUJyn/vuArvKFKyQ/imY+fFja28HKyRH5GXW/CSqfLywRiZEUqbxS31hlJj5FaWER83tHW3nDTr7erJ0h5cGEdrbMNxS3DhxFbzXrS9w8oPu6ANoQdfYCEwwbm5ogsHvXBpuPeHXXPoS+Nr7Grc3isjL8+9EXat3MHTrvLQyYM7PGcSX5BfjfnPfVupFgYWeL4Qo3l9Xh2641fNu1Rv6LLFzfcxDXdh9Qer80sbRAx5FD4d+5A4wEAuSkpuH2wWNIjNDue3djFNCtE+tzjqG3SMvLeZ6Gsxs2Y8h75RXG+cbGGPPpfGyYu9DAM2s86lRNmlSNw+GwWlCIRSJc231AL9d++kBhq1xL7bcuUQeHw8HMlUuVAmF5fCMjTFn6rdaryariERyI6b8swScHt6PLuJEaBcIA8DDsMrI0WB2oLcX+wrFayheWl3gvkrXi3KxDO5VVh8d9uZC1NfLZg0c4tpJ63TUEylulNVsd9mnbmnWcpOUPVCmPnrCOtbE6zOFwWFvCnz181GBXumpDJpOxtkp7tgzSynZdxdYxl5tAOyVFqU9i1QoUC7KycV1Pv+vrKuos++tpNUA/NTF0ITPxqcoUFUV7f1ih9q6mi1t3qtVX/fjqv9V+nzm/aSvunThT7ZiIU+dw5NfVyFJRVNDKwR6D3n4dX53ch+m/LIHfy5SqDiOGYNGZgxj7+Udo1b83WoR2RbcJYzBv6994Z8NqvaV4NVRBcosDAPCwHgXDAHB+41a8kFsJDu7dA8G9G35LtPqCgmEdCejehdVO6d6JMyjI0k9F7GSlYNgwRbQCe3SBa/NmNY4zEgjQY6Jm25UBwMhEgPbDB2HI3DkY9M5stAjtCg5X+Ue6Waf2mPO/lfhw5z9oM6gfq0ozUF78SLGgj6LctAzs/m6pxnOsDfl84cLsHKTH1ZxaUBtKucNvsvNQOowYgo6jhjLHwuJibP1kEW3RaiCUimhpmDcsvzKckZCEotw8bUyLoVxEq+55cU5+PqwPfU1pi3QF+SJaplaWde5NaWJhzupQkJeeicizF+p0zobqvy++rzZtpSArG+ve+VDr/1Z05UXSM6TGVKZwtOwdqpNCUPrgGRLMKpynKDctHZsXfoWb+w+rfc6inFysffN9ZCY9U/m8VCLB0ZV/4cr2PWqfUyaVYuun32Dfj78onTcjIQl7f/gZWxZ+hfObtuGn4ROwYe7HKndi8fh8tBnUD+9tWoOvTh3Aaz99A4GZ6laa/p074K2/V1HhpSpwOBwE9ezGHGckJNW7LcjisjIcWLqS9diYz+aDL6C/U21omO96DUBPhXZKl/9T/82yrlJj4iEuK2NyXQyVN9x2yEC1x3YcPRTn/9mKwiz1CrL0mj4JA+fMgpm1FevxrOTn2P/Tr3h86Spa9u2JfrOnV1ktOvt5KsL+/Q839h2GWFiGPjNfQ69pk1RWYE28F6n23OpCYG4GD7liQrpsixV99QaePXwMz+Dyn4+g0G6Y+vNiFGZlIzc9E4PemsUav/eHFXjxtH79giBVy0hIQkFWNizt7QBotjJsbmPNupmn7S3SAJARnwhRqZD5gOauhWBYqb/w7Xt1PmdDo9itwCskGJmJT2t9vk5jRrA+ZF/ZubfJtFNSJCwqxto356HDiCHoPnEcvF52a8hLz8SN/YdxZccevfye0KbI0+eZm9amVpbw79KxwbXz4fJ5mPDNp6wb3df3HUJeWgYgkyH50RM8vnyN1VtZXS+SnuHnsVPQZlBfdBw1DLauLigrKUXszTu4umt/rYImmVSKK9v34OqOvXCuSGHJzWP1h68Y9zDsMh6GXYaDtye6TxyHzqOHw1Qh59jWteZeyO5BAej+6jiEbd6u8XwbO/egANbnPkO3VKrKo4tX8DDsCoJ7l69i23u4o9+sKTi1dqOBZ9bwUTCsAw7enqyqdEkR9/Xai1UiEuH5k1jmF7WhKkpXfAhXh4WtLb67cAwFWdlIfRKL509ikfokDqlPYpEenwhxWRkzdtgH76D/G9NVnsfeww2v/7Ec+RmZsHFR/QsiLS4B5zZsQfjxU6wPdec3bUPYlh1o3rkjrJwdMHTe20xrg5Z9e+ol99q3XWt2vvAd3faIPrvuX8z87SfmuN2QASrH3T58HHcOH9fpXIj2JYRHovWAPgDKtyEbm5qgrKS0xtd5t1HMF47U+tykEgmeP4llbla5a2GbtHy+sFQqRYIO5l3fPXvA/l3jGRKEO0dO1Opciuk+IqGwSbVTUkUqluDWgaO4deBoeaElI75a/6bqq6izFzD43TeY41YDeje4YLjX1EmsopNJkQ+w57tlkEmlWjm/RCTC3aOncPfoKa2cr4JMJkNajHrFFV8kPcOh5b/jxB//Q/vhg9Fj8niml7y6ur06loJhFRS3SNenfGFFB5b+huZdO8Lo5Ypwv9nTcfvwcWSnpBp4Zg0bBcM60GMSe8vvpf92630OyQ8eM8GwrasLLOxt9X7HurRQ88rLlvZ2sOzWGQHdOjOPScRiZCY+ReqTWBTnFyh9fxVxuVyVgXBS5AOc27AZD85fqrLSp1QsQfTVGwAAM0srjPr4fQDlW7k7jR6Gi1t2aPw1aUI5X1i3wbB3q5p7LBfm5GLfkhU6nQfRjYS7EUwwzDPiw7t1CGJu1NwuQtfFsyqkPH7CBMO2ri4wt7WpUx9m+V6wqdGxKNVD9ff6Ji89E3kZmbB+2b7Oqw695luEdoODlwdzfO/EGb30yW4oJGJxg08bSX0ShxdPk5m/55C+vbB38c9aCyR1zc7dlRXMS8Ri7P5uaYOZv6bKSkpxfc9BXN9zEL7t22Di91/A0dtLrdc6envC3Ma6wWzj1xf5xavSwqJ6nV6TlZyC85u2YdDbrwMoTxf8cOcmSCVSSERiJNyLxNWd+xCng1ozjRnlDGuZwNwMncew2ylFntJtOyVVlPpNBmuv36S6HoZd0cp5eHw+XPz90G7YoBoDYVWir97Amtffw6opb+D+uYtqt7y4dfAoRMLKohjdJozR+NqaataxMhguys1DusK2KW1ybxGAvq9PrXGcqaUFBHJ9W0nDofhLXd2t0vLBcHFevlb7XMtLUcgbrks/TTsPN1axPsUCYk2J/E4k96CAWueBKqf76P/GLtE9+W4OlvZ28G3XuurB9cy4rz6GsakJc3xx8w6DV/LXl4S7EXhy7ZZGr6mp2nZTY2Fny+rH/uTazXp/g+vchs3ITc9gjs2srWFhZwtrZ0e0Hdwf7278E5OXLAKXT3/X6qJgWMs6KbRTuqqndkqKnj1ULKKl/63SEafOIV/Nqo2n/7cJF7fuROzNOxq1f6lOXkYmfps4C3+/Nb9Wd8mK8/JZfaGdfL3h37mDVuamisBMOV9Yl70q1b2xwOPz0XXcSJ3Ng+jO8+gYlBYVMcfqFNHi8fms1cTEiCid/RwqtueR//nXVDPFfOF6fHdf155GVb7/842N4arhdkqg/P0usIdcO6W7EU2unVJToVgQrVX/PgaZh6baDu6PoNDKwkdZyc9xau0GA85I/6oq7qVKcV4+rQoraBHajZVrXp+3SFfg8fng8qoP3zqOGorRn8zXz4QaAQqGtag8v6ryTnp5O6X9BplLelwiq9S/R0v9rwyLy8qw9ZNFrNVVVY7/8T+cWP03Di5bib9mz8XXoYPxXf9RWPfOhzjy25+4e/QkUmPiIBFpdlMhIyEJyQ8f1+VLwNVd+1jH3SeOq9P5quPTrjVrBUcX/YXlNevcvuZBL/l36ajDmRBdkUokrHYjXq1b1ni32K1FAKvqqK62SANAWmw86991XfKG5bdIA017ZfipQo2K2vQbDn2NvSpsiHQfoh/Poh4iL72yZ21DaLFkamWJ0Z99yHps35KfG3T+dm3cPXqSVVOlOrcOHq1VEbHGTL6KNAA8unzNQDNRX5dxo2DloFzoVVH3V8fC1tVFDzNq+CgY1qLAHl3g6FOZu3Hv+BmDVZaUSiRIeVzZx9NQRbTibt3F/96arzJ/JzctHTsX/Ygzf/+j9Fx+RiYeX76O8xu3Yttn32LFuKn4vEs/ZKco992rSp5CQ/raSIq4j+fRMcxxSN9esHSwr/N5VZFvqQTopr+wPGMTk5oHvUQtGRqueLkWSwIz0xr7+eorXxgov2GWFleZClCXXsPylaQzEpIaXFVfbXqm0F5P02DYxNKC1VYtNz0DUU20nVJTIJPJWH+/tq4u8Ag2zGcGdQ2f/y6s5H4Xhx8/rbIFUWNXlJOLi1t31jhOJpPh0aX6H+jpE5fPQ2D3Lszxs4eP1e5BbUhdx49WaxyXx0PnsSNqHkgoGNam0Cmvso4NnV8lvzpg5ejAyqfTJ76REav/7/3zl7DunQ+xZMgrGvX8k4hEuLH/iNrj7x45qdE8q3J1V+XqPs+Ir7M3l2adKoPh4rx8tatM1lbO8zSdjCX1S4LCduGatkrLB8MSsVjnlfBTHlXetHPw8mClmajLytGBVegpTsdV2Ou70oJCVp63p4Y7gzortFO6umNfk22n1FREyuUNA0DrgX0NMxE1+LZrzarhUZyfj4PLVhpsPoZ27Pe1uFnDZyMOh4NxXyyAwFx1L+KmyKdta1abqoawRZrD5bLaHtbEyc9Hd5PRAI/Ph2dIMPw7d9Bo/vpCwbCWOPp4sXJXEiOilO7O61vyA/YWYU0/EGmLYp7t6bUb8Pjy9Vpt17m+5wBK8gtqHJfy6AmeXLup8flVuXvkJCvvsuv40azgXhuMTU1ZRc7i7+g2XxgAbh06pvbY24eorVJD9fT+Q4hFIubYt0P1RbR821YWz3keHaPzbYfJCkW03GpRRMtPoTBYwp2IKkY2HfI3Q538fNT+EMzhctFjcmU9AZFQiOt7m3Y7paYg4W4Eq1J4RRX6+obH52P8ok9Zjx39bQ0KsrINNCPDk0ml2LloCda++T6izoahJL8A4rIyZCY9Y31fnHy9MfH7Lw040/olWK6KNFDex7fek8kg1aBSuqGrqvMFAgx+9w18dfoA5m/fgHc2rManh3bgo13/ot3QgQadmzwKhrVEvhcjAFzeZvj8KsVg3MNAW6Wby+WbFufnI+VxTDWjq1eYlYONH3zKCk4VZSWnYNMHn2otmBQWF7P6C9q5uaJFaLdqXqE5n7atwDOqzBfWdUslALhz+ARyUmte8U15/KTeNqEnNROVClm5875tW4PD4agca+vqwtpBosst0hXkV4aB2m2V9lNIMWjKxbMqyK/oc7lctbe9tgjtBgfPylX28OOnqZ1SEyCVSHD//CXm2NHHC87NfA04I9X6zJoCF38/5jjhbgRu7D1kwBnVHzHXb+Gf+Z/hqx6D8GmH3lg64lWsmfUuhMXFzJg2g/qh17RJBpxl/RHUqzIYLsjKVurCUh/JZDKNauEoLorpk7GpKd5Z/wcGvTObldIAlHc5mLr8ewz74B0DzY6NgmEtEJiboePoYcxxXkYmIk+fN+CMymUmPWMFjYZor2RiYc7KV469ebfOd6rib4dj5aTXcXP/EVaRsMLsHJzbsBkrJ72uVpCnias7FQtpjdXq+RXzhXVdPAsAykpKsP7dBcjPfFHlmMzEp9g47xOD310kdSO/Umpua1PlNiV95gtXeB4dw7rT7R5Ui5VhuXzh7OepWv/33xA9japdES1qp9R0RSlslW5Vz1aHHbw8MPCtWcyxWCTC7u+X6XwXVUOWkZCEXYt+ZD024sP3GlT7LF2wdXNh3VR5fPl6g/k5ur77gFrjREIhbh08qtvJVGPMZx8qfaZQ1P+N6fXifYaCYS3oNHo4TMwN305JkUwqZbXCkO+lpi/NOrZj9bWLvXFbK+fNTHyKnYuWYFGvoVg+ejKWjpyI7/qPxNGVf2mtNZO81CexSIyoDAxahHaDrZv2qvQ161RZ2bk4Px/P9dQnMS02Hr9OmIGz6zejMLuy4FBuWjqO//E/rHxtNnLT0vUyF6I78kW0AMBXoQ1RBUMEw2UlJchMfMoca7oybGZtBdfmzZhjWhUu9zw6lrU9Xr5dVlWc/XxYBWXi79xTWrknjdeT67dQWlh5A711PWuxNP7rT2EkqCzmeH7TVqTHJRhwRg3DvZNnWUW2eEZ8TFvxAyzsbQ04K8MK7tWDddyQdr/dPnyC1SWiKhnxSQZrpWVhb4sOI4eoNbbPjNd0PJuaUTBcRxwOh9WCQlxWhut7DhhuQgrkt0iY21jDzt1Vr9f378xuyROjpWC4QllJCdLjE5GZ+FTnBV6u7qwspMXlctF1/BitnNfY1IR1oyLhToReV2ILsrJx7Pe/8G3fEfi2z3B802cYFg8cgzN//4PSgkK9zYPoTkJ4JOtYMce2grdcMJyblq63GyEpcnnDTr7eGlUvV1zhoGC4nLisjFUJX52V4R4K6T7UTqlpkYhEeCiXN+keFAA7DzcDzqhSh5FD0bxr5eeJzKRnOPP3vwacUcNy5JfVrJub1k6OmLrse9ZiRVMiv0VaIhYj+uoNA85GMxKRCOveXVDj52n3oAB0GDm02jG60qpfH/CNjNQa69O2FWxcnHU8o+pRMFxHgaFd4ejtyRyHG7CdkirKecP6XR2W/+WVl5HJqnDa0EScOsdade4ybiSrL3BtebdpxXrTiL2t25ZKVZFJpSjIyq5XP79EO0ry85EqV53cV0UwbGxqCrcAf+ZYH6vCFeR3sHB5PLjKzaMmiv2FE+5S8awK8jlwNi7O1baFK2+nVJnuk5uWjvvnwnQ6P1L/KG2V7mf4nsPmNtYY/fH7rMf2Ll4OsVBYxSuIIolYjM0Lv2TtAGvepSOGzJ1jwFkZhpGJAP6dKgu7JoRHNrgb/yX5+Vj7xjz8OfMd3Dp4DAnhkYi9eQdRZ9nv2a98tZDVaUFfLDXcdWBhZ9hdChQM11HP1xTbKe0y0ExUe6ZUUVp/RbQs7G1Z2xdjb97R27V1QayQf2Fpb4eQ/nX/oGCIfGHS9MivmNq5uSrdifVqFcy6uaPXYFihorQmW6Xl84ULsrIb9A03bVNsi+VVTapM57EjIDAzZY6vUDulJunx5eusWhz1ocXSiAVzYW5rwxzfOnhM67vMmoK89Exs/fQbVo2G/m9MR8s+oQaclf75d+rA2n3UEFoqVSX+zj3s+GoxVk9/C3/Nnot/5n/G6v4hMDPD1OXfa2XhRhMlhVUXuVWltNCwNyMoGK4DJ19vtAjtyhwn3otirXDUB1nPklGcX7maqc/2SvJ33gDtb5E2hGsKhQu6v1r3QlrywXBJQWGdqm0TUhXFFVM/hRZLhsgXrpDyuHYVpQVmZqyCW7RFmk2xiJZnFVulOVwuqyOCSCjEDWqn1CSVlZQg+up15tinbStYOToYbD7NOrVH5zEjmOOinFwc/uUPg82noYu5fgsnVv/NemzykkWw93A30Iz0T36LNNCw8oXVsW/JCmQmPWOOPVsGYej7b+t1Dpq0qcpISMKLp8k6nE3NKBiuA6X8qm31a1W4gnzesEdwiyrbqmibfxd2MBx7o2GvDAPlhbtirlcG9XVtIG5kImDl8iXc1W++MGk64u/eYx37tm/LOpYPhstKSpESrb/CSaUFhchKTmGO3dUMhr3bhLDueFMwzJaR+JRVEKmqIlpBPbuzPgyHHzttsMIrxPAiz7C3Wob062WQefCNjTFBoafw4V/+oFZfdXRu/WY8DKsMVkytLDHj1x/BF6hfq6Ehkw+Gs1NSG10RNmFxMbZ9+g0kospCvn1nTUFAt856m0N2Sqravb8vb9+j49nUjILhWjKxMEfHUZWJ6XnpmYg8Y/h2SqrIb5U2tbSAvZ7yB+T7C794mtxo2p1c3cVus9RtQu1Xh71bh4BvbMwcx90yTL4wafzy0jORlfycOZYvosXhcODdJoQ5fnr/od63yMrvqnFp7geeGsU3/BSqYlMwzCaTSll1I6rqKEDtlIi8h2FXWB+kDdX6pP+bM+Do48Ucx9y4jVsHjxlkLo2JTCbDf198z/p94B4UgHGff2TAWemHi78f7NwqC8k2tlXhCs8ePMKxVWtZj03+cZHecnNf+epjWNrb1Tju/rkwXNu1v8ZxukbBcC0pt1Oqv/lVikW09LFV2tbNBQ6elUF3zM2Gv0W6wv3zF1m9eTuOHqpR9Vt5ivnCcZQvTHRIfqu0i78fzKytAABOfj4ws7JintPnFukK8i18+EZGcPH3rfE18sFwSUEhq0gYKSefN2xmZaVUTMXZz4e1YhB3J1xp2zppWkry8xF7q3InV7OO7Zj3Cn1x9vNBv9nTmGORUIg9i5frdQ6NWUl+PjYv+ALisjLmsS6vjGJtSdcFgZkZekwej/k7NmLx5ZNYdPYQpi77TmVRR11Q3CL9UIPtvA1N2L//sapkWznYY9KSr3W+O3Twe2+i6/jRrMekCjseJWIJzq7fjH8XfAmpxPCxEwXDtaC6nVL9za9KNkARreYKLZVirzeeYFgqluDG/sPMsZmVFdoO7l+rc8n3Fy4tLKIPoUSnlLdKl38AMWS+cAVNi2jxjY3ZKQbhlGKgytP77Juhii2W5H+XAcDlbbQqTIBIuarSPD5fr0WWOBwOxi/6lNVl4cy6f/FCLg+S1F3yw2js+/EX1mPjvlwI9xYBVbyibpyb+eLjA9sw7osF8GwZBDNrK1g7OaLdsEGY++9ajF/0KThc3YYl8sFwWUkpYm823t14MpkM279czNquHBTaDT2nTtTZNbtPHIdBb7/Oeuzg8t+xZPA4pMcnMo8VvmzpWV8WESkYroUWod1Yd9fDj59mlauvb3JS01j/GPSxMqyUL9zItv9e332QdTer26vjND6Hqg/z9eEOGWm8lIpovcwbVgyGkyIMsDL8mB0M15Q37BkSBCO5HDfaIq3aM8UiWnJ5w6ZWlqw+lOXtlC7qbW6k/npw7iJrNadV/z56u3bnsSNYuz7S4xNxfuNWvV2/Kbmx9xCrS4aRiQDTf10CE0sLrV7H3NYGb/3vd9i6ulQ5ptuEMRj2/ltava48UytL+LSp/F0Xe/NOo2/PVfAiCzu+/oH12PAP32UVntSW1gP7YuwXC1iPnd+4FRe37EBuWjqSIu4zj1s62uu9wnV1KBiuhYaYX5X8sHJ12D0oUOd33+TzhZ8/ia3XNwtqIzctHY8uXWOOvVu31PjNxbt1S9aHecoXJrqWkZDEujHGrAzLfUBIj09k9dPWl8KsHOSmZzDHNf178lMoAEbBsGq56RmstA75G3Cdxyi2U9pLN+QIgPI2ZYnhkcxxQPfOEJiZ6ex6Vo4OsHMvb/k2YsFc1nO7v1sKiUiks2s3dXt/+BnPoyu7WDh4emCylrfThk4eD2tnxxrH9Zo+WWd5rYHdu7ACsMa8RVre40vXELZlB3PMNzLC1GXfw9jUtJpXaaZZx3aYsvRbcOVii9uHjuPoyjXMcc7zVObPXC4X1i5OWrt+XVEwrCEnX28E9qhsp5RwN6LetVNSRb6IlsDMtE4VkGvi5OvNasXQGKpIq6JUSEvDNkuUL0wMIUHuA65HUCBs3VxY7weG2CJdIUXuvdQtoDm4PF6VY+VXjspKSpXSQUilp3J5w+4tAsDj88HhclkdEUSlQtzYe8gQ0yP1VNTZyqrSRgIBgnp20+r5+QIBek2fhM+P7sY35w7jyxP78OWJvaz6Bdf3HFTa0UK0S1QqxL8ffYGSgsperyF9e6HPrClau0aXcaPUGsc3MkJHud0q2qTUUqkB9xfW1NHf1rDqcjj5emPMZx9q5dyuAf6YtWo5qxjso0tXsfObJZDJZMxj2c/ZRXTlC5kZGgXDGlLKr2oAq8IAkKzHIlrNu3ZiHTeG/sKqRF+5geyUyjtd7YcNgomFeTWvYGPlCxcVKeVMEqIL8h8seUZ89Jo2ifW8QYNhuZx5Y1MTViVZeVweDz7tKlezkyLvQyIWqxxL2P2GjQQCuAY0Q3DvHrD3cGMev3v0JLVTIixRZy+wjrVZVdrE0gLvbliN0R9/wEo7k78BVpxfgCO//am1a5KqvXiajB1fsbfTDnv/bdbnlNpy8vVWa1W4gnOzmosnaorD5aKF3EJWakwcctPStX6d+koiEmHrp4sgLC5hHusybmSt691UsHN3xZy1v8FUblt9UuQDbF7wpVI+sPzKMFBeaLe+oGBYAyrbKSn8sqivnikW0aqixYY2+HeuzBeWSiSIv9M4VzxlUimrcJrAzAwdRgxR67V8Y2N4t65sZZMYHlVvCgmQxk1xlUXxjn3ivUgYirpFtNwCm7Oq+dMW6eo9u694MzRY6cbupQZyY5foT87zNDyTS7EK6tWdtfpTF5OXfM1q56aKsYmAtUpMdOv+uTBWbjaXx8OMX3/EpCWL8P7WdXh/23pM+OazGhdTOFwuvNuEYOi8t/DR7n/x6aEd1Y5XpItUDc+QINb260dNZIu0vIyEJBxY+hvrsfHffAY799qt0Jrb2mDO2pWsnaAZCUnY8N4ClJWUKo1XbK9aXf64vlEwrIFOY0awcmau7NzbYAKY/MwXyEvPZI49g3VTUZrD5cK/c+WdxGf3H6G0sEgn16oPbuw/xOrHqO5Waa9Wwax2THG3KV+Y6EfK4ycQFhczx/I5o8V5+chMfGqIaQFgb5MGAPdg1cGwX8e2rGMKhquneDO089gRCJDbwRN3OxypT2L1PS3SAESdvsD8WWBmxmrDVVvOzXwR0rdXjeP4xsYIVajRQnTr2Kq1rJQtcxtrdBo1FN5tQuDduiW6jh+N+Ts2Yury71k3RkwsLdBmcH9MXrII354/gve3rsOAOTNrVZlasR2oNgT36sE6ftiEtkjLu7n/MO6dOMMcm1paYMrS76pNSVLF2NQUb/z5C2v3Vl5GJv5+e36VO4xy0zNYNzpqG4TrAgXDauJwuQh9TS6/Siis1+2UVHn2sPINxq1Fc3D5mv3wq8O9RQDrTm7MzcaZL1yhMCuHtZXMtXkz+LRtXePr/ChfmBiIVCJhVXWUl3gvipXjo2+56RmsYntVrQzLF8+SiMRIilT99ZByIqEQhdmVhdMU2ytd2rZL31MiDYTyVunedT5nx5Hq7aAqH6ub/FGimlQiwZaPv4aotPoqy+2GDsSs35ehz4zX8M6G1fj+4nFMX/EDOo4aWqcCWKWFRQg/drrWr69KUM/KfOHi/Pwqfwc2Bbu/X8ZK8fNp2wqD3pmt9uu5/PIdA/K/R0oKCrHunQ+Ro5AXLE8qliAvo3JRjlaGGxAbF2eE9OuFIXPnwMGT3U6pKCfXcBOrBfnVASOBAC7N/LR+jeaKLZUaab6wvKs72YW0uk+seXXYv2Pl6rmwuEQnd0IJUcXEwhzmNtYqn7NxcYKZtWG3JabIbZV2C2yuVNGUw+HA72UVbKB8FaGmD25NmbmNNeZuXgsLOzuVz0slErx4lqLnWZGGIiMhCWlxCcxxyz4963wj3cbFWe2xZtZWWq16S2pm4+LM2rlWlRahXTFy4Tz4d+5QZZuc4rx83D12Ctu/WqzW7pP0uATWziVtsHJ0gIfcLqPoKzeadNX80oJCbPv0G1adjf5vzlAq6qoKh8PBxO++RIvQyvxrcVkZNr3/CVKfxNX4evlgmXKGGwAXfz/MXr0CX57ch1m/L8OAN2ewnm8ohbPkKeWN6SBvWL6lkkgoRIIBi/HoS9ztcGQkJDHHbQb1qzLYAACekRErVyrxXmSD2W5PGjaBmRne3rC6yh6+boHN8d4/f8HUylLPM6uULFfx0tTSAnYe7qznnfx8YG5rwxzH372np5k1TNN//bHatBguj4c3/lyhUfE/0rTIrw6b21ijWcfaF1UyNjWFvdzCQk2kUinEorJaX49orruGnTEUpcbE4dyGzVg9421803sYtn36DW4fPIa1b77P6maginebEFbvc21QrILelKpIVyUxIgqn1m5kjrlcLl5b+m2NN8OHz3+XVTtJKpVi66ffqL27MVuuiJaNs7PO27yqq37Mop7xbhOCeVv+RnDvHqyeWRVkMhkcvVVXOa3P5HsNA9qvKM3j8+Ert30x8V5Uo29oXuHqrv3Mn/nGxug0ZkSVY71CgmBsasIcx92iLdJEPwbPfbPGegEu/n4Y/uG7epqRMqUiWgp5w/ItlQAg/vY9Hc+o4fLr0Bb+alSDtXF2qvY9izRtUWcusI5b9dd8q7SxqSn6vj4VX57YC+/WLdV+XfztcLpZrGeK77k1EQmFeHT5GvYtWYEfBo/FinFTcXTlX0i4G8FagS3MzsHq6W/hr9lzcfvQccTfuYcn124i4tQ51vle+WphlZ0EaiNILl9YKpXi8ZXrWjt3Q3Z23b+sINbG2QkTv/+iyvG9pk9C39ensh7bt2SF0vtDdeSLaPGM+LCWK75lSBQMK+ALBJjx64/V3iXncDiYvOTrerXfXR1FObmsPAGPltotouXdJoQV5DXWlkqq3D50jLVVs9uEMVU2rKd8YWIIxqYm6KxmwNNxxFCDrQ7L90IEAI8gdgGWZnLBsFQqRYIBq1/Xd51GD1d7bOcx6o8lTUvKoyfISn7OHLfq37vK32+KBGZm6Dd7Or46uQ8jPnxP43zSy9v3aDSeaIGaf7dAeVeVRT2HYP07H+HKjr3V5oxWiL15B9u//B5/znwH/5vzATYv+BK3Dx1nnheYmWHa8sXgGRnVavryeEZGCOhWWSzwadSDBpfiqCsyqRT/ffYtivPymcdC+vVGt1fHwjWgGQK6dYJnSDC4fB7aDx+E0R9/wHr9qbUbcU1uIUgdij8f9WWrNAXDCtoM6gdrp5r7ofGNjdWuHFyfyOemujZvprU2CQC7pRJQ/obXVJTkFyD8RGXRBwcvDzTv2lHlWPmVmrKSUjy7/1DlOEK0yadta1YvwOoYmQjUWlHUhezkFJQUFDLHilu6feWC4dToWJTKjSVsmlTrtHWrP5U9Sf0jv1XaytGB1RpQFYG5Gfq/MQNfntyH4fPfYaU2AIBYJIJUIq32HPdOnMH9s2G1nTKppbTYeLXHJkU9UNlGR1P7lqxgdTJwDwrAiI/eq/N5m3Vsy+oCQ1uk2XLTM7Bz0Y+sx175ciEW7t2Kt/5ehfnbN+Db80cweck3rDHX9hzAyT/XaXw9CoYbiDYD+6o9trUGY+sL+a3SfCMjuAb4a+3c8vnCpYVFSjnKjd3Vnew7ZN1eHac0hsfnw7tNK+Y4MSKKVcSAEF3RNCdUYG6YHFKZTIaUx5Wrw/IVpe083GDj7MQcxzXSHubaIipTP9dSrMFY0vREnWEHpTN/X4o5a39D57EjWcWWBOZm6P/mDHx1cj+GffC2Uv0MUakQF7fsxJLB47DunfmsFecK4rIyhG3ejm2ff2vQ6vZNlSadUrTVVUVYXIwtn3zNeh/qNXUiWvYJrdN5g3qyWypRMKzs/rkwViFYxTxecxsbcHmVj90/fxH7flhRq2vJ5wwD9ecmrOryb02YWTWFjxRVVySpvlIqotWyhVZWJo1NTVh3iuPv3Gty1fqe3X+I5IfRTL5Nyz6hsHJyRL5cKXnPlkGsvq5xt6i/MNGP/MwsjcYXvNBsvDalPIpmVqbNbW1g4+KM3LR01hZpAEi4G2GA2TUc8bfvISi0W80DQb2aSfVMra0gk0qZD8qW9nYI7NEVgT26Yui8Odj22bfwadcavadNUlmER1QqxNXd+3F+41bmvSU/8wV+Gj4BLXp0hV+HNuAZGyM7OQXhx05X2auU6F7crbt4dOkqqx2RKjE3buPJ1Rtau27Koyc48uufGPPZh8xjExd/hV/GT0NeemY1r6yafPGsvPRM1o1WUun54xi1xuVlZGLLx4tq/fk+NzWddUwrw/WU/N75Gsfmqz+2vlAsTqOtIlq+7duCZ1R5b6Up5QvLu7qr8u4aj89H13EjWc9TvjAxlKTI+6yaAdXJf5Fl0DQHxfcp95d5w34d2P9+qJJ09W7uP6z2iu+VHXt1PBvSUPl1bIdZv/1UZeVXK0cHvL3+DwydO0cpEC4rKcWFf//DkiHjcGj570o32WRSKR5duoqjK//CoeW/4/J/eygQrge2LPwa0dUUmoq9eQf/fPi51lfuL23bhQcXLjPH5jbWmLLsO3B5mrfzcvDyYBXienSJVoWrEjplglrjTCwswDeq/TqquKwM+XLvAXb1pPYSBcMKFBvMVzv2tPpj64uS/AJkJj1jjrVVRKu5Qr5wUw2Gw4+dRmlhEXPcZfxo1pu4f6fKD/OiUiGeRlG+MNEPmVSKsM3b1Rp7aesug27fT3moUFH65VZpX7n+whkJSSjMytHrvBqawuwcHPp5VY3jbu4/QrtUSJVGLpjLutmtimJBrbKSUlz45z8sGToOh1f8gYKsbF1OkWiZsLgY6975COve/Qj3z19E9vNU5KSm4WHYFWyY+zHWvvm+zuo17Pz6B+SmZzDHzTq0w4A5MzU+j3wVaYCC4ao4N/OFi7+fWmMFZqYI7t2j5oHVyJG7KU/bpOupeyfOYPj8d2Fpb1ftOLFIxFoFbEiSHzyCo7cnAMClmS+MTU3qXADBX65YVGF2DtJiam6+3RiVlZTgzpET6DHpFQDlpeqDe/fA/XMXweXz4NOuNTM2MSIKEpHIUFMlTdCV7Xvg3iIAncdWXVU6/PhpnN+0VY+zUpaR+BRlJaVMdXr3oEBYOTow71sA5Qur68qOvZCIxRi5YJ5S3rhEJMalbbtw5Lc/DTQ7Ut+5BwXAKyRY7fFlJaW4smMvLvy7jW5WNXAymQyPL13D40vX9Hrdotw8bPvsW7yz/g9mMWHgW7MQd+uuRrvpgntVbvMWi0SIud40F2lqUlO8o8jCTrPxinJS0+Ddpjytsr505aGVYQWiUiH+/egLCItLqhwjlUiw65uf1N5yWN88lasozeXx4BYYUM3omplaWcG9ReU5Ym/dbdJFL64qlJrvNqG86rhHcAtWVUPaIk30TSaTYeeiJdi56EekKtywykhIwp7Fy7Ht028gk1Zf5VXXZFIpnj+pzGHyCAqEn9yqMEA5rpq4vucgvus3Eru+/QnX9xzEzQNHcOTX1Vg8cDQO//KHwf++Sf3lEaRZz9ntX32PI7+upkCY1En87XCc/t8m5pjL42HK0u/UrtUjMDNjpaXF3w6HsLhY6/NsDEoKCjQaX9cdAfIVpY1MBLCw16zdmi7QyrAKCXcjsHr6Wxjx0XsI7N6F9dyzB49wfNX/EK3FogH6lvzgMevYs2ULJNahV6d/p3bgyuUSNdUt0hXSYuKQcDeC2dLZIrQr7Dzc0IzyhUk9cXP/YdzcfxiOPl4wt7ZGcX4+MhKSDD0tlpRHT+DzsvK6tbMj2gzuz3o+4Q4Vz9JEWUkJbuw9hBt7Dxl6KqQh0aDnLACUFhTVPIgQNZz5+x/4d+7AfHaydnbExMVfYeO8j2t8bfOuncCX61P8kKpIVyn1SRxyUtPUWqWViMR4XE0uuToUK0rbubka/OYZBcNVeB4dg7/fmg97Tw94BgeCw+MhPS4Bz6PVq7hWn6U8egKpVMoEsHXNG/bvwu6nG9vEg2GgvJCWfH5jtwljWG2sREIhnkY+MMTUCGFkJj5F7Wp06l6yQt5wSL9ezJ8r8tcIIbqVHpug9lipVIqM+ETdTYY0KVKJBNs++wYL9mxhVoRb9glFzymv4tK2XdW+Vn6LNAA8unhFZ/Ns6KQSCa7u3Ifh89+tcWzk6XPIz3xRp+sp9xp2NXj9HNomXYOsZ8m4d/Iswo+dahSBMFBeGEF+FUiTfCBV5PsL56Sm4cXT5DqdrzGIPH0BRTm5zHH3V8fBv1NlkbGkyAfU15OQaqQoVJSWL0RHW6QJ0Y/EiCillIqqPL50jVX4iJC6ykvPxM6vf2A9NmLBXKbDQFVayLVUykx8Sp9LaxD27/Zqq4cD5alU+5f+VudrKd7Irg95wxQMN1Hy/YadfL0hMDerZnTVrBwd4Oznwxwbsh1LfSIuK8Pd46eZYxMLcxgJjJljHp8HntwWHkIIW1psPMRVFJijYJgQ/Tm68i9Ia8grFwmFOLlmvZ5mRJqSBxcu4+LWncwx38gI05YvZtVgkeceFABrJ0fm+CFVka6RRCzGhnmf4MI//7E6ogDlW6PvHj2J1TPeZi3y1JbiyrCdu+ErSlMw3EQlP3zEOta0SEYF/y4KLZWoWh+A8qJigd07V/m8b7s2eH3VcnD5mvfOI6QpMLEwR3Gu6l7umYlP9TwbQpquRxevYOfXS6q8OVVaWIRNH3yG5IePVT5PSF0d+fVPVuqMo48Xxn25UOXYoJ6KW6QpGFaHRCTC4V/+wPf9R2Hzwq+w/6dfsP3LxVg8cDS2ffatVgJhoHx3qnwvcVoZJgbzTKmIVlCtztO8MztfOIZWhgEAoz/5AE4+3tWOaRHaFX1mvKanGRHScNh5uGH+jk2wcrRX+fz0X5bALbC5nmdFSNN1+9AxLB3+Ks6s+xdpsfHIS89EyuMnOLryL/w0fEKNWywJqQuJSIQtn3zNqgjdcdRQdBg5VGlskFy+cGlREeKpWKlGhMXFiDh5Fpf/24Pbh47ppEe4/OqwrRsFw8RAnkfHQCIWM8e1LaIlvzKckZCE/Iz6Wo5HfyzsbNFu2EC1xvaY9AorF5KQpo7L42H26hXVbp2ytLfDG3/+UuU2OUKI9uWkpuH4qrX4eewUfD9gFH6dMAPnNmxGYTa1USK69yLpGfb+sIL12CtfLYSDXP95c1sbeLVqyRw/uXaL9VmX1A/yecO0MkwMRlQqRFpsPHPsGaL5yrC9pwfs3Co/sDb1lkoVAnt0ZZX0r46NizOrRzMhTV3Lvj3h0sy3xnHWzo7oOEp5VYAQQkjjdOfwcdw+dJw5FpiZYfrPPzA1WFr06Mpq9UlbpOsn+fZKJhbmMLWyMuBsKBhu0uT7DTt4emj8w9hcMV+YgmEAgKmlhWbjrTQbT0hj1nHkELXHdhih/lhCCCEN374lK1h1I9yDAjD5h68xfP47GPzuG6yxjy9f0/f0iBqUimgZeKs0BcNNmHLesGZFtORbKkmlUsTduquVeTV0mm4ZK8zO1c1ECGmArJ2d1B5r4+Ksw5kQQgipb4TFxdjyydesgm7thg1Ev9nTYe/pzjxWVlJa604pRLeUew1TMEwM5NkDhYrSwepvleZwOGjWqT1z/PxxDIrzVFd+bWoeX74GYXGJWmMzEpIaTf9qQrShrLRU/bEl6v07I4QQ0nikPHqC02s3VjvG2NQE7/3zF+w83PQ0K6KuHLlt0gBg62bY9koUDDdhqTFxrDtrmuQNuzT3g6W9HXNMW6QrlRYW4ca+Q2qNvbhlZ82DCGlCNGnPRu87hBDSNKlTeMnS3g6jP35fD7Mhmshu6CvDJm58DM0NxkhxK/DM2S/3/8wRAxICMaygJbqf94NVGxOl11sECdD1lC+G5bfEwKctEPitk8pZqHMuUjcSkYi1KumpQUVpf4WWSrE36UOpvKMr/0JsDdvGb+4/gmu79+tpRoQ0DNf3HKyyn6miKzv36Xg2hBBC6hsTSwu0Hz5YrbHBvUMppaaeKcnPR2lREXNs6IrSGgfDQctcIS6UKj3u/6kjAr50QuzPL3BzTCLEhVJ0O+kLgTOfGWNkw0W3k76ADLg5LglPfsiA34eOCPzWWeNzEe2QL6Jl6+oCC3tbtV4nny8sEYkRfydC63NryMRCIda9/SFOrlmv1KPtxdNk7FuyAjsXLTHQ7AipvwpeZOHAT7/VOO7kmvVIi4nTw4wIIYTUJ14hQTA2VW+RjMvjwbd9Gx3PiGhKPm/YzsDbpDWKLu1CzeA02AIxSzPRcnnlxLkCDvw/cUTMskwkrskCAORcK0b/uBbwec8e0YvSAQDeb9mDa8rF7fFJEBdI8QIA34qLwEXOiPs5E+ICqdrnItqhWETLI7gFHl+qvvoel8dDs47tmOOnUQ8od08FcVkZTv21AWfX/QvPkGCYWJqjMCsHKY+iIZPJDD09Quqta7v3o6ykBCMXzmOlYwBASX4BTv61AZe2UooBIYQ0RUYCgU7HE93LeZ4G1+bNABh+m7T6wTAXCFnphic/ZECUK2E9ZdvdDEbWPKTuzmMekxTLkH4kH06DLZkA1mmIJTJPFUBcULmy/HxnHoKXusK+tznSjxSofS6iHYpFtLxaBtUYDHu0bAETC3PmmPL2qicRi5F4L9LQ0yCkQblz5ATunTyLkH694BncAuBwkBYbj8jT51BWon6RLUIIIY1LtkIBppooFmwihpeTWrkybG5jDYGZGYTFxQaZi9rbpH3esgPPhMOs1sqzCBRAKpahMEbIerzwsRAWLQSscYXR7DElz0QQF0lhESjQ6FxEO9LjEiAqrfxee7SsuYhWc4V84Zibd7Q+L0IIkYhEiDh5Fkd++xNHfl2N24eOUSBMCCFNXOqTOCQ/jFZrbPbz1BpruBD9y05RrChtuNVhtVaGjex4CPzOGeEzkiETKz9vbMuDpFAKKKQSi3Ik4JtzwTHiQCaSwciWp7SqXDHOyJan0bnkjRS3UufLUC289i9tDKQSCVIeP4FP2/LvoTpFtOTzhctKSpEUcV9n8yOEEEIIIUTemXX/YOZvP9U47uz6zZBJlWsdEcOSXxkGyusWpcXGG2Quaq0Mt1jsjNybJcg4XlDlGJUpkBwVT1Y1Tn6IuuciWiG/VdrK0QFWTo5VjuUbG8OnXeXNh4TwCEjUrPxKCCGEEEJIXUWduYAjv66udsz5jVtxffcB/UyIaES513A9Xhm2CBbAa5YtrvSNB9+6PHbmmZX/38iaC5lEhrIcCfiW3PLQWu7mi5END+IiKbOaLMqRwMiGp3QNI2sus2Ks7rnkHeZHqffVqrDoVq1f2mgoFtHyCgnC/XOZKsf6tG3FKkRA+cKEEEIIIUTfzm/ahsSI++g1dSJa9ukJnhEfUokE0Vdv4NK23Yi+ct3QUyRVyFHoNWzIitI1B8P+AnCNueh5xV/puYFPg5C0IRspO3LB5XNg7m+Moidlla8NFKDwcWU+amG0kMkNrmDiYQS+BY/JJS6MFqp1LqI9z+4/ZB17tGyB++cuqhzr36UD6zj2BuULE0IIIYQQ/Uu4G4GEuxHgGRnB1NICpUXFEAspXqjvCrKyISoVwsikPC405Mpwjduks68U4Wr/eNZ/McszAAA3RiQg7pdM5FwthihPArfx1szreKYcOI+wQsbJyq3VGScK4DjIAjyLysu6vWoNSbEUWWHlzZfVPRfRnsykZ6zm157BVRfRks8XLskvQPIj9QoYEEIIIYQQogsSkQiF2TkUCDcg8nnDtq71eJt0WZaECVQrmHobAQCyLhVDUlS+lzl2eSYCvnSCKEeCwmgh/OY7gMMFElZXVp9O+l8WfOfao9MeL8T+nAkzX2MELnJC3MoXTLslqVCm1rmI9sikUqQ8esL0Dq6qiJbA3AyectWm427fpaIEhBBCCCGEEI3kpKbBydcbQD3PGVZX7LJMcLiA/6dOMLbnIfdOCa4NSUBZRmWSryhXimuDEtBqlRs6H/CBKFeC+N+zEP1dusbnItr17MEjJhg2t7WBnburUtlzvw7twONX/shQvjAhhBBCCCFEU/L9oq0cHcA3Noa4rKyaV+hGrYLh5M25SN6cq/R4zE+ZiPlJdeGlCoWPhLg2MKHGa6hzLqI9z+4/Yh17tAz6f3v3HR5FuX8B/GxPdtN7AoSEFjoivSgiKhYUe++93OvF7r22a//ZxS6Wa1fsBRVUxIL0XoRQQwukbsqWbP/9sUlINmUnIe3LnM/z5NFsJmcPSSbZd+addxoMhvuGXC+8dQkHw0RERERE1DKhi2jFpaeieNeeDu+h6NZKdPgLXVG6sanSda8XrigqRsGOvPauRUREREREh5nQew0ndNJUaQ6GCQBQsmcvnBUHFygLXUTLEh+HjJy+te9vW8ZVpImIiIiIqOWs+0LvNdw5t1fiYJhq7fn74Nnh7gNzoNFoat/vMzpkijRvqURERERERK0QOk26sxbR4mCYau3dePC64ciYaCRmdq99v+4UaQDYunR5h/UiIiIiIqLDR3lRMXyeg4sjd9btlTgYplq7QxbRqnsbpbpnhkv27mtwNIeIiIiIiEiJgN+PsoKDdxRK4DRp6mx7m1hEKy4tFck9e9Q+zlWkiYiIiIjoUNQ9ucZp0tTprPsPwFZqrX2/e/VgOPSWSlw8i4iIiIiIDkXdFaVjU5Kh1es6vAMHw1RPvUW0BuRAo9WiT+j1wst4ZpiIiIiIiFqv7plhrU6HuNSUDu/AwTDVs6fOdcMmsxmpvbLQd/TBwfD+rdthK7E29qlERERERESKlOaH3F6pExbR4mCY6qm7ojQAHHnKVMSmJte+v3UpzwoTEREREdGhaXh7pY5fRIuDYapnT8giWuPPPaPe+7xemIiIiIiIDlVXuNcwB8NUT0VRMcoLi2rfj4yJrv1/v8+H7StWd0YtIiIiIiI6jJQdKIDf7699vzNur8TBMDWwJ2SqdI29f+eiqtLWwW2IiIiIiOhw4/N6UVFUXPs+rxmmThcZE42Y5KRGP+ZyOKHRaDq4ERERERERHY46+17DHAxTLXNsDG5651VkDh7Y6Mf7jhmB8x+5jwNiIiIiIiI6ZNY6K0rHpad2+DiDg2GqdeY9tyO9b+9mtxl52kkYfca0DmpERERERESHq9I6Z4b1BgOim5ih2l44GCYAQGxqMoYeP1nRtkddfF47tyEiIiIiosOddX/9FaUTOvi6YQ6GCQAwcNJE6PR6Rdum9+2NpJ492rkREREREREdzqz79td7P75bx64ozcEwAQheL9ye2xMREREREdUVema4o1eU5mCYAACOsooWbl/eTk2IiIiIiEgNGgyGO3hFaQ6GCQCw8bc/4fN6FW2bv2UbinfvbedGRERERER0OPNUuVBZUlr7fkIGp0lTJ6goKsbaefMVbfvn+7PbuQ0REREREalBZ95rmINhqvXlY88gf8u2ZrdZ9tUcLPt6Tgc1IiIiIiKiw1ndqdK8Zpg6jbOiEi9fdj0WfvQZquz2eh+z7j+Ar//vOXz6wGOd1I6IiIiIiA43dc8MGyMjEJUQ32HPrexeOqQaVTY7vnr8WfzwwmvIHj4UERYLKopLsHP1OgT8/s6uR0REREREh5HS/JDbK6WnwVZq7ZDn5mCYGuWyO7B54ZLOrkFERERERIexumeGgeB1w3s2buqQ5+Y0aSIiIiIiIuoU1v0Nzwx3FA6GiYiIiIiIqFOEnhlO6NZxt1fiYJiIiIiIiIg6RZXNDkdFRe37PDNMREREREREqtBZ9xrmYJiIiIiIiIg6jbXOitLxGZwmTURERERERCpQWufMcGR0FCKiozrkeTkYJiIiIiIiok5j3R9ye6UOum6Yg2EiIiIiIiLqNJ21ojQHw0RERERERNRp6l4zDPDMMBEREREREalA6JnhjlpRmoNhIiIiIiIi6jT2snK4HM7a9xM6aEVpDoaJiIiIiIioU9W/vRLPDBMREREREZEK1F1RmtcMExERERERkSrUvW44KiEexsiIdn9ODoaJiIiIiIioU5V2worSHAwTERERERFRp+qMFaU5GCYiIiIiIqJOVfeaYQCIT2//FaU5GCYiIiIiIqJOVbqv/jTphG48M0xERERERESHOVtJKbxud+37vGaYiIiIiIiIDnuBQADW/QW178dncJo0ERERERERqUC9ew1zAS0iIiIiIiJSA2ud64ZjU5KhMxja9fk4GCYiIiIiIqJOVxqyonRcWmq7Ph8Hw0RERERERNTpQu81nNCtfa8b5mCYiIiIiIiIOp01v/7tldp7RWkOhomIiIiIiKjThZ4Zbu9FtDgYJiIiIiIiok5XXlgEn9db+35CO99eiYNhIiIiIiIi6nR+nw/lBUW177f3mWF9uA3Sz4xBr1uSENXPBJ1FC+cuD/Z+aMW2p4oR8ARqt+tzdzKyrkuAMUmPshVObJiRj4q1VfWyogaYMHhmBhLGmuEp82H326XIfagQ8Nd/TiVZREREREREdHix7j9Qu3BWp18zbEzUo+Q3O9Zeuw9Lp+Vh9zul6PvvFAx6+uAp6z53JaPfPSnY9lQxlp2eB6/Nj3HzsmFKPTjWNsRpMW5eNhAAlp25C1seKUSvW5KR89/6y2UrySIiIiIiIqLDT93rhmNTk6HV6drtucKOMHe9UVrv/ZLf7DDE6JB1QyI2/CsfWpMGfe5MxtYnipD3SgkAwLrYgSnb+yPrpkTk3l8AAOh5XSK0kVqsOHsXvJV+FAPQx2iRc38qtj9VBG+lX3EWERERERERHX5K66wordPrEZuSDGvI/YfbSquuGXaX+KA1agAA8ePNMMTqsP+z8tqP+xwBFMypQMrU6NrHUk6MRtFPlfBWHpwTnT+7HDqzFomTLC3KIiIiIiIiosNPR64orXzusRbQmTSIPTIS2f9IRN7rwTO3UTkm+L0B2La66m1u2+xCxrlxte9H5ZhQvMBWbxvnHg+8dj+ickwomFOpOCvUqd4hiv8ZDaxu/acSERERERFR2wk9C9ye1w0rHgyfXDEIuojgieQ971nx953BksZ4HXw2f4NFsDxWH/QWLTQGDQKeAAzxOnjKfA1yPVYfDPG6FmURERERERHR4cdaZ5o0AMR3a7/bKykeDP911HbozFrEjTKj370pGPJCBtb/Mx8AEGhsfKqp/m/dDza1Xd1NlGbV8Z1+ffPlm3H/8lZ/KhEREREREbUh6/7660QldIUzw+Wrg7c2Kv3LAXexF8Pf6YHtzxXDbfVBH60NXn1c54yuIU4Hr92PQPU9kz1WHwxxDVcCM8Rqa88YK80iIiIiIiKiw4/P40F5YRFiU5IBtO81w61aQKt8tRMAYM42wJbrglavgaWPsd42UTkm2DYfvPbXlutCVI6p3jYR3Q3QR+lgy3XVbqMki4iIiIiIiA5Pda8bjs9ov2nSrRoMJ4wPrv7s2OmBdZEDnnIfMs6Orf24LlKD1GkxKJxXWftY4dxKJJ8QBV3UwafMODcWPocfJb/bAUBxFhERERERER2erPsOXjccn54KjUbTzNatF3aa9Jjvs1A03wbb31UI+IK3P+p9SxL2zS6DY4cbALDtySL0uycFHqsPtlwXes1IgkYL7HyppDZn1+slyP5HIkZ9noltTxXBnG1Ezv0p2P58ce3tlvyugKIsIiIiIiIiOjzVPTOsNxoRlZiAyuK2Hw+GHQyXrXCix6XxMGcZEPACjh1ubLqnALteP1hm2xNF0GiBPnelwJioQ9lKJxafuBPuwoMX+XrK/Fh8wk4MeSEDo7/OgqfMhx0zS5D7YP0LpJVkERERERER0eGpNORewwnd0jtnMJz7QAFyHygItxm2Pl6ErY8XNbuNbZMLi4/f2SZZREREREREdPhpcHul9DTsWruhzZ+nVdcMExEREREREbUHa8iZ4fZaUZqDYSIiIiIiIuoy6l4zDATPDLcHDoaJiIiIiIioy3A7q2Artda+n9CtfW6vxMEwERERERERdSn17jXMM8NERERERESkBnWvG+Y1w0RERERERKQKdc8Mm8xmWOJi2/w5OBgmIiIiIiKiLqV0X8jtldrh7DAHw0RERERERNSldMSK0hwMExERERERUZfS4F7D7bCiNAfDRERERERE1KWU5odMk+aZYSIiIiIiIjrcVVXa4Ky01b6fwGuGiYiIiIiISA3q3Ws4g9OkiYiIiIiISAWsdVaU5mrSREREREREpAp1zwybY2JgspjbNJ+DYSIiIiIiIupyGqwo3cZTpTkYJiIiIiIioi4ndEXpBA6GiYiIiIiI6HDX8Mxw2143zMEwERERERERdTl1rxkG2v5ewxwMExERERERUZdjK7XC7ayqfT+hG6dJExERERERkQrUu9cwzwwTERERERGRGtS9bpjXDBMREREREZEq1D0zHJ2YAEOEqc2yORgmIiIiIiKiLql0X/3bK7XlVGkOhomIiIiIiKhLas8VpTkYJiIiIiIioi6pwb2G23BFaQ6GiYiIiIiIqEsqzec0aSIiIiIiIlKZyqJieD2e2vcT2nBFaQ6GiYiIiIiIqEsKBAIoO1BQ+358BqdJExERERERkQpY97XPvYY5GCYiIiIiIqIuq+6K0jHJSdDp9W2Sy8EwERERERERdVnWOotoabVaxKaltEkuB8NERERERETUZYXeazihja4b5mCYiIiIiIiIuqzSfSG3V2qj64Y5GCYiIiIiIqIuK/TMcFvda5iDYSIiIiIiIuqyygoK4ff5at9P6MZp0kRERERERHSY83t9KC8sqn2fZ4aJiIiIiIhIFaz5bX+vYQ6GiYiIiIiIqEure91wXGoqNNpDH8pyMExERERERERdWmmdew3rDHrEJicdciYHw0RERERERNSl1Z0mDbTNVGkOhomIiIiIiKhLazAYboMVpTkYJiIiIiIioi6t7jRpoG1WlOZgmIiIiIiIiLq0sv0F9d7nNGkiIiIiIiI67HndblQUl9S+n8Azw0RERERERKQG9e81zGuGiYiIiIiISAWsda4b5jXDREREREREpAp1zwwbIkyISow/pDwOhomIiIiIiKjLs+6vf3ulkaedDJ1e3+o8DoaJiIiIiIioS+s9cjiOufyieo+deus/cO9PX2HcOWe0KpODYSIiIiIiIuqyciaMxXWzXkBCt4aLZsUkJ+Hs++/ECddf2eJcDoaJiIiIiIioSzJGRuCixx+AztD8dOipN12D7gP7tyibg2EiIiIiIiLqkoafdDws8XGKtp144dktyuZgmIiIiIiIiLqk/hPHtcu2AAfDRERERERE1EVFRFmUb2tRvi0AhF2HOv2sGHS/OB6xR0bCEKuFLdeN7c8WIX92eb3t+tydjKzrEmBM0qNshRMbZuSjYm1VvW2iBpgweGYGEsaa4SnzYffbpch9qBDwo8VZREREREREdHirKC5pl20BBWeGe92SDK/Nj4237ceyM3ah5HcbRnyYiaybEmu36XNXMvrdk4JtTxVj2el58Nr8GDcvG6bUg2NtQ5wW4+ZlAwFg2Zm7sOWRQvS6JRk5/02t93xKsoiIiIiIiOjwt/rHn5Vv+8NPLcoOO8JcPj0P7hJf7fslC+wwpRvQe0YS8l4ugdakQZ87k7H1iSLkvRIciVsXOzBle39k3ZSI3PsLAAA9r0uENlKLFWfvgrfSj2IA+hgtcu5PxfaniuCt9CvOIiIiIiIiosNf7sIl2L91O9L79m52O5fDicWfftWi7LBnhusOhGtUrHHCmBIcR8ePN8MQq8P+zw5Om/Y5AiiYU4GUqdG1j6WcGI2inyrhrTw4Jzp/djl0Zi0SJ1lalEVERERERESHv0AggP/dfBfKDjR9YtTjcuG92+9BWUFhi7JbNfc4fpwZtr+D1/BG5Zjg9wZg2+qqt41tswsZ58bVvh+VY0LxAlu9bZx7PPDa/YjKMaFgTqXirFCneoe05p8RtLr1n0pERERERETtq2TvPjx//pU47trLMfK0k2sX1fJ5vdjw6x+Y/8a72Ld5S4tzWzwYTjrWgrTTYrDm6r0AAGO8Dj6bv8EiWB6rD3qLFhqDBgFPAIZ4HTxlDc8ye6w+GOJ1LcoiIiIiIiIi9agsKcVXjz+LOc+9jNReWdDqdCjZsw/2svLwn9yEFg2GI3sacOT7PXDg2wrsfa+s9vFAY+NTTSMfbGq7upsozarjO/36JjuHc//yVn8qERERERERdSBPlQt7/85tkyzF9xk2xOswZk4WnLs9WH3pntrH3VYf9NHaBkmGOB28dj8C3urSVh8McbqGubHa2jPGSrOIiIiIiIiIDoWiwbAuUoPR3/aE1qjB0tPy4HMcPENry3VBq9fA0sdY73OickywbXbV2y4qx1Rvm4juBuijdLDlulqURURERERERHQowg6GNTpgxOxMWPqYsHRaHtxF9a/7tS5ywFPuQ8bZsbWP6SI1SJ0Wg8J5lbWPFc6tRPIJUdBFHXzKjHNj4XP4UfK7vUVZRERERERERIci7DXDQ17qhtSTY7BhRj4MCTrEjYms/VjF6ir4XQFse7II/e5Jgcfqgy3XhV4zkqDRAjtfKqnddtfrJcj+RyJGfZ6JbU8VwZxtRM79Kdj+fHHt7ZaUZhEREREREREdirCD4eTjowAAg5/PaPCxX3pvhnOXB9ueKIJGC/S5KwXGRB3KVjqx+MSdcBcevMjXU+bH4hN2YsgLGRj9dRY8ZT7smFmC3Afr3y9KSRYRERERERHRoQhZy1l9li9fjlGjRnV2DSIiIiIiImoHTY35FK8mTURERERERHS44GCYiIiIiIiIVIeDYSIiIiIiIlIdDoaJiIiIiIhIdTgYJiIiIiIiItXhYJiIiIiIiIhUh4NhIiIiIiIiUh0OhomIiIiIiEh1OBgmIiIiIiIi1eFgmIiIiIiIiFSHg2EiIiIiIiJSHQ6GiYiIiIiISHU4GCYiIiIiIiLV4WCYiIiIiIiIVIeDYSIiIiIiIlIdDoaJiIiIiIhIdTgYJiIiIiIiItXhYJiIiIiIiIhUh4NhIiIiIiIiUh0OhomIiIiIiEh1OBgmIiIiIiIi1eFgmIiIiIiIiFSHg2EiIiIiIiJSHQ6GiYiIiIiISHU4GCYiIiIiIiLV4WCYiIiIiIiIVIeDYSIiIiIiIlIdDoaJiIiIiIhIdTgYJiIiIiIiItXhYJiIiIiIiIhUh4NhIiIiIiIiUh0OhomIiIiIiEh1OBgmIiIiIiIi1eFgmIiIiIiIiFSHg2EiIiIiIiJSHQ6GiYiIiIiISHU4GCYiIiIiIiLV4WCYiIiIiIiIVIeDYSIiIiIiIlIdDoaJiIiIiIhIdTgYJiIiIiIiItXhYJiIiIiIiIhUh4NhIiIiIiIiUh0OhomIiIiIiEh1OBgmIiIiIiIi1eFgmIiIiIiIiFSHg2EiIiIiIiJSHQ6GiYiIiIiISHU4GCYiIiIiIiLV4WCYiIiIiIiIVIeDYSIiIiIiIlIdDoaJiIiIiIhIdTgYJiIiIiIiItXRK9nI3NuIPrclIW6MGTGDI1Cy0I7FU3Y22K7P3cnIui4BxiQ9ylY4sWFGPirWVtXbJmqACYNnZiBhrBmeMh92v12K3IcKAX/Ls4iIiIiIiIhaQ9GZ4eiBJqScFA37VjdsW1yNbtPnrmT0uycF254qxrLT8+C1+TFuXjZMqQfH24Y4LcbNywYCwLIzd2HLI4XodUsycv6b2uIsIiIiIiIiotZSNBgumFOJX7JzsfL83aj8u+FgWGvSoM+dydj6RBHyXilB8Xw7Vp63C4EAkHVTYu12Pa9LhDZSixVn70LxLzbsmlWKLQ8XoPeMJOijtS3KIiIiIiIiImotZdcMB5r/cPx4MwyxOuz/rLz2MZ8jgII5FUiZGl37WMqJ0Sj6qRLeyoNzovNnl0Nn1iJxkqVFWURERERERESt1SbzjqNyTPB7A7BtrX/W2LbZhYxz4+ptV7zAVm8b5x4PvHY/onJMKJhTqTirrlO9Q1pffnXrP5WIiIiIiIhkapPVpI3xOvhs/gaLYHmsPugtWmgMGgCAIV4HT5mvwed7rD4Y4nUtyiIiIiIiIiJqrTZbkSrQ2FRqTSMfbGq7upsozar2nX69oo6NuX95qz+ViIiIiIiIhGqTM8Nuqy+4AFZImiFOB6/dj4A3+L7H6oMhTtfg8w2x2tozxkqziIiIiIiIiFqrTQbDtlwXtHoNLH2M9R6PyjHBttlVb7uoHFO9bSK6G6CP0sGW62pRFhEREREREVFrtclg2LrIAU+5Dxlnx9Y+povUIHVaDArnVdY+Vji3EsknREEXdfBpM86Nhc/hR8nv9hZlEREREREREbWWomuGdZEapJwUvK1RRDcDDNFapJ8ZAwAo/LESPmcA254sQr97UuCx+mDLdaHXjCRotMDOl0pqc3a9XoLsfyRi1OeZ2PZUEczZRuTcn4LtzxfX3m7J71KWRURERERERNRaigbDxhQ9Rn7as95jNe//0nsznLs82PZEETRaoM9dKTAm6lC20onFJ+6Eu/DgRb6eMj8Wn7ATQ17IwOivs+Ap82HHzBLkPlhQL1tJFhEREREREVFrhazjrD7Lly/HqFGjOrsGERERERERtYOmxnxtcs0wERERERERkSQcDBMREREREZHqcDBMREREREREqsPBMBEREREREakOB8NERERERESkOhwMExERERERkepwMExERERERESqw8EwERERERERqQ4Hw0RERERERKQ6HAwTERERERGR6nAwTERERERERKrDwTARERERERGpDgfDREREREREpDocDBMREREREZHqcDBMREREREREqsPBMBEREREREakOB8NERERERESkOhwMExERERERkepwMExERERERESqw8EwERERERERqQ4Hw0RERERERKQ6HAwTERERERGR6nAwTERERERERKrDwTARERERERGpDgfDREREREREpDocDBMREREREZHqcDBMREREREREqsPBMBEREREREakOB8NERERERESkOhwMExERERERkepwMExERERERESqw8EwERERERERqQ4Hw0RERERERKQ6HAwTERERERGR6nAwTERERERERKrDwTARERERERGpDgfDREREREREpDocDBMREREREZHqcDBMREREREREqsPBMBEREREREamOvrMLENHhSaPRoMeQgYhLS4XHWYW8tevhrKjs7FpERERERAA4GCaidjD69Gk49qpLkJyVWfuY21mF1T/8hO9nvgq7tazzyhERERERgYNhRYyRkdDqtKiy2Tu7ClGXd8otN+LYKy9p8LgxMgJjzjoNvUcdiZcuux6VxSWd0I6IiIiIKIiD4SYYIkwYe9Z0jDv3DKT2ygIAlBUUYtmX32Hhx5/zzBZRIwZOmtjoQLiupMzuOP/he/HGDbd0UCsiIiJqKY1Ggz6jRyAjpy80Gg3yt2zD1qUrEPD7O7saUZvhYLgRUQnxuPb159Gtf796j8elpuCEG67CmDNPw+vX/QsF23d2UkOirunoS85TtF3/iWORkt0ThTt3tXMjIiIiaqlBk4/CabffjKTM7vUeL9m7D3OefRnrfl7QSc2I2hYHw424/LnHGwyE64pNTcY1rz6Lp06/CC6HowObEXVdkTEx6DtmpOLth009Fj+/9r8WPUdKdk8MPvZomGNiYLOWYf3831GyZ29LqxLRIYqMicbYs07D6DNORVLPHvD7fNi1dgMWzf4Sa3/69ZDOHMWmJiM6MRFVdjtKdu9FIBBow+ZEFM6IU0/C+Y/cC6224U1nErt3w2XPPoZP//s4ln7xbSe0I2pbHAyH6DN6BLKPHBZ2u/j0NIw87ST89ckXHdCqc1ji4xBhscBWauWgn5ql1eswaPJRLfqcE66/CjnjxmDnmnXYuWod8tasg6O8otFtY1KScd6D/0H/iWPrPX7qbf/Ahl9/x6f//T9eukDUQVKye+K6WTMRl5Za+5hWq0XvkcPRe+RwjD5jGt6ZcTfczqoW5Q46ZiImXX4heo8YXvtY8e69WPjx5/jrk8/h9/pa3NUSF4tRp0/DgKPHI8JiQWVJCVb/8DPW/vQrvG53i/Pak06vR0xKEgI+P8qLirvsVFSdXg+j2QyXw96q7wl1bdFJiTjngbsaHQjXdeY9t2PLomWw7j/Q4udI7N4NCd0z4HW5sG/zVridztbWBQD0HTMSQ4+fDEt8HJwVldjw6x/Y/NeSLrsPUdeiAaDqQ67Lly/HqFGjat+/4NH7MfK0kxR97p6Nm/D8+Ve2V7VOodFoMOLUkzDxonPQY2B/AIDf58Pff/yF39/9GDtWrmlVbkxyEkafeSqyhg2GVqdD0a49WPbld9i3eUuruxojIzD0+GORkt0Tfr8Pu9f9jc0LF8Pv65p/nDUaTZc+wxGTnISU7J4I+P04sG0H7GXlzW6vqX7xe8SJx2HoccfAEh93yB0KduQhb/W64AB59ToU79qD6MQE/PODN5DYPaPZz3vxkuvgrGh8MN2U7OFDMf78s9B75HAYIkyw7juA5d98j+XffM8F81opOjEBhsgI2EpKWzwYoq4vIjoKt3/xPuLT05rdbu1Pv+K92+5RnHv89VfixJuuafLjmxYuxv9uvgs+j0dx5rCpU3DeQ/fAZI5s8DHr/gN4+593Ij93q+K8uiKiLMjI6QudwYDiXXtaNSCoEZ+ehmMuvxAjTj0JkdFRAIDywiIs+fwb/PHBbFRV2lqdbYyMRHRiAlxOB2wl1lbnAEC/caNx1EXnImfCGOj0enjdbqz/5Tf88cFs7F7/9yFlt7XMIQOR3rc3AgFg36bcQ3qtoTbHXXcFTvrHtYq2/WXWO/jxxdcVZ+eMH4Pjrr0cvUYcUftYlc2OFd/+gJ9efSvs645QSZndcekzjzY6m7Mobzfeu/3eVu/jXZ1Or8eQKZMw+oxpSMzsDp/Hi7zV67Do0y+x9+/cVmXqTSYcMXUKjjjpOEQnJKDKZsPfv/+FZV9/3+LXV3UlZXZHzoSxMJkjUVFUgg0L/jik32utFTrmq8HBcMgX5h/vvqbozDAAeFwuvHvrPdi+fFWLjmrFZ6QhKbMHfB4P8nO3HvKL7ri0VAw9YTJiEhPhtNmw6Y9Frdr5tTodLnriQRwxdUqT23z1+DNY+NHnLcqdcvVlmHrj1dAZGk5EWPfLb/j4Pw+1+Kjg5CsuwpRrLq994VDDuv8Avnr8WWxc8GeL8tpL5tBBOOrCczBw0kRERAXPsq+ZNx8LP/oMRXm7W5VZ8wsw+8hh0BkMKNmzFyvnzENFUXGr8rr174cTbrwKA4+eAK1OBwDwejxY9/MCzHv5DRTvPjgNWaPRIOuIITjipOMx9PjJiElKbNVzKlVZUgqvx4P4OmegmvLXJ1/gy0efVpSr0Wpx5j23Y/y5ZzT68bKCQrx5463Yv2V7i/oCwReMY8+ejoycvkAggPwt27Dk86+xZfHyFme1F41Gg75jR2LIcZNhiYuFo6ICG+b/jty/lrbqgI1Wr8PYs6ZjwvlnIa1PLwCAz+PFul8W4Ld3Pmz1H2Yg+L2KTUmGRqtBeWHRIZ+JiklOwohpU5HYozt8Hg92rFqLDfN/h8/rPaRcoO0OeGk0GvQbPwY540fDaI5ERWExVv3wE4p37Tm0XK0WsclJ0Op1KC8oatW/edKlF+C0O25WtO1TZ16MA1vD70ODJh+FK194Mux2f7w/G988+byi5+4/cSyueunp2t9pjbFby/D8BVeidN9+RZlAcJbK1BuuwpGnTIUxMqL28S2Ll+Hn1//X4gPGPQYNwDWvPQdLXGyjHy/K243Xrv4nygoKW5SbOXQQjrnsQgw+9mjo9MG/vfm5W7Hw48+x/OvvW3zQeNqt/8DkKy5q9GN+vx/fPPFci18bAEDvkcMx4YKzkX3kMOiNBpTszcfyr7/Him9+aNWMtP4Tx+KUGTcGf//WsXv93/jumRdbfUBfTf714ZvIHDpI0bZ2axl+efNdFO7chaKdu1Gav7/Js7Hjzj0DZ993Z5NZxbv34uUrbkRFYZGi545LTcHNH72J2JTkJrdxVlTihYuvOezWJ4lLTcFVrzyDjH59Gv34X598ga8ef7ZFZ8a7D8zBFS88ibjUlAYfczkc+Pg/D2H9/N9b1DM+PQ1n3X8nBkwcF5LnxJIvvsH3z73SogOch4qD4SaEfmGue+MF9Bvb8AvVHK/Hg50r1yJ30RJs/mtJky+ge40cjuOvu6JevttZhVXfz8O8V95s8WAmIsqCs+67E0dMndLgD/6OlWsw+/5H6w1kwjn5XzdgytWXht3u9WtvVvzC/tirLsUpM25odpvcRUvxxg23Kt5pp91yEyZfeXGTH/f7/fjwzvuxZt58RXntpbkzHV6PB7PvewSrvv+pRZmDjz0aZ913Z4NBqM/jxZIvvsE3Tzzfohe4OePH4IqZT8AQYWr0446KCrx+zc3Q6nQ44sTjMGzqlEZ/UbZU0e69KNq5C1lHDIE5NuaQ8wCgyuHAYyeeCbs1/JHlk26+Hsddc1mz21QUl+DZsy9FZUmpouc3Rkbi0mcfbfBLv8amPxfhvdvubdV0sLQ+vTDytJOR0C0dnioXti9fhdVzf4anytXirOSsTFz27GNI79u7wccKd+7Ce7ff06KDAHqTCVe9+CT6jRvd6Md9Hi8+ue/hFv+sm2NjcPSl52PsWdMRnZgAIPjzuPybH/DbOx8pfsFUQ6fXY/pdMzD27Om1g4MaFUXF+PzhJ1t1EC0luycmXngOhp1wLKIS4uGstOHv3xdi4UeftepsWeaQgbjwsQfq3aO7xvr5v+OT+x5p8RH1iOgoHH3RuRh79umITQ2+cKyy2bHiux/x2zsfwpqv/KzmHV9/hLTe2Yq2tR4owP7cbXBXVcFTVQW3swqeKlf9910uHHP5RUhp5N8byuVw4vFp58JhLYPf52v2wMOd33xceyeI5iz7ag5m3/+oon9PYo/uuOl/r9R+DUP5vF58fM/DWP2Dsp/1yJgY3PXtx7U/303Z8/dmzDz/SsUHWkafcWpwmmsTBwI2/rYQ7976H8UvQsefdybOuveOsNu9edPt2PTHX4oytTodzvnv3Rh9+rRGP16avx9vXH9LiwYxR06bigsevb/J6b0+jxfv3PJv/P37QsWZNTQaDXoMGYj49DS4nVXYtXZ9k5f1KGGymDHy1JMweMokmGNi4Cgvx7pffsOqOfNafVlaau9sTKg70yn/AFZ8+wNWz50Pr6vpvxUajQYZOX3Rb9wo9Bs3Gn3HjIQmzBTppnjdbhTt2hMcHOftRmHebhTu3AVjRASuf+vFsFOvt69YjVeuuFHRcymdybnpz0V488bbFGXW6DFoACZccBb6jh0FY2QEyguKsHLOXCz94ttD+r63BWNkBP718dthfw8vePsDzHnuZUWZiT26Y8bHbzX7eszn9eKNG27F1iXKXv/HZ6Thn+/PavZgxaaFi/H2P+/osMstOBhuQugXpiXTQ5pSXliE3EVLkfvXUmxZvAyO8gocecoJwV/STfxxKisoxCuX34iSvfsUPYcxMgI3vPUyMocMbHKbypJSvHjxtYoyTWYz7v/1W0RYLGG33bJkOV6/JvyZgejEBNz789fQGwxht33v9nuxVsHgNXPoIPzrwzfDbldlt+Ph46a36Kx7VEI8xpx1Go48ZSpik5PgcjqRu3AJ/vrkixZPsRp9xqk476H/NLuNz+vFa1f/U/GR6iFTJuHSZx9r9o/J2p9+xfu336voRVNUQjz+/f1niIhq/nvu8/mga+bsCgCU7M3H2nm/YM3c+Rg5/WQcfXHTq0qX7tuPly67DuUFRdBoNEjJ7oms4UORPXwoso4YiuSePcJ2b47L4YDdWg57WRns1nI4ysths5bBXlYOR1k5vB4Pzr73DugU/Fz+POt/mPviLEXPe/Urz2DAUeOb3ebvP/7CWzfdrigPCL5guvCx+zH42EkNPuYor8BnDz2BdT/9qjgvPj0N//r4rWZffDvKKzDzoqsVn4U897//xpizTmt2G5/HixcuvgZ7/96sKDOhewZuePMlJHRLb/TjlSWlmHXdDMUzYDQaDS595lEMPX5yk9v4/X68e8t/sOFX5Ue+j5w2Fec/dG+js14A4McXX8cvs95RnNd9YH/c+L9XGp3WW2P3hr/x6pU3KZ6CHpOSjBvefBEp2T0b/bijogJv3HArdq/b2OBjNVOBa9/690X3ATnQaDTK/kHtzO/zwef1wuf1wu89+P9arRYxyUmKMrweDz6592GUHSiEo6wc9vJyOMorGrw402g0uPXz95o8E1M376kzLlK0/xxz2YU49fZ/Kuo567oZyF20NOx2WUcMxU3vvNLsGXEAWPjRZ/jq8WfD5ml1Otwz70tFB0Hz1q7Hixcre/102p3/wqRLzm92m7KCQjxz1iWKBh9xqSn49w+fQW80Nrtdlc2OR6ae2aIpn6Omn4xjr7q03j7kcbmw+sef8f3zr7R4+nnfMSNxydOPNDobwG4tw7u3/gfbV6xuUebUm67BCdc3ftle8Z69ePPG2+rNRotLTUG/caPRb9wo9BkzMuwBmY70/XOvoKygADq9Hlq9HlqdDjq9PvhmCD4WYbHg6EvOa3BgszF+vx+Pn3IOSvfmK3r+U2bcgGOvavzEkN1ahrf+eQd2rd3Qon8TAKT3641x55wR/B2q06Jgex6WfvENdq5e16KciReegzP+fWvY7XxeLx6ZeqaiA8cXPHY/Rp4a/sBC/pZteOas5m+fWePa159HzvgxYbf7+onn8ecHsxVlHioOhpsQ+oWJTkrEvT99pWgAp4Tf78eBrTuQ1ic77B+n/NytePacyxQNZKbeeDVOuOGqsNttXrgEb9xwC/RGI8xxsbDUvMXHwRIXW/tY5uAByDpiqOJ/l9ftgc/rCb748Bx8IVL3xYklNrbJI+ihKopLqqdo+hHw+eGv/m8gEAieAfAH4Pf70H/C2NppmOG0ZEp3r5HDccXM/4M5pvGjYvNeeRM/vfqWoiyNVot75n4R9po6IDi17vVr/xV2O0OECff9/E2TU+nqevfW/4S95YFWp8Nx116BqTeG/xlqStmBAqyZNx9r5s7Hng31z4CNP+9MTL7i4nqDGa/bjTXz5mPOsy+jsrikydyoxHhkHzEUWcOHYvCxRyOpR/cmt21v7qoqLP3iO7jsdrgcDrjsDlTZ6vy/3QGX3Y6MnL645KmHFWW+cuVN2L58VdjtdAYDbnjrJWQPb3q/9Pv9eO+2e7D+l98UPffFTzyI4SefEHa7jQv+xNs3Nz2drUZMchLu/ekrRS9IVv/wEz6464Gw22l1Otz2+Xth9/PygiI8cdr5is6iDD3hWFz2TPizf3ZrGR46/vRmz6LU6D1yOK5/88Wwv9dn3/coln09J2weANwy+x10H5gTdrsfXngN8994N+x2Go0GN3/0JjIHN33QFABspVbMum4G4jPSkNGvDzL690NGTt9mr9M/3DkrbXCUl1cfRKuAzqBXvFr+jpVrkLt4GUyRETBGRsIYGQlDhKn6/yNgjIiA0RyJ5J6Z0BuVvdZwVlaiYHte8HePwwmX3QG301n/fYcD4849Az0GDQib5/V48NVjzwAAjOZgR1PIf43mSMSlpjQ6i6QpW5euQEVRcfD3pN2OKpsDVXZ7nfft0BuNuPLFJxX93vjxpVn47Z2PoNProDcYoDMYoDPUDIwM1Y/pMf68MzFq+imKOn7z5Ez88f4nirY96Z/X4bhrL2/y4yV78/Hy5dejvEDZTJUegwbgpndebXI2FhCcAfHyZdcrPgh/zOUX4dTb/tHsNmUFhfj++VfQc8gg9Bs3usmDY4eriuIS7M/dipJ9+1G6dx9K9uajdF8+Svbmw1lRWbudkq+lo6ICz513heLBtVanw5n33I5x55ze6Mc3/rYQH9x5v+JZYy2ZnVNeWISKmtdbgUBwfBHAwXFGIACNToseA/srng2wdclyVJaUwuf1we87+FYzBvD7fIiIimryMrRQRbv24IlTz2vRJUaxqckYc8apyBw2GDqdDoV5u7H0i2/DHiDnYLgJjX1hjrr4PJx+14xmP2/xZ1/jzw9mI2fCWPSfMAa9Rg6HwdT0LzelfnjxdRzYuh1anS74ptVCo9NCp9NBo9VBq9NCbzDgxJuvR2SYM3o1XA5ns2caDlfOShu2LlmO0vz9sObvR+m+A8H/37e/3gvolOye+NfHb4U9K/7lo083uXq4JS4WMSlJiElKQr9xo3HM5Rcq7lm8ey/cVVXBXySe+gcUgmc8vIhJSQ77graGvbwcBdt2Qm8ywmAyQW80wlDz/yYj9EajohchjakoKsa6nxdg9Y+/YNfa9c3+8tJoteh15DDEpaXC7XRi5+p1sJW28Aj62FG4/o0XWtW1q9q/bQeWfzWn9gViVaUNTpsNLpsdzur33U6n4qmJlSWlePj40+HzeKDRaGCIiIDJYobJHAmT2QyTxQyjORKxKck46947FH3vA4FAcIpvINDki0+dXg9DZITiA4eBQAD7NuVWH0yoeRHvgLv6hXzNYylZmTg6zBmjGr++/QH+/n1hnW7BswahL5qPvvR8JGcqm3Gw7Ks52LZ8Fbxud/DNVf1fj+fg/7s9OP/R+9BLwfoS1gMFePXKm6DT66E3Gmv3Qb3BAIPJCJ3RCL3RgLTevRRdpgIEX4zNfekNeN1u+DzVvys8Hvg8Hng9wd8ZXo8H3fr3xRn/btn0wLZkLyuHz+OBISIChghTmx1kJjoULocDO1atRUVhMSqKi4P/LSpBRVERKopKUFlcAp/Xi/4Tx+KaV58Lm7d1yQq8do2yM/zXv/miooMqNScywjFZzHjg1+9gMpsVPX84HpcLeWvWo/vA/g3WZAlVWVKKZ865FLHJyUjJzkRyVk+kZPdESlYmkntmNjvg70ocFRUo2ZuPsv0F6H/UOBjCzC4AWrZGyVn33Rl2YLh54RK8eeOtta+p9EYjEnt0Q3LPTCRn9Qj+t2cPJPXs0e5rtXSGb56aidy/lqJo1+6wU6aPu+4KnHD9lY2+lln706/45N6Hm5w5xcFwE5r6wow79wxMu/WmBgMkr8eDP97/BD/MfK3eNa6GCBN6jRiOnAlj0H/CWEXXKlHnsZeV1w6MU7J7KjrbXGWz47d3P0J0YgKikxIRm5yE6ORExCQnHfYv8ipLS/H+7fdhx8o1HXqrAq1Oh3vnfaVohoHdWoY18+ZXz36IgzkupnYGRFscqOpINYvbhDvrWMNRUQmdXtdmL4iIGlO8ey9sViuyhg0Ju63H5cLDx02vtzqsVq+DwWSCMSIChjpnSK+Y+YTiF3jLvp4Dt7OqdtqkVl9nCmX1+9GJiYrOsBM1xVZqhcFkhEnBpWNAcFVle1l58ACcwRA8+FXz/9UH5iyxsc1eqhFq76Zc+NweoPqyBI1GA2hq/quBBhpY4mMVzUJrzr5NW7Bl8TJsWbIMO1atg9flQveBObhu1gtNXkPqrKjEGzfe2uR0YY1Gg7j0VKRkZyG1VxZOu/2frb4OuSvyejxYPPsrOCoqUGW3w2Wzo6pm5pjNXnuwOyYlSdGlfQCw8fe/oDfokdwzE3HpqWGvrz4ced1uFGzPQ/6Wbdi/ZRv2b92G/C3bai9FUHIp6+aFS/DmTbc1+lpV3GA4aoAJg2dmIGGsGZ4yH3a/XYrchwqBNn4d3tQXBgheRzv8lBOQOWhA7fz+Fd/9oOj6kPj0NORMGIOcCWMw9Djlv/w6i9fjUTygczudWD//d2i1Wmirr+E4+EJED51OB61ej4Ru6YqvQwn4/fD5fNBoNNBotar8JdCVKb1OvD0cfcn5mH5n+KnkzU1HNUZGVl8eEIsjT56KSZddoOi5A4FAl7k+kqijeKpc2L91O/JztyI/dyv2bd6K/Vu3wWV3QKPR4MoXn8LASROazfj6/57Dnx9+quj5Jl95MabdclPY7TYtXIw3bwh/rZxGq8W/v/9M0TTvLYuW4s+PPoclLgbm2IOXDpljYw5eShQbi+ikBMUHp0L5/X64nc7qBcSCC4e5HU7EZ6QpvrbZuv8AXHYHjOZIRFgsMJnNTV6rfqh8Xi/cjmBfr8eNxO7dFH2e3++Ho6wcJrNZzFlBNSo7UIAti5djy+Jl2Lp0RZMzthK7d8Nx112O4SceX/v99LrdWDN3Pn6e9b8WrW6vZE2NGnOefRm712+Er+byuzoz5Wpm0Pm8Xlz10tPoMTj8JQFVdjsObNuJxO4ZXera6I5QVlCIypJSaKCpfzAFCB5Q0Wig1emQkt1T8WsdlyM4nVun19XOYm1vlSWlKMzbjezhQxWND96ZcXejK1+LGgwb4rQ4Zl0/VG5yYdtTRbD0MmLgU+nYMbMYufcXtOlzNTcYbiuPLv4l7CJF7Slv7Xrs27QF9rJy2K1lweug6iwwZC8rh9vpxI3/ewW9Rw4Pmzf35Tfw82tvh90utXc27vz6I0UdG7u+t2ZQrNFqodVpodFoMfnKi3H8dVcoyizdlw9LfHyXniLu9/mwe8MmaABo6xxUCD3jYbJYYDCFn7pTk1m8ey88Lhc8Lhe8Ljc81dM9a993uZA5eKCiPyQA8NXjz2LhR58dwr/00Jx9/11NXm8DAL+98xG+e+ZFRVnGyAjc/8u3iIyJDrvtt0+9gEWfflk97diCCIu5+v/NiIiy1P7/qOknIz3MwjrSWPMPwGmzVU+/PTgV11vnfXNMdJOrSIdyO50o2rUHJnNw2rbJbO7S+6bauBxOfPbfx5GfuxVFu/Y0e+sdvcmEc/97N0ZMO7HBxzwuF75/7hXFA2EgeH38ta89hz6jRzS5TXlhEV669DrFt0E64sTjwl7H73I4MPPCq1GwfWfYvGFTp+DSpx9R9NwbFvyBrx57tnYA7HW7G92ux+CBmPFx+LUo3M4qPHz89AYLSQX/Nphr96mIKAsue/axZldvreuLR5/CnvWbqq89dtb+N3SV6atffbbJVfLrWvTpV/ji4SfrdQv+nrQgIsqCiOr/DjpmoqK1C4DgLK5V38+DzxOc+l9zCYDPc/D3kd/rRb/xY5q9LWRd1v0HoNPrEZWYoLoD7y9eci3y1qxv0edERFmQnNUTGk3w+s6619gqlTNhLK59LfyU8wPbd+LpMy5SdP1o/6PG4ZpXwi8C99G/H8TKOXMBBA+MJ3RLR2L3DCR071b9/92Q2D0DyVmZrb6ErCOU5u9H8a490BkMil6rez0ePHL86YruiHHZs48pmrVQlLcbT5x2fr3vj0ajgUanhVZXczJMh6iEBNz+xXthF7RrL7mLlmLWdTMaPN7UmK9Lftd7XpcIbaQWK87eBW+lH8UA9DFa5Nyfiu1PFcFb2XHTNNvC378vxJGnTFW07a9vvYcdK9fC7/fXXoge8Pvh9/rg9/vg9wUfP/+Rexu9yXgoZ6UNr1/zL0UX5n/+0BP45/uzml1afff6v/H7u8oGuAXbd2LV9/PC/tuLd+/F8q9/aPB4wO+HL2Saw8KPPsOE888KezueureisMTFIj4jHQnd0pGQkY74mv9mpCGxRzcYIyKazWqMs9KGiqLiOm8l9d4/7Y6bFS1isvSr7/D5g0+E3S6tTy/c8dWHirr99s6H+P75V8Nul9A9A3d/Ozvs2YWaW7B0ps8fegLbl6/CxIvOqTdFc/uK1fjj/dktWgHY7azCd8+8iHMfbH617/wt27D4s6/gqXLBU+VqdkbIno2bcNM74b/mAPC/m+9EYd7u4IvDqChEREchMsoCU5QFkVFRiIiKQmRMFIaffILi2RoFO/KQn7s1eO2t01l9Ha69dmGd4AtdB07/961Izc4Km1e4cxeeOE3ZdbtKF/P49ukXsfjTr+o9ptFqYay+xjk4QI7ExAvOxugzTlX03NuWr8Kyr+Y0er1szYtln9eLiReegzFnKst87/Z7UVFUHLye1xC8ntdgMkJvMEJnNMBgMiEi2oIpV1+m+Pvz+/ufoOxAQfU1xx54Pe6D/199bbJWr8dVLz5V7961TdmyeDm+ffqF4LXRNbNzaqZj1pmeOWDSBAw/8ThFHTcu+AOrf/xZ0bZelwsf/ftB/DLrHYw+fRqSs3rA5/Uhb+16rPjmhxbfesTn8eCNG2/D9Dv/hdGnn9LgBVTuoqX47MH/a9EtoNbM/QWWuFhMv2tGoy9wHeUV+N+MuxUNhAFgw/zfUXagAHEK7nn+y6x3UXYg/IH7PRv+xm/vfBR2jYkvH3u60a+pz+uFo7yi3sd+e/cjTL8j/EyaPRs3YdEnX4bdDgC+eeJ5ZA4e2OwCjiV78zHv5Tea7VZj05+LMPCYiYou65j70iwsmh2+54YFf6L/hLFhTzxUlpTiyekXwu10QqvTISohHjHJScG3lCTEJCUiJiUJcWmpig4AtITP423R2fyivN3wuN1A9cCj7uJHgeD/wBIX1+Sq+6HKCgpbtQpylc3eYJHMlsr9awl+f/+TZlcQd1RU4IM771e8kNLmPxfj84eexJn33Nbk2ckfXnitdiAMBA/KHti2Awe27Wiw7eBjJ+GKmf+n6Lnba9ZYZUkpinftQdGuPSjatbv6v3tQsmdv7a0U9SYT/vXhGw3upR3q17feV3xryJ9eews5E8aGPUD9/cxXG3x/AoEAAl4f/F4fam7s6ayoxPJvfmj2JEaNT//7OGylVqT364OMfn2Q3rc3knr2OKQDVZlDlN0nu0aXPDM8fkEvVOV7sOqig1MwInsYcNzO/lh2eh4K5rT8qFRTOuLMsNLbAZUdKMCjJ52l6H5bg46ZiCtffCrsdi25NQwQHHSd/8i9DQZyfr8fa+fNx+cPPdGi2xXpTSZc+tTDGDT5qEY/Xrx7L2ZdN0PxLaUAIPvIYbjqpaebXNyhaNcevHbVP1BWUBi+n9GIB36bA3N0+LOEAPDxPQ9j7U/zw97ftduAfrjpndea/cVSVlCImRdcpfj+0pc//38YMqXhLXbqclba8PQZFyn6twPA2LOn45wH7m7y4z6PF+/e+m9s/K3l92VsL9GJCYiMiYajvKLFC3LVNeH8s3DaHTc3euRy5+p1eOeWu1t0y4zLnnscQ487ptlt1v28AO/e2vwgvMb0O2fg6EuavkVVDZ/Hi0emnqHo50jp740P7rxf8cAoc8hA3PDWy80O4nIXLcWbN92m6HdbTHIS7pn3paKB5lNnXowDW8PfEzkuLRW3f/lB2AVh1v3yG9695d9h8wDg3Af/o2iAvX3larxyubL7ZjZ3S48aPq8XL19+g6IXtZExMbjv568VnYF/4eJrWvVCua1Z4uMwZMokRCclwmV3YPPCxS2612yoxB7dMf68MzDgqPGIsFhQWVKK1T/8hGVfz2nxoD3riKG49vXnm/16/vjSLPzy+v9alHvsVZdgyjWXNVijpKK4BN888TzWzP1FcZbOYMB1b8xE7xFNnzmqstvxyuU3tuiWgWl9euHiJx9qdGXpnavW4v0771O8ojIATLzw7LCLu+3ZuAkvXXp9k2fWQ+WMH4MrZj7R5BTtKpsdb1x/C/LWKjszet0bL6DfWGWvD9+97R4c2Lr94Blrrwc+j6/2QJ3PGxwm/PODWYquuVd6v11jZCQe+PU7RbMPlc7qa09HXXQujr3qkgaXB2xZshxfP/4sCnbktTgzI6cvjrroXAw9YTIiLBa4nVXYuOAP/PnRZy36nabV63DvXGVrlPwy6x38+tb7MEUFZ4wFD27XnwVhirJg2PGTww5aa2xbthKvXtX8StY1ohMTcMULT6Ln0MYHfQve/gDfP/9Ki1Zo7jN6BC5/7vFGZ835PF58+fgzWPLZ14rzDBEmXP3Ks+gz6sgmt5n38hv4qZGfSWNkBFJ7ZSO9Xx+k9+uNjH59kD18mOKDSS6HE/8Zc2yDx0VNkz4hfwDyXivBlofqv6A/qXwQtjxUgO3P1H/Rd6o3/C+Wpty/+u12HwwDwPHXX4kTb7qmyY+7HE7MuvZfin9JA8E/oKfMaPqX5Zp58/HhXQ80O92tKT2HDUb/ieNgsphRWVyCNXN/adFR+bo0Gg0GTpqAceediayhg6HV61CUtwdLv/wWK779UfFy8nUlZXbHMVdchCNPnlr7wqSypBRLv/gWv737UYum8Zx2x82YdGn4a0iL9+zF/51yruJfLlnDhuCSpx9u9ExCfu5WvDPj3y06CGCymHHNq881easdZ6UNb998J3a08P6EQ6ZMwsn/uqHBrRb2/p2Lb59+QdFtgKSKSozHmDNOQ++RR0AfYYJ13wEs/+Z7bFu2ssVZepMJFz52P4ad0PAXMBBc5fCj/zyk6LY9QPCG9bd9/n7YAVxLVrUEgAkXnI3T776lyaOuc559CQv+p2wWQo3MIQNx3sP3NjhD7PN4sfyb7/HV/z2n+N8NBBcwPPu+5m/t9NNrb9c7ExVO75HDceWLTzX5onHnqrV448Zb4bKHv1UTELx/74yP3mr2hZPL4cDLl92geNCh1elw4eMPYPhJxzf6cZ/Xi9n3PVrvTEc4I6adiAsfb/6WVr+//wm+fXKm4kw16z4wB9PvnIFeI46o93hp/n78/Orbim+jFcpkNuOIE6cgpVcWAj4/dm/chI2//lE7iGoJY2QEzrznDoyYNrXBGbP83K345N5HWjQQrqvP6BEYNPkoREZHBxctnPsL9mzc1Kqsoy89H6fMuLHRA1/blq/Ce7f+p94CbEp0H9gfU2+6Gv0njqv9HefzerHxt4WY+9IsxTMBAGDA0RNw9cvhf7cqHbgCQO9RR+K6WTObnY7r83jx6tX/wM5VaxVlKjmwULxnL54//8pWTXFua1q9DjnjxyKhWzq8Lhd2rFpb7x7Ih0JnMDSY5t8SQ4+fjMuefazZbYp378XzF1yl6F7V3Qfm4JbZ7yh67ndvuwfrfvpV0bZAcGZV/4njMPqMaUjK7A6fx4Odq9dh8adftfoAoiUuFqPPmIYjTjwe0YkJcNps2PT7X1j02VeKbyVVl95oxNGXnIfx551Zb6G3vDXrseB/H7ZoVt/0u2bg6IvDnyAAgrNDnz+v4SWVogbDpzgH4++79mPnC/XvRXpcXn/s/cCKzffWn34kYTAMAKPPOBUn3HBlg5X/dqxcg6+feA77NrX8j1O/caNxzGUXIGfC2NrH9m3egoUffY7l33zfoSv/dgZDhAlxaanwe32w7j/QqoF/VGI8/vXRW0jIaHqqkd/nw9s334VNf/zVomytXofBx07CoEkTERFtga3EijXz5mPb0hUtOmJXQ2cwYMyZp2L8eWfWHqF3VlRi+bc/4M8PZiu+nq4xvUYOR1rvbAQCAezduLnVL3DULmvYEIw953Rk5ASvIc7P3YrFn33dqrNu2UcOw1UvPtXk9c3rfl6AD+68v8UvmLv174eJF52DoccHj6S7HE5s+PV3/PnhZ4c0Ha7P6BHoO2YkDJERwftQ//iL4pkPoUaedjKm3XpTgwVPnBWV+Om1txXfJ7SuhG7pOPqS8zHytJNrDzLs37odi2Z/iaVfftfiF1GJPbrj8ucfR0Yj14tb9x/A+3fc1+Lvu0ajwbCpUzDxwnNqD3x5XC6smTsff7z/Sdj7KDZm2NQpmH7nvxpcS1plt+PXt95XdM9iqi+tb29kDRsMncGAorzd2Lp0RZf7exuXmoIjTjwOManJcDud2LJoGXasXNPZteqJTkrEmLNOQ68jh0FvNKJk7z4s//r7Q+4Zl5qC1D69gEAA+Vu2NXtv++ZMu/UfmHzFRU1+3Lr/AF669HpF0+JrDD3hWFz46P2NnsF2O6vw4d3/bdEgAQguQnfyzdc3Ol34wLYdeOsftx/S6wM1OXLaVJx9312NzgDZt2kL3r75zhZ9vy956mEcEeZylV1rN+Cly69XNHtKIq1Oh5ReWYgwm1FRXNyqn8X0fr1x+xcfKNr284efbHBZFiBxMHznfux8MWQwvKs/9r5nxeb72m4RrY6YJl2XRqtFv7GjkNSzB3weD/LWrG/02oWWMsfGICohHlV2ByoKlU9VoqDE7t1wxQtPNDoFrMpux+z7H2vREbuOEBEdBb3RAEdZRasOApAMMSnJmHD+WRg1/WTEpiTD5/Vix4o1+Gv2F9gw//dWHVSp61CPpLcnncGAIcceje6DBkCj0eDAtu1Y+9OvTd5DUCmtTgdzXAy8bg+qKm2HlKXRaNB37EgcMfU4WBLiUFVpx8bf/sSGBX8c8gsbk9kMY2QEHOUVrTpDWJdWr8OgY45C5pCB0Op0KNyRhzVz59e75zoRNTT27Ok49qpL6q2q7fV4sHbefMx59uVWHfCLSUnGuLOnY8hxx9Re9rP+5wVY8sW3rT6AmNA9A+POOR19Ro2A3mRE2f4CLP/m+zb5XaQ2kTExGH36Keg7bhSMkREoLyjCyu9+RO5fS1v8N1dvMuHiJx5s8jK3vDXr8fY/72jxLAg1UnJgoShvN54997JGXyeIGgyfkD8Aea+WYMvDIdOkywZiy8OFDaZJH4qOHgxT11Uz5WTEtKmISUmC2+HE5oVLsOK7Hw/5BTNRW9Dp9cFF9Q5xAExERMppNBpkHzkMcemp8DirsHP1ukNas4LUp+/YURh3zunoPrA/NFoNCnbkYenn32Djbwt5QkMhQ4QJlz7zKAYe3fit/YrydmPW9TOaPPMsajVpW64LUTn1p49EdDdAH6WDLVf5dWdELRHw+7Hpj79aPBWaqKMc6tlBIiJquUAg0OWmmJMsW5csx9Ylyzu7hmieKhfe/scdGHjMRIw/90xkDg3OdCrK242lX3yHlXN+bNXMsS45GC6cW4netyVBF6WFzxa8Bifj3Fj4HH6U/K58JWMiIiIiIiKSLxAIYOOCP7FxwZ9tltkl7za+6/US+F0BjPo8E0lTLMi8Oh4596dg+/PF4u4xTERERERERF1PlxwMe8r8WHzCTmh0Goz+Ogs5D6Rix8wS5P637RbOIiIiIiIiIvXqktOkAcC2yYXFxyu/HxwRERERERGRUl3yzDARERERERFRe+JgmIiIiIiIiFSHg2EiIiIiIiJSHQ6GiYiIiIiISHU4GCYiIiIiIiLV4WCYiIiIiIiIVIeDYSIiIiIiIlIdDoaJiIiIiIhIdTgYJiIiIiIiItXhYJiIiIiIiIhURwMg0NklOlNhYSF27drV7DaxIyIBAOUrnW32vBIyJXSUkimho5RMCR3VnCmho5RMCR2lZEroKCVTQkcpmRI6qjlTQkcpmV2hY8+ePZGSktLgcdUPhpU41TsEAPCdfr2qMiV0lJIpoaOUTAkd1ZwpoaOUTAkdpWRK6CglU0JHKZkSOqo5U0JHKZlduSOnSRMREREREZHqcDBMREREREREqsPBMBEREREREakOB8NERERERESkOhwMExERERERkepwMExERERERESqw8EwERERERERqQ4Hw0RERERERKQ6HAwTERERERGR6nAwTERERERERKrDwTARERERERGpDgfDREREREREpDocDBMREREREZHqaAAEOrsEERERERERUUfimWEiIiIiIiJSHQ6GiYiIiIiISHU4GCYiIiIiIiLV4WCYiIiIiIiIVIeDYSIiIiIiIlIdfWcX6GoSJ1uQcmI0onJMMMbrEAgAnjIfbLkuFP5YiZLf7J2ap+ZMCR2lZEroKCVTQkc1Z0roKCVTQkcpmRI6SsmU0FHNmRI6SsmU0FFSZg3eWqmaIV6HUV9kImGiBY6dbtg2u+Cx+gANYIjTISrHBHMvI0r+tGPF2buDH+vAPDVnSugoJVNCRymZEjqqOVNCRymZEjpKyZTQUUqmhI5qzpTQUUqmhI6SMhsT4BsCw9/tHpi8sV8gdmRkk9vEjogMTN7QNzD8ne4dnqfmTAkdpWRK6CglU0JHNWdK6CglU0JHKZkSOkrJlNBRzZkSOkrJlNBRUmYjb636pMPu7cTigYHUU6PDbpd2WkzgxOKBHZ6n5kwJHaVkSugoJVNCRzVnSugoJVNCRymZEjpKyZTQUc2ZEjpKyZTQUVJm6BsX0KoW8Aeg0WjCb6gJbtvReWrOlNBRSqaEjlIyJXRUc6aEjlIyJXSUkimho5RMCR3VnCmho5RMCR0lZYbiYLjagW8rMPCpNMSPNze5Tfw4MwY+kYYDX1d0eJ6aMyV0lJIpoaOUTAkd1ZwpoaOUTAkdpWRK6CglU0JHNWdK6CglU0JHSZmhNAieIlY9fbQWIz7JRPLxUXAd8MKW64KnzAcEAH31BdoRaXoU/WzDygt2w1vp79A8NWdK6CglU0JHKZkSOqo5U0JHKZkSOkrJlNBRSqaEjmrOlNBRSqaEjpIyQ3EwHCJ+rBnJU6Nql+4GALe1eunuuZUoW+rs1Dw1Z0roKCVTQkcpmRI6qjlTQkcpmRI6SsmU0FFKpoSOas6U0FFKpoSOkjJrcDBMREREREREqqPv7AJdkS5Ki6h+RhjidUCg+qbOW9zw2Vp+6r098tScKaGjlEwJHaVkSuio5kwJHaVkSugoJVNCRymZEjqqOVNCRymZEjpKygQ4GK4naYoF/e5NRfxYMzRaBM+bVwv4AOsSB7Y8XIDiX+2dkqfmTAkdpWRK6CglU0JHNWdK6CglU0JHKZkSOkrJlNBRzZkSOkrJlNBRUmZdnCZdLf3sWIz4sAcK51Uif3Y5Kje74LH6AA1giNMhur8JGefGInlqNFZdtBv7v2h+xbK2zlNzpoSOUjIldJSSKaGjmjMldJSSKaGjlEwJHaVkSuio5kwJHaVkSugoKbMxAb4hcMzavoEBj6eF3W7A/6UFjlnXt8Pz1JwpoaOUTAkdpWRK6KjmTAkdpWRK6CglU0JHKZkSOqo5U0JHKZkSOkrKDH3TggAA5l5GFP5YGXa7wh8qYc42dniemjMldJSSKaGjlEwJHdWcKaGjlEwJHaVkSugoJVNCRzVnSugoJVNCR0mZoTgYrmbf6kLa9Jiw26VNj4F9q6vD89ScKaGjlEwJHaVkSuio5kwJHaVkSugoJVNCRymZEjqqOVNCRymZEjpKygzFBbSqbX6gACM/7YnowRHI/6ys+qbOfiAQgKH6ps4ZZ8cicZIFK87d3eF5as6U0FFKpoSOUjIldFRzpoSOUjIldJSSKaGjlEwJHdWcKaGjlEwJHSVlhuICWnUkTDCj7z0pSJxkgdagOfiV0QB+TwAlv9mx5dFCWBc5OiVPzZkSOkrJlNBRSqaEjmrOlNBRSqaEjlIyJXSUkimho5ozJXSUkimho6TMujgYboTGoIGld/V9rAB4rD7Yt7sR8LTuS9XWeWrOlNBRSqaEjlIyJXRUc6aEjlIyJXSUkimho5RMCR3VnCmho5RMCR0lZQIcDBMREREREZEKcQEtIiIiIiIiUh0OhpswzT0YJ9sHNXj8FOdgnFI1uNPz1JwpoaOUTAkdpWRK6KjmTAkdpWRK6CglU0JHKZkSOqo5U0JHKZkSOkrK5GrSTdjySCECvkYef7QQGk3n56k5U0JHKZkSOkrJlNBRzZkSOkrJlNBRSqaEjlIyJXRUc6aEjlIyJXSUlMlrhomIiIiIiEh1OE2aiIiIiIiIVIfTpEMkTrYg5cRoROWYYIzXIRAAPGU+2HJdKPyxEiW/2Ts1T82ZEjpKyZTQUUqmhI5qzpTQUUqmhI5SMiV0lJIpoaOaMyV0lJIpoaOkzBqcJl3NEK/DqC8ykTDRAsdON2ybXfBYfYAGMMTpEJVjgrmXESV/2rHi7N3Bj3VgnpozJXSUkimho5RMCR3VnCmho5RMCR2lZEroKCVTQkc1Z0roKCVTQkdJmY0J8A2B4e92D0ze2C8QOzKyyW1iR0QGJm/oGxj+TvcOz1NzpoSOUjIldJSSKaGjmjMldJSSKaGjlEwJHaVkSuio5kwJHaVkSugoKbORt1Z90mH3dmLxwEDqqdFht0s7LSZwYvHADs9Tc6aEjlIyJXSUkimho5ozJXSUkimho5RMCR2lZEroqOZMCR2lZEroKCkz9I0LaFUL+APQKFmTWxPctqPz1JwpoaOUTAkdpWRK6KjmTAkdpWRK6CglU0JHKZkSOqo5U0JHKZkSOkrKDMXBcLUD31Zg4FNpiB9vbnKb+HFmDHwiDQe+rujwPDVnSugoJVNCRymZEjqqOVNCRymZEjpKyZTQUUqmhI5qzpTQUUqmhI6SMkNpEDxFrHr6aC1GfJKJ5OOj4DrghS3XBU+ZDwgA+uoLtCPS9Cj62YaVF+yGt9LfoXlqzpTQUUqmhI5SMiV0VHOmhI5SMiV0lJIpoaOUTAkd1ZwpoaOUTAkdJWWG4mA4RPxYM5KnRtUu3Q0Abmv10t1zK1G21NmpeWrOlNBRSqaEjlIyJXRUc6aEjlIyJXSUkimho5RMCR3VnCmho5RMCR0lZdbgYJiIiIiIiIhUR9/ZBboiXZQWUf2MMMTrgED1TZ23uOGztfzUe3vkqTlTQkcpmRI6SsmU0FHNmRI6SsmU0FFKpoSOUjIldFRzpoSOUjIldJSUCXAwXE/SFAv63ZuK+LFmaLQInjevFvAB1iUObHm4AMW/2jslT82ZEjpKyZTQUUqmhI5qzpTQUUqmhI5SMiV0lJIpoaOaMyV0lJIpoaOkzLo4Tbpa+tmxGPFhDxTOq0T+7HJUbnbBY/UBGsAQp0N0fxMyzo1F8tRorLpoN/Z/0fyKZW2dp+ZMCR2lZEroKCVTQkc1Z0roKCVTQkcpmRI6SsmU0FHNmRI6SsmU0FFSZmMCfEPgmLV9AwMeTwu73YD/Swscs65vh+epOVNCRymZEjpKyZTQUc2ZEjpKyZTQUUqmhI5SMiV0VHOmhI5SMiV0lJQZ+qYFAQDMvYwo/LEy7HaFP1TCnG3s8Dw1Z0roKCVTQkcpmRI6qjlTQkcpmRI6SsmU0FFKpoSOas6U0FFKpoSOkjJDcTBczb7VhbTpMWG3S5seA/tWV4fnqTlTQkcpmRI6SsmU0FHNmRI6SsmU0FFKpoSOUjIldFRzpoSOUjIldJSUGYoLaFXb/EABRn7aE9GDI5D/WVn1TZ39QCAAQ/VNnTPOjkXiJAtWnLu7w/PUnCmho5RMCR2lZEroqOZMCR2lZEroKCVTQkcpmRI6qjlTQkcpmRI6SsoMxQW06kiYYEbfe1KQOMkCrUFz8CujAfyeAEp+s2PLo4WwLnJ0Sp6aMyV0lJIpoaOUTAkd1ZwpoaOUTAkdpWRK6CglU0JHNWdK6CglU0JHSZl1cTDcCI1BA0vv6vtYAfBYfbBvdyPgad2Xqq3z1JwpoaOUTAkdpWRK6KjmTAkdpWRK6CglU0JHKZkSOqo5U0JHKZkSOkrKBDgYJiIiIiIiIhXiAlpERERERESkOhwMN2GaezBOtg9q8PgpzsE4pWpwp+epOVNCRymZEjpKyZTQUc2ZEjpKyZTQUUqmhI5SMiV0VHOmhI5SMiV0lJTJ1aSbsOWRQgR8jTz+aCE0ms7PU3OmhI5SMiV0lJIpoaOaMyV0lJIpoaOUTAkdpWRK6KjmTAkdpWRK6Cgpk9cMExERERERkepwmjQRERERERGpDqdJh0icbEHKidGIyjHBGK9DIAB4ynyw5bpQ+GMlSn6zd2qemjMldJSSKaGjlEwJHdWcKaGjlEwJHaVkSugoJVNCRzVnSugoJVNCR0mZNThNupohXodRX2QiYaIFjp1u2Da74LH6AA1giNMhKscEcy8jSv60Y8XZu4Mf68A8NWdK6CglU0JHKZkSOqo5U0JHKZkSOkrJlNBRSqaEjmrOlNBRSqaEjpIyGxPgGwLD3+0emLyxXyB2ZGST28SOiAxM3tA3MPyd7h2ep+ZMCR2lZEroKCVTQkc1Z0roKCVTQkcpmRI6SsmU0FHNmRI6SsmU0FFSZiNvrfqkw+7txOKBgdRTo8Nul3ZaTODE4oEdnqfmTAkdpWRK6CglU0JHNWdK6CglU0JHKZkSOkrJlNBRzZkSOkrJlNBRUmboGxfQqhbwB6BRsia3JrhtR+epOVNCRymZEjpKyZTQUc2ZEjpKyZTQUUqmhI5SMiV0VHOmhI5SMiV0lJQZioPhage+rcDAp9IQP97c5Dbx48wY+EQaDnxd0eF5as6U0FFKpoSOUjIldFRzpoSOUjIldJSSKaGjlEwJHdWcKaGjlEwJHSVlhtIgeIpY9fTRWoz4JBPJx0fBdcALW64LnjIfEAD01RdoR6TpUfSzDSsv2A1vpb9D89ScKaGjlEwJHaVkSuio5kwJHaVkSugoJVNCRymZEjqqOVNCRymZEjpKygzFwXCI+LFmJE+Nql26GwDc1uqlu+dWomyps1Pz1JwpoaOUTAkdpWRK6KjmTAkdpWRK6CglU0JHKZkSOqo5U0JHKZkSOkrKrMHBMBEREREREamOvrMLdEW6KC2i+hlhiNcBgeqbOm9xw2dr+an39shTc6aEjlIyJXSUkimho5ozJXSUkimho5RMCR2lZEroqOZMCR2lZEroKCkT4GC4nqQpFvS7NxXxY83QaBE8b14t4AOsSxzY8nABin+1d0qemjMldJSSKaGjlEwJHdWcKaGjlEwJHaVkSugoJVNCRzVnSugoJVNCR0mZdXGadLX0s2Mx4sMeKJxXifzZ5ajc7ILH6gM0gCFOh+j+JmScG4vkqdFYddFu7P+i+RXL2jpPzZkSOkrJlNBRSqaEjmrOlNBRSqaEjlIyJXSUkimho5ozJXSUkimho6TMxgT4hsAxa/sGBjyeFna7Af+XFjhmXd8Oz1NzpoSOUjIldJSSKaGjmjMldJSSKaGjlEwJHaVkSuio5kwJHaVkSugoKTP0TQsCAJh7GVH4Y2XY7Qp/qIQ529jheWrOlNBRSqaEjlIyJXRUc6aEjlIyJXSUkimho5RMCR3VnCmho5RMCR0lZYbiYLiafasLadNjwm6XNj0G9q2uDs9Tc6aEjlIyJXSUkimho5ozJXSUkimho5RMCR2lZEroqOZMCR2lZEroKCkzFBfQqrb5gQKM/LQnogdHIP+zsuqbOvuBQACG6ps6Z5wdi8RJFqw4d3eH56k5U0JHKZkSOkrJlNBRzZkSOkrJlNBRSqaEjlIyJXRUc6aEjlIyJXSUlBmKC2jVkTDBjL73pCBxkgVag+bgV0YD+D0BlPxmx5ZHC2Fd5OiUPDVnSugoJVNCRymZEjqqOVNCRymZEjpKyZTQUUqmhI5qzpTQUUqmhI6SMuviYLgRGoMGlt7V97EC4LH6YN/uRsDTui9VW+epOVNCRymZEjpKyZTQUc2ZEjpKyZTQUUqmhI5SMiV0VHOmhI5SMiV0lJQJcDBMREREREREKsQFtIiIiIiIiEh1OBgmIiIiIiIi1eFgmIiIiIiIiFSHg2EiIiIiIiJSHQ6GiYiIiIiISHU4GG6h2CMjMOyNbl02T82ZEjpKyZTQUUqmhI5qzpTQUUqmhI5SMiV0lJIpoaOaMyV0lJIpoWNXzORguIXMPY3ocWl8l81Tc6aEjlIyJXSUkimho5ozJXSUkimho5RMCR2lZEroqOZMCR2lZEro2BUz9W3aRLCEo8yKtosaFNEpeWrOlNBRSqaEjlIyJXRUc6aEjlIyJXSUkimho5RMCR3VnCmho5RMCR0lZYbiYLja+Pm9gAAAjYKNAx2fp+ZMCR2lZEroKCVTQkc1Z0roKCVTQkcpmRI6SsmU0FHNmRI6SsmU0FFSZigOhqt5Sn0onFeJrU8UNbtdyvFRGPhkeofnqTlTQkcpmRI6SsmU0FHNmRI6SsmU0FFKpoSOUjIldFRzpoSOUjIldJSUGYqD4WrWpQ6Ys42w/e1qdrvoHFOn5Kk5U0JHKZkSOkrJlNBRzZkSOkrJlNBRSqaEjlIyJXRUc6aEjlIyJXSUlBmKC2hVK/ixEtCGPwfv2OXGnvetHZ6n5kwJHaVkSugoJVNCRzVnSugoJVNCRymZEjpKyZTQUc2ZEjpKyZTQUVJmKA1aPcOaiIiIiIiISCaeGSYiIiIiIiLV4TXDIXQWLRInWRCVY4IhXgcEAE+ZD7ZcF0p+t8Nn93dqnpozJXSUkimho5RMCR3VnCmho5RMCR2lZEroKCVTQkc1Z0roKCVTQkdJmTU4GK4j578p6DUjCTqzFj6HHx6rD9BoYIjVQmcJPrb9uWJsebCwU/LUnCmho5RMCR2lZEroqOZMCR2lZEroKCVTQkcpmRI6qjlTQkcpmRI6SsoMFeAbAv0eSAmcVDYw0Pu2pEBEd0ODj0d00wd63ZoUOMk6MNDv/pQOz1NzpoSOUjIldJSSKaGjmjMldJSSKaGjlEwJHaVkSuio5kwJHaVkSugoKbORt1Z90mH3dtyu/oHMq+PDbpd5dXzguF39OzxPzZkSOkrJlNBRSqaEjmrOlNBRSqaEjlIyJXSUkimho5ozJXSUkimho6TM0DcuoFXNEKeDY4c77HaOHW4Y4nQdnqfmTAkdpWRK6CglU0JHNWdK6CglU0JHKZkSOkrJlNBRzZkSOkrJlNBRUmYoDoarWZc60Pv2ZOjMTd/LSmfWoM8dybAucXR4npozJXSUkimho5RMCR3VnCmho5RMCR2lZEroKCVTQkc1Z0roKCVTQkdJmaF4n+FqUf1NGDsvG7oIDQp/ssGW64K3zIdAIHhUIirHhJQTouBzBbDkhJ2w5bo6NE/NmRI6SsmU0FFKpoSOas6U0FFKpoSOUjIldJSSKaGjmjMldJSSKaGjpMxQHAzXoY/VIuv6RKRMjTq4dDcAjzW4dHfhXBvyXi+Bt1zZ8t1tnafmTAkdpWRK6CglU0JHNWdK6CglU0JHKZkSOkrJlNBRzZkSOkrJlNBRUmZdHAwTERERERGR6vCaYQUSjjI3O1e9s/PUnCmho5RMCR2lZEroqOZMCR2lZEroKCVTQkcpmRI6qjlTQkcpmRI6dvVMDobD0QLjf+mFqBxT18xTc6aEjlIyJXSUkimho5ozJXSUkimho5RMCR2lZEroqOZMCR2lZEroKCCTg2El2vZARtvnqTlTQkcpmRI6SsmU0FHNmRI6SsmU0FFKpoSOUjIldFRzpoSOUjIldOzimRwMExERERERkepwMBxOACj5ww5vZetWKGv3PDVnSugoJVNCRymZEjqqOVNCRymZEjpKyZTQUUqmhI5qzpTQUUqmhI4CMrmaNBEREREREamOvrMLSBCZZYA52wjHTjeceZ5DztOaNBj8fAa2P1ME+zZ3GzQEInsagADg3H3o/QAg8RgLogeYEPADFeuqYF3sUPy5caMjUbbc2eaHWSz9jNBoNPVuqJ12WgzMvY1w5rlR8GMl/FUte1KNDogfZ0ZUfxOMCXoEfAG4CrywLnXAvrV13xudRYvESZaD90ILAJ6y4L3QSn63w2dvwyNj1bQmDUwpejj3tM33X6MHItINbZYHtH1HoO16ch/vGvs40Pb7OffxprX1ft6VO7b1Pg60/X7OfZz7eFfdf+rqqq83JOzjQNvu52rZx4H22c9rcDBcTaMHBj6Vju4XxUFr1CDvtVJsuvsABr+QgazrE4IbBYB9s8ux+vI9QJjfg7rIpq/q1sfpkHllPPZ/WY6qfcGdwecM/0OReXU8DnxVAXeJr/ax7H8mou9/UmBMCN6A2l3sRe7Dhdj1WmnYPAAY+FQafM4Acu8vAACY0vQY+XlPxI+OhN8dADSAVq9B0S82rLxgN7wV4f8ATFzYG+4iL/I/r8C+2WWwLlK+czbGlKbH6K97InZ4JACgeIENK87ZjVFf9kTiJAt8zgB0kRo4drixeOpOOHcp+wWT/Y9E9Ls3JfiHrubbFUDtfInSxQ6su3EfbH+7mkmpL+e/Keg1Iwk6sxY+hx8eqw/QaGCI1UJnCT62/blibHmwsGVfhDBST47GiE8yMce0Iey2WTckoNeMJJhS9Kjc5ELeyyXY+2FZvW1ij4zExD97K8prj47t0ZP7eNfdx2t6tfV+rtZ9HOic/byzO7b1Pg60/X7OfZz7eFM6e/9pj55q3MeBtt/P1byPA+2zn9fFwXC1Pncko+dVCdj+fDE8pT5k35QIY5IOadNjseaKvShb7UTiBAsGPpmGntcmhP3hPalsUPNPqAHGzMmqfVfJL4GhL3dDxdoquEucAII726Bn0pH/WTn2f1EOAEg/KxZDZmbAW+bDvk/Kw2ZmnB2LTf8+UPv+kBcyEJGmx6Jjd6B0YXDHSJxkwfD/dcegp9Ox9tp9YTMBoHxtFbqdH4us6xNQtc+DfZ+WI392GcpXVyn6/LoGPJYGY6Iey8/aBU+5D/0fTMXo77JgjNdhwaAtsG91I6q/CaM+z0T/R9Kw+pI9YTN7/SsRAx5Pw86XS1D0sw1+VwBxoyPRe0YSch8uRNkyB7JuSMTEP3pj4VHbYdsUfgfr90DwD+iWhwuxb3Y5qvbW38kjuumRcV4ccu5LAQLAlofa9g+pEhnnxmLwzAzs+6Qc5WucSBhvxhFvd0fqaTFYfdmeFh+pay/t0ZP7eFBX3MeBtt/P1bqPAzL2cwn7OND2+zn3ce7jbYH7eNfdx4G238/Vuo8D7bOfh+JguFr3i+KQ+2ABtj9TDAAoW+7A+AW9sPH2/bVHsWx/u2DK0CPz8viwO5jP6Ye3wo/tzxbDXeKt9zGdRYshL2Rg29NFsG1uwTct5OBV7xlJ2Pt+GdZctbf2sf1fViDgCaDXv5IU/RE1JuvhrPPLPnlqNNZcuad25wKAkt/t2PSfAxg8M0PxDpb7QAHKVzuRcmI0Ms6LQ89rE9D7liTYt7mx75My7JtdBvsWZdMako6Nwqa796NgTiUAYO11+zB5Yz+svGB37dQI22YXtjxahAGPpSrKzLop+Mdu6+NF9f6dFWurMHJ2Jn7K2IS11+yDPlqHAY+nYfnpu8JmZl6ZgI2378fuN62Nfrxqnxc7ni2Gt8KHfvelKvojOu7nbEX/HmOSsl25961J2P5sMTbdHfyluuNZIOlYC4a/1wPj5/fC0lPz4Cn1hUlp347t1ZP7eFBX3MeBtt/P1bqPA22//0joCLT9Pg60w37OfZz7eBM6e/+R8HpDxD4OtPl+rtZ9HGif/TwUV5OuFtnTGJw7X61sZfD/6z4GAKV/OWDuZQyb9+uALSj+3Y6+dydDH6PD3g/LsPf94Nu+j8oAAIVzK2sfaw1zbxP2zW74ufs+LUfUwAhFGc7dHkT1O3jD6oA30OjKbJ5KP7TGlt3QK+AFCuZUYvUle/BTxiasungPKjdVoc+dyZi8vh+OXtYHvW9LCptjiNWi6sDBX1BV+4P/7yqs/0vLVeCBIU6nqFtEhh7WZQ2nhFiXOqCzaBGZHfwe7/u4DIkTLYoyDXE6OHaE/6Xh2OFW3DPhKAtMKXq4S3zNvnltyv6gROWYUPhjZb3Hin+1Y+GE7dDHaDFxYW9FP9/t2bG9enIfD+qK+zjQ9vu5WvdxoO33Hwkdgbbfx4H238+5j3Mf7yr7j4TXGxL3ceDQ93O17uNA++znoXhmuJrP7oc+9uCxAb8rAL8rAJ+j/g+bRgdo9OF/0Fz7vVh9yR4kTDRj8HMZyLoueLSx6CfbIfXURmhqr29wl3gR8DWcZhLwBYCAsukne96xot/9qShZaId9ixt737ei779TYF3qgLc8+G83xOvQ9+5klPxhb3Vvf1UA+Z+VI/+zcuijtUg7IwbdzotDzkOptUf4mmLb4kbaaTEo+S34/OnTY+B3BZAyNRqlfx7cQVJOjIZ9u7IjWLZcFzLOikXx/Pr/poyzYhHwBmqnRnkrfYoPGVmXOtD79mRYlzjgczT+9deZNehzR3AbJSo3VMG2xYVVFzY/lST9zBiM+DgzbJ6n3A9jYsNfQM5dHvx11HaMEJVzXQAAIj9JREFU/i4LE//shS2PFjXy2R3Tsb16ch/vuvs40Pb7uVr3caDt9x8JHYG238eB9tnPuY9zH29MZ+8/El5vSNnHgbbdz9W6jwPts5+H4mC4mm2LC3EjzSj4rvooVgD4IXpjg+2iB0bAmad8ykDpQgf+GL0NWdcn4Mj3e8C6xIEtj7T+GpPxv/Q6+I4GiBtlbvADEjMkQvGqfNueLkL0QBMmre6LkgV22La4EDMsAsft7I/KDVW1ee4SH1ZfGn5uvxLeSj/2vleGve+VwZAQ/sjQ9meKcOQHPZAwzgxPhR8JE81Ye9VeDHmlGyK6GVCxrgqxwyORcW4sNvwzX1GHLQ8WYuRnmbDkmFA83wa/O4C4kWaknRaNvNdLaxcfiBkWWW81vOZsuDkfY+dl47id/VH4kw22XBe8ZT4EAsGjzVE5JqScEAWfK4AlJ+xUlFm2zIHkqdHhN6xZSCCM8lVOpE2Pwf4vKxp8zFPmx+Ljd2Lkp5kY/Hy64hUG27pje/XkPt5193Gg7fdzte7jQNvvPxI6Au23jwNtu59zH+c+3qhO3n8kvN6Qso8Dbbufq3UfB9pnPw/F+wxXSz8jBoZEXZPXidQYMycL1uWOVq0iaEjQof/DqehxeTy0eg0WHbej3pGScLpfEtfgMdcBL4p+rn/0asTsTNhyXbWrzimRPDUKPS6LR/xoM0xpekADeKw+2Da7UPB9JXa9UQqfTdmtBMb9ko31N+W3+oeyManTotHt/DhoDBrseceKwh8rkXiMBQOfSEdUfxOcu9zYNasUO18qUZwZP96MfvekIGZYBHQRWti3ubBrVil2/89au1fEjY5EwBNQvJiAPlaLrOsTkTI16uAtGVD9tcx1oXCuDXmvl9QeyQvH3MuI6IGm2usvmqKNqL7VQZil+tPPikGvGUlYdtqu4AqZjYYFF39IPi4K8/vmdnjH9urJfbxr7+NA2+/natzHgbbffyR0BDpmHwcObT/nPs59vCmdvf9IeL0hYR8H2m8/V+M+DrTPfl4XB8OdIGqgCZbeRpT+5Wjx4gFE1PVxHyc6/HE/Jzq8cR9XBw6Gm6HRVU/lb6N7q7d1npozJXRUMynfH7X+XKo1k/t425Hw/ZaSKaGjlEzu421LwvdHrZkSOkrJ5DXDdRiTdci+KREpU6MR1d8EnTl4JbbP4Q9OQZhbibyXS+AuVnZ0qK3z1JwpoaNSsUdGIOuGRKy9RtnS952R2dI8Kd8ftf5cqjWT+3jbZUr4fkvJlNBRSib38bbNlPD9UWumhI6SMuvimeFqMUMjMHZeNhAACuZUoHKzCx6rDxoNoK9eNCFtWjSg0WDx1J2oXN/8nPS2zlNzpoSOLZF+RgxGfJKp6MbtnZXZkjwp3x+1/lyqNZP7eNtlSvh+S8mU0FFKJvfxts2U8P1Ra6aEjpIyQ3EwXG38r9nw2vxYed5u+JxNLKcfqcGI2ZnQWbRYPKX5VQTbOk/NmRI6AkDCUeaw2wBA4qQo5NyXouiPU1tntkdHKd8ftf5cqjVTrft4e2RK+H5LyZTQUUom9/G2zZTw/VFrpoSOkjJDcZp0tbiRZiydntfkFxoAfM4Atj9XjNFfZ3V4npozJXQEgPHzeym/NYLCQ1BtndkeHaV8f9T6c6nWTLXu4+2RKeH7LSVTQkcpmdzH2zZTwvdHrZkSOkrKDMXBcDV3sRdR/UwoWdD8zaqjckzwlHg7PE/NmRI6AoCn1IfCeZXY+kTzN5BPOT4KA59M75TM9ugo5fuj1p9LtWaqdR9vj0wJ328pmRI6SsnkPt61/5ZL+BmSkimho6TMUBwMV8ubVYqBT6bDmKBD/uflsG+tf7NuSx8j0s+ORd+7k7H18eZ/+bRHnpozJXQEAOtSB8zZRtj+bv6ebdE5JkV57ZHZHh2lfH/U+nOp1ky17uPtkSnh+y0lU0JHKZncx7v233IJP0NSMiV0lJQZitcM19HnrmT0uSMZ+mgtAr4AvDY/EAD00VpodBp4K/3Y9mQRtj2p7Ivd1nlqzpTQsef1Ceh+cTz+mri92e1ij4xA1o2JWHt1+NUd2zqzPToCMr4/7ZEpoaOaM9W4j7dXpoTvt5RMCR2lZHIf79p/yyX8DEnJlNBRUmZdHAyH0Bo1iB9vRlSOCYZ4HQDAY/XBluuCdZEDfnfLvlxtnafmTAkd1UzK90etP5dqzeQ+3nYkfL+lZEroKCWT+3jbkvD9UWumhI6SMmtwMExERERERESqo+3sAl2eBhj3czYsfYxdM0/NmRI6SsmU0FFKpoSOas6U0FFKpoSOUjIldJSSKaGjmjMldJSSKaGjgEwOhsPRAImTLNBHt9GXqq3z1JwpoaOUTAkdpWRK6KjmTAkdpWRK6CglU0JHKZkSOqo5U0JHKZkSOgrI5GCYiIiIiIiIVIeDYSIiIiIiIlKlAN+af0s82hLQWbRdNk/NmRI6SsmU0FFKpoSOas6U0FFKZuLRloDOrGn7jirMlNBRSqaEjmrOlNBRSqaEjl09k6tJE1Gb0+iAQACAX12ZEjqqOVNCR0mZRERE0uk7u0BXorNo0fOaBKScHI3o/iYYEnQI+ABXgRfWpQ7sfrsUJQvsnZan5kwJHaVktkdHY7IO2TclImVqNKL6m6AzB6/A8Dn8sG12oWBuJfJeLoG72HdYZUroqOZMCR0lZYYTe2QEsm5IxNpr9jGzi+WpOVNCx66SqYvUIP3MWBhT9Kj8uwpFP9saHEAzZxvQ9z8pijLbOk/NmRI6Ssqsi2eGq5l7GTFuXjaMKXpUrK+C3+VHzKAI6GN12Pu+FcYUPZKnRGHfx2VYe92+sF+1ts5Tc6aEjlIy26NjzNAIjJ2XDQSAgjkVqNzsgsfqg0YD6ON0iMoxIW1aNKDRYPHUnahcX3VYZEroqOZMCR0lZSqRfkYMRnySiTmmDW2Sp+ZMCR2lZEro2BUyTWl6TPijN8xZBvgcfujMWthyXVh9+V6Ur3TWbhc3OhIT/+wdNrOt89ScKaGjpMxQPDNcbfDMDLiKvPhz/Da4i4JHyrUmDYa+2g2WPkYsOnYnLH2MmPBHb/S6xYUdzxZ3aJ6aMyV0lJLZLh2fT0fZcgdWnrcbPmfjo+eNkRqMmJ2Jwc+nY/GUnYdFpoSOas6U0FFKZsJR5rDPCQBRgyIUbafmTAkdpWRK6Cgpc8CjafC7/FgwcAvs29yIHhKBwc+lY8KCXlh9+R7s/7JCcVZ75Kk5U0JHSZmhOBiuljjRjJUX76kdIACA3xXApv8cwPG7+iOypwH2bW5sfawQWTcmhh0ktHWemjMldJSS2R4d40aasXR6XpMvugHA5wxg+3PFGP11Vtg8KZkSOqo5U0JHKZnj5/cKzhLRKHhyhXPN1JopoaOUTAkdJWUmTbZg450HYN/mBgBUrq/C4uN2YsDjaTjyo0xsums/dswsURbWDnlqzpTQUVJmKA6Gq/ndARgauXGzPloLaACtIfgbp2J9FSJ7GDo8T82ZEjpKyWyPju5iL6L6mcJeZxyVY4KnxHvYZEroqOZMCR2lZHpKfSicV4mtTxQ1u13K8VEY+GS6oo5qzZTQUUqmhI6SMg3xOrgLG/4+2PTvA3DscmPw8xmI6GHE/s/LOyVPzZkSOkrKDMXBcLUD31ZgwONpqMr3ouSP4AuIqIEmDHutG+zb3bVHJIyJOriLw794aOs8NWdK6Cglsz065s0qxcAn02FM0CH/83LYt7rrfdzSx4j0s2PR9+5kbH28+T/ckjIldFRzpoSOUjKtSx0wZxth+9vV7HbROSZF/dScKaGjlEwJHSVl2re7ETcqsva1QV27XiuFu8CL4e/1QNLRlk7JU3OmhI6SMkNxMFxt4237MeKTTIz7JRt+TwABL6CL0MCR58bKi/bUbhfV36Rofnpb56k5U0JHKZnt0XHb/xUBAaDPHcnI+W8qAr4AvDY/EAiecdboNPBW+rH1sSJse1LZi3kJmRI6qjlTQkcpmQU/VqL7xfFht3PscmPP+1ZFHdWaKaGjlEwJHSVlFs23IfOqBGx/trjRqdX7v6qAe1oeRn3Rs1Py1JwpoaOkzFBcTTpE3JhIxA6LhDZCA/t2N4rmVSKg7ARZh+SpOVNCRymZ7dFRa9QgfrwZUTkmGOJ1AACP1QdbrgvWRQ743S3/VSMhU0JHNWdK6Cgpk4gOT6ZUPWJHRKL0Tzu8lU3fkDwqx4S40ZHY+35Zh+apOVNCR0mZoTgYJiIiIiIiItVpuJIONUtr0iheWKgz8tScKaGjlMz26KjRQ5WZEjqqOVNCRymZEjpKyZTQUUqmhI5qzpTQUUqmhI5dMZOD4RZKPTkaU7bldNk8NWdK6Cgls6V5WTck4NjcfjjJOhATF/VG94viGmwTe2TkYZcpoaOaMyV0lJIpoaOUTAkdpWRK6KjmTAkdpWRK6Cgpsy4OhonokGScG4vBMzNgXepE7sOFqMr34Ii3u2PE7ExoI5TcBFFmpoSOas6U0FFKpoSOUjIldJSSKaGjmjMldJSSKaGjpMxQXE262rifsxVtZ0xS9iVr6zw1Z0roKCWzPTr2vjUJ258txqa7DwAAdjwLJB1rwfD3emD8/F5YemoePKU+xXlSMiV0VHOmhI5SMiV0lJIpoaOUTAkd1ZwpoaOUTAkdJWWG4pnhaglHWWBK0cNd4mv2zWtT9gVv6zw1Z0roKCWzPTpG5ZhQ+GNlvceKf7Vj4YTt0MdoMXFhb5h7GRXnScmU0FHNmRI6SsmU0FFKpoSOUjIldFRzpoSOUjIldJSUGYpnhqtVbqiCbYsLqy7c0+x26WfGYMTHmR2ep+ZMCR2lZLZHR0+5H8ZEXYPHnbs8+Ouo7Rj9XRYm/tkLWx5Vdo9UKZkSOqo5U0JHKZkSOkrJlNBRSqaEjmrOlNBRSqaEjpIyQ/HMcLWyZQ7EjzGH3zCA4A2pOjhPzZkSOkrJbI+O5aucSJse0+jHPGV+LD5+J8pWOjH4+XRlgUIyJXRUc6aEjlIyJXSUkimho5RMCR3VnCmho5RMCR0lZTYmwDcEzL2MgdRp0WG300ZoApGZhg7PU3OmhI5SMtujY/pZMYEJf/YKGOJ1TW+nRWDoq90CU7bmHDaZEjqqOVNCRymZEjpKyZTQUUqmhI5qzpTQUUqmhI6SMkPfNNX/Q0RERERERKQanCbdDI0ObfoVaus8NWdK6CglU0JHKZkSOqo5U0JHKZkSOkrJlNBRSqaEjmrOlNBRSqaEjlIyuYBWHcZkHbJvSkTK1GhE9TdBZw5+pX0OP2ybXSiYW4m8l0vgLla20m5b56k5U0JHKZkSOkrJlNBRzZkSOkrJlNBRSqaEjlIyJXRUc6aEjlIyJXSUlFkXp0lXixkagbHzsoEAUDCnApWbXfBYfdBoAH2cDlE5JqRNiwY0GiyeuhOV66s6NE/NmRI6SsmU0FFKpoSOas6U0FFKpoSOUjIldJSSKaGjmjMldJSSKaGjpMzGtOpi48Ptbfyv2YHR3/YM6CI1TW6ji9QERn/bMzBufnaH56k5U0JHKZkSOkrJlNBRzZkSOkrJlNBRSqaEjlIyJXRUc6aEjlIyJXSUlNnIW6s+6bB7O7liUCBxsiXsdomTLYGTygd1eJ6aMyV0lJIpoaOUTAkd1ZwpoaOUTAkdpWRK6CglU0JHNWdK6CglU0JHSZmhb1xAq5q72Iuofqaw20XlmOAp8XZ4npozJXSUkimho5RMCR3VnCmho5RMCR2lZEroKCVTQkc1Z0roKCVTQkdJmaG4gFa1vFmlGPhkOowJOuR/Xg77Vne9j1v6GJF+diz63p2MrY8XdXiemjMldJSSKaGjlEwJHdWcKaGjlEwJHaVkSugoJVNCRzVnSugoJVNCR0mZobiAVh197kpGnzuSoY/WIuALwGvzAwFAH62FRqeBt9KPbU8WYduTyr7YbZ2n5kwJHaVkSugoJVNCRzVnSugoJVNCRymZEjpKyZTQUc2ZEjpKyZTQUVJmXRwMh9AaNYgfb0ZUjgmGeB0AwGP1wZbrgnWRA353y75cbZ2n5kwJHaVkSugoJVNCRzVnSugoJVNCRymZEjpKyZTQUc2ZEjpKyZTQUVJmDQ6GiYiIiIiISHW4gFYLafRAZA9Dl81Tc6aEjlIyJXSUkimho5ozJXSUkimho5RMCR2lZEroqOZMCR2lZEro2BUzORiuI+uGBByb2w8nWQdi4qLe6H5RXINtYo+MxJRtOZ2Sp+ZMCR2lZEroKCVTQkc1Z0roKCVTQkcpmRI6SsmU0FHNmRI6SsmU0FFSZl0cDFfLODcWg2dmwLrUidyHC1GV78ERb3fHiNmZ0EZoOj1PzZkSOkrJlNBRSqaEjmrOlNBRSqaEjlIyJXSUkimho5ozJXSUkimho6TMxrTqBsWH29tRS3oHBvxfWr3Hko61BI7f2z8w8a/eAUOCLgAgEDc6MjDNNbjD89ScKaGjlEwJHaVkSuio5kwJHaVkSugoJVNCRymZEjqqOVNCRymZEjpKygx945nhalE5JhT+WFnvseJf7Vg4YTv0MVpMXNgb5l7GTstTc6aEjlIyJXSUkimho5ozJXSUkimho5RMCR2lZEroqOZMCR2lZEroKCkzFAfD1TzlfhgTdQ0ed+7y4K+jtsNd4sXEP3shbqS5U/LUnCmho5RMCR2lZEroqOZMCR2lZEroKCVTQkcpmRI6qjlTQkcpmRI6SsoMxcFwtfJVTqRNj2n0Y54yPxYfvxNlK50Y/Hx6p+SpOVNCRymZEjpKyZTQUc2ZEjpKyZTQUUqmhI5SMiV0VHOmhI5SMiV0lJQZioPhans/tMLcy1h7I+dQ/qoAlp2+C7vfssK529PheWrOlNBRSqaEjlIyJXRUc6aEjlIyJXSUkimho5RMCR3VnCmho5RMCR0lZYbSIHjxMBEREREREZFq8MwwERERERERqQ4Hw0RERERERKQ6HAwTERERERGR6ug7uwAREdHhome0DkemGpBh0cFs0CDWqMGX26qwqrB1C3sQERFR++FgmIiI6BANTNDjiaNiMD7D1OBjdk+Ag2EiIqIuiKtJExFRq5Tc0PC+fi5fAAV2Hxbtd2PmKju2lHk7oVnHGpqkx3fTExGp1+CVdXZ8sMmB7WU+/nElIiLq4nhmmIiIDskTyytr/z/GqMGRKUacn2PGtF4ROOWrEmwoOXwHxFoN8OqUOJh0Glw6z4q5ea7OrkREREQKcTBMRESH5MkVtgaP/d/EGFwzxILrh1rwjwXlndCqY0zqbkT/BANmrbNzIExERCQMB8NERNTmFuxx4ZohFiRGNn7TgtN7R+CygWYMSTIgUq9BocOH5QUevLLWjjVF9a+vPbNPBC6t3jZCp8HuSh8+3+LEi2tscPvr5zY2dbvGl1uduOaXstr3o40azBgehWm9ItA9SocqXwCrCjx4aY0Nv+9zK/p3jk8PXiO8qdSDV4+NxdHdTUiI0KK0yo/f97rw9EobdpT7Gnxea577gpxIvHRsXJNdEl/dX/v/d46Mwl2jonHaNyX4Kz/8v+WlybG4oL8ZR3xQiD2VDfuW3JCOhftcmP5taYufo0e0DmsuTsHHmx21B0amZUfg3RPjsaLAjVO+LoG3zvexf4IeP5+ZhAq3H5M+K0ax099EcvM9RqUa8Pm0BFS6Azj1mxLsrDj47zJqgRuGWXBW30hkx+jhCwSwocSLN9bb8c32qib7z1xtw/1jYzAu3QijDlhf7MVTKyrx296G//7WPEdddo8f++1+/LCzCjNX21Dm4sR7IqK2xsEwERG1uUndg4PE0IEtcHDgVez0Yc7OKpQ4/ciwaDGxmwnbyrz1PmfmMbG4eIAZ+2w+zNlRhXKXHyNTjfjPmGgc1d2Is74rhS9kjLC7wouPc50NnndT6cHp2jFGDX48IxH9EwxYVeDG6zuqkBCpxem9I/D5qQm4/Y8KvPu3I+y/M9kcHOw/dXQstBrgx50ubC3zom+cHuf0i8RJWRE447vSev+mQ33uH3ZWYX3xwbwLciKRGSPrz/mcnVV4c70dVw+x4J7R0XhwSXCqfaQeeOv4OJh0wPXzy8IOhJtyZIoBn56SAJsngOnf1h8IG7TAZ9MSMLGbCVusXry10Q6zXoNTe0Xg7RPi8dwqGx5ZWtkgMzNGh7lnJmFTqRfv/u1AqlmL0/tE4tNTEnDtL2X4us4At7XPsb7Ygx92BnMsBg0mdTfh5uFRGJduxIlflbTqa0FERE2T9deTiIi6nDtHRtX+f7RRg+EpRoxJM2BuXhVeXmOvt+2lAyJxQX8zVhW4ceacUlS6D45ktRoguc6Z5AtyInHxADPm7KjCdb9YUVXnhGXN2cCrBpsxa339gePuSl+jU7fremBsNPonGPDORjtu+6Oi9vEXVtsw/6wkPD4xBr/ucTV6lrQunz/YX6/V4KqfrPUGRKf3jsBbJ8TjtSlxGPdJUe2CWq19bl31l+b7nVX4pM5gf0KGUdxgGADuW1SBUWlG/OMIC/7c58ave1x48qhY9E8w4MkVlfhT4dn5UEOT9PhsWgKcvgBO/7YE20POzN80zIKJ3Uz4eVcVLvrRWnsw5ckVNvx8ZiJuOTIK8/KqsLyg/oGcCRkmvLjGhv8uPjiIfXODA3PPSMQzk2Ixf7cLlZ7AIT3HhmJPvZ9draYSc89IxKg0I5Iita0+OEBERI1rfP4aERGRQneNiq59u3FY8CzWFqsXX25zwuapf9r2miEWAMCtf5TXGwgDgD8AFDgOvti/dogFHl8A/1xQVm8gDABPr7ShxOnHOX0jW9xXrwXO6RcJm9uPh0POzu0o92HWejtMOg3O6xc+21Xda1G+q95AGAC+3l6Fxfvd6Buvx9h04yE/t0GrqX7Ow2O6rNsPXP2zFQ5PAK9MicVNwyy4sL8Zf+W78FSYgxlNGZSoxxenJsLjD+CMb0uxtazhwYwL+5vhDwRw36KKerMKip1+PL0y+LyXDDA3+Lxylx9Ph/RaU+TB51udiDNpcUqviEN+jlAaADqtBk5vABUuDoSJiNqavEPJRETUpdS9VtWs16B/gh73j43GrOPi0T/ehkeXVdZ+bGCiAQUOH9YXN7/CdKQeGJykR0mVH9cPtTS6jdsXQL/4lv8Z6xunh8WgxZL97kavw/xznxu3jwSGJhnCZtUMTJs6i/nnPhfGpRsxJEkfHBgfwnNHG6oHw17lg+ELciIxIcOIAIKDuX02H37d44KziS//9UMtKG/hoKulz1HXjnIfbv2jHLOOi8dD42NQ7PThul/K4G/FeH9Agh53jIxCQoQWs9bZkWttWCDKoEHvOD3ybb5GB8o138chjXz91xV7GhzcAYC/8t24oH/wmvZPcp2H9ByDkwy1My2iDBoc08OErBgd7v2rosH18UREdOg4GCYiojbj8AawqtCDS+dasf7SFPzzCAv+t9GOfLsfsabgYG6/Pfyr+jiTFlqNBsmROtw1KrpNO8YYgz0KHI1Pga55PKa6b3Mc1QPTume062VV/1tjTdpDfu6E6inkRS2YKntB/4ZnH61VftzxZzm+2lbV4GNNHXhoy+cI9dseNypcfsSYtPh2e5Win4/GPDohBpXuADYUe3DlYDO+3OZsMA1Z6dc/tpGvf2FT3+Pqx2uyD+U5hiQZGgySVxS4kVdx+N6ejIioM3EwTEREba7CHcC2Mh+OSDZgWLIB+XYXyqvPhKZbwl+hU1G97doiD479vLjNuwFAilnX6MdTqx8PncbdmAK7rzqr8X9TavW/taL6tN6hPHev6uuCd4e5jrmuuissx5k0OK1XBJ44KhYvHBOH+bsLavvUaG416dY+RzivTIlFjEmLYqcPlw4048ttwenlLeXwBHDOnFKUufz47dwkvDolDpM+LYa9zpl0pV//0K9L8HOa+B6ba77HgUN+jrorbpt0wKBEA545OhafnpKAk78uwYqChgvSERFR6/GaYSIiahdx1We+qi91hcMbwN8lHqSadRiS1PyxWLs3gE2lHvRP0NfmtJVtZV7YPX4MSdQj1tgwe2K34PW9axtZCTtUzeBkQoax0Y/XPL6uyHvIzz0i1YD9Nl+TZ6HDKXMF8N4mJ+bvccFs0GBAQtsfD2/pc/zzCAuOy4zAZ1ucOP3bUnj8wKzj4pAQ0fLv+Yzfy7G6yIOdFT7c91cFsmP1eGxiTL1tbJ4AdpR7kW7Roldsw8Fqzdd/XSNf/6FJBkQZGvaq+R7XrPB9KM9Rl8sHrCr04OmVldBpNTizT8uvjyciouZxMExERG3u5CwTsmL0cPsCWHbg4Iv+WeuDq0s/e3QsokMGgxocPMsGAK+sDS4m9eLkuNqpp3XFGjUYGmZQ3RiPH/h8axWijFr8e3T9KdhZMTpcO8QCty+AT7c0vD1TqL9LvVhd6MZR3Uw4OctU72On9orAhIzg7aKWVJ/pbO1zXznIjDSLDt/sCD/tuDk6DdAzOjhAa6/71ip9jhEpBvxndDS2l3lx+x/l2FTqxb1/VSAjSoeXJse1+HnrrrT83iYnfsyrwsUDzA2+Lx9tdkCr0eDBcTG1B2oAICFCg9tHBK/X/XBzw1tbxZq0uL3OyukAcESyAWf3jUS5y4/v63xvWvscjRmUGJw2fXgsm0ZE1LVwmjQRER2SurdWMhs0yInX47jM4ADkkaWV9a5xfX+TE2PTjTg/x4zlFybjx50ulFT5kWbW4qhuJny42VF7a5mPNjtxRLIBVw22YOVFKfh1jwv7Kn2Ii9CiZ7QO4zKM+GizA7fXuT2RUg8tqcC4dCOuGWLB8BQDFu5zIyEieK/fKKMGd/1ZoXg68s0LyvHd6Yl4Z2o8fsirwrYyH/rG6XFSlgmVbj9unF9WbyDTkuc+ItmA/46LxlHdTNhZ7sXTKxrem7Y5J2aZ0Dcu+Kc+PkKDk7IiMDDRgMX73Y0uMNUa4Z6jR3TDs6MxRg3eOD4OAQDX/GytXZjqnb8dOLq7EdN7R+LGYRa8stbe4HOVmvFbOUaca8Bzx8RixexiFFb/HL60xo4pmRE4OTsCf5ybhJ93uWDWa3Ba7wikmHV4YbUNSw80PGv7V74LlwwwY0SKAcsOeGrvM6zVALf+Xl57W6VDeY66C2hF6DQYmKjHlEwTqrwBfKxw8ExERMpxMExERIek7gJXXn8AxU4/5uW58OYGO37b2/Daz5t+LceCPS5cOtCM03tHwKjToMDhw+L9bszNq3/m884/K/DLbhcuH2jGpO5GxBq1sLr82Ffpw0trbPhMwdnbxpS5Apj6ZTFuOTIKp2RH4IZhFlRVL/714hpbo72b8nepF8d9Xow7RkZhUncTTuypRUmVH19uq8LTKyuxLWRF4ZY8d984PVLNOsxcZcOLa2ywtvBs7o3DDh6oqHD5scfmw2NLK2vP0LeF1jzHC5Nj0TNGj3v+qsDakJXF//VbOYYlG3DfmGgs2e/GqsLWXSdb7PRjxm/l+OjkBMycHIsLfrACCJ6dP+u7Etw4zIKz+kbimiEW+PwBbCjx4p6/KvBlE4t+7a7w4fbfK3D/2GhcPsgMo1aDdUUePLWyEgv21P95ae1z1F1Ay+UL4IDdhy+2VuHFNTZsLOEiWkREbU0DzrwhIiIialSPaB3WXJxSb3ErIiI6PPCaYSIiIiIiIlIdDoaJiIiIiIhIdTgYJiIiIiIiItXhNcNERERERESkOjwzTERERERERKrDwTARERERERGpDgfDREREREREpDocDBMREREREZHqcDBMREREREREqvP//h2ux9ouu0UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 8))\n",
