sim_av_patient.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic Configurations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [],
   "source": [
    "# Import necessary modules for data analysis and visualisation\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configure Seaborn styles\n",
    "sns.set(style='whitegrid',palette='muted',color_codes=True)    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/IPython/core/interactiveshell.py:3058: DtypeWarning: Columns (5,6,8,9,17,18,20,22,26,32) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "# Read files\n",
    "patient = pd.read_csv('./data/sim_av_patient.csv', delimiter=',')\n",
    "sact_patient = pd.read_csv('./data/sim_sact_patient.csv', delimiter=',')\n",
    "tumour = pd.read_csv('./data/sim_av_tumour.csv', delimiter=',')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ICD 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ICD10 Code\n",
    "icd_codes = pd.read_csv('icd_codes.csv', delimiter=\",\", header=None, names=['Category Code', 'Diagnosis Code', 'Full Code', 'Abbreviated Description', 'Full Description', 'Category Title'])\n",
    "icd_codes_3char = pd.read_csv('icd_codes_3char.csv', delimiter=\",\", header=None, names=['Code', 'Description'])\n",
    "# icd_codes[icd_codes['Category Code'] == 'C449']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<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>PATIENTID</th>\n",
       "      <th>SEX</th>\n",
       "      <th>LINKNUMBER</th>\n",
       "      <th>ETHNICITY</th>\n",
       "      <th>DEATHCAUSECODE_1A</th>\n",
       "      <th>DEATHCAUSECODE_1B</th>\n",
       "      <th>DEATHCAUSECODE_1C</th>\n",
       "      <th>DEATHCAUSECODE_2</th>\n",
       "      <th>DEATHCAUSECODE_UNDERLYING</th>\n",
       "      <th>DEATHLOCATIONCODE</th>\n",
       "      <th>NEWVITALSTATUS</th>\n",
       "      <th>VITALSTATUSDATE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10000001</td>\n",
       "      <td>2</td>\n",
       "      <td>810000001</td>\n",
       "      <td>A</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A</td>\n",
       "      <td>2017-01-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10000002</td>\n",
       "      <td>2</td>\n",
       "      <td>810000002</td>\n",
       "      <td>Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A</td>\n",
       "      <td>2017-01-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10000003</td>\n",
       "      <td>1</td>\n",
       "      <td>810000003</td>\n",
       "      <td>A</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A</td>\n",
       "      <td>2017-01-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10000004</td>\n",
       "      <td>1</td>\n",
       "      <td>810000004</td>\n",
       "      <td>A</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A</td>\n",
       "      <td>2017-01-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10000005</td>\n",
       "      <td>2</td>\n",
       "      <td>810000005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A</td>\n",
       "      <td>2017-01-16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PATIENTID  SEX  LINKNUMBER ETHNICITY DEATHCAUSECODE_1A DEATHCAUSECODE_1B  \\\n",
       "0   10000001    2   810000001         A               NaN               NaN   \n",
       "1   10000002    2   810000002         Z               NaN               NaN   \n",
       "2   10000003    1   810000003         A               NaN               NaN   \n",
       "3   10000004    1   810000004         A               NaN               NaN   \n",
       "4   10000005    2   810000005       NaN               NaN               NaN   \n",
       "\n",
       "  DEATHCAUSECODE_1C DEATHCAUSECODE_2 DEATHCAUSECODE_UNDERLYING  \\\n",
       "0               NaN              NaN                       NaN   \n",
       "1               NaN              NaN                       NaN   \n",
       "2               NaN              NaN                       NaN   \n",
       "3               NaN              NaN                       NaN   \n",
       "4               NaN              NaN                       NaN   \n",
       "\n",
       "  DEATHLOCATIONCODE NEWVITALSTATUS VITALSTATUSDATE  \n",
       "0               NaN              A      2017-01-17  \n",
       "1               NaN              A      2017-01-14  \n",
       "2               NaN              A      2017-01-17  \n",
