Assignment2_Dodie.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# About our data\n",
    "Our data is about English health, specifically information of patients, tumours and treatments. \n",
    "All the data is in tabular type (CSV files)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "pycharm": {
     "is_executing": false
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   "outputs": [],
   "source": [
    "# import packages...\n",
    "from pandas import Series, DataFrame\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Describe: sim_sact_drug_detail.csv\n",
    "Let's have a look at this table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
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   "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>MERGED_DRUG_DETAIL_ID</th>\n",
       "      <th>MERGED_CYCLE_ID</th>\n",
       "      <th>ORG_CODE_OF_DRUG_PROVIDER</th>\n",
       "      <th>ACTUAL_DOSE_PER_ADMINISTRATION</th>\n",
       "      <th>OPCS_DELIVERY_CODE</th>\n",
       "      <th>ADMINISTRATION_ROUTE</th>\n",
       "      <th>ADMINISTRATION_DATE</th>\n",
       "      <th>DRUG_GROUP</th>\n",
       "      <th>MERGED_PATIENT_ID</th>\n",
       "      <th>MERGED_TUMOUR_ID</th>\n",
       "      <th>MERGED_REGIMEN_ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10000001</td>\n",
       "      <td>10000001</td>\n",
       "      <td>EKD02</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2015-06-07</td>\n",
       "      <td>STEROID</td>\n",
       "      <td>10000235</td>\n",
       "      <td>10000001</td>\n",
       "      <td>10000001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10000002</td>\n",
       "      <td>10000002</td>\n",
       "      <td>EGU02</td>\n",
       "      <td>30.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NOT CHEMO</td>\n",
       "      <td>10000315</td>\n",
       "      <td>10000002</td>\n",
       "      <td>10000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10000003</td>\n",
       "      <td>10000003</td>\n",
       "      <td>EGU05</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RITUXIMAB</td>\n",
       "      <td>10000337</td>\n",
       "      <td>10000003</td>\n",
       "      <td>10000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10000004</td>\n",
       "      <td>10000004</td>\n",
       "      <td>EXO</td>\n",
       "      <td>8.0</td>\n",
       "      <td>X723</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2015-03-23</td>\n",
       "      <td>NOT CHEMO</td>\n",
       "      <td>10000480</td>\n",
       "      <td>10000004</td>\n",
       "      <td>10000004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10000005</td>\n",
       "      <td>10000005</td>\n",
       "      <td>ETD02</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2013-03-11</td>\n",
       "      <td>NOT CHEMO</td>\n",
       "      <td>10000533</td>\n",
       "      <td>10000005</td>\n",
       "      <td>10000005</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   MERGED_DRUG_DETAIL_ID  MERGED_CYCLE_ID ORG_CODE_OF_DRUG_PROVIDER  \\\n",
       "0               10000001         10000001                     EKD02   \n",
       "1               10000002         10000002                     EGU02   \n",
       "2               10000003         10000003                     EGU05   \n",
       "3               10000004         10000004                       EXO   \n",
       "4               10000005         10000005                     ETD02   \n",
       "\n",
       "   ACTUAL_DOSE_PER_ADMINISTRATION OPCS_DELIVERY_CODE  ADMINISTRATION_ROUTE  \\\n",
       "0                            10.0                NaN                   1.0   \n",
       "1                            30.0                NaN                   2.0   \n",
       "2                          1000.0                NaN                   1.0   \n",
       "3                             8.0               X723                   2.0   \n",
       "4                          1000.0                NaN                   2.0   \n",
       "\n",
       "  ADMINISTRATION_DATE DRUG_GROUP  MERGED_PATIENT_ID  MERGED_TUMOUR_ID  \\\n",
       "0          2015-06-07    STEROID           10000235          10000001   \n",
       "1                 NaN  NOT CHEMO           10000315          10000002   \n",
       "2                 NaN  RITUXIMAB           10000337          10000003   \n",
       "3          2015-03-23  NOT CHEMO           10000480          10000004   \n",
       "4          2013-03-11  NOT CHEMO           10000533          10000005   \n",
       "\n",
       "   MERGED_REGIMEN_ID  \n",
       "0           10000001  \n",
       "1           10000002  \n",
       "2           10000003  \n",
       "3           10000004  \n",
       "4           10000005  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read table sim_sact_drug_detail\n",
    "drug = pd.read_csv('sim_sact_drug_detail.csv', delimiter=',')\n",
    "drug.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3544584, 11)\n",
      "['MERGED_DRUG_DETAIL_ID' 'MERGED_CYCLE_ID' 'ORG_CODE_OF_DRUG_PROVIDER'\n",
      " 'ACTUAL_DOSE_PER_ADMINISTRATION' 'OPCS_DELIVERY_CODE'\n",
      " 'ADMINISTRATION_ROUTE' 'ADMINISTRATION_DATE' 'DRUG_GROUP'\n",
      " 'MERGED_PATIENT_ID' 'MERGED_TUMOUR_ID' 'MERGED_REGIMEN_ID']\n"
     ]
    }
   ],
   "source": [
    "# get the shape of the table\n",
    "print(drug.shape)\n",
    "print(drug.columns.values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    " \n",
    "This table contains 3544584 rows and 11 columns, which are about the details of drugs used in patients including dosages, categories, drug providers and information about administrations.\n",
    "The columns are:\n",
    "\n",
    "- MERGED_DRUG_DETAIL_ID: unique id of drug details. Type: int\n",
    "- MERGED_CYCLE_ID: foreign key of cycles(in sim_sact_cycle.csv). Type: int\n",
    "- ORG_CODE_OF_DRUG_PROVIDER: organization codes of drug providers. Type: string\n",
    "- ACTUAL_DOSE_PER_ADMINISTRATION: actual dosages per administration. Type: float\n",
    "- OPCS_DELIVERY_CODE: OPCS delivery codes. Type: string\n",
    "- ADMINISTRATION_ROUTE: routes of administration. Type: float\n",
    "- ADMINISTRATION_DATE: dates of administration. Type: string\n",
    "- DRUG_GROUP: group names of drug. Type: string\n",
    "- MERGED_PATIENT_ID: foreign key of patients(sim_sact_patient.csv). Type: int\n",
    "- MERGED_TUMOUR_ID: foreign key of tumours(sim_sact_tumour.csv). Type: int\n",
    "- MERGED_REGIMEN_ID: foreign key of regimens(sim_sact_regimen.csv). Type: int\n",