    "\n",
    "sns.pointplot(x=month_year_stats.index.to_timestamp(), y=month_year_stats.values)\n",
    "sns.pointplot(x=month_year_stats.index.to_timestamp(), y=month_year_stats_total.values)\n",
    "\n",
    "\n",
    "# ax.set_xticklabels(labels=month_year_stats.reset_index().год_месяц.values\n",
    "plt.legend(['Больных коров', 'Всего коров'])\n",
    "plt.xlabel('Всего больных коров')\n",
    "plt.title('Изменение числа больных коров')\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "63d5d124",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 8))\n",
    "\n",
    "sns.pointplot(x=month_year_stats.index.to_timestamp(), \n",
    "              y=month_year_stats / month_year_stats_total)\n",
    "\n",
    "plt.title('Изменение соотношения больные/все')\n",
    "plt.xlabel('Всего больных коров')\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "effe42dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15322"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_df.номер_животного.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "de95571a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2767"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_df[total_df.событие == 'МАСТИТ'].номер_животного.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "f6ae42b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>номер_животного</th>\n",
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       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>213</td>\n",
       "      <td>2019-03-15</td>\n",
       "      <td>МВ</td>\n",
       "      <td>1</td>\n",
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       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>216</td>\n",
       "      <td>2019-03-18</td>\n",
       "      <td>F006T003</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.514031</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
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       "      <td>2019-04</td>\n",
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       "   номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "5              321    1               6              FA               3   \n",
       "6              321    1               6              FA               3   \n",
       "7              321    1               6              FA               3   \n",
       "8              321    1               6              FA               3   \n",
       "9              321    1               6              FA               3   \n",
       "\n",
       "  дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "5    2009-09-11                                   62   \n",
       "6    2009-09-11                                   62   \n",
       "7    2009-09-11                                   62   \n",
       "8    2009-09-11                                   62   \n",
       "9    2009-09-11                                   62   \n",
       "\n",
       "   дней_стельности_при_событии  номер_группы_животного  \\\n",
       "5                          291                      18   \n",
       "6                          291                      18   \n",
       "7                          291                      18   \n",
       "8                          291                      18   \n",
       "9                          291                      18   \n",
       "\n",
       "   предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "5                                 18   МАСТИТ                     213   \n",
       "6                                 18   МАСТИТ                     215   \n",
       "7                                 18  ПЕРЕВОД                     216   \n",
       "8                                 18   МАСТИТ                     221   \n",
       "9                                 18  ЗДОРОВА                     230   \n",
       "\n",
       "  дата_события примечание_события  живых_потомков  вылечена   возраст  месяц  \\\n",
       "5   2019-03-15                 МВ               1         0  9.505818      3   \n",
       "6   2019-03-17             ТМ6_34               1         0  9.511294      3   \n",
       "7   2019-03-18           F006T003               1         0  9.514031      3   \n",
       "8   2019-03-23            КМ4_134               1         0  9.527721      3   \n",
       "9   2019-04-01             МАСТИТ               1         0  9.552361      4   \n",
       "\n",
       "    год год_месяц  \n",
       "5  2019   2019-03  \n",
       "6  2019   2019-03  \n",
       "7  2019   2019-03  \n",
       "8  2019   2019-03  \n",
       "9  2019   2019-04  "
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "eec855f7",
   "metadata": {},
   "outputs": [
    {
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       "      <td>18</td>\n",
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       "      <td>221</td>\n",
       "      <td>2019-03-23</td>\n",
       "      <td>КМ4_134</td>\n",
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       "      <td>43</td>\n",
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       "      <td>8.736482</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
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       "    номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "5               321    1               6              FA               3   \n",
       "6               321    1               6              FA               3   \n",
       "8               321    1               6              FA               3   \n",
       "89             1540    1               6              FA               1   \n",
       "92             1540    1               6              FA               1   \n",
       "\n",
       "   дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "5     2009-09-11                                   62   \n",
       "6     2009-09-11                                   62   \n",
       "8     2009-09-11                                   62   \n",
       "89    2010-07-18                                   56   \n",
       "92    2010-07-18                                   56   \n",
       "\n",
       "    дней_стельности_при_событии  номер_группы_животного  \\\n",
       "5                           291                      18   \n",
       "6                           291                      18   \n",
       "8                           291                      18   \n",
       "89                            0                      43   \n",
       "92                            0                      43   \n",
       "\n",
       "    предыдущий_номер_группы_животного событие  дни_доения_при_событии  \\\n",
       "5                                  18  МАСТИТ                     213   \n",
       "6                                  18  МАСТИТ                     215   \n",
       "8                                  18  МАСТИТ                     221   \n",
       "89                                 43  МАСТИТ                     173   \n",
       "92                                 43  МАСТИТ                     183   \n",
       "\n",
       "   дата_события примечание_события  живых_потомков  вылечена   возраст  месяц  \\\n",
       "5    2019-03-15                 МВ               1         0  9.505818      3   \n",
       "6    2019-03-17             ТМ6_34               1         0  9.511294      3   \n",
       "8    2019-03-23            КМ4_134               1         0  9.527721      3   \n",
       "89   2019-04-03              КМ3_4               1         0  8.709103      4   \n",
       "92   2019-04-13             КМ5_34               1         0  8.736482      4   \n",
       "\n",
       "     год год_месяц  \n",
       "5   2019   2019-03  \n",
       "6   2019   2019-03  \n",
       "8   2019   2019-03  \n",
       "89  2019   2019-04  \n",
       "92  2019   2019-04  "
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.событие == 'МАСТИТ'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "f17af4e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2767"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.номер_животного.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73e3b37d",
   "metadata": {},
   "source": [
    "## Парсинг актуальных переходов между группами: данные в изначальных колонках неактуальны"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "d90cbd09",
   "metadata": {},
   "outputs": [
    {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>216</td>\n",
       "      <td>2019-03-18</td>\n",
       "      <td>F006T003</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.514031</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>231</td>\n",
       "      <td>2019-04-02</td>\n",
       "      <td>F004T012</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.555099</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>252</td>\n",
       "      <td>2019-04-23</td>\n",
       "      <td>F004T012</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.612594</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>675</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>FD</td>\n",
       "      <td>1</td>\n",
       "      <td>2009-11-02</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>3</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>191</td>\n",
       "      <td>2019-04-02</td>\n",
       "      <td>F010T007</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.412731</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>784</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-04-27</td>\n",
       "      <td>60</td>\n",
       "      <td>279</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>430</td>\n",
       "      <td>2019-03-06</td>\n",
       "      <td>F017T018</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8.856947</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "7               321    1               6              FA               3   \n",
       "10              321    1               6              FA               3   \n",
       "17              321    1               6              FA               3   \n",
       "45              675    1               7              FD               1   \n",
       "48              784    1               7              MA               1   \n",
       "\n",
       "   дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "7     2009-09-11                                   62   \n",
       "10    2009-09-11                                   62   \n",
       "17    2009-09-11                                   62   \n",
       "45    2009-11-02                                   60   \n",
       "48    2010-04-27                                   60   \n",
       "\n",
       "    дней_стельности_при_событии  номер_группы_животного  \\\n",
       "7                           291                      18   \n",
       "10                          291                      18   \n",
       "17                          291                      18   \n",
       "45                            0                      43   \n",
       "48                          279                      18   \n",
       "\n",
       "    предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "7                                  18  ПЕРЕВОД                     216   \n",
       "10                                 18  ПЕРЕВОД                     231   \n",
       "17                                 18  ПЕРЕВОД                     252   \n",
       "45                                  3  ПЕРЕВОД                     191   \n",
       "48                                 18  ПЕРЕВОД                     430   \n",
       "\n",
       "   дата_события примечание_события  живых_потомков  вылечена   возраст  месяц  \\\n",
       "7    2019-03-18           F006T003               1         0  9.514031      3   \n",
       "10   2019-04-02           F004T012               1         0  9.555099      4   \n",
       "17   2019-04-23           F004T012               1         0  9.612594      4   \n",
       "45   2019-04-02           F010T007               0         0  9.412731      4   \n",
       "48   2019-03-06           F017T018               1         0  8.856947      3   \n",
       "\n",
       "     год год_месяц  \n",
       "7   2019   2019-03  \n",
       "10  2019   2019-04  \n",
       "17  2019   2019-04  \n",
       "45  2019   2019-04  \n",
       "48  2019   2019-03  "
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_moves = df[df.событие == 'ПЕРЕВОД'].copy()\n",
    "\n",
    "df_moves.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "1237daa2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8    44884\n",
       "Name: примечание_события, dtype: int64"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Длина примечаний\n",
    "df_moves.примечание_события.str.len().value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "771d1110",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F    44884\n",
       "Name: примечание_события, dtype: int64"
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Первые символы в примечаниях\n",
    "df_moves.примечание_события.str[0].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "id": "a5fdc2d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "T    44884\n",
       "Name: примечание_события, dtype: int64"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Пятые символы в причаниях\n",
    "df_moves.примечание_события.str[4].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b100f84",
   "metadata": {},
   "source": [
    "Все примечания по переводам между группами состоят из 8 символов, первый из которых - `F`, а пятый - `T`\n",
    "\n",
    "Тогда номер группы, из которой осуществляется переход - три цифры между `F` и `T`\n",
    "\n",
    "Аналогично, номер группы, в которую осуществляется переход - это цифры после `T`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "59084f0f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def from_transitions_parser(trans_log):\n",
    "    return int(trans_log[1:4])\n",
    "\n",
    "def to_transition_parser(trans_log):\n",
    "    return int(trans_log[5:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "id": "ffb6523d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Log to parse:\t F006T003\n",
      "6 3\n"
     ]
    }
   ],
   "source": [
    "test_log = df_moves.iloc[0]['примечание_события']\n",
    "print(f'Log to parse:\\t', test_log)\n",
    "\n",
    "print(from_transitions_parser(test_log), to_transition_parser(test_log))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "id": "1ae79bb9",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_moves[['номер_группы_животного', 'предыдущий_номер_группы_животного']] = \\\n",
    "    df_moves.примечание_события.apply([to_transition_parser, from_transitions_parser])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "f1eb9bb9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>пол</th>\n",
       "      <th>номер_лактации</th>\n",
       "      <th>результат_отела</th>\n",
       "      <th>легкость_отела</th>\n",
       "      <th>дата_рождения</th>\n",
       "      <th>дней_в_сухостое_предыдущей_лактации</th>\n",
       "      <th>дней_стельности_при_событии</th>\n",
       "      <th>номер_группы_животного</th>\n",
       "      <th>предыдущий_номер_группы_животного</th>\n",
       "      <th>событие</th>\n",
       "      <th>дни_доения_при_событии</th>\n",
       "      <th>дата_события</th>\n",
       "      <th>примечание_события</th>\n",
       "      <th>живых_потомков</th>\n",
       "      <th>вылечена</th>\n",
       "      <th>возраст</th>\n",
       "      <th>месяц</th>\n",
       "      <th>год</th>\n",
       "      <th>год_месяц</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>216</td>\n",
       "      <td>2019-03-18</td>\n",
       "      <td>F006T003</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.514031</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>231</td>\n",
       "      <td>2019-04-02</td>\n",
       "      <td>F004T012</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.555099</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>252</td>\n",
       "      <td>2019-04-23</td>\n",
       "      <td>F004T012</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.612594</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>675</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>FD</td>\n",
       "      <td>1</td>\n",
       "      <td>2009-11-02</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>191</td>\n",
       "      <td>2019-04-02</td>\n",
       "      <td>F010T007</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.412731</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>784</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-04-27</td>\n",
       "      <td>60</td>\n",
       "      <td>279</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>430</td>\n",
       "      <td>2019-03-06</td>\n",
       "      <td>F017T018</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8.856947</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "7               321    1               6              FA               3   \n",
       "10              321    1               6              FA               3   \n",
       "17              321    1               6              FA               3   \n",
       "45              675    1               7              FD               1   \n",
       "48              784    1               7              MA               1   \n",
       "\n",
       "   дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "7     2009-09-11                                   62   \n",
       "10    2009-09-11                                   62   \n",
       "17    2009-09-11                                   62   \n",
       "45    2009-11-02                                   60   \n",
       "48    2010-04-27                                   60   \n",
       "\n",
       "    дней_стельности_при_событии  номер_группы_животного  \\\n",
       "7                           291                       3   \n",
       "10                          291                      12   \n",
       "17                          291                      12   \n",
       "45                            0                       7   \n",
       "48                          279                      18   \n",
       "\n",
       "    предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "7                                   6  ПЕРЕВОД                     216   \n",
       "10                                  4  ПЕРЕВОД                     231   \n",
       "17                                  4  ПЕРЕВОД                     252   \n",
       "45                                 10  ПЕРЕВОД                     191   \n",
       "48                                 17  ПЕРЕВОД                     430   \n",
       "\n",
       "   дата_события примечание_события  живых_потомков  вылечена   возраст  месяц  \\\n",
       "7    2019-03-18           F006T003               1         0  9.514031      3   \n",
       "10   2019-04-02           F004T012               1         0  9.555099      4   \n",
       "17   2019-04-23           F004T012               1         0  9.612594      4   \n",
       "45   2019-04-02           F010T007               0         0  9.412731      4   \n",
       "48   2019-03-06           F017T018               1         0  8.856947      3   \n",
       "\n",
       "     год год_месяц  \n",
       "7   2019   2019-03  \n",
       "10  2019   2019-04  \n",
       "17  2019   2019-04  \n",
       "45  2019   2019-04  \n",
       "48  2019   2019-03  "
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_moves.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "c1ba0cfe",
   "metadata": {},
   "outputs": [],
   "source": [
    "output = df_moves.copy().drop(\n",
    "    ['живых_потомков', 'вылечена', 'возраст', 'месяц', 'год', 'год_месяц']\n",
    "    , axis=1\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "6492b0d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['номер_животного', 'пол', 'номер_лактации', 'результат_отела',\n",
       "       'легкость_отела', 'дата_рождения',\n",
       "       'дней_в_сухостое_предыдущей_лактации', 'дней_стельности_при_событии',\n",
       "       'номер_группы_животного', 'предыдущий_номер_группы_животного',\n",
       "       'событие', 'дни_доения_при_событии', 'дата_события',\n",
       "       'примечание_события'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "id": "c6d490b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "output.columns = ['Номер Животного', 'Пол', 'Номер лактации', 'Результат отела'\n",
    "                    , 'Легкость отела', 'Дата рождения', 'Дней в сухостое предыдущей лактации'\n",
    "                    , 'Дней стельности при событии', 'Номер группы животного'\n",
    "                    , 'Предыдущий номер группы животного', 'Событие', 'Дни доения при событии'\n",
    "                    , 'Дата события', 'Примечание события']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "48d4d8e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Номер Животного</th>\n",
       "      <th>Пол</th>\n",
       "      <th>Номер лактации</th>\n",
       "      <th>Результат отела</th>\n",
       "      <th>Легкость отела</th>\n",
       "      <th>Дата рождения</th>\n",
       "      <th>Дней в сухостое предыдущей лактации</th>\n",
       "      <th>Дней стельности при событии</th>\n",
       "      <th>Номер группы животного</th>\n",
       "      <th>Предыдущий номер группы животного</th>\n",
       "      <th>Событие</th>\n",
       "      <th>Дни доения при событии</th>\n",
       "      <th>Дата события</th>\n",
       "      <th>Примечание события</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>216</td>\n",
       "      <td>2019-03-18</td>\n",