       "3               NaN              A      2017-01-13  \n",
       "4               NaN              A      2017-01-16  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Have a glance at the table\n",
    "patient.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## About this table\n",
    "This table contains 12 columns, which are about the synthetic patients' demographic information and vital status, as well as death cause of those who are deceased. The columns are:\n",
    "- Patient ID\n",
    "- Sex\n",
    "- Link Number (allows linkeage to another table)\n",
    "- Ethnicity\n",
    "- Death Cause Code * 5 (1A, 1B, 1C, 2, Underlying)\n",
    "- Death Location Code\n",
    "- Vital Status\n",
    "- Vital Status Date\n",
    "\n",
    "There are 1,322,100 entries in this table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1322100 entries, 0 to 1322099\n",
      "Data columns (total 12 columns):\n",
      "PATIENTID                    1322100 non-null int64\n",
      "SEX                          1322100 non-null int64\n",
      "LINKNUMBER                   1322100 non-null int64\n",
      "ETHNICITY                    1192249 non-null object\n",
      "DEATHCAUSECODE_1A            330280 non-null object\n",
      "DEATHCAUSECODE_1B            98085 non-null object\n",
      "DEATHCAUSECODE_1C            18106 non-null object\n",
      "DEATHCAUSECODE_2             141982 non-null object\n",
      "DEATHCAUSECODE_UNDERLYING    327910 non-null object\n",
      "DEATHLOCATIONCODE            330381 non-null object\n",
      "NEWVITALSTATUS               1322100 non-null object\n",
      "VITALSTATUSDATE              1322100 non-null object\n",
      "dtypes: int64(3), object(9)\n",
      "memory usage: 121.0+ MB\n"
     ]
    }
   ],
   "source": [
    "patient.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inconsistent delimiters in death cause code columns\n",
    "There are several columns in this table which represent death causes of the patients. These death causes are recorded with ICD-10 codes and if a patient died because multiple factors, their codes are separated by commas.\n",
    "\n",
    "However, in some of the rows, the delimiter is space(' '), semicolon(';'), or full-stop('.') rather than comma, which should be fixed. In the following cell, I used a function `to_comma` to do the replacement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [],
   "source": [
    "# Define a function which is used to turn all other delimiters in death cause code columns with commas.\n",
    "def to_comma(code):\n",
    "    if type(code) == str:\n",
    "        if code.count('.') > 0 and any(x.isdigit() for x in code): # Replace full-stops with commas.\n",
    "            code = code.replace('.', ',')\n",
    "            return code\n",
    "        elif code.count(';') > 0 and any(x.isdigit() for x in code):  # Replace semicolons with commas.\n",
    "            code = code.replace(';', ',')\n",
    "            return code\n",
    "        elif code.count(' ') > 0 and any(x.isdigit() for x in code):   # Replace space with commas.\n",
    "            code = code.replace(' ', ',')\n",
    "            return code\n",
    "      \n",
    "        else:\n",
    "            return code\n",
    "    else:\n",
    "        return code\n",
    "    \n",
    "    \n",
    "# Apply the function to all the death cause code columns with `Series.map()`.\n",
    "patient['DEATHCAUSECODE_1A'] = patient['DEATHCAUSECODE_1A'].map(to_comma)\n",
    "patient['DEATHCAUSECODE_1B'] = patient['DEATHCAUSECODE_1B'].map(to_comma)\n",
    "patient['DEATHCAUSECODE_1C'] = patient['DEATHCAUSECODE_1C'].map(to_comma)\n",
    "patient['DEATHCAUSECODE_2'] = patient['DEATHCAUSECODE_2'].map(to_comma)\n",
    "patient['DEATHCAUSECODE_UNDERLYING'] = patient['DEATHCAUSECODE_UNDERLYING'].map(to_comma)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After converting all the inconsistent delimiters, I tried to split all the cells containing multiple death causes and calculate how many times a death cause code showed in this table, this is to see:\n",
    "1. If all the delimiters were correctly turned into commas.\n",
    "2. If there was any other value that was not recoreded in ICD-10 codes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "death_causes = {} # Init a dict to store all the death cause codes and how many times.\n",
    "\n",
    "# Define a function to split multiple codes and calculate the numbers of each code.\n",