    "\n",
    "Reference information:\n",
    "\n",
    "* [What is administration routes](https://en.wikipedia.org/wiki/Route_of_administration)\n",
    "* [Administration Routes Code](https://www.datadictionary.nhs.uk/data_dictionary/attributes/s/sup/systemic_anti-cancer_therapy_drug_route_of_administration_de.asp?shownav=1?query=%22route+of+administration%22&rank=66.66667&shownav=1)\n",
    "* [organisation code of drug provider](https://www.datadictionary.nhs.uk/data_dictionary/attributes/o/org/organisation_code_de.asp?shownav=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# Data Cleaning: sim_sact_drug_detail.csv\n",
    "1. Because some entries are with invalid codes of administration routes, I cleaned these entries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "drug = drug.loc[(drug['ADMINISTRATION_ROUTE']>0.0) & (drug['ADMINISTRATION_ROUTE']<=14.0) | \n",
    "                (drug['ADMINISTRATION_ROUTE']==99.0)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "2. Because actual dosages per administration can not be negative, so I cleaned those entries with value below zero."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "drug = drug.loc[drug['ACTUAL_DOSE_PER_ADMINISTRATION']>=0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "3. Because actual dosages per administration should be integers, so I converted all the values into type 'int'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "drug['ACTUAL_DOSE_PER_ADMINISTRATION'] = drug['ACTUAL_DOSE_PER_ADMINISTRATION'].astype('int')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. I deleted all the entries with null values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "drug.dropna(axis=0, how='any', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%% md\n"
    }
   },
   "source": [
    "# Explore: sim_sact_drug_detail.csv\n",
    "\n",
    "## Simple statistics\n",
    "\n",
    "1. The maximum value of dosages per administration is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "1801201"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.max(drug['ACTUAL_DOSE_PER_ADMINISTRATION'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "2. The minimum value of dosages per administration is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.min(drug['ACTUAL_DOSE_PER_ADMINISTRATION'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Drug Group Information\n",
    "Because some drug groups have too small sizes, I included all the drug groups having amount below 40000 in category 'OTHERS'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "drug_groups = drug['DRUG_GROUP'].value_counts()\n",
    "\n",
    "# add all drug groups having amount below 40000 to OTHERS\n",
    "drug_groups_others_num = np.sum(drug_groups.loc[drug_groups<40000])\n",
    "drug_groups_others = pd.Series([int(drug_groups_others_num)], index=['OTHERS'])\n",
    "drug_groups = drug_groups.loc[drug_groups>=40000]\n",
    "drug_groups = drug_groups.append(drug_groups_others)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "The bar chart below shows amount of different drug groups.\n",
    "\n",
    "**What I've found:** \n",
    "From this bar chart, we can clearly see the most frequently used drug group is NOT CHEMO and this drug group is at a much higher frequency used than other drug groups."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
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   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot\n",
    "fig1, ax1 = plt.subplots(figsize=(10,5))\n",
    "sns.set_style(\"whitegrid\")\n",
    "ax1.set_ylabel(\"drug groups\")\n",
    "ax1.set_xlabel(\"amount\")\n",
    "ax1.set_title(\"amount of drug groups\")\n",
    "ax1 = sns.barplot(x=drug_groups.values, y=drug_groups.index.values, palette=\"Set2\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Administration Route Information\n",
    "The pie chart below shows proportion of different administration routes. To make the small proportions more visible, a right subplot is ploted showing administration routes excluding Intravenous, Oral and Subcutaneous.\n",
    "\n",
    "**What I've found:** \n",
    "Intravenous constitutes the largest proportion of administration routes. And Oral and Subcutaneous are respectively the secondly and thirdly largest parts. Other administration routes are much smaller compositions of the whole, which may be easily neglected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "admin_routes_groupby = drug.groupby(['ADMINISTRATION_ROUTE'])\n",
    "admin_routes = admin_routes_groupby.count()\n",
    "\n",
    "# Pie chart\n",
    "admin_route_labels = [ 'Intravenous', \n",
    "                       'Oral',\n",
    "                       'Intrathecal', \n",
    "                       'Intramuscular', \n",
    "                       'Subcutaneous', \n",
    "                       'Intraarterial', \n",
    "                       'Intraperitoneal', \n",
    "                       'Intravesical (Intra-Vesicular)', \n",
    "                       'Cutaneous (Topical)', \n",
    "                       'Intradermal', \n",
    "                       'Intratumour', \n",
    "                       'Other' ]\n",
    "admin_route_sizes = list(admin_routes['MERGED_DRUG_DETAIL_ID'])\n",
    "\n",
    "# plot\n",
    "fig2, ax2 = plt.subplots(1, 2, figsize=(16,8))\n",
    "explode = (0,0,0,0,0,0,0,0,0,0,0,0)\n",
    "ax2[0].pie(admin_route_sizes,\n",
    "        explode=explode,\n",
    "        labels=admin_route_labels,\n",
    "        shadow = False,\n",
    "        startangle =90,\n",
    "        pctdistance = 0.6,\n",
    "        textprops={'fontsize': 16, 'color':'w'})\n",
    "ax2[0].legend(admin_route_labels, loc='best', title='administration route')\n",
    "ax2[0].axis('equal')\n",
    "ax2[0].set_title(\"proportion of administration routes\")\n",
    "\n",
    "admin_route_labels_ = [ 'Intrathecal', \n",
    "                        'Intramuscular', \n",
    "                        'Intraarterial', \n",
    "                        'Intraperitoneal', \n",
    "                        'Intravesical (Intra-Vesicular)', \n",
    "                        'Cutaneous (Topical)', \n",
    "                        'Intradermal', \n",
    "                        'Intratumour', \n",
    "                        'Other' ]\n",
    "admin_route_sizes_ = admin_route_sizes[2:4]\n",
    "admin_route_sizes_.extend(admin_route_sizes[5:])\n",
    "explode = (0,0,0,0,0,0,0,0,0)\n",
    "ax2[1].pie(admin_route_sizes_,\n",
    "        explode=explode,\n",