       "      <td>F006T003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>231</td>\n",
       "      <td>2019-04-02</td>\n",
       "      <td>F004T012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>252</td>\n",
       "      <td>2019-04-23</td>\n",
       "      <td>F004T012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>675</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>FD</td>\n",
       "      <td>1</td>\n",
       "      <td>2009-11-02</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>191</td>\n",
       "      <td>2019-04-02</td>\n",
       "      <td>F010T007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>784</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-04-27</td>\n",
       "      <td>60</td>\n",
       "      <td>279</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>430</td>\n",
       "      <td>2019-03-06</td>\n",
       "      <td>F017T018</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Номер Животного  Пол  Номер лактации Результат отела  Легкость отела  \\\n",
       "7               321    1               6              FA               3   \n",
       "10              321    1               6              FA               3   \n",
       "17              321    1               6              FA               3   \n",
       "45              675    1               7              FD               1   \n",
       "48              784    1               7              MA               1   \n",
       "\n",
       "   Дата рождения  Дней в сухостое предыдущей лактации  \\\n",
       "7     2009-09-11                                   62   \n",
       "10    2009-09-11                                   62   \n",
       "17    2009-09-11                                   62   \n",
       "45    2009-11-02                                   60   \n",
       "48    2010-04-27                                   60   \n",
       "\n",
       "    Дней стельности при событии  Номер группы животного  \\\n",
       "7                           291                       3   \n",
       "10                          291                      12   \n",
       "17                          291                      12   \n",
       "45                            0                       7   \n",
       "48                          279                      18   \n",
       "\n",
       "    Предыдущий номер группы животного  Событие  Дни доения при событии  \\\n",
       "7                                   6  ПЕРЕВОД                     216   \n",
       "10                                  4  ПЕРЕВОД                     231   \n",
       "17                                  4  ПЕРЕВОД                     252   \n",
       "45                                 10  ПЕРЕВОД                     191   \n",
       "48                                 17  ПЕРЕВОД                     430   \n",
       "\n",
       "   Дата события Примечание события  \n",
       "7    2019-03-18           F006T003  \n",
       "10   2019-04-02           F004T012  \n",
       "17   2019-04-23           F004T012  \n",
       "45   2019-04-02           F010T007  \n",
       "48   2019-03-06           F017T018  "
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "944a32c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "output.to_csv('group_transitions.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "id": "d131623e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Номер Животного</th>\n",
       "      <th>Пол</th>\n",
       "      <th>Номер лактации</th>\n",
       "      <th>Результат отела</th>\n",
       "      <th>Легкость отела</th>\n",
       "      <th>Дата рождения</th>\n",
       "      <th>Дней в сухостое предыдущей лактации</th>\n",
       "      <th>Дней стельности при событии</th>\n",
       "      <th>Номер группы животного</th>\n",
       "      <th>Предыдущий номер группы животного</th>\n",
       "      <th>Событие</th>\n",
       "      <th>Дни доения при событии</th>\n",
       "      <th>Дата события</th>\n",
       "      <th>Примечание события</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>216</td>\n",
       "      <td>2019-03-18</td>\n",
       "      <td>F006T003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Номер Животного  Пол  Номер лактации Результат отела  Легкость отела  \\\n",
       "0              321    1               6              FA               3   \n",
       "\n",
       "  Дата рождения  Дней в сухостое предыдущей лактации  \\\n",
       "0    2009-09-11                                   62   \n",
       "\n",
       "   Дней стельности при событии  Номер группы животного  \\\n",
       "0                          291                       3   \n",
       "\n",
       "   Предыдущий номер группы животного  Событие  Дни доения при событии  \\\n",
       "0                                  6  ПЕРЕВОД                     216   \n",
       "\n",
       "  Дата события Примечание события  \n",
       "0   2019-03-18           F006T003  "
      ]
     },
     "execution_count": 197,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('group_transitions.csv').head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "d5a44343",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    44884\n",
       "Name: группа_изменена, dtype: int64"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_moves['группа_изменена'] = 1\n",
    "\n",
    "df_moves.группа_изменена.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "6f388668",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['номер_животного', 'пол', 'номер_лактации', 'результат_отела',\n",
       "       'легкость_отела', 'дата_рождения',\n",
       "       'дней_в_сухостое_предыдущей_лактации', 'дней_стельности_при_событии',\n",
       "       'номер_группы_животного', 'предыдущий_номер_группы_животного',\n",
       "       'событие', 'дни_доения_при_событии', 'дата_события',\n",
       "       'примечание_события', 'живых_потомков', 'вылечена', 'возраст', 'месяц',\n",
       "       'год', 'год_месяц', 'группа_изменена'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_moves.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "544e6434",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['номер_животного', 'пол', 'номер_лактации', 'результат_отела',\n",
       "       'легкость_отела', 'дата_рождения',\n",
       "       'дней_в_сухостое_предыдущей_лактации', 'дней_стельности_при_событии',\n",
       "       'номер_группы_животного', 'предыдущий_номер_группы_животного',\n",
       "       'событие', 'дни_доения_при_событии', 'дата_события',\n",
       "       'примечание_события', 'живых_потомков', 'вылечена', 'возраст', 'месяц',\n",
       "       'год', 'год_месяц'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "id": "797bd7ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "select_df = ['номер_животного', 'номер_лактации', 'дней_в_сухостое_предыдущей_лактации'\n",
    "                  ,  'дней_стельности_при_событии', 'событие' \n",
    "                  , 'дата_события','примечание_события', 'группа_изменена']\n",
    "merge_on = ['номер_животного', 'номер_лактации', 'дней_в_сухостое_предыдущей_лактации'\n",
    "        ,'дней_стельности_при_событии', 'событие', 'дата_события','примечание_события']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "id": "be245e2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>год_месяц</th>\n",
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       "      <td>2019-03-15</td>\n",
       "      <td>МВ</td>\n",
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       "      <td>МАСТИТ</td>\n",
       "      <td>215</td>\n",
       "      <td>2019-03-17</td>\n",
       "      <td>ТМ6_34</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
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       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>216</td>\n",
       "      <td>2019-03-18</td>\n",
       "      <td>F006T003</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.514031</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>221</td>\n",
       "      <td>2019-03-23</td>\n",
       "      <td>КМ4_134</td>\n",
       "      <td>1</td>\n",
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       "      <td>FA</td>\n",
       "      <td>3</td>\n",
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       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ЗДОРОВА</td>\n",
       "      <td>230</td>\n",
       "      <td>2019-04-01</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.552361</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "0              321    1               6              FA               3   \n",
       "1              321    1               6              FA               3   \n",
       "2              321    1               6              FA               3   \n",
       "3              321    1               6              FA               3   \n",
       "4              321    1               6              FA               3   \n",
       "\n",
       "  дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "0    2009-09-11                                   62   \n",
       "1    2009-09-11                                   62   \n",
       "2    2009-09-11                                   62   \n",
       "3    2009-09-11                                   62   \n",
       "4    2009-09-11                                   62   \n",
       "\n",
       "   дней_стельности_при_событии  номер_группы_животного  \\\n",
       "0                          291                      18   \n",
       "1                          291                      18   \n",
       "2                          291                      18   \n",
       "3                          291                      18   \n",
       "4                          291                      18   \n",
       "\n",
       "   предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "0                                 18   МАСТИТ                     213   \n",
       "1                                 18   МАСТИТ                     215   \n",
       "2                                 18  ПЕРЕВОД                     216   \n",
       "3                                 18   МАСТИТ                     221   \n",
       "4                                 18  ЗДОРОВА                     230   \n",
       "\n",
       "  дата_события примечание_события  живых_потомков  вылечена   возраст  месяц  \\\n",
       "0   2019-03-15                 МВ               1         0  9.505818      3   \n",
       "1   2019-03-17             ТМ6_34               1         0  9.511294      3   \n",
       "2   2019-03-18           F006T003               1         0  9.514031      3   \n",
       "3   2019-03-23            КМ4_134               1         0  9.527721      3   \n",
       "4   2019-04-01             МАСТИТ               1         0  9.552361      4   \n",
       "\n",
       "    год год_месяц  группа_изменена  \n",
       "0  2019   2019-03              NaN  \n",
       "1  2019   2019-03              NaN  \n",
       "2  2019   2019-03              1.0  \n",
       "3  2019   2019-03              NaN  \n",
       "4  2019   2019-04              NaN  "
      ]
     },
     "execution_count": 202,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_updated = pd.merge(\n",
    "    df, df_moves[select_df],\n",
    "    on=merge_on\n",
    "    , how='left'\n",
    ")\n",
    "\n",
    "df_updated.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "id": "e3d5db92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape[0] - df_moves.shape[0] - df_updated.группа_изменена.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e811a61",
   "metadata": {},
   "source": [
    "Смерджили правильно :)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "id": "51c6cefa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_updated.группа_изменена = df_updated.группа_изменена.fillna(0)\n",
    "\n",
    "df_updated.isna().sum().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "id": "721ede74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>пол</th>\n",
       "      <th>номер_лактации</th>\n",
       "      <th>результат_отела</th>\n",
       "      <th>легкость_отела</th>\n",
       "      <th>дата_рождения</th>\n",
       "      <th>дней_в_сухостое_предыдущей_лактации</th>\n",
       "      <th>дней_стельности_при_событии</th>\n",
       "      <th>номер_группы_животного</th>\n",
       "      <th>предыдущий_номер_группы_животного</th>\n",
       "      <th>событие</th>\n",
       "      <th>дни_доения_при_событии</th>\n",
       "      <th>дата_события</th>\n",
       "      <th>примечание_события</th>\n",
       "      <th>живых_потомков</th>\n",
       "      <th>вылечена</th>\n",
       "      <th>возраст</th>\n",
       "      <th>месяц</th>\n",
       "      <th>год</th>\n",
       "      <th>год_месяц</th>\n",
       "      <th>группа_изменена</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>213</td>\n",
       "      <td>2019-03-15</td>\n",
       "      <td>МВ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.505818</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>215</td>\n",
       "      <td>2019-03-17</td>\n",
       "      <td>ТМ6_34</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.511294</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>216</td>\n",
       "      <td>2019-03-18</td>\n",
       "      <td>F006T003</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.514031</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>221</td>\n",
       "      <td>2019-03-23</td>\n",
       "      <td>КМ4_134</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.527721</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2009-09-11</td>\n",
       "      <td>62</td>\n",
       "      <td>291</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>ЗДОРОВА</td>\n",
       "      <td>230</td>\n",
       "      <td>2019-04-01</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.552361</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "      <td>0.0</td>\n",
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       "      <th>225664</th>\n",
       "      <td>912242</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>2019-12-29</td>\n",
       "      <td>0</td>\n",
       "      <td>259</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>306</td>\n",
       "      <td>2022-08-31</td>\n",
       "      <td>СКОУ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.672142</td>\n",
       "      <td>8</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-08</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225665</th>\n",
       "      <td>912242</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-29</td>\n",
       "      <td>0</td>\n",
       "      <td>259</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>СУХ2</td>\n",
       "      <td>306</td>\n",
       "      <td>2022-08-31</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.672142</td>\n",
       "      <td>8</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-08</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225666</th>\n",
       "      <td>912253</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>2019-12-30</td>\n",
       "      <td>0</td>\n",
       "      <td>266</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>СУХОСТ</td>\n",
       "      <td>280</td>\n",
       "      <td>2022-07-30</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.581793</td>\n",
       "      <td>7</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-07</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225667</th>\n",
       "      <td>912253</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-30</td>\n",
       "      <td>0</td>\n",
       "      <td>266</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>280</td>\n",
       "      <td>2022-07-30</td>\n",
       "      <td>F017T045</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.581793</td>\n",
       "      <td>7</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-07</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225668</th>\n",
       "      <td>912253</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-30</td>\n",
       "      <td>0</td>\n",
       "      <td>266</td>\n",
       "      <td>45</td>\n",
       "      <td>17</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>325</td>\n",
       "      <td>2022-09-13</td>\n",
       "      <td>СКОУ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.704997</td>\n",
       "      <td>9</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-09</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>225669 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "0                   321    1               6              FA               3   \n",
       "1                   321    1               6              FA               3   \n",
       "2                   321    1               6              FA               3   \n",
       "3                   321    1               6              FA               3   \n",
       "4                   321    1               6              FA               3   \n",
       "...                 ...  ...             ...             ...             ...   \n",
       "225664           912242    1               1              FA               1   \n",
       "225665           912242    1               1              FA               1   \n",
       "225666           912253    1               1              FA               1   \n",
       "225667           912253    1               1              FA               1   \n",
       "225668           912253    1               1              FA               1   \n",
       "\n",
       "       дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "0         2009-09-11                                   62   \n",
       "1         2009-09-11                                   62   \n",
       "2         2009-09-11                                   62   \n",
       "3         2009-09-11                                   62   \n",
       "4         2009-09-11                                   62   \n",
       "...              ...                                  ...   \n",
       "225664    2019-12-29                                    0   \n",
       "225665    2019-12-29                                    0   \n",
       "225666    2019-12-30                                    0   \n",
       "225667    2019-12-30                                    0   \n",
       "225668    2019-12-30                                    0   \n",
       "\n",
       "        дней_стельности_при_событии  номер_группы_животного  \\\n",
       "0                               291                      18   \n",
       "1                               291                      18   \n",
       "2                               291                      18   \n",
       "3                               291                      18   \n",
       "4                               291                      18   \n",
       "...                             ...                     ...   \n",
       "225664                          259                      17   \n",
       "225665                          259                      17   \n",
       "225666                          266                       3   \n",
       "225667                          266                      17   \n",
       "225668                          266                      45   \n",
       "\n",
       "        предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "0                                      18   МАСТИТ                     213   \n",
       "1                                      18   МАСТИТ                     215   \n",
       "2                                      18  ПЕРЕВОД                     216   \n",
       "3                                      18   МАСТИТ                     221   \n",
       "4                                      18  ЗДОРОВА                     230   \n",
       "...                                   ...      ...                     ...   \n",
       "225664                                 17   ВАКЦИН                     306   \n",
       "225665                                 17     СУХ2                     306   \n",
       "225666                                 17   СУХОСТ                     280   \n",
       "225667                                 17  ПЕРЕВОД                     280   \n",
       "225668                                 17   ВАКЦИН                     325   \n",
       "\n",
       "       дата_события примечание_события  живых_потомков  вылечена   возраст  \\\n",
       "0        2019-03-15                 МВ               1         0  9.505818   \n",
       "1        2019-03-17             ТМ6_34               1         0  9.511294   \n",
       "2        2019-03-18           F006T003               1         0  9.514031   \n",
       "3        2019-03-23            КМ4_134               1         0  9.527721   \n",
       "4        2019-04-01             МАСТИТ               1         0  9.552361   \n",
       "...             ...                ...             ...       ...       ...   \n",
       "225664   2022-08-31               СКОУ               1         0  2.672142   \n",
       "225665   2022-08-31                  -               1         0  2.672142   \n",
       "225666   2022-07-30                  -               1         0  2.581793   \n",
       "225667   2022-07-30           F017T045               1         0  2.581793   \n",
       "225668   2022-09-13               СКОУ               1         0  2.704997   \n",
       "\n",
       "        месяц   год год_месяц  группа_изменена  \n",
       "0           3  2019   2019-03              0.0  \n",
       "1           3  2019   2019-03              0.0  \n",
       "2           3  2019   2019-03              1.0  \n",
       "3           3  2019   2019-03              0.0  \n",
       "4           4  2019   2019-04              0.0  \n",
       "...       ...   ...       ...              ...  \n",