    "        labels=admin_route_labels_,\n",
    "        shadow = False,\n",
    "        startangle =0,\n",
    "        pctdistance = 0.6,\n",
    "        textprops={'fontsize': 16, 'color':'w'})\n",
    "ax2[1].legend(admin_route_labels_, loc='best', title='administration route')\n",
    "ax2[1].axis('equal')\n",
    "ax2[1].set_title(\"proportion of administration routes (exclude Intravenous & Oral & Subcutaneous)\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## The relation between dosages and administration routes\n",
    "The bar chart below shows the average dosages per administration of every administration route.\n",
    "\n",
    "**What I've found:** \n",
    "From the bar chart, we can see Intraaterial is related to the highest average dosage, and Intratumour is related to the lowest one. Different administration routes lead to different plans of dosages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ave_dosage_adminRoute = admin_routes_groupby.mean()['ACTUAL_DOSE_PER_ADMINISTRATION']\n",
    "\n",
    "# plot\n",
    "fig3, ax3 = plt.subplots(figsize=(10,5))\n",
    "sns.set_style(\"whitegrid\")\n",
    "ax3.set_ylabel(\"average dosage per admininstration\")\n",
    "ax3.set_xlabel(\"administration route\")\n",
    "ax3.set_title(\"average dosage of administration route\")\n",
    "ax3 = sns.barplot(x=ave_dosage_adminRoute.index, y=ave_dosage_adminRoute.values, palette=\"Set2\")\n",
    "ax3.legend(list(zip(ave_dosage_adminRoute.index,admin_route_labels)), loc='best', title='administration route')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# Describe: sim_sact_cycle.csv\n",
    "Let's have a look at this table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "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>MERGED_CYCLE_ID</th>\n",
       "      <th>MERGED_REGIMEN_ID</th>\n",
       "      <th>CYCLE_NUMBER</th>\n",
       "      <th>START_DATE_OF_CYCLE</th>\n",
       "      <th>OPCS_PROCUREMENT_CODE</th>\n",
       "      <th>PERF_STATUS_START_OF_CYCLE</th>\n",
       "      <th>MERGED_PATIENT_ID</th>\n",
       "      <th>MERGED_TUMOUR_ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10000001</td>\n",
       "      <td>10000001</td>\n",
       "      <td>4</td>\n",
       "      <td>2015-06-07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10000235</td>\n",
       "      <td>10000001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10000002</td>\n",
       "      <td>10000002</td>\n",
       "      <td>2</td>\n",
       "      <td>2016-08-07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>00</td>\n",
       "      <td>10000315</td>\n",
       "      <td>10000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10000003</td>\n",
       "      <td>10000003</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X715</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10000337</td>\n",
       "      <td>10000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10000004</td>\n",
       "      <td>10000004</td>\n",
       "      <td>2</td>\n",
       "      <td>2015-03-23</td>\n",
       "      <td>X712</td>\n",
       "      <td>0</td>\n",
       "      <td>10000480</td>\n",
       "      <td>10000004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10000005</td>\n",
       "      <td>10000005</td>\n",
       "      <td>1</td>\n",
       "      <td>2013-03-11</td>\n",
       "      <td>X711</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10000533</td>\n",
       "      <td>10000005</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   MERGED_CYCLE_ID  MERGED_REGIMEN_ID  CYCLE_NUMBER START_DATE_OF_CYCLE  \\\n",
       "0         10000001           10000001             4          2015-06-07   \n",
       "1         10000002           10000002             2          2016-08-07   \n",
       "2         10000003           10000003             3                 NaN   \n",
       "3         10000004           10000004             2          2015-03-23   \n",
       "4         10000005           10000005             1          2013-03-11   \n",
       "\n",
       "  OPCS_PROCUREMENT_CODE PERF_STATUS_START_OF_CYCLE  MERGED_PATIENT_ID  \\\n",
       "0                   NaN                        NaN           10000235   \n",
       "1                   NaN                         00           10000315   \n",
       "2                  X715                        NaN           10000337   \n",
       "3                  X712                          0           10000480   \n",
       "4                  X711                        NaN           10000533   \n",
       "\n",
       "   MERGED_TUMOUR_ID  \n",
       "0          10000001  \n",
       "1          10000002  \n",
       "2          10000003  \n",
       "3          10000004  \n",
       "4          10000005  "
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read table sim_sact_cycle\n",
    "cycle = pd.read_csv('sim_sact_cycle.csv', delimiter=',', low_memory=False)\n",
    "cycle.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1462099, 8)\n",
      "['MERGED_CYCLE_ID' 'MERGED_REGIMEN_ID' 'CYCLE_NUMBER'\n",
      " 'START_DATE_OF_CYCLE' 'OPCS_PROCUREMENT_CODE'\n",
      " 'PERF_STATUS_START_OF_CYCLE' 'MERGED_PATIENT_ID' 'MERGED_TUMOUR_ID']\n"
     ]
    }
   ],
   "source": [
    "# get the shape of the table\n",
    "print(cycle.shape)\n",
    "print(cycle.columns.values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " \n",
    "This table contains 1462099 rows and 8 columns, which are about the amount, start date, procurement and performance status  of cycles.\n",
    "The columns are:\n",
    "\n",
    "- MERGED_CYCLE_ID: unique id of cycle. Type: int\n",
    "- MERGED_REGIMEN_ID: foreign key of regimen(sim_sact_rigemen). Type: int\n",
    "- CYCLE_NUMBER: numbers of cycle. Type: int\n",
    "- START_DATE_OF_CYCLE: start date of cycles. Type: string\n",
    "- OPCS_PROCUREMENT_CODE: OPCS codes of procuring drugs. Type: string\n",
    "- PERF_STATUS_START_OF_CYCLE：Performance Status. Type: float\n",
    "- MERGED_PATIENT_ID: foreign key of patients(sim_av_patient). Type: int\n",
    "- MERGED_TUMOUR_ID: foreign key of tumours(sim_av_tumour). Type: int\n",
    "\n",
    "Reference information:\n",
    "\n",
    "* A cycle means that you have a single cancer drug or a combination of drugs and then have a rest to allow your body to recover. You might have some chemotherapy injections over a day or two and then have some time with no treatment. The treatment and rest time make up one treatment cycle.\n",
    "* [What is OPCS code](https://en.m.wikipedia.org/wiki/OPCS-4)\n",
    "* [Performance status](https://en.wikipedia.org/wiki/Performance_status)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Cleaning: sim_sact_cycle.csv\n",
    "\n",
    "1. Some codes of performance status are not digits, so I cleaned the entries with these value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "cycle['PERF_STATUS_START_OF_CYCLE'] = pd.to_numeric(cycle['PERF_STATUS_START_OF_CYCLE'], errors='coerce')\n",
    "# remove NaN\n",
    "cycle = cycle.dropna(subset=['PERF_STATUS_START_OF_CYCLE'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "2. Some codes of performance status are in different format, so I rewrote these value in ECOG PERFORMANCE STATUS format."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# 0\n",
    "cycle['PERF_STATUS_START_OF_CYCLE'].replace('00', '0', inplace=True)\n",
    "# 1\n",
    "cycle['PERF_STATUS_START_OF_CYCLE'].replace('01', '1', inplace=True)\n",
    "cycle['PERF_STATUS_START_OF_CYCLE'].replace('70.0', '1', inplace=True)\n",
    "cycle['PERF_STATUS_START_OF_CYCLE'].replace('70', '1', inplace=True)\n",
    "# 2\n",
    "cycle['PERF_STATUS_START_OF_CYCLE'].replace('02', '2', inplace=True)\n",
    "# 3\n",
    "cycle['PERF_STATUS_START_OF_CYCLE'].replace('03', '3', inplace=True)\n",
    "# 4\n",
    "cycle['PERF_STATUS_START_OF_CYCLE'].replace('04', '4', inplace=True)\n",
    "cycle['PERF_STATUS_START_OF_CYCLE'].replace('10', '4', inplace=True)\n",
    "# 5\n",
    "cycle['PERF_STATUS_START_OF_CYCLE'].replace('05', '5', inplace=True)\n",
    "\n",
    "# convert all the float type to int type\n",
    "cycle['PERF_STATUS_START_OF_CYCLE'] = cycle['PERF_STATUS_START_OF_CYCLE'].astype('int')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "3. Some codes of performance status are negative numbers, so I cleaned these entries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "cycle = cycle.loc[cycle['PERF_STATUS_START_OF_CYCLE']>=0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "4. Some codes of performance status are with no meaning values, so I cleaned these entries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "cycle['PERF_STATUS_START_OF_CYCLE'].replace('70', '1', inplace=True)\n",
    "cycle = cycle.loc[cycle['PERF_STATUS_START_OF_CYCLE']<=5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "5. I deleted all the entries with null values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "cycle.dropna(axis=0, how='any', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# Explore: sim_sact_cycle.csv\n",
    "\n",
    "## Simple statistics\n",
    "\n",
    "1. The maximum number of cycles is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "262"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.max(cycle['CYCLE_NUMBER'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "2. The minimum number of cycles is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.min(cycle['CYCLE_NUMBER'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "3. The most common procurement code is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'X702'"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opcs_procureCode_count = cycle.groupby(['OPCS_PROCUREMENT_CODE']).count()\n",
    "opcs_procureCode_count.loc[\n",
    "    opcs_procureCode_count['MERGED_CYCLE_ID']==np.max(opcs_procureCode_count['MERGED_CYCLE_ID'])].index[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Cycle Number Information\n",
    "\n",
    "The histogram below shows the distribution of cycle numbers. The right histogram focuses on cycle number from 0 to 30.\n",
    "\n",
    "**What I've found:** \n",
    "From the histogram, we can see that cycle numbers are generally in the range of 2 to 20, and especially common around 5. The trend shows the amount of cycle numbers sharply increases from 2 to 5 and steeply decreases from 5 to 8. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Nb5RQRSREuaF37rnnHu69915+//vf6+cVRiAQ4I9//KOp85SphUtERETEZBo0LyIiImIyFVwiIiIiJlPBJSIiImKyqBk0X1JS0mWyuXA8Hk+vtu9vsRRvLMUKitdsZsXr8XhCs2fHuo8//jg0YWU0i6VrL1ZiVZyRFStxQu9zWNQUXE6ns1cPizTr4ZJmiaV4YylWULxmMyvesrKyiB+zv1gslpj4ncbStRcrsSrOyIqVOKH3OUxdiiIiIiImU8ElIiIiYjIVXCIiIiImC1twBYNB5s+fz6xZsygsLKS8vPygbWpqajj//PPxeDxA24yt9913H7Nnz2b69OmsXr068pGLiISh/CUi0SJswbVq1Sq8Xi/Lly/n5ptvZsmSJV3Wr127lquuuoq9e/eGXnvppZfw+/08++yzPPHEE90mORERsyl/iUi0CFtwFRcXU1BQALQ9Ub60tLTrAaxWli5dSmpqaui1t99+m+zsbH784x9zxx13cO6550Y4bBGR8JS/RCRahC24GhsbcblcoWWbzYbf7w8tT5o0ibS0tC771NbWUl5ezh/+8Ad+9KMf8ctf/jKCIYuI9Izyl4hEi7DzcLlcLpqamkLLwWAQu/3wu6WmpnL22WdjsVg47bTT2LZtW9hAPB5Pr+a0aG1tjal5fGIp3liKFRSv2WIt3s76Kn8Fg8GY+BnF0u8yVmJVnJEVK3EeibAF14QJE1i9ejXTpk2jpKSE/Pz8sAedOHEia9as4YILLmDjxo3k5OSE3UcTn0aPWIoVFK/ZYnni077KX1arNSZ+p7F07cVKrIozsmIlTuh9DgtbcE2dOpV169Yxe/ZsDMNg0aJFLF26lNzcXKZMmdLtPjNnzuSuu+5i5syZGIbBPffc06ugREQiQflLRKJF2ILLarWyYMGCLq/l5eUdtN1bb70V+t7hcLB48eIIhCcicuSUv0QkWkTNsxR7y+pMoqK2ObTsdtpJSXT0Y0QicsyyWLvko2jltbuoqG1WvhTpBzFbcLUGLBRv+nrunLPyM5VARKRfBA0o6pSPolVlVSU52YbypUg/0KN9REREREymgktERETEZCq4REREREymgktERETEZCq4REREREymgktERETEZCq4REREREymgktERETEZCq4REREREymgktERETEZCq4REREREymgktERETEZCq4REREREymgktERETEZCq4REREREymgktERETEZCq4REREREymgktERETEZCq4REREREymgktERETEZCq4REREREymgktERETEZCq4REREREwWtuAKBoPMnz+fWbNmUVhYSHl5+UHb1NTUcP755+PxeLq8vmXLFiZOnHjQ6yIifUH5S0SiRdiCa9WqVXi9XpYvX87NN9/MkiVLuqxfu3YtV111FXv37u3yemNjI/fffz8OhyOyEYuI9JDyl4hEi7AFV3FxMQUFBQCMGzeO0tLSrgewWlm6dCmpqamh1wzD4M477+TnP/85CQkJEQ5ZRKRnlL9EJFrYw23Q2NiIy+UKLdtsNvx+P3Z7266TJk06aJ/f/e53TJ48mZNOOqnHgXg8HsrKynq8vR8nlVXVoeV96RYaqg7uLogWra2tvTq//hRLsYLiNVusxdtZX+UvMKisqjzacE3n9/morKqM+nwJsXPdKc7IipU4j0TYgsvlctHU1BRaDgaDoWR1KC+//DLZ2dmsXLmS6upqrrrqKv7yl78cdh+n08no0aN7GDZ8unkHOdk5oeWMzAyGpg3r8f59raysrFfn159iKVZQvGYzK96+SKp9lb/A0iUfRavKqkpysnOiPl9C7HxOFGdkxUqc0PscFrbgmjBhAqtXr2batGmUlJSQn58f9qBvvPFG6Ptzzz2Xp59+uldBiYhEgvKXiESLsAXX1KlTWbduHbNnz8YwDBYtWsTSpUvJzc1lypQpfRGjiMgRUf4SkWgRtuCyWq0sWLCgy2t5eXkHbffWW291u/+hXhcRMZvyl4hEC018KiIiImIyFVwiIiIiJlPBJSIiImIyFVwiIiIiJlPBJSIiImIyFVwiIiIiJlPBJSIiImIyFVwiIiIiJlPBJSIiImIyFVwiIiIiJlPBJSIiImIyFVwiIiIiJlPBJSIiImIyFVwiIiIiJlPBJSIiImIyFVwiIiIiJlPBJSIiImIyFVwiIiIiJlPBJSIiImIyFVwiIiIiJlPBJSIiImIyFVwiIiIiJlPBJSIiImIyFVwiIiIiJlPBJSIiImKysAVXMBhk/vz5zJo1i8LCQsrLyw/apqamhvPPPx+PxwNAQ0MD1157LXPnzmXWrFl88sknkY9cRCQM5S8RiRZhC65Vq1bh9XpZvnw5N998M0uWLOmyfu3atVx11VXs3bs39NrSpUv5j//4D5555hkWL17MggULIh+5iEgYyl8iEi3s4TYoLi6moKAAgHHjxlFaWtplvdVqZenSpcyYMSP02pVXXonD4QAgEAjgdDojGbOISI8of4lItAhbcDU2NuJyuULLNpsNv9+P3d6266RJkw7aJzk5GYDq6mpuueUWfvWrX4UNxOPxUFZW1uPA/TiprKoOLe9Lt9BQdXB3QbRobW3t1fn1p1iKFRSv2WIt3s76Kn+BQWVVZURiNpPf56OyqjLq8yXEznWnOCMrVuI8EmELLpfLRVNTU2g