       "225664      8  2022   2022-08              0.0  \n",
       "225665      8  2022   2022-08              0.0  \n",
       "225666      7  2022   2022-07              0.0  \n",
       "225667      7  2022   2022-07              1.0  \n",
       "225668      9  2022   2022-09              0.0  \n",
       "\n",
       "[225669 rows x 21 columns]"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_updated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "id": "c3362a32",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tmp = df_updated.copy().sort_values('дата_события')\n",
    "\n",
    "df_moves = df_moves.sort_values('дата_события')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "id": "5b7658ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>пол</th>\n",
       "      <th>номер_лактации</th>\n",
       "      <th>результат_отела</th>\n",
       "      <th>легкость_отела</th>\n",
       "      <th>дата_рождения</th>\n",
       "      <th>дней_в_сухостое_предыдущей_лактации</th>\n",
       "      <th>дней_стельности_при_событии</th>\n",
       "      <th>номер_группы_животного</th>\n",
       "      <th>предыдущий_номер_группы_животного</th>\n",
       "      <th>событие</th>\n",
       "      <th>дни_доения_при_событии</th>\n",
       "      <th>дата_события</th>\n",
       "      <th>примечание_события</th>\n",
       "      <th>живых_потомков</th>\n",
       "      <th>вылечена</th>\n",
       "      <th>возраст</th>\n",
       "      <th>месяц</th>\n",
       "      <th>год</th>\n",
       "      <th>год_месяц</th>\n",
       "      <th>группа_изменена</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9718</th>\n",
       "      <td>611004</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-11-01</td>\n",
       "      <td>0</td>\n",
       "      <td>274</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>173</td>\n",
       "      <td>2019-03-05</td>\n",
       "      <td>F009T005</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.338125</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "9718           611004    1               1              MA               1   \n",
       "\n",
       "     дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "9718    2016-11-01                                    0   \n",
       "\n",
       "      дней_стельности_при_событии  номер_группы_животного  \\\n",
       "9718                          274                       5   \n",
       "\n",
       "      предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "9718                                  9  ПЕРЕВОД                     173   \n",
       "\n",
       "     дата_события примечание_события  живых_потомков  вылечена   возраст  \\\n",
       "9718   2019-03-05           F009T005               1         0  2.338125   \n",
       "\n",
       "      месяц   год год_месяц  группа_изменена  \n",
       "9718      3  2019   2019-03                1  "
      ]
     },
     "execution_count": 237,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_moves.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "id": "784a7e8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "group_history = dict()\n",
    "undetected_cows = []\n",
    "\n",
    "for cow in df_tmp.номер_животного.unique():\n",
    "    if cow not in group_history.keys(): \n",
    "        if df_moves[df_moves.номер_животного == cow].size == 0:\n",
    "            undetected_cows.append(cow)\n",
    "        else:\n",
    "            group_history[cow] = [df_moves[df_moves.номер_животного == cow] \\\n",
    "                                      .iloc[0]['предыдущий_номер_группы_животного']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "id": "38f12024",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[44]"
      ]
     },
     "execution_count": 239,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "group_history[605084]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "id": "b55190e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>пол</th>\n",
       "      <th>номер_лактации</th>\n",
       "      <th>результат_отела</th>\n",
       "      <th>легкость_отела</th>\n",
       "      <th>дата_рождения</th>\n",
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       "      <th>событие</th>\n",
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       "      <th>возраст</th>\n",
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       "      <th>год_месяц</th>\n",
       "      <th>группа_изменена</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8041</th>\n",
       "      <td>605084</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-05-17</td>\n",
       "      <td>54</td>\n",
       "      <td>265</td>\n",
       "      <td>21</td>\n",
       "      <td>44</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-03-06</td>\n",
       "      <td>F044T021</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.800821</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8042</th>\n",
       "      <td>605084</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-05-17</td>\n",
       "      <td>54</td>\n",
       "      <td>265</td>\n",
       "      <td>2</td>\n",
       "      <td>21</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>10</td>\n",
       "      <td>2019-03-15</td>\n",
       "      <td>F021T002</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.825462</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68951</th>\n",
       "      <td>605084</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-05-17</td>\n",
       "      <td>54</td>\n",
       "      <td>265</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>198</td>\n",
       "      <td>2019-09-19</td>\n",
       "      <td>F010T012</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.340178</td>\n",
       "      <td>9</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-09</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154109</th>\n",
       "      <td>605084</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-05-17</td>\n",
       "      <td>54</td>\n",
       "      <td>265</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>351</td>\n",
       "      <td>2020-02-19</td>\n",
       "      <td>F007T006</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.759069</td>\n",
       "      <td>2</td>\n",
       "      <td>2020</td>\n",
       "      <td>2020-02</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169156</th>\n",
       "      <td>605084</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-05-17</td>\n",
       "      <td>54</td>\n",
       "      <td>271</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>384</td>\n",
       "      <td>2020-03-23</td>\n",
       "      <td>F017T018</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.849418</td>\n",
       "      <td>3</td>\n",
       "      <td>2020</td>\n",
       "      <td>2020-03</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180707</th>\n",
       "      <td>605084</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-05-17</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>44</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>1</td>\n",
       "      <td>2020-04-16</td>\n",
       "      <td>F044T021</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.915127</td>\n",
       "      <td>4</td>\n",
       "      <td>2020</td>\n",
       "      <td>2020-04</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185185</th>\n",
       "      <td>605084</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-05-17</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>21</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>8</td>\n",
       "      <td>2020-04-23</td>\n",
       "      <td>F021T002</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.934292</td>\n",
       "      <td>4</td>\n",
       "      <td>2020</td>\n",
       "      <td>2020-04</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193035</th>\n",
       "      <td>605084</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-05-17</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>44</td>\n",
       "      <td>2</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>21</td>\n",
       "      <td>2020-05-06</td>\n",
       "      <td>F002T044</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.969884</td>\n",
       "      <td>5</td>\n",
       "      <td>2020</td>\n",
       "      <td>2020-05</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "8041             605084    1               2              FA               1   \n",
       "8042             605084    1               2              FA               1   \n",
       "68951            605084    1               2              FA               1   \n",
       "154109           605084    1               2              FA               1   \n",
       "169156           605084    1               2              FA               1   \n",
       "180707           605084    1               3              MA               1   \n",
       "185185           605084    1               3              MA               1   \n",
       "193035           605084    1               3              MA               1   \n",
       "\n",
       "       дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "8041      2016-05-17                                   54   \n",
       "8042      2016-05-17                                   54   \n",
       "68951     2016-05-17                                   54   \n",
       "154109    2016-05-17                                   54   \n",
       "169156    2016-05-17                                   54   \n",
       "180707    2016-05-17                                   55   \n",
       "185185    2016-05-17                                   55   \n",
       "193035    2016-05-17                                   55   \n",
       "\n",
       "        дней_стельности_при_событии  номер_группы_животного  \\\n",
       "8041                            265                      21   \n",
       "8042                            265                       2   \n",
       "68951                           265                      12   \n",
       "154109                          265                       6   \n",
       "169156                          271                      18   \n",
       "180707                            0                      21   \n",
       "185185                            0                       2   \n",
       "193035                            0                      44   \n",
       "\n",
       "        предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "8041                                   44  ПЕРЕВОД                       1   \n",
       "8042                                   21  ПЕРЕВОД                      10   \n",
       "68951                                  10  ПЕРЕВОД                     198   \n",
       "154109                                  7  ПЕРЕВОД                     351   \n",
       "169156                                 17  ПЕРЕВОД                     384   \n",
       "180707                                 44  ПЕРЕВОД                       1   \n",
       "185185                                 21  ПЕРЕВОД                       8   \n",
       "193035                                  2  ПЕРЕВОД                      21   \n",
       "\n",
       "       дата_события примечание_события  живых_потомков  вылечена   возраст  \\\n",
       "8041     2019-03-06           F044T021               1         0  2.800821   \n",
       "8042     2019-03-15           F021T002               1         0  2.825462   \n",
       "68951    2019-09-19           F010T012               1         0  3.340178   \n",
       "154109   2020-02-19           F007T006               1         0  3.759069   \n",
       "169156   2020-03-23           F017T018               1         0  3.849418   \n",
       "180707   2020-04-16           F044T021               1         0  3.915127   \n",
       "185185   2020-04-23           F021T002               1         0  3.934292   \n",
       "193035   2020-05-06           F002T044               1         0  3.969884   \n",
       "\n",
       "        месяц   год год_месяц  группа_изменена  \n",
       "8041        3  2019   2019-03                1  \n",
       "8042        3  2019   2019-03                1  \n",
       "68951       9  2019   2019-09                1  \n",
       "154109      2  2020   2020-02                1  \n",
       "169156      3  2020   2020-03                1  \n",
       "180707      4  2020   2020-04                1  \n",
       "185185      4  2020   2020-04                1  \n",
       "193035      5  2020   2020-05                1  "
      ]
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_moves[df_moves.номер_животного == 605084]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "id": "96117059",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 241,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.номер_животного.nunique() == len(group_history) + len(undetected_cows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "id": "923d4871",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tmp = df_tmp.reset_index().drop('index', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "id": "d605e40d",
   "metadata": {},
   "outputs": [],
   "source": [
    "counter = 0\n",
    "\n",
    "for i in range(df_tmp.shape[0]):\n",
    "    row = df_tmp.iloc[i]\n",
    "    \n",
    "#     print(row['группа_изменена'])\n",
    "    \n",
    "    if row['группа_изменена'] == 1:\n",
    "                \n",
    "        trans_log = row['примечание_события']\n",
    "        \n",
    "#         print(from_transitions_parser(trans_log), to_transition_parser(trans_log))\n",
    "\n",
    "        df_tmp.at[i, 'предыдущий_номер_группы_животного'] = from_transitions_parser(trans_log)\n",
    "        df_tmp.at[i, 'номер_группы_животного'] = to_transition_parser(trans_log)\n",
    "        \n",
    "        group_history[row['номер_животного']].append(row['номер_группы_животного'])\n",
    "        \n",
    "    elif row['номер_животного'] not in undetected_cows:\n",
    "        df_tmp.at[i, 'предыдущий_номер_группы_животного'] = group_history[row['номер_животного']][-1]\n",
    "        df_tmp.at[i, 'номер_группы_животного'] = group_history[row['номер_животного']][-1]\n",
    "        \n",
    "    else:\n",
    "        df_tmp.at[i, 'предыдущий_номер_группы_животного'] = -1\n",
    "        df_tmp.at[i, 'номер_группы_животного'] = -1\n",
    "    \n",
    "#     counter += 1    \n",
    "#     if counter == 3: break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "id": "3c4ca378",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2018-02-09</td>\n",
       "      <td>0</td>\n",
       "      <td>266</td>\n",
       "      <td>22</td>\n",
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       "      <td>55</td>\n",
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      "text/plain": [
       "   номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "0           312037    1               3              MA               1   \n",
       "1           605084    1               2              FA               1   \n",
       "2           802054    1               0              FA               1   \n",
       "3           802055    1               0              FA               1   \n",
       "4           501121    1               3              FD               1   \n",
       "\n",
       "  дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "0    2013-12-06                                  130   \n",
       "1    2016-05-17                                   54   \n",
       "2    2018-02-09                                    0   \n",
       "3    2018-02-09                                    0   \n",
       "4    2015-01-16                                   55   \n",
       "\n",
       "   дней_стельности_при_событии  номер_группы_животного  \\\n",
       "0                          282                       4   \n",
       "1                          265                      44   \n",
       "2                          266                      22   \n",
       "3                          275                      22   \n",
       "4                           48                      10   \n",
       "\n",
       "   предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "0                                  7  ПЕРЕВОД                     223   \n",
       "1                                 44   ПРОФОТ                       0   \n",
       "2                                 25  ПЕРЕВОД                     389   \n",
       "3                                 25  ПЕРЕВОД                     389   \n",
       "4                                 10  РАСЧКОП                      20   \n",
       "\n",
       "  дата_события примечание_события  живых_потомков  вылечена   возраст  месяц  \\\n",
       "0   2019-03-05           F007T004               1         0  5.242984      3   \n",
       "1   2019-03-05              ПРОФ2               1         0  2.798084      3   \n",
       "2   2019-03-05           F025T022               1         0  1.065024      3   \n",
       "3   2019-03-05           F025T022               1         0  1.065024      3   \n",
       "4   2019-03-05                РДК               0         0  4.131417      3   \n",
       "\n",
       "    год год_месяц  группа_изменена  \n",
       "0  2019   2019-03              1.0  \n",
       "1  2019   2019-03              0.0  \n",
       "2  2019   2019-03              1.0  \n",
       "3  2019   2019-03              1.0  \n",
       "4  2019   2019-03              0.0  "
      ]
     },
     "execution_count": 245,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "id": "9285b344",
   "metadata": {},
   "outputs": [
    {
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       "      <td>Э1</td>\n",
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       "      <th>12</th>\n",
       "      <td>801023</td>\n",
       "      <td>30</td>\n",
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       "      <td>F022T030</td>\n",
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       "      <td>605084</td>\n",
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       "      <td>44</td>\n",
       "      <td>-</td>\n",
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       "      <td>44</td>\n",
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       "      <td>F022T030</td>\n",
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       "      <th>18</th>\n",
       "      <td>802099</td>\n",
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       "      <td>25</td>\n",
       "      <td>F025T022</td>\n",
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       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>802097</td>\n",
       "      <td>22</td>\n",
       "      <td>25</td>\n",
       "      <td>F025T022</td>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "    номер_животного  номер_группы_животного  \\\n",
       "0            312037                       4   \n",
       "1            605084                      44   \n",
       "2            802054                      22   \n",
       "3            802055                      22   \n",
       "4            501121                      10   \n",
       "5            701044                       9   \n",
       "6            802061                      22   \n",
       "7            611004                       5   \n",
       "8            802070                      22   \n",
       "9            403091                      44   \n",
       "10           504012                       5   \n",
       "11           403091                      44   \n",
       "12           801023                      30   \n",
       "13           605084                      44   \n",
       "14           705140                      44   \n",
       "15           705140                      44   \n",
       "16           801017                      30   \n",
       "17           702045                       5   \n",
       "18           802099                      22   \n",
       "19           802097                      22   \n",
       "\n",
       "    предыдущий_номер_группы_животного примечание_события  \n",
       "0                                   7           F007T004  \n",
       "1                                  44              ПРОФ2  \n",
       "2                                  25           F025T022  \n",
       "3                                  25           F025T022  \n",
       "4                                  10                РДК  \n",
       "5                                   9            1H11917  \n",
       "6                                  25           F025T022  \n",
       "7                                   9           F009T005  \n",
       "8                                  25           F025T022  \n",
       "9                                  44                  -  \n",
       "10                                  4           F004T005  \n",
       "11                                 44                 Э1  \n",
       "12                                 22           F022T030  \n",
       "13                                 44                  -  \n",
       "14                                 44              ПРОФ2  \n",
       "15                                 44                  -  \n",
       "16                                 22           F022T030  \n",
       "17                                  8           F008T005  \n",
       "18                                 25           F025T022  \n",
       "19                                 25           F025T022  "
      ]
     },
     "execution_count": 249,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp[\n",
    "    ['номер_животного', 'номер_группы_животного'\n",
    "     , 'предыдущий_номер_группы_животного', 'примечание_события']\n",
    "].head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "id": "b49f8f6d",