5GAyGktXhfPHFF/z85z/n1ltv5bTTTgu7vdPpZPTo0WG36/Dp5h3kZOeEljMyMxiaNqzH+/e1srKyXp1ff4qlWEHxms2sePsiqfZV/gJLl3wUrSqrKsnJzon6fAmx8zlRnJEVK3FC73NY2DFcEyZMoKioCICSkhLy8/PDHvTLL7/kxhtv5MEHH2Ty5Mm9CkhEJFKUv0QkWoT9U2/q1KmsW7eO2bNnYxgGixYtYunSpeTm5jJlypRu93nwwQfxer0sXLgQaPsr84knnohs5CIiYSh/iUi0CFtwWa3Wg+7SycvLO2i7t956K/S9kpOIRAPlLxGJFpr4VERERMRkKrhERERETKaCS0RERMRkKrhERERETKaCS0RERMRkKrhERERETKaCS0RERMRkKrhERERETKaCS0RERMRkKrhERERETKaCS0RERMRkKrhERERETKaCS0RERMRkKrhERERETKaCS0RERMRkKrhERERETKaCS0RERMRkKrhERERETKaCS0RERMRkKrhERERETKaCS0RERMRkKrhERERETKaCS0RERMRkKrhERERETKaCS0RERMRkYQuuYDDI/PnzmTVrFoWFhZSXlx+0TU1NDeeffz4ejweA1tZWfvrTnzJnzhx+9KMfUVNTE/nIRUTCUP4SkWgRtuBatWoVXq+X5cuXc/PNN7NkyZIu69euXctVV13F3r17Q6/97W9/Iz8/n7/+9a9ceumlPP7445GPXEQkDOUvEYkWYQuu4uJiCgoKABg3bhylpaVdD2C1snTpUlJTU7vd56yzzuLdd9+NZMwiIj2i/CUi0cIeboPGxkZcLldo2Waz4ff7sdvbdp00aVK3+7jdbgCSkpJoaGgIG4jH46GsrKzHgftxUllVHVrel26hoerg7oJo0dra2qvz60+xFCsoXrPFWryd9VX+AoPKqsqIxGwmv89HZVVl1OdLiJ3rTnFGVqzEeSTCFlwul4umpqbQcjAYDCWrnuzT1NREcnJy2ECcTiejR48Ou12HTzfvICc7J7SckZnB0LRhPd6/r5WVlfXq/PpTLMUKitdsZsXbF0m1r/IXWLrko2hVWVVJTnZO1OdLiJ3PieKMrFiJE3qfw8J2KU6YMIGioiIASkpKyM/PD3vQCRMmsGbNGgCKioqYOHFir4ISEYkE5S8RiRZhW7imTp3KunXrmD17NoZhsGjRIpYuXUpubi5Tpkzpdp/LL7+c2267jcsvv5y4uDgefPDBiAcuIhKO8peIRIuwBZfVamXBggVdXsvLyztou7feeiv0fUJCAo888kgEwhMROXLKXyISLTTxqYiIiIjJVHCJiIiImEwFl4iIiIjJVHCJiIiImEwFl4iIiIjJVHCJiIiImEwFl4iIiIjJVHCJiIiImEwFl4iIiIjJVHCJiIiImEwFl4iIiIjJVHCJiIiImEwFl4iIiIjJVHCJiIiImEwFl4iIiIjJVHCJiIiImEwFl4iIiIjJVHCJiIiImEwFl4iIiIjJVHCJiIiImEwFl4iIiIjJVHCJiIiImEwFl4iIiIjJVHCJiIiImGzAFFwrP65gT31rf4chIhITAkGD/ynaqrwp0kfCFlzBYJD58+cza9YsCgsLKS8v77J+xYoVTJ8+nZkzZ7J69WoAdu3axdy5c7niiiv4yU9+QktLiznRt2v0+PnNG5v5x4ZKU99HRGJLLOSv/vLe1n0s/EcZz31c0d+hiBwTwhZcq1atwuv1snz5cm6++WaWLFkSWlddXc2yZct49tlneeqpp3jooYfwer386U9/4sILL+Qvf/kLo0aN4rnnnjP1JHz+YNvXgGHq+4hIbImF/NVfXl2/C4DNuxv7ORKRY0PYgqu4uJiCggIAxo0bR2lpaWjd+vXrGT9+PA6HA7fbTW5uLhs3bmT06NHU19cD0NjYiN1uNyn8Nr5AW8HlD6rgEpGvxUL+6g/+QJB/llYB8EVVQz9HI3JsCJtJGhsbcblcoWWbzYbf78dut9PY2Ijb7Q6tS0pKorGxkezsbB588EFeffVVvF4v119/fdhAPB4PZWVlPQ7cj5PKqmoA9jT6Aais2k1ZmbfHx+hLra2tvTq//hRLsYLiNVusxdtZX+UvMKisiv4hDX6fj8qqSlY3N7K/2cewlDi+3NNA6WefY7Na+ju8LmLlulOckRUrcR6JsAWXy+WiqakptBwMBkN/8R24rqmpCbfbzfz581m8eDEFBQX8+9//5rbbbuPJJ5887Ps4nU5Gjx7d48A/3byDnOwcALz7moD9pGVkMnp0fo+P0ZfKysp6dX79KZZiBcVrNrPi7Yuk2lf5CyyhfBTNKqsqycnO4e3N1bjj7cw750TueLGUpKzhjMhM6u/wuoiVz4nijKxYiRN6n8PCdilOmDCBoqIiAEpKSsjP/7qgGTt2LMXFxXg8HhoaGtiyZQv5+fkkJyeH/nIcPHhwqHneLB1jt/zBoKnvIyKxJRbyV1/zB4IUbd7L+d/IZsyQFEDdiiJ9IWwL19SpU1m3bh2zZ8/GMAwWLVrE0qVLyc3NZcqUKRQWFjJnzhwMw+Cmm27C6XRy5513smDBAoLBIIZhMH/+fFNPQmO4RKQ7sZC/+trmPY00evxc9M0cRg5u627dvLuB75yS3c+RiQxsYQsuq9XKggULuryWl5cX+n7mzJnMnDmzy/qRI0fy5z//OUIhhhcquHSXooh0Egv5q6+tr9hPcrydb4/MJM5mZWhaApv26E5FEbMNiIlPO7oUA2rhEhE5JH/AoKyqgcn5g4iztaX/E7PcbFKXoojpBkjBFezyVUREDrZtvxevP8i5oweHXhuV5Wbr3kblTxGTDYiCy9+eKNTCJSJyaJv3eUhy2hmfmxp6LT/LhS9gUL6v6TB7isjRGhAFl6+90NJM8yIi3fP4A2yr9XLKccnYrV+n/vystjsyv6jSOC4RMw2MgivUwqUmcRGR7mysbMAfhLFDU7u8PnKwC6sFNu3WOC4RMw2Igqvj7kSfuhRFRLq1fmcdSXFWhmckdnk9Ps5Gbnoim/eo4BIx04AouEItXOpSFBE5SKsvwKbdDYzMcGC1HPwIn/wstyY/FTHZACm4NNO8iMihfF5ZTyBoMCrT2e36/Cw32/Y14/EH+jgykWPHACm4NNO8iMihbKioIzUhjmxX93Ndj8pyEQgafLVXdyqKmGVAFFx+zTQvItKtZq+fzXsaGDM0BUs33YkAJ2Z33KmobkURswyIgqtjsLy6FEVEuvp8Vz1BA8YOST3kNiMyk7BZLWzerakhRMwyMAoutXCJiHRrfUUd6UkOjkuNP+Q2TruNEZlJfKGpIURMMyAKLn9o0LwKLhGRDo0eP1uqGxk75NDdiR3ys1xsVsElYpoBUXD59GgfEZGDlO6swwDGDE0Ju+2owW7Ka5pp9elORREzDKiCSw9fFRH52oaddQxyOclOPnR3YocTs90YBny5R+O4RMwwIL0goHkAACAASURBVAquji5FtXCJiLSpb/GxbW/TYe9O7Cw/ywXoET8iZhkQBZcvqHm4REQ6K93V1p04dkj47kSA4RlJxNksbNKdiiKmGBgFl2aaFxHpYn1FHdnJ8QzuQXciQJzNSt4gl1q4REwS8wVX0DBCXYmaFkJEBPY3e9le08zYHgyW72xUllsFl4hJYr7g6lxkqUtRRKRtsDzAmB52J3bIH+yioraFJo/fjLBEjmkxX3B1vjPRr7sURURYX1HHkNQEMlzdP6z6UPLbH/GzWXcqikTcgCm4EuJsauESkWPevkYPO/e39Lp1CyA/q63gUreiSOTFfMHV0aWY6LBpDJeIHPNC3Ym9HL8FkJueiNNu1YzzIiaI+YKrY0qIRKdN83CJyDFvfUUduemJpCU6er2vzWph5GAXX2hqCJGIi/2CK9TCZQ8VXyIix6I9Da1U1bceUXdih/wst1q4REwQtuAKBoPMnz+fWbNmUVhYSHl5eZf1K1asYPr06cycOZPVq1cD0NzczK233sqcOXO47LLLWL9+vTnR8/UYriSHDcOAoFq5RKRdtOevSNtQUYeF3t+d2NmoLBeVda3Ut/oiF5iIYA+3wapVq/B6vSxfvpySkhKWLFnCE088AUB1dTXLli1j5cqVeDwe5syZw6RJk3jqqacYNWoUDzzwABs3bmTjxo2MHTvWlBPouDMx0dF2Kr5gEKfVZsp7iUhsifb8FUmGYbB+Zx3DM5JITog74uOc2D5wfvPuBiYOT49UeCLHvLAtXMXFxRQUFAAwbtw4SktLQ+vWr1/P+PHjcTgcuN1ucnNz2bhxI2+//TZxcXFcffXVPP7446H9zdDRpZjkbCuyNI5LRDpEe/6KpN31HqobPL2e7PRAX9+pqHFcIpEUtoWrsbERl8sVWrbZbPj9fux2O42Njbjd7tC6pKQkGhsbqa2tpb6+nqeeeooXX3yR+++/nwceeOCw7+PxeCgrK+tx4H6cVFZVU13TCoA12DZR32dlG3E5oq+Fq7W1tVfn159iKVZQvGaLtXg766v8BQaVVZUmnUXPvLu9CQswyN56yFj8Ph+VVZXsS7fQUFXe7TZBwyDebuG9snLGuZtMjPjwYuW6U5yRFStxHomwBZfL5aKp6esPXTAYxG63d7uuqakJt9tNamoq5557LgDnnHMOTz75ZNhAnE4no0eP7nHgn27eQU52DhUtNUAjGSlJwD7yRuaTntT7u3PMVlZW1qvz60+xFCsoXrOZFW9fJNW+yl9gISc7J6Kx94ZhGHy1fhMnDEoiL3fIIberrKokJzuHjMwMhqYNO+R2J2bXsNdn79frNFY+J4ozsmIlTuh9DgvbpThhwgSKiooAKCkpIT8/P7Ru7NixFBcX4/F4aGhoYMuWLeTn5zNx4kTWrFkDwIcffsjIkSN7FVRvhKaFaG/V0mzzItIh2vNXpOza38q+Ji9jh6ZG5Hhtz1RUl6JIJIVt4Zo6dSrr1q1j9uzZGIbBokWLWLp0Kbm5uUyZMoXCwkLmzJmDYRjcdNNNOJ1O5s2bxx133MGsWbOw2+3cf//9pp1AaAxX+6B5zTYvIh2iPX9Fyvqd+7Fa4OTjkiNyvBOz3DxXXEFtk5e0KOwxEIlFYQsuq9XKggULuryWl5cX+n7mzJnMnDmzy/rU1FR+97vfRSjEwws92ifUwqWCS0TaRHv+igTDMNiws46Rg12hu7WP1qistnFvm3Y3cPoJGRE5psixLuYnPvUHgtitFuy2tlPxa/JTETmG7KhtYX+zj7FDItOdCJ3uVNRDrEUiJuYLLl/AwG6zYLdaAHUpisixZUPFfmxWC9+IUHciQE5KPG6nXTPOi0TQACi4gsTZrNg6Ci51KYrIMSLY3p2YP9hFfFzkpsOxWCyMynLxRZUKLpFIifmCyx80iLNZO7VwqUtRRI4N5fuaqW/1MyZCdyd2lp/lZrO6FEUiJuYLLl/7GC6buhRF5BizvmI/cTYLo3Pc4TfupfwsNzVNXvY2eiJ+bJFj0YAouLq0cKlLUUSOAYGgQemuek7McuO0R/7pGqGB8+pWFImIAVBwGcTZOrdwqUtRRAa+r/Y20eQxpzsRIL/T1BAicvQGQMHV0cLVPi2EWrhE5BiwYed+HDYrJ2ZFvjsRYJDbSWpinKaGEImQmC+4/AEDe6e7FAMawyUiA1wgaFC6s56Tctw47OakcYvFQv5gt7oURSIk5guuthYuC3abBs2LyLHhyz2NtPgCEZ3stDujslxs2t2AYSivihytmC+4/EGDOGvnebg0hktEBrbPdtXhtFtDj+Axy4nZbupb/exp0J2KIkdrQBRcNpsFm0UtXCJybNhe08zxGUnE2cxN4aMGt40P0wSoIkcv5guuQDCIzdK5S1EtXCIycHl8AaobPAxNSzD9vXSnokjkDICCy8DWeeJT3aUoIgPYzv0tGMDQtETT3yvD5STT5VDBJRIBMV9wBYNgs1q+nhZCXYoiMoBV1LYA9EkLF7R1K27arakhRI5WTBdchmEQMA5o4VLBJSID2I7aZtKTHCQ57X3yfidmu9msOxVFjlpMF1wdtVVbC5fuUhSRga+itqXPWregbWqIJm+Anftb+uw9RQaimC64OiY5tVksmvhURAa8+lYfdS2+Phm/1aHjmYqb1a0oclQGRsHVqYXLp0HzIjJA7WwfvzWsD1u48tunhtDAeZGjE9sFl/F1wfV1C5e6FEVkYNpR24zVAjkpfVdwpSTGkZXs5AsVXCJHJbYLrm66FNXCJSIDVUVNC1nJ8aY9P/FQ8rPc6lIUOUoDo+CyWrC0F10awyUiA1HQMKjY39yn47c65Ge52byngaDyq8gRGxAFl7W9dctuteBTl6KIDED7Gr20+oJ9On6rQ36Wi1ZfkB21zX3+3iIDRWwXXJ3GcEFbwRVQl6KIDEAV7cVOf7RwjcrqGDivbkWRIxXbBVd7C1fHHYp2m1UTn4rIgLSjtgWHzcrgZGefv/eowXqmosjRCltwBYNB5s+fz6xZsygsLKS8vLzL+hUrVjB9+nRmzpzJ6tWru6z78MMPmTx5cmQj7iTUpWj5uoVLD68WkQ7RnL96q6K2meNSE0L5ri+54+MYkpqggkvkKIR9NsSqVavwer0sX76ckpISlixZwhNPPAFAdXU1y5YtY+XKlXg8HubMmcOkSZNwOBxUVlby9NNP4/f7TQu+86B5ALvNoodXi0hINOev3vAHglTWtXLmCRn9FsOoLJe6FEWOQtgWruLiYgoKCgAYN24cpaWloXXr169n/PjxOBwO3G43ubm5bNy4EY/Hw1133cXdd99tWuDQTcFlVZeiiHwtmvNXb1TVtxIIGgxN7/vxWx1OzHKzpbpRj08TOUJhW7gaGxtxuVyhZZvNht/vx26309jYiNvtDq1LSkqisbGRBQsWcNVVV5GVldXjQDweD2VlZT3e3o+Tvfv2AbC/dh/79roIBnzsq93fq+P0ldbW1qiMqzuxFCsoXrPFWryd9VX+AoPKqsoIRt7VZ1VtM8w7/A1UVh35nYJ+n4/Kqkr2pVtoqCoPv0MnSYEGvP4gqz/cwNAUxxHH0FOxct0pzsiKlTiPRNiCy+Vy0dTUFFoOBoPY7fZu1zU1NREXF8dHH33E9u3beeyxx6irq+Omm27iN7/5zWHfx+l0Mnr06B4H/unmHaSkpgH1DM4cREZmBgnxTpJc7l4dp6+UlZVFZVzdiaVYQfGazax4+yKp9lX+Ags52TlmnAIAb1fsIMlpJz93CJajGMNVWVVJTnYOGZkZDE0b1qt9fe79PLSumoBrMKNHm3euHWLlc6I4IytW4oTe57CwXYoTJkygqKgIgJKSEvLz80Prxo4dS3FxMR6Ph4aGBrZs2cLYsWN5/fXXWbZsGcuWLSMlJaUHyerIHNilGGe1agyXiIREc/7qjYraFoalJRxVsXW0Rg52YbFoagiRIxW2hWvq1KmsW7eO2bNnYxgGixYtYunSpeTm5jJlyhQKCwuZM2cOhmFw00034XT23S3LBxZcNqtFY7hEJCSa81dPtfoCVDd6+OawlH6NI9FhZ1haop6pKHKEwhZcVquVBQsWdHktLy8v9P3MmTOZOXPmIfdft27dUYR3eAe1cNk0LYSIfC2a81dPVdS2jd/qjwlPD9T2TEUVXCJHIrYnPjUObuHSsxRFZCD5eob5vn+kz4Hys1xsrW7C69cftiK9FdsFV2ji07Zlu82KT7csi8gAUlHbQkaSg0RH2A4J0+VnufEHDbbtawq/sYh0MSAKLrvV2v5VLVwiMrBU1DZHResWtBVcoEf8iByJAVFw2To9S9GnuxRFZICoa/FR3+qPivFbACcMSsKqOxVFjkhsF1ztY7jaG7jUwiUiA0rH+K1hUdLCFR9n4/iMJDZVqYVLpLdiu+DqaOHq9PBqjeESkYGiorYFqwVyUqOj4IK2bsVNe1RwifRWzBdcVguhyQDtNrVwicjAsaO2mZyUBOJs0ZOq87NclO9rptUX6O9QRGJK9HyKj0AwaITGb0Hb4HkVXCIyEAQNg521LVEzYL7DqCw3gaDB1mrdqSjSGzFdcPmNAwsuCz5NfCoiA8DeBg8efzBqBsx3ODG77U7FzepWFOmVmC64gkEjNH4L2ic+1V2KIjIAfD3DfHS1cB2fkYTdatHUECK9FNMFV+DALkWbFZ+6FEVkANhR24zTbmWQO7qe7+iwWxmRmcQXVZoaQqQ3BlbBpWkhRGSAqKhtYUhqAtZOrfjRIj/brS5FkV6K7YLrwDFcNk0LISKxzxcIUlXXGnXjtzrkD3azvaaZFq/uVBTpqdguuNTCJSIDUFVdKwHDiLrxWx3ys1wYBny5R92KIj0V+wWXpesYLr8GzYtIjNvRMcN8epS2cGXrmYoivRX7BdcBLVx+TQshIjGuorYFd7yd5Hh7f4fSreHpiThsVhVcIr0Q8wWX9YCJT4NG23QRIiKxqqK2maFpiaGnaEQbu81K3mCXCi6RXojtgqubQfMAfhVcIhKjWrwB9jZ6o+aB1YeSn+Vi026N4RLpqehsr+6hQNDAaW+rGf2BIE0ePwDl+5pIcNhwO+2kJDr6M0QRkV6p2N82fsvMOxT9gSAV7ePEjlRWspOd+1vYVFVPojPy/5V47a4uMSqfS6yL6YIrGDRCc9S0+IJs29f24Vy7eS/xcTbOys/UB1REYkrHDPNDUs1r4WrxBflkS83RHcPbNl72hU92mTK4v7Kqkpzsr3srlM8l1sV0l6L/gEHz7T2KmhpCRGJWRU0zmS4nCQ5bf4dyWIPbZ8DfXd/az5GIxIaYLriCB4zh6hhAHzRUcIlI7DEMgx21LVE/fgsgLclBnM2igkukh2K64DpwHq6O79XCJSKxqK7FR6PHH7UTnnZmtVgY7I5nT4Onv0MRiQmxX3B1buGydLRw9VdEIiJHrmP8VrQ+0udAg91OtXCJ9NDAKrg6uhRVcYlIDKqobcZmsZCTEt/fofRIVnI89a1+PVNRpAfCFlzBYJD58+cza9YsCgsLKS8v77J+xYoVTJ8+nZkzZ7J69WoAdu3axZVXXklhYSFz585l69atpgR/4DxcHd8GNIZLRIju/NWdHbUt5KTGY7fFxt/CWcltA+f3NKiVSyScsJ/qVatW4fV6Wb58OTfffDNLliwJrauurmbZsmU8++yzPPXUUzz00EN4vV4efvhh5s6dy7Jly5g3bx4PPfSQKcEfNIZLg+ZFpJNozl8HChoGO/e3xMT4rQ6Dk9ta4nbXaxyXSDhh5+EqLi6moKAAgHHjxlFaWhpat379esaPH4/D4cDhcJCbm8vGjRu57bbbcLvbHm4aCARwOp2mBH/IMVx6nKKIEN3560DVDR68/mDMjN8CSE2Iw2G3ahyXSA+ELbgaGxtxuVyhZZvNht/vx26309jYGEpMAElJSTQ2NpKeng7A1q1buf/++3nsscfCBuLxeCgrK+tx4D7DQdCA5uYmKqsqOSnTQd3+WgD27K3G6oljX7qFhqryMEfqG62trb06v/4US7GC4jVbrMXbWV/lLzCorKo8qlg/39NWtDgDjVRWmVPA+H2+UL482ng7pMVb2bG3nsqqyD73sSPWDtGUzzuLlc+H4ux/YQsul8tFU1NTaDkYDGK327td19TUFEpg7733Hvfccw8PPPAAJ5xwQthAnE4no0eP7nHgH21s++ClJrvJyR5MQmIimRkZQD0pqenkDHKRkZnB0LRhPT6mmcrKynp1fv0plmIFxWs2s+Lti6TaV/kLLORk5xxVrO9X7cRptzL6+KGh1vpIa5u9PYeExMSjjrfDsF0BSnbsp2y/lTNOyIzYhK0dsXaIpnzeWax8nhVn5PU2h4UdwzVhwgSKiooAKCkpIT8/P7Ru7NixFBcX4/F4aGhoYMuWLeTn5/Pee++xcOFC/vjHPzJmzJhenkLPdDygunOX4qD2mY+r1LwtIkRv/upORW0zQ9MSTCu2zHLOSYPJG+RiVdke7n99I//cUEl9i6+/wxKJOmFbuKZOncq6deuYPXs2hmGwaNEili5dSm5uLlOmTKGwsJA5c+ZgGAY33XQTTqeTRYsW4fP5uP322wEYMWIECxYsiGjgHZObdk5OKQlxJMfb2VHTDHkRfTsRiUHRmr8O5AsEqaprpWDUIFPfxwxpiQ5+eObxVNa1sGZTNW9/uZd3tu5jQm4qZ40aRIarb8bAiUS7sAWX1Wo9KNnk5X1dzcycOZOZM2d2Wf/yyy9HKLxD666FC2BYeiI72icPFJFjW7TmrwNV7m8haBATj/Q5lJyUBGZ/K5epoz2s3byX4u21fLStllOGpDA5fxDHmfgwbpFYELbgilaHKrhy0xP5bFc9jR5/f4QlItJrO2JshvnDyXA5uXT8EM4dPZh3vtzL+1/VsGFnHflZLibnD2ZEZlJ/hyjSL2K34AocuuAC2roVRURiQEVtM8nxdpIT4vo7lIhJjo/jO6fkMDl/MO99tY91X+7lf9ZuZXh6IpNPHMSJWW4sMTZeTeRoxG7BdYgWruNSE7BaYLsKLhGJERW1LQOidas7CQ4b55w4mEl5mXxUXsPbm/fy53fLyU6OZ3L+IE4ZknJQHhcZiGK/4DrgL6Q4m5WclAS1cIlITGj2+tnX5OXU4Wn9HYqpHHYrZ+ZlcvqIDD7dsZ81m6tZ/tEO3ijbTcGoTCbkphEXI480EjkSsV9wdfOX0bD0RD4urw3dySgiEq0qOsZvpQ/MFq4D2awWJgxPY1xuKmWV9azZVM1LJbt4q2wPF3/zOE4ZktLfIYqYImb/nAgcpuDKSY7HGwhS3aDne4lIdKuobcYCDDnG7uKzWiycfFwK103O4+pvjyA5IY6/fbCdtZurMfQ8XBmAYrbgOtSgeYDUxLaBp3q+l4hEu4raFjLdTuLjIjNDe6yxWCzkDXLx47NO4OTjkvlnaRUvf7qLoIouGWBituDyHWIMF0BqogPQjPMiEt0Mw2BHbUtMz78VKXE2K7NPy6VgVCbvf1XDqxvr8fgD/R2WSMTEbMF1uC7FlAS1cIlI9Nvf4qPJ4x+wdyj2ltVi4cJTcrhk3HFs3+/jf4q26jFBMmDEbMF1uEHzDruVJIeNqjqN4RKR6BUaMK8Wri5OH5HBRScls7fJyxNrtlBVpz+eJfbFfMFlPcT8LamJDnUpikhUq6hpxma1kJ0S39+hRJ3j0xz8uOAEDMPgD0Vb+OCrmv4OSeSoxHzBZT/ETMWpiXHsUcElIlFsR20Lx6XEY7fGbCo21XGpCVx39kjSEh3c8n/rWf7h9v4OSeSIxeyn/HBjuABSE+Koqm/V7cUiEpUCQYOd+5s1fiuMlIQ4fnzWCUw8Po3bVm7gv1/fSFBzLEoMitmCq2NaiMN1Kbb6guxv1oBLEYk+1Q0efAFD47d6ID7OxgMzxnD5acN4bPUWblxeQqtPdzBKbInZmeZ94Vq42ufi2rm/hbQkR5/FJSLSExW1bY8fG6YWrh6x26ws+v4YctOTuP+1jVTVtfBk4anK7xIzYraFK3CYebjg67m4du5v6bOYRER6akdtC/FxVtJdKhh6ymKxcN3ZeTx6+Xg+rahj+hPvsG1vU3+HJdIjMVtwHW5aCGgbwwWws1YFl4hEn4ratvFb1kP80SiHdvE3j+Ov15zO/mYv0594h+Ly2v4OSSSsAVtwJTpsxMdZ1cIlIlHH6w+yu75V47eOwqnHp/P8TyaRHG/n8v95j7+vr+zvkEQOK+YLrkPUW1gsFrKT49mlgktEokxlXQtBQ+O3jtaIzCSe/8kkxg5J4f/768f8Yc0W3ZkuUStmB837AwY2qwXLYZrjByfH8/bmvZy2cBXTxuRw9/dO7sMIRUS6t6N9qMMQtXAdtfQkB89cczq/+L9PWfzPjXxUXstgtxNfIIjXH8QXMPCGvu/0NWDg9QfwBYzQ6x3b+YMGIzKTODMvgzPzMjnjhAxS2m/EEjlSMVtwBYLGIQfMdzjt+DR27W/BbrXw1/e3c9mpQxmamkBKogapikj/qahtJiUhjuR4/SfeU/5AMHRnZ3du/c6JpCc5eKlkF1ZL28Ow2/5ZsLd/7VhOcNhItlmxWy0Hbeewtf0h/+WeRlZ8tIM/v1uOBcjPdjNxeBoTc1MZOzSVBIcNAK/d1W1cbqdd/9dIFzFbcPmCxiHHb3X47tjjOC41kcq6Fh5960seX72FX047SR8CEelXFbUtGr/VSy2+IJ9sOfzjfU7KTuak7yRH5P1OPi6F747NYUdNC1urG9lS3cjyD3bw1/e3Y7NYGJaeQN4gFyk2D+NGBg56WsBZ+Zn6v0a6iLmCa92Xe/nbB9tDXYo9kZOSwLC0BD7YVkNdi481m8q5dNwQkpwxd/oiEuOaPH5qmrycdnx6f4ciYditVkZkJjEiM4kpo7Pw+oNs29fUXoA18dbGPRjAqxsbOD4zkRMyXeQNdpHTi2djBoMGTV4/Da1+6lt9bV9bfKHvG1r9DHI7OXV4GiMykw47jEaiW8xVHDVNXl5dX0m229HjggvgtBHprPx4J5f9/l2avQF213v4+dR8EyMVkWNFoBePmqloH7+lFq7Y47Bbyc9yk5/lBqDFG6B48w5q/A62VDfy2mdV8BkkxNl44/PdnDYiHY8vQP1BxZSfhlYf9S0+Gj1+enr5ZCQ5mDA8jVOHpzFxeBpjhqbgtNtMPGOJpJgruKZ+Iwu3005Vg5f0XswwPGZIKqvK9nDCoCTirFaeea+cn5ydR3ycLlYROTpf1bTy6Eebyc9yMyrLxfD0pEP+QVhR24wFGJKqgivWJThs5GU4+XZ2DgD1rb621q89TWysqmfNpmosFnA57STHx+GOt5OcEMeQ1HiS490kJ7S/1mndgcsup53tNc0Ul9fy0bZaistreOPz3QA4bFbGDE0JFWATh6eR4XL2549EDiNswRUMBrn77rv54osvcDgc3HfffQwfPjy0fsWKFTz77LPY7Xauu+46zjnnHGpqavjFL35Ba2srgwcPZvHixSQkRCa5xMfZmDYmh+Uf7ejVhIEOu5VbLjiRb4/MoHRXPdf/9RP++PZW8jJdVNa18sMzj+9Vi5mItCndWYfF0jbmJdr0Vf7KSIojPs7G2s3VrNlUjdNuJW+Qi1FZLvIHu7s8fqaitoVBbidO/bE34CTHxzFuWBrjhqVxxglp+IIG8XG2I57cttUXoNUXINFho2BUJgWjMoG2np4NO+so3VnHhoo6nnr7K/5QtBVoazkdOySFMUNTGDMkhdyMtsl1DzW4v4PLYSPObqO+1Ud9i5+6Fl+oa7OjVa6+xYfdZiXT5SDD5SDT5SQjyUmmy0FakoM4W8zONNUnwhZcq1atwuv1snz5ckpKSliyZAlPPPEEANXV1SxbtoyVK1fi8XiYM2cOkyZN4vHHH+eiiy5i+vTpPPnkkyxfvpwrr7wyYkHPmDiU5R/twN7LAslqsdDiC1LX7GNIagIPr9qMr/0h2Gs3VzNj4lBeKtlFdnI8M08dRmVdCxurGjh9RDonD0nh0x37afUFmJCbRpzdyvZ9zaQkxpGTHE+T1099q5+MJAdOu5X6Vj8WS9udKgCtvmDbnZVWC8GgQcAwQhdnMGhgsbTNHWYYRmi77vrqO+aYUT++mMUwDJq8AQJBg+R4O03eIKU760hJiCPT5eTtL/fyRVU93x41iJLttdz79zIswF3fO5m5p+dG1bXZV/krLcHOjwpOoNUXYGt1I5t2N7JpTwOfV9YDkOlykp/lIj/LzY7aZkZnR2Zgt0SvVr/BJ9v3m3Z8CxbGDEllzJBUfIEgO2tbKK9ppnxfE//eVM0/SquAtu7N3PREku1+4hN20dJexLV9DYaWPb4ggTBzmCXE2QgE26bZ6E5qYhwZSQ4yXG1FWEaSkwxX+3L76xkuB6kJcXgDQZq9AVq8bbG0fe9ny7YGPq4vp8Xb9lqzty2+Zq8/tH1z+z4GkBhnI8lpI8FhJzHORoLDRmL7vwSH/evv42wkOuwHrG973d9p6hCPP4DH3z5NiD/49fed1ne8Pimzd7+zsAVXcXExBQUFAIwbN47S0tLQuvXr1zN+/HgcDgcOh4Pc3Fw2btxIcXEx8+bNA+Css87ioYceimjB9a3j03o9hqszi8XClJMG83/FFfzwjGEkJzh4+M3NrP6imgyXg4YWP8veK+/x8awWuvTB262W0MSsdquFgGHQdh1vw2m34vG3Xaxx7bcfe9uXnXYr/uDXBZfDZiXYvm+gvRDr/J5WiwWr1RL6PmgYBI22/zCDBgQNAwvt21ksWNq3s1gIbUv7dgaEtjUMA5ttGxbatu34DLZt1Xn56HT+7XX8H23p9OqB/28fGEfHa4ZhgGVbj9+j8/scqjY4MO8YB5xtT+ZWPPDYHe8ZNIJYLeWHfO/+1pF8oO1JDm3X3baDtvv1vzYBcN7owQQNuPPFUpIcNqZPGNqH0R5eX+ev+Dgb3zguhW8cl4JhGOxtnoROLwAADQJJREFU9LJpdwOb9zTwwVc1vLNlH6D5tySy4mxWjs9M4vjMJGBQ6Nor39dEeU0z2/c180WjhzhbK/FxNuLj2goNl9NOpstBfJyNUYNdoS5Md7wdV7wdt7Ptq8vZ9s9us4b+IKtt8lLb7KW2ydf2tdlLbbOv/XUfn++qp7bZR12L7wjOqLrTuVlw2tvijXdY2762/7MCTV4/exs9ocKxo4jszbjKI/XPH57Qq+3DFlyNjY24XK7Qss1mw+/3Y7fbaWxsxO12h9YlJSXR2NjY5fWkpCQaGhrCBuLxeCgrK+tx4EundyT19geX7m9i/IF/NB7mtfHJNi4/saNrwc/UwhE9fm8ROdgtp7uAhh5/jj0ej7kB0Xf5y2YxGJ/czUOUU+D8IQlAdwVW3z90eXxyctv7dpcbo0wo1g5RGvNBcXbo73hTgCFOwAmk9XAnA/C1/2vnaft34DNbUoFUO4xIaX8vrO3vdeyMIettDgtbcLlcLpqavr6YgsEgdru923VNTU243e7Q6/Hx8TQ1NZGcHP6qGzduXK8CFxEJR/lLRKJF2BFuEyZMoKioCICSkhLy87+eSmHs2LEUFxfj8XhoaGhgy5Yt5OfnM2HCBNasWQNAUVEREydONCl8EZFDU/4SkWhhMcI86bPjLp9NmzZhGAaLFi2iqKiI3NxcpkyZwooVK1i+fDmGYTBv3jwuuOAC9u7dy2233UZTUxNpaWk8+OCDJCbqIa0i0reUv0QkWoQtuERERETk6GjSDBERERGTqeASERERMVlMPdon3KzR0eTSSy8N3Vo+dOhQZs2axcKFC7HZbHz729/m+uuv7+cI4dNPP+XXv/41y5Yto7y8nNtvvx2LxcKoUaO46667sFqt/O53v+Pf//43drudX/3qV4wdOzYq4v3ss8+49tprOf744wG4/PLLmTZtWlTE6/P5+NWvfsXOnTvxer1cd911jBw5Mmp/vt3Fm52dHbU/32gSyzlp8eLF/RxRVz3JR9GgJ3mov/UmB0VbnIfKPf0tEAhwxx138NVXX2Gz2Vi8eDGGYfTuZ2rEkNdff9247bbbDMMwjE8++cS49tpr+zmi7rW2thqXXHJJl9e+973vGeXl5UYwGDSuueYao7S0tJ+ia/Pkk08aF110kXHZZZcZhmEY8+bNM9577z3DMAzjzjvvNP71r38ZpaWlRmFhoREMBo2dO3ca06dPj5p4V6xYYTz11FNdtomWeJ977jnjvvvuMwzDMGpqaozJkydH9c+3u3ij+ecbTWI5J0WTnuSjaPD/t3f3MU2dXwDHv5UXX1BTETROR0K76CLEGENMDMSZbI5F07kY6sQZMmFk+0fFV15MdaaFSUYwUceyTZdtxapo1CVGQ+bUGJmiLtEpjW6iUbHEiW4YUFeg/f1B6KwWd0ks9+mP8/kHCk/b01Puyem95Dla6pAKtNYgvWmtPSr46aef/EVFRX6/3+8/c+aM/5NPPulzTtX4yKDRi3aNVsmVK1d4/Pgxubm55OTkcO7cObxeL0lJ3WNPMjIyOH36tK4xJiUlsXXr1sDthoYGpk+fDnTvrv3LL7/w66+/kpGRgcFg4JVXXqGrq4sHDx4oEe/ly5c5ceIEH3zwASUlJbS1tSkT7zvvvMPy5csDt6OiopTOb6h4Vc6vSiK1Jl24cEHvkIJoqUcq0FKHVKC1BulNa+1RwVtvvYXdbgfA4/GQkJDQ55xGVMPV267RqhkyZAh5eXns2LGDjRs3UlxcHDT8Vuvu1eGUmZkZ2AASusfj9MzA64nv2XzrGfez8U6ZMoW1a9eyc+dOXn31Vb744gtl4o2Li2P48OG0tbWxbNkyCgoKlM5vqHhVzq9KIrUmrV69Wqk4tdQjFWipQyrQWoP0prX2qCI6OprCwkLsdjuZmZl9zmlENVwv2jVaJcnJybz77rsYDAaSk5MZMWIEf//97xBTrbtX96enrzv3xNfbTtwqmD17NqmpqYHv3W63UvE2NzeTk5PDvHnzsFgsyuf32XhVz68qIrUmGY1G7t2799931Emo40VFoY4TVWipQSrQUntUUl5eTm1tLTabLWi0j5acRlTD9aJdo1Wyb98+Nm3aBMDdu3d5/Pgxw4YN49atW/j9fk6dOkVaWprOUQabPHky9fX1QPfu2mlpaUybNo1Tp07h8/nweDz4fD7i4+N1jrRbXl4ev/32GwCnT58mJSVFmXhbWlrIzc1lzZo1ZGVlAWrnN1S8KudXJZFak9ra2khMTNQ5qt6FOl5UFOo4UYHWGqQ3rbVHBQcPHuSrr74CYOjQoRgMBlJTU/uU04ja+DTUrtFms1nvsJ7j9XopLi7G4/FgMBhYvXo1gwYNoqysjK6uLjIyMlixYoXeYdLU1MTKlSupqanhxo0b2Gw2Ojo6MJlMOBwOoqKi2Lp1KydPnsTn81FcXKzrQfp0vA0NDdjtdmJiYkhISMButzN8+HAl4nU4HBw5cgST6d9J8uvWrcPhcCiZ31DxFhQU8PnnnyuZX5VEck2aNm2a3mEF0VKPVKClDumtLzVIT32pPXp79OgRxcXFtLS00NnZSX5+PmazuU9/pxHVcAkhhBBCRKKIuqQohBBCCBGJpOESQgghhAgzabiEEEIIIcJMGi4hhBBCiDCThksIIYQQIsyk4RIvxf79+6moqOj3562vr1diiw0hhL7+H2pQUVER7e3t3Lx5k+zsbBYtWsSGDRvw+XzPrT1//jxWq5UFCxawbdu2wM+3bdtGVlYWCxcuDOxntWvXLt3HyQlpuIQQQgjdHT58mJSUFOLi4vjss88oKCjA5XLh9/v5+eefn1tfVlZGZWUlNTU11NfX43a7aWho4OzZs+zdu5fKyko2btwIgNVqpaqqiq6urv5+WeIp6s2gELp58uRJYHPEjo4ObDYb1dXVWCwWZs2aRWNjI+Xl5WzZsuW5dU9zOp0cOnQIg8HAnDlzyMnJCfq9xWJh+vTpXL16FYPBQFVVFW63m927d7N582YA0tPTqauro6ioiOjoaDweD16vlzlz5nD8+HGam5upqqoC4ObNm+Tl5fHXX3+RnZ2N1Wrl6tWrOBwOAIxGI2VlZbjdbioqKoiJiWHBggW89957/ZBVIYRWA7kGOZ3OwNzAZ4ci19XVMXv27KDXUFNTQ3R0NO3t7bS1tWE0Gjl69GjIAfPx8fGkpKRw4sQJ3nzzzZf4jom+kDNcImD37t2MHz+ePXv2sGnTJi5evIjVauXAgQNA93iQrKyskOt6XLt2jcOHD+NyuXC5XBw9epTr168HPU97eztz586lurqaMWPGBEaj9Gb8+PF8++23mEwmmpqa+Oabb3j77bc5duwYAB0dHXz55Ze4XC62b9/OgwcPsNlsbNiwAafTycyZM9m+fTsA//zzDy6XS5otIRQ0UGvQkydPaG5uDozK0jIUOTo6mgsXLmCxWEhISCA+Pv6FA+YnTZrE2bNntb0RIizkDJcIuH79OjNnzgRg4sSJTJw4Eb/fT2lpKffv36euro6VK1dit9ufW7d//34Afv/9dzweDx9++CEAra2t3Lp1K2h0A3TP9QIYN25c0ADQHk8PQOhZO3LkyMDjjBw5Eq/XC8DUqVOJjY0FwGw209TURGNjY+B0ekdHB8nJyQCBr0II9QzUGtTa2sqoUaMCt0MNmq6urqa2thaAiooKxo4dy9SpUzl27BibN2/m66+/xmg09jpgPjExkTNnzoTMu+gfcoZLBJjNZi5dugTA7du3WbVqFQaDAYvFQmlpKenp6cTExIRc18NkMvHaa6/xww8/4HQ6mT9/fsiBvj2f3noMHjyYe/fuAXDnzh1aW1t7Xfsst9tNZ2cnjx49orGxkaSkJJKTkykvL8fpdLJmzRreeOMNILiQCSHUMlBr0KhRo4IapVCDphcvXozT6cTpdDJmzBgWLVoUiDEuLo5Bgwa9cMD8w4cPB/yweb3JGS4RsHDhQkpKSli8eDFdXV2UlJQAMH/+fGbNmsWPP/7Y67o//vgDgNdff50ZM2aQnZ2N1+tlypQpjB079j+fOzU1lREjRmC1WjGbzUyYMEFz3IMHDyY/P5+HDx+ydOlSjEYjn376KYWFhYF/Ei0tLeXPP//sa0qEEP1ooNag2NhYEhISuH//PqNHj6awsBCbzUZlZSUmk4nMzMyg9QaDgdzcXPLz84mNjSUxMRGHw0FcXBxpaWm8//77+Hw+1q9fH7jPxYsXSU9P1/yaxMsnw6vFf7p79y5r167l+++/1zsUIcQANBBq0KFDh2hpaQlcCn2ZOjs7WbJkCd999x1RUVEv/fGFNnJ9RbxQbW0tH330UdApeyGE6C8DpQbNnTuXhoaGoEuLL8uePXv4+OOPpdnSmZzhEkIIIYQIMznDJYQQQggRZtJwCSGEEEKEmTRcQgghhBBhJg2XEEIIIUSYScMlhBBCCBFm0nAJIYQQQoTZ/wDqPJZiAz6RwgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig4, ax4 = plt.subplots(1,2,figsize=(10,5))\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "ax4[0] = sns.distplot(cycle['CYCLE_NUMBER'], ax=ax4[0])\n",
    "ax4[0].set_xlabel(\"cycle number\")\n",
    "ax4[0].set_title(\"distribution of cycle numbers\")\n",
    "\n",
    "ax4[1] = sns.distplot(cycle['CYCLE_NUMBER'], ax=ax4[1])\n",
    "ax4[1].set_xlabel(\"cycle number (0-30)\")\n",
    "ax4[1].set_title(\"distribution of cycle numbers (focus on 0-30)\")\n",
    "plt.xlim(0, 30)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Starting PS information\n",
    "\n",
    "The pie chart below shows the proportion of different performance status of the start. To make the small proportions more visible, a right subplot is ploted showing performance status excluding 0, 1 and 2.\n",
    "\n",
    "**What I've found:** \n",