   "metadata": {},
   "outputs": [
    {
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       "      <td>2.798084</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>802054</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-02-09</td>\n",
       "      <td>0</td>\n",
       "      <td>266</td>\n",
       "      <td>22</td>\n",
       "      <td>25</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>389</td>\n",
       "      <td>2019-03-05</td>\n",
       "      <td>F025T022</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1.065024</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>802055</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-02-09</td>\n",
       "      <td>0</td>\n",
       "      <td>275</td>\n",
       "      <td>22</td>\n",
       "      <td>25</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>389</td>\n",
       "      <td>2019-03-05</td>\n",
       "      <td>F025T022</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1.065024</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>501121</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FD</td>\n",
       "      <td>1</td>\n",
       "      <td>2015-01-16</td>\n",
       "      <td>55</td>\n",
       "      <td>48</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>РАСЧКОП</td>\n",
       "      <td>20</td>\n",
       "      <td>2019-03-05</td>\n",
       "      <td>РДК</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.131417</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225664</th>\n",
       "      <td>901205</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-01-25</td>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>ПЕРЕВОД</td>\n",
       "      <td>287</td>\n",
       "      <td>2022-09-15</td>\n",
       "      <td>F005T006</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.638604</td>\n",
       "      <td>9</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-09</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225665</th>\n",
       "      <td>903083</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-03-13</td>\n",
       "      <td>57</td>\n",
       "      <td>217</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>СУХОСТ</td>\n",
       "      <td>279</td>\n",
       "      <td>2022-09-15</td>\n",
       "      <td>CEBA</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.509925</td>\n",
       "      <td>9</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-09</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225666</th>\n",
       "      <td>810181</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-10-31</td>\n",
       "      <td>72</td>\n",
       "      <td>217</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>СУХОСТ</td>\n",
       "      <td>391</td>\n",
       "      <td>2022-09-15</td>\n",
       "      <td>CEBA</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.874059</td>\n",
       "      <td>9</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-09</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225667</th>\n",
       "      <td>910195</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-10-31</td>\n",
       "      <td>0</td>\n",
       "      <td>218</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>СУХОСТ</td>\n",
       "      <td>275</td>\n",
       "      <td>2022-09-15</td>\n",
       "      <td>CEBA</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.874743</td>\n",
       "      <td>9</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-09</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225668</th>\n",
       "      <td>805015</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-05-03</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>ОСЕМЕН</td>\n",
       "      <td>96</td>\n",
       "      <td>2022-09-15</td>\n",
       "      <td>1H15879</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.369610</td>\n",
       "      <td>9</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-09</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>225669 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "0                312037    1               3              MA               1   \n",
       "1                605084    1               2              FA               1   \n",
       "2                802054    1               0              FA               1   \n",
       "3                802055    1               0              FA               1   \n",
       "4                501121    1               3              FD               1   \n",
       "...                 ...  ...             ...             ...             ...   \n",
       "225664           901205    1               2              FA               1   \n",
       "225665           903083    1               2              FA               1   \n",
       "225666           810181    1               2              FA               1   \n",
       "225667           910195    1               1              MA               1   \n",
       "225668           805015    1               3              MA               1   \n",
       "\n",
       "       дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "0         2013-12-06                                  130   \n",
       "1         2016-05-17                                   54   \n",
       "2         2018-02-09                                    0   \n",
       "3         2018-02-09                                    0   \n",
       "4         2015-01-16                                   55   \n",
       "...              ...                                  ...   \n",
       "225664    2019-01-25                                   63   \n",
       "225665    2019-03-13                                   57   \n",
       "225666    2018-10-31                                   72   \n",
       "225667    2019-10-31                                    0   \n",
       "225668    2018-05-03                                   59   \n",
       "\n",
       "        дней_стельности_при_событии  номер_группы_животного  \\\n",
       "0                               282                       4   \n",
       "1                               265                      44   \n",
       "2                               266                      22   \n",
       "3                               275                      22   \n",
       "4                                48                      10   \n",
       "...                             ...                     ...   \n",
       "225664                            0                       6   \n",
       "225665                          217                       7   \n",
       "225666                          217                       6   \n",
       "225667                          218                       5   \n",
       "225668                            0                      23   \n",
       "\n",
       "        предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "0                                       7  ПЕРЕВОД                     223   \n",
       "1                                      44   ПРОФОТ                       0   \n",
       "2                                      25  ПЕРЕВОД                     389   \n",
       "3                                      25  ПЕРЕВОД                     389   \n",
       "4                                      10  РАСЧКОП                      20   \n",
       "...                                   ...      ...                     ...   \n",
       "225664                                  5  ПЕРЕВОД                     287   \n",
       "225665                                  7   СУХОСТ                     279   \n",
       "225666                                  6   СУХОСТ                     391   \n",
       "225667                                  5   СУХОСТ                     275   \n",
       "225668                                 23   ОСЕМЕН                      96   \n",
       "\n",
       "       дата_события примечание_события  живых_потомков  вылечена   возраст  \\\n",
       "0        2019-03-05           F007T004               1         0  5.242984   \n",
       "1        2019-03-05              ПРОФ2               1         0  2.798084   \n",
       "2        2019-03-05           F025T022               1         0  1.065024   \n",
       "3        2019-03-05           F025T022               1         0  1.065024   \n",
       "4        2019-03-05                РДК               0         0  4.131417   \n",
       "...             ...                ...             ...       ...       ...   \n",
       "225664   2022-09-15           F005T006               1         0  3.638604   \n",
       "225665   2022-09-15               CEBA               1         0  3.509925   \n",
       "225666   2022-09-15               CEBA               1         0  3.874059   \n",
       "225667   2022-09-15               CEBA               1         0  2.874743   \n",
       "225668   2022-09-15            1H15879               1         0  4.369610   \n",
       "\n",
       "        месяц   год год_месяц  группа_изменена  \n",
       "0           3  2019   2019-03              1.0  \n",
       "1           3  2019   2019-03              0.0  \n",
       "2           3  2019   2019-03              1.0  \n",
       "3           3  2019   2019-03              1.0  \n",
       "4           3  2019   2019-03              0.0  \n",
       "...       ...   ...       ...              ...  \n",
       "225664      9  2022   2022-09              1.0  \n",
       "225665      9  2022   2022-09              0.0  \n",
       "225666      9  2022   2022-09              0.0  \n",
       "225667      9  2022   2022-09              0.0  \n",
       "225668      9  2022   2022-09              0.0  \n",
       "\n",
       "[225669 rows x 21 columns]"
      ]
     },
     "execution_count": 250,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "id": "edf2387e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(225621, 20)"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "id": "df9c4514",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(225669, 20)"
      ]
     },
     "execution_count": 256,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp = df_tmp.drop('группа_изменена', axis=1)\n",
    "\n",
    "df_tmp.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "id": "e86e9bcd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>номер_животного</th>\n",
       "      <th>пол</th>\n",
       "      <th>номер_лактации</th>\n",
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       "      <th>дата_события</th>\n",
       "      <th>примечание_события</th>\n",
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       "      <th>возраст</th>\n",
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       "      <th>год</th>\n",
       "      <th>год_месяц</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>502124</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2015-02-18</td>\n",
       "      <td>146</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>23</td>\n",
       "      <td>2019-03-10</td>\n",
       "      <td>МВ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.054757</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>761</th>\n",
       "      <td>502124</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2015-02-18</td>\n",
       "      <td>146</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>24</td>\n",
       "      <td>2019-03-11</td>\n",
       "      <td>МВ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.057495</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>783</th>\n",
       "      <td>411137</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-11-25</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ЗДОРОВА</td>\n",
       "      <td>36</td>\n",
       "      <td>2019-03-11</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.290212</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>812</th>\n",
       "      <td>702674</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-12-22</td>\n",
       "      <td>180</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>225</td>\n",
       "      <td>2019-03-12</td>\n",
       "      <td>КМ5_23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8.219028</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1011</th>\n",
       "      <td>502124</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2015-02-18</td>\n",
       "      <td>146</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ЗДОРОВА</td>\n",
       "      <td>25</td>\n",
       "      <td>2019-03-12</td>\n",
       "      <td>ГИНЕКОЛ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.060233</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
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       "    <tr>\n",
       "      <th>1016</th>\n",
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       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>МАСТИТ</td>\n",
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       "      <td>2019-03-12</td>\n",
       "      <td>КМ5_12</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.060233</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1057</th>\n",
       "      <td>502124</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2015-02-18</td>\n",
       "      <td>146</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>26</td>\n",
       "      <td>2019-03-13</td>\n",
       "      <td>КМ3_12</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.062971</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1059</th>\n",
       "      <td>502124</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2015-02-18</td>\n",
       "      <td>146</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>26</td>\n",
       "      <td>2019-03-13</td>\n",
       "      <td>КМ6_12</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.062971</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1294</th>\n",
       "      <td>702674</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-12-22</td>\n",
       "      <td>180</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>АБОРТ</td>\n",
       "      <td>227</td>\n",
       "      <td>2019-03-14</td>\n",
       "      <td>69 ДНИ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8.224504</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1295</th>\n",
       "      <td>702674</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-12-22</td>\n",
       "      <td>180</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ЯЛОВАЯ</td>\n",
       "      <td>227</td>\n",
       "      <td>2019-03-14</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8.224504</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296</th>\n",
       "      <td>702674</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-12-22</td>\n",
       "      <td>180</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ПРОДАНА</td>\n",
       "      <td>227</td>\n",
       "      <td>2019-03-14</td>\n",
       "      <td>ПРОДАНА ; МясоКомбинат ; УВЗ13</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8.224504</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1442</th>\n",
       "      <td>411137</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-11-25</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ЗДОРОВА</td>\n",
       "      <td>40</td>\n",
       "      <td>2019-03-15</td>\n",
       "      <td>ХРОМОТА</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.301164</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2031</th>\n",
       "      <td>601186</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-01-31</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>БОЛЕЗНЬ</td>\n",
       "      <td>73</td>\n",
       "      <td>2019-03-19</td>\n",
       "      <td>ТОЩ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.129363</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2101</th>\n",
       "      <td>411137</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-11-25</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ЗДОРОВА</td>\n",
       "      <td>44</td>\n",
       "      <td>2019-03-19</td>\n",
       "      <td>ПРОЧИЕ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.312115</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2115</th>\n",
       "      <td>601186</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-01-31</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>74</td>\n",
       "      <td>2019-03-20</td>\n",
       "      <td>КМ6_2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.132101</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2129</th>\n",
       "      <td>601186</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-01-31</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>БОЛЕЗНЬ</td>\n",
       "      <td>74</td>\n",
       "      <td>2019-03-20</td>\n",
       "      <td>ТОЩ2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.132101</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2147</th>\n",
       "      <td>411137</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-11-25</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>45</td>\n",
       "      <td>2019-03-20</td>\n",
       "      <td>КМ1_2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.314853</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2233</th>\n",
       "      <td>601186</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-01-31</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>РАСЧКОП</td>\n",
       "      <td>75</td>\n",
       "      <td>2019-03-21</td>\n",
       "      <td>КАН</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.134839</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2234</th>\n",
       "      <td>601186</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-01-31</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ЗДОРОВА</td>\n",
       "      <td>75</td>\n",
       "      <td>2019-03-21</td>\n",
       "      <td>ХРОМОТА</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.134839</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2692</th>\n",
       "      <td>502124</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2015-02-18</td>\n",
       "      <td>146</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>36</td>\n",
       "      <td>2019-03-23</td>\n",
       "      <td>КМ5_123</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.090349</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3118</th>\n",
       "      <td>411137</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-11-25</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ПРОДАНА</td>\n",
       "      <td>51</td>\n",
       "      <td>2019-03-26</td>\n",
       "      <td>ПРОДАНА ; Прочее ; УВЗ8</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.331280</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4694</th>\n",
       "      <td>403180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ОСЕМЕН</td>\n",
       "      <td>59</td>\n",
       "      <td>2019-03-29</td>\n",
       "      <td>1H11344</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.021218</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4737</th>\n",
       "      <td>601186</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>FA</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-01-31</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ПРОДАНА</td>\n",
       "      <td>84</td>\n",
       "      <td>2019-03-30</td>\n",
       "      <td>ПРОДАНА ; Прочее ; УВЗ8</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.159480</td>\n",
       "      <td>3</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4840</th>\n",
       "      <td>502124</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2015-02-18</td>\n",
       "      <td>146</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>НЕОСЕМ</td>\n",
       "      <td>45</td>\n",
       "      <td>2019-04-01</td>\n",
       "      <td>ВЫМЯ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.114990</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5459</th>\n",
       "      <td>502124</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2015-02-18</td>\n",
       "      <td>146</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ПРОДАНА</td>\n",
       "      <td>49</td>\n",
       "      <td>2019-04-05</td>\n",
       "      <td>ПРОДАНА ; МясоКомбинат ; УВЗ13</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.125941</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7814</th>\n",
       "      <td>403180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>71</td>\n",
       "      <td>2019-04-10</td>\n",
       "      <td>КОГЛАВАК</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.054073</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7815</th>\n",
       "      <td>403180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>71</td>\n",
       "      <td>2019-04-10</td>\n",
       "      <td>ЛЕПТО</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.054073</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10231</th>\n",
       "      <td>403180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>85</td>\n",
       "      <td>2019-04-24</td>\n",
       "      <td>СУПРАВАК</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.092402</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12124</th>\n",
       "      <td>403180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ЯЛОВАЯ</td>\n",
       "      <td>90</td>\n",
       "      <td>2019-04-29</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.106092</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12784</th>\n",
       "      <td>403180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ОСЕМЕН</td>\n",
       "      <td>94</td>\n",
       "      <td>2019-05-03</td>\n",
       "      <td>1H11978</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.117043</td>\n",
       "      <td>5</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13777</th>\n",