    "From the pie chart, we can see the most common starting performance status is 0 (Fully active, able to carry on all pre-disease performance without restriction), secondly 1 (Restricted in physically strenuous activity but ambulatory and able to carry out work of a light or sedentary nature) and thirdly 2 (Ambulatory and capable of all selfcare but unable to carry out any work activities; up and about more than 50% of waking hours). Only a few patients start a cycle with performance status 3 (Capable of only limited selfcare; confined to bed or chair more than 50% of waking hours), 4(Capable of only limited selfcare; confined to bed or chair more than 50% of waking hours), 5(dead)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot\n",
    "fig5, ax5 = plt.subplots(1, 2, figsize=(16,8))\n",
    "explode = (0,0,0,0,0,0)\n",
    "ax5[0].pie(cycle['PERF_STATUS_START_OF_CYCLE'].value_counts().values,\n",
    "        explode=explode,\n",
    "        labels=cycle['PERF_STATUS_START_OF_CYCLE'].value_counts().index,\n",
    "        shadow = False,\n",
    "        startangle =90,\n",
    "        pctdistance = 0.6,\n",
    "        textprops={'fontsize': 16, 'color':'w'})\n",
    "ax5[0].legend(cycle['PERF_STATUS_START_OF_CYCLE'].value_counts().index, loc='best', title='PS code')\n",
    "ax5[0].axis('equal')\n",
    "ax5[0].set_title(\"proportion of starting performance status\")\n",
    "\n",
    "explode = (0,0,0)\n",
    "ax5[1].pie(cycle['PERF_STATUS_START_OF_CYCLE'].value_counts().values[3:],\n",
    "        explode=explode,\n",
    "        labels=cycle['PERF_STATUS_START_OF_CYCLE'].value_counts().index[3:],\n",
    "        shadow = False,\n",
    "        startangle =90,\n",
    "        pctdistance = 0.6,\n",
    "        textprops={'fontsize': 16, 'color':'w'})\n",
    "ax5[1].legend(cycle['PERF_STATUS_START_OF_CYCLE'].value_counts().index[3:], loc='best', title='PS code')\n",
    "ax5[1].axis('equal')\n",
    "ax5[1].set_title(\"proportion of starting performance status (excluding 0, 1, 2)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## The relation between cycle numbers and starting PS\n",
    "\n",
    "The violin plot below shows the relation between cycle numbers and performance status of the start.\n",
    "The line plot shows the mean of cycle numbers with regard to performance status.\n",
    "\n",
    "**What I've found:** \n",
    "Generally, the cycle numbers of each performance status of the start are around 2. And there is not obvious difference between cycle numbers of different performances status."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig6, ax6 = plt.subplots(figsize=(10,5))\n",
    "sns.set_style(\"whitegrid\")\n",
    "ax6.set_title(\"Relation between cycle numbers and starting PS\")\n",
    "ax6 = sns.violinplot(x='PERF_STATUS_START_OF_CYCLE', y='CYCLE_NUMBER', data=cycle, showmean=True, palette=\"Blues\")\n",
    "plt.ylim(-3, 20)\n",
    "\n",
    "# plot mean line plot\n",
    "sns.lineplot(x=\"PERF_STATUS_START_OF_CYCLE\", y=\"CYCLE_NUMBER\", err_style=\"band\", ci='sd', \n",
    "             estimator=\"median\", data=cycle, color=\"coral\", ax=ax6)\n",
    "ax6.set_xlabel(\"performance status of the start\")\n",
    "ax6.set_ylabel(\"cycle number\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reflect and Hypothesise\n",
    "\n",
    "## Reflect\n",
    "\n",
    "While cleaning the data, I found there are some invalid formats and abnormal values. I think this may due to different reasons, such as typos occurred during manually input, false data produced by medical detecting instruments and errors made during transferring data. It is easy to notice those invalid formats and abnormal values, but it is somewhat tricky to redress these values. Because this is the first time I got in touch with these medical terms and jargons, I looked up through NHS website and Pubmed to find the correct interpretation of these concepts and corresponding reference tables. Although holding these references, I still get confused whether I should delete some certain types of entries because they may have meanings in some circumstances. Eventually I chose the best way I supposed to clean this data, trying not to delete entries but transform them into uniform formats.\n",
    "\n",
    "What I have surprisingly found in this data set is the performance status of the start seems have weak ties with the corresponding cycle number. Before analysing it, I used to think the worse starting performance status people are in, the larger cycle number they may have. Whereas, the truth is not like that. Plus, it also amazes me that most patients starts their cycles in quite good performance status, being fully active or at least being capable to live independently.\n",
    " \n",
    "\n",
    "## Hypothesise\n",
    "\n",
    "### H1\n",
    "\n",
    "- What: After cycles, patients' performance status will get worse than the start.\n",
    "- Why: According to the pie chart showing proportion of starting performance status, most patients start with a quite good psychical condition, so I think they may be in worse performance stauts after definitely cycles which put burden on patients' bodies.\n",
    "- How: I can combine my analysed data with my group members' data. They have analysed some data related to the ending performance status.\n",
    "\n",
    "### H2\n",
    "\n",
    "- What: Normally, the best cycle number is around 5.\n",
    "- Why: According to the histogram showing distribution of cycle numbers, the most patients received 5 cycles.\n",
    "- How: I can ask the data holder or find some related studies concerning cycles in cancer.\n",
    "\n",
    "### H3\n",
    "\n",
    "- What: Intraaterial is an administration route which demands a big number of dosages.\n",
    "- Why: According to the bar chart showing average dosage of administration route, Intraaterial is with the highest value.\n",
    "- How: Firstly, I can ask the data holder if this data are reliable. Then I can turn to further studies, like searching the related medical publications.\n",
    "\n",
    "### H4\n",
    "\n",
    "- What: Intravenous is an administration route has the best therapeutic effect on curing cancers.\n",
    "- Why: According to the pie chart showing proportion of administration routes, Intravenous constitues the biggest proportion.\n",
    "- How: Because my group members have analysed some data related to the outcome of treatment, I can refer to their analysed data and find the relation between Intravenous and the outcome of treatment."
   ]
  }
 ],
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