       "      <td>403180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>102</td>\n",
       "      <td>2019-05-11</td>\n",
       "      <td>МВ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.138946</td>\n",
       "      <td>5</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13839</th>\n",
       "      <td>403180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>102</td>\n",
       "      <td>2019-05-11</td>\n",
       "      <td>MB</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.138946</td>\n",
       "      <td>5</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15119</th>\n",
       "      <td>403180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>105</td>\n",
       "      <td>2019-05-14</td>\n",
       "      <td>КРОВЬ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.147159</td>\n",
       "      <td>5</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15596</th>\n",
       "      <td>403180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ВАКЦИН</td>\n",
       "      <td>108</td>\n",
       "      <td>2019-05-17</td>\n",
       "      <td>СИБИР</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.155373</td>\n",
       "      <td>5</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15652</th>\n",
       "      <td>403180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>108</td>\n",
       "      <td>2019-05-17</td>\n",
       "      <td>МВ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.155373</td>\n",
       "      <td>5</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16767</th>\n",
       "      <td>403180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>МАСТИТ</td>\n",
       "      <td>109</td>\n",
       "      <td>2019-05-18</td>\n",
       "      <td>МВ</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.158111</td>\n",
       "      <td>5</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18160</th>\n",
       "      <td>403180</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>FA</td>\n",
       "      <td>1</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>ПРОДАНА</td>\n",
       "      <td>115</td>\n",
       "      <td>2019-05-24</td>\n",
       "      <td>ПРОДАНА ; Прочее ; УВЗ8</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.174538</td>\n",
       "      <td>5</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       номер_животного  пол  номер_лактации результат_отела  легкость_отела  \\\n",
       "512             502124    1               3              FA               1   \n",
       "761             502124    1               3              FA               1   \n",
       "783             411137    1               3              MA               1   \n",
       "812             702674    1               5              FA               1   \n",
       "1011            502124    1               3              FA               1   \n",
       "1016            502124    1               3              FA               1   \n",
       "1057            502124    1               3              FA               1   \n",
       "1059            502124    1               3              FA               1   \n",
       "1294            702674    1               5              FA               1   \n",
       "1295            702674    1               5              FA               1   \n",
       "1296            702674    1               5              FA               1   \n",
       "1442            411137    1               3              MA               1   \n",
       "2031            601186    1               2              FA               3   \n",
       "2101            411137    1               3              MA               1   \n",
       "2115            601186    1               2              FA               3   \n",
       "2129            601186    1               2              FA               3   \n",
       "2147            411137    1               3              MA               1   \n",
       "2233            601186    1               2              FA               3   \n",
       "2234            601186    1               2              FA               3   \n",
       "2692            502124    1               3              FA               1   \n",
       "3118            411137    1               3              MA               1   \n",
       "4694            403180    1               3              FA               1   \n",
       "4737            601186    1               2              FA               3   \n",
       "4840            502124    1               3              FA               1   \n",
       "5459            502124    1               3              FA               1   \n",
       "7814            403180    1               3              FA               1   \n",
       "7815            403180    1               3              FA               1   \n",
       "10231           403180    1               3              FA               1   \n",
       "12124           403180    1               3              FA               1   \n",
       "12784           403180    1               3              FA               1   \n",
       "13777           403180    1               3              FA               1   \n",
       "13839           403180    1               3              FA               1   \n",
       "15119           403180    1               3              FA               1   \n",
       "15596           403180    1               3              FA               1   \n",
       "15652           403180    1               3              FA               1   \n",
       "16767           403180    1               3              FA               1   \n",
       "18160           403180    1               3              FA               1   \n",
       "\n",
       "      дата_рождения  дней_в_сухостое_предыдущей_лактации  \\\n",
       "512      2015-02-18                                  146   \n",
       "761      2015-02-18                                  146   \n",
       "783      2014-11-25                                   59   \n",
       "812      2010-12-22                                  180   \n",
       "1011     2015-02-18                                  146   \n",
       "1016     2015-02-18                                  146   \n",
       "1057     2015-02-18                                  146   \n",
       "1059     2015-02-18                                  146   \n",
       "1294     2010-12-22                                  180   \n",
       "1295     2010-12-22                                  180   \n",
       "1296     2010-12-22                                  180   \n",
       "1442     2014-11-25                                   59   \n",
       "2031     2016-01-31                                   65   \n",
       "2101     2014-11-25                                   59   \n",
       "2115     2016-01-31                                   65   \n",
       "2129     2016-01-31                                   65   \n",
       "2147     2014-11-25                                   59   \n",
       "2233     2016-01-31                                   65   \n",
       "2234     2016-01-31                                   65   \n",
       "2692     2015-02-18                                  146   \n",
       "3118     2014-11-25                                   59   \n",
       "4694     2014-03-21                                   54   \n",
       "4737     2016-01-31                                   65   \n",
       "4840     2015-02-18                                  146   \n",
       "5459     2015-02-18                                  146   \n",
       "7814     2014-03-21                                   54   \n",
       "7815     2014-03-21                                   54   \n",
       "10231    2014-03-21                                   54   \n",
       "12124    2014-03-21                                   54   \n",
       "12784    2014-03-21                                   54   \n",
       "13777    2014-03-21                                   54   \n",
       "13839    2014-03-21                                   54   \n",
       "15119    2014-03-21                                   54   \n",
       "15596    2014-03-21                                   54   \n",
       "15652    2014-03-21                                   54   \n",
       "16767    2014-03-21                                   54   \n",
       "18160    2014-03-21                                   54   \n",
       "\n",
       "       дней_стельности_при_событии  номер_группы_животного  \\\n",
       "512                              0                      -1   \n",
       "761                              0                      -1   \n",
       "783                              0                      -1   \n",
       "812                              0                      -1   \n",
       "1011                             0                      -1   \n",
       "1016                             0                      -1   \n",
       "1057                             0                      -1   \n",
       "1059                             0                      -1   \n",
       "1294                             0                      -1   \n",
       "1295                             0                      -1   \n",
       "1296                             0                      -1   \n",
       "1442                             0                      -1   \n",
       "2031                             0                      -1   \n",
       "2101                             0                      -1   \n",
       "2115                             0                      -1   \n",
       "2129                             0                      -1   \n",
       "2147                             0                      -1   \n",
       "2233                             0                      -1   \n",
       "2234                             0                      -1   \n",
       "2692                             0                      -1   \n",
       "3118                             0                      -1   \n",
       "4694                             0                      -1   \n",
       "4737                             0                      -1   \n",
       "4840                             0                      -1   \n",
       "5459                             0                      -1   \n",
       "7814                             0                      -1   \n",
       "7815                             0                      -1   \n",
       "10231                            0                      -1   \n",
       "12124                            0                      -1   \n",
       "12784                            0                      -1   \n",
       "13777                            0                      -1   \n",
       "13839                            0                      -1   \n",
       "15119                            0                      -1   \n",
       "15596                            0                      -1   \n",
       "15652                            0                      -1   \n",
       "16767                            0                      -1   \n",
       "18160                            0                      -1   \n",
       "\n",
       "       предыдущий_номер_группы_животного  событие  дни_доения_при_событии  \\\n",
       "512                                   -1   МАСТИТ                      23   \n",
       "761                                   -1   МАСТИТ                      24   \n",
       "783                                   -1  ЗДОРОВА                      36   \n",
       "812                                   -1   МАСТИТ                     225   \n",
       "1011                                  -1  ЗДОРОВА                      25   \n",
       "1016                                  -1   МАСТИТ                      25   \n",
       "1057                                  -1   МАСТИТ                      26   \n",
       "1059                                  -1   МАСТИТ                      26   \n",
       "1294                                  -1    АБОРТ                     227   \n",
       "1295                                  -1   ЯЛОВАЯ                     227   \n",
       "1296                                  -1  ПРОДАНА                     227   \n",
       "1442                                  -1  ЗДОРОВА                      40   \n",
       "2031                                  -1  БОЛЕЗНЬ                      73   \n",
       "2101                                  -1  ЗДОРОВА                      44   \n",
       "2115                                  -1   МАСТИТ                      74   \n",
       "2129                                  -1  БОЛЕЗНЬ                      74   \n",
       "2147                                  -1   МАСТИТ                      45   \n",
       "2233                                  -1  РАСЧКОП                      75   \n",
       "2234                                  -1  ЗДОРОВА                      75   \n",
       "2692                                  -1   МАСТИТ                      36   \n",
       "3118                                  -1  ПРОДАНА                      51   \n",
       "4694                                  -1   ОСЕМЕН                      59   \n",
       "4737                                  -1  ПРОДАНА                      84   \n",
       "4840                                  -1   НЕОСЕМ                      45   \n",
       "5459                                  -1  ПРОДАНА                      49   \n",
       "7814                                  -1   ВАКЦИН                      71   \n",
       "7815                                  -1   ВАКЦИН                      71   \n",
       "10231                                 -1   ВАКЦИН                      85   \n",
       "12124                                 -1   ЯЛОВАЯ                      90   \n",
       "12784                                 -1   ОСЕМЕН                      94   \n",
       "13777                                 -1   МАСТИТ                     102   \n",
       "13839                                 -1   МАСТИТ                     102   \n",
       "15119                                 -1   ВАКЦИН                     105   \n",
       "15596                                 -1   ВАКЦИН                     108   \n",
       "15652                                 -1   МАСТИТ                     108   \n",
       "16767                                 -1   МАСТИТ                     109   \n",
       "18160                                 -1  ПРОДАНА                     115   \n",
       "\n",
       "      дата_события              примечание_события  живых_потомков  вылечена  \\\n",
       "512     2019-03-10                              МВ               1         0   \n",
       "761     2019-03-11                              МВ               1         0   \n",
       "783     2019-03-11                          МАСТИТ               1         0   \n",
       "812     2019-03-12                          КМ5_23               1         0   \n",
       "1011    2019-03-12                         ГИНЕКОЛ               1         0   \n",
       "1016    2019-03-12                          КМ5_12               1         0   \n",
       "1057    2019-03-13                          КМ3_12               1         0   \n",
       "1059    2019-03-13                          КМ6_12               1         0   \n",
       "1294    2019-03-14                          69 ДНИ               1         0   \n",
       "1295    2019-03-14                               -               1         0   \n",
       "1296    2019-03-14  ПРОДАНА ; МясоКомбинат ; УВЗ13               1         0   \n",
       "1442    2019-03-15                         ХРОМОТА               1         0   \n",
       "2031    2019-03-19                             ТОЩ               1         0   \n",
       "2101    2019-03-19                          ПРОЧИЕ               1         0   \n",
       "2115    2019-03-20                           КМ6_2               1         0   \n",
       "2129    2019-03-20                            ТОЩ2               1         0   \n",
       "2147    2019-03-20                           КМ1_2               1         0   \n",
       "2233    2019-03-21                             КАН               1         0   \n",
       "2234    2019-03-21                         ХРОМОТА               1         0   \n",
       "2692    2019-03-23                         КМ5_123               1         0   \n",
       "3118    2019-03-26         ПРОДАНА ; Прочее ; УВЗ8               1         0   \n",
       "4694    2019-03-29                         1H11344               1         0   \n",
       "4737    2019-03-30         ПРОДАНА ; Прочее ; УВЗ8               1         0   \n",
       "4840    2019-04-01                            ВЫМЯ               1         0   \n",
       "5459    2019-04-05  ПРОДАНА ; МясоКомбинат ; УВЗ13               1         0   \n",
       "7814    2019-04-10                        КОГЛАВАК               1         0   \n",
       "7815    2019-04-10                           ЛЕПТО               1         0   \n",
       "10231   2019-04-24                        СУПРАВАК               1         0   \n",
       "12124   2019-04-29                               -               1         0   \n",
       "12784   2019-05-03                         1H11978               1         0   \n",
       "13777   2019-05-11                              МВ               1         0   \n",
       "13839   2019-05-11                              MB               1         0   \n",
       "15119   2019-05-14                           КРОВЬ               1         0   \n",
       "15596   2019-05-17                           СИБИР               1         0   \n",
       "15652   2019-05-17                              МВ               1         0   \n",
       "16767   2019-05-18                              МВ               1         0   \n",
       "18160   2019-05-24         ПРОДАНА ; Прочее ; УВЗ8               1         0   \n",
       "\n",
       "        возраст  месяц   год год_месяц  \n",
       "512    4.054757      3  2019   2019-03  \n",
       "761    4.057495      3  2019   2019-03  \n",
       "783    4.290212      3  2019   2019-03  \n",
       "812    8.219028      3  2019   2019-03  \n",
       "1011   4.060233      3  2019   2019-03  \n",
       "1016   4.060233      3  2019   2019-03  \n",
       "1057   4.062971      3  2019   2019-03  \n",
       "1059   4.062971      3  2019   2019-03  \n",
       "1294   8.224504      3  2019   2019-03  \n",
       "1295   8.224504      3  2019   2019-03  \n",
       "1296   8.224504      3  2019   2019-03  \n",
       "1442   4.301164      3  2019   2019-03  \n",
       "2031   3.129363      3  2019   2019-03  \n",
       "2101   4.312115      3  2019   2019-03  \n",
       "2115   3.132101      3  2019   2019-03  \n",
       "2129   3.132101      3  2019   2019-03  \n",
       "2147   4.314853      3  2019   2019-03  \n",
       "2233   3.134839      3  2019   2019-03  \n",
       "2234   3.134839      3  2019   2019-03  \n",
       "2692   4.090349      3  2019   2019-03  \n",
       "3118   4.331280      3  2019   2019-03  \n",
       "4694   5.021218      3  2019   2019-03  \n",
       "4737   3.159480      3  2019   2019-03  \n",
       "4840   4.114990      4  2019   2019-04  \n",
       "5459   4.125941      4  2019   2019-04  \n",
       "7814   5.054073      4  2019   2019-04  \n",
       "7815   5.054073      4  2019   2019-04  \n",
       "10231  5.092402      4  2019   2019-04  \n",
       "12124  5.106092      4  2019   2019-04  \n",
       "12784  5.117043      5  2019   2019-05  \n",
       "13777  5.138946      5  2019   2019-05  \n",
       "13839  5.138946      5  2019   2019-05  \n",
       "15119  5.147159      5  2019   2019-05  \n",
       "15596  5.155373      5  2019   2019-05  \n",
       "15652  5.155373      5  2019   2019-05  \n",
       "16767  5.158111      5  2019   2019-05  \n",
       "18160  5.174538      5  2019   2019-05  "
      ]
     },
     "execution_count": 259,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp[df_tmp.номер_группы_животного == -1].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "id": "879a7c6b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['номер_животного', 'ушная_бирка_животного', 'пол', 'номер_лактации',\n",
       "       'результат_отела', 'легкость_отела', 'дата_рождения',\n",
       "       'дней_в_сухостое_предыдущей_лактации', 'дней_стельности_при_событии',\n",
       "       'номер_группы_животного', 'предыдущий_номер_группы_животного',\n",
       "       'событие', 'дни_доения_при_событии', 'дата_события',\n",
       "       'примечание_события', 'год', 'год_месяц'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 261,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "id": "adf34f87",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tmp = df_tmp.copy().drop(\n",
    "    ['живых_потомков', 'вылечена', 'возраст', 'месяц', 'год', 'год_месяц']\n",
    "    , axis=1\n",
    ")\n",
    "\n",
    "df_tmp.columns = ['Номер Животного', 'Пол', 'Номер лактации', 'Результат отела'\n",
    "                    , 'Легкость отела', 'Дата рождения', 'Дней в сухостое предыдущей лактации'\n",
    "                    , 'Дней стельности при событии', 'Номер группы животного'\n",
    "                    , 'Предыдущий номер группы животного', 'Событие', 'Дни доения при событии'\n",
    "                    , 'Дата события', 'Примечание события']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "id": "4a81a408",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 263,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tmp.isna().sum().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "id": "2c60575f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tmp.to_csv('damp_with_valid_groups.csv', index=False)"
   ]
  }
 ],
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