    "def calculate_death_causes(code):\n",
    "    if type(code) == str:\n",
    "        for i in code.split(','):\n",
    "            if i.strip() not in death_causes and i != '':\n",
    "                death_causes[i.strip()] = 1  # If the death code is not in the dict, put it in and set its number to 1.\n",
    "            elif i != '':\n",
    "                death_causes[i.strip()] += 1 # Otherwise, add 1 to its number.\n",
    "    else:\n",
    "        pass\n",
    "\n",
    "# Apply this function to all the death cause code columns.\n",
    "patient['DEATHCAUSECODE_1A'].map(calculate_death_causes)\n",
    "patient['DEATHCAUSECODE_1B'].map(calculate_death_causes)\n",
    "patient['DEATHCAUSECODE_1C'].map(calculate_death_causes)\n",
    "patient['DEATHCAUSECODE_2'].map(calculate_death_causes)\n",
    "patient['DEATHCAUSECODE_UNDERLYING'].map(calculate_death_causes)\n",
    "\n",
    "# Turn the dict into a Pandas Series Object.\n",
    "death_causes_series = pd.Series(death_causes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Length of all the indicdes in the new Series should be less than 5 characters, according to ICD-10 Code standard. However, I then found some descriptive phrases as below about patiens' death causes but they were not recorded in ICD-10 codes.\n",
    "\n",
    "There were many problems with these phrases. For example:\n",
    "- **Inconsistent**: same causes but in different ways of recording: 'ISCHAEMIC HEART DISEASE' and 'Ischaemic Heart Disease'.\n",
    "- **Words lost**: like 'ASPIRATION', which can be 'ASPIRATION PNEUMONIA'.\n",
    "- **Ambiguous**: like 'CANCER OF LUNG' and 'PNEUMONIA'.\n",
    "- **Not listed in ICD-10**: like 'CEREBROVASCULAR ACCIDENT'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "R688     9092\n",
       "C241      479\n",
       "I259    26056\n",
       "J189    21889\n",
       "C170     1418\n",
       "        ...  \n",
       "C688        3\n",
       "Y288        1\n",
       "D386        1\n",
       "C723        1\n",
       "G523        1\n",
       "Length: 2510, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dc_not_coded = death_causes_series[np.where(death_causes_series.index.map(len) >= 5)[0]]\n",
    "dc_not_coded.index\n",
    "icd_pattern = '^[A-Z]{1}\\d{2,}$'\n",
    "np.array([death_causes_series[x] for x in death_causes_series.index if re.match(icd_pattern, x) == None]).sum()\n",
    "death_causes_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Int64Index([313039], dtype='int64')\n",
      "Int64Index([450463], dtype='int64')\n",
      "Int64Index([479682, 533235], dtype='int64')\n",
      "Int64Index([479682, 533235], dtype='int64')\n",
      "Int64Index([571984, 623525, 641417], dtype='int64')\n",
      "Int64Index([590975], dtype='int64')\n",
      "Int64Index([571984, 623525, 641417], dtype='int64')\n",
      "Int64Index([626674, 649707], dtype='int64')\n",
      "Int64Index([635287, 666329], dtype='int64')\n",
      "Int64Index([637211], dtype='int64')\n",
      "Int64Index([637672], dtype='int64')\n",
      "Int64Index([571984, 623525, 641417], dtype='int64')\n",
      "Int64Index([626674, 649707], dtype='int64')\n",
      "Int64Index([635287, 666329], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n",
      "Int64Index([], dtype='int64')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(1322066, 12)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This is to check if any entry in a death cause code column contains death causes not listed in the ICD-10 code.\n",
    "# It returns a list which cosist of True(for not listed) and False.\n",
    "\n",
    "def check_dc_not_coded(values):\n",
    "    arr = []\n",
    "    for value in values:\n",
    "        if type(value) == str:\n",
    "            if any(i.strip() in dc_not_coded.index for i in value.split(',')):\n",
    "                print(patient[patient['DEATHCAUSECODE_1A'] == value].index)\n",
    "                arr.append(True)\n",
    "            else:\n",
    "                arr.append(False)\n",
    "        else:\n",
    "            arr.append(False)\n",
    "    return arr\n",
    "\n",
    "# Collect all the rows where the death causes are not listed.\n",
    "\n",
    "dc_to_drop = np.where(np.array(check_dc_not_coded(patient['DEATHCAUSECODE_1A']))\n",
    "+ np.array(check_dc_not_coded(patient['DEATHCAUSECODE_1B']))\n",
    "+ np.array(check_dc_not_coded(patient['DEATHCAUSECODE_1C']))\n",
    "+ np.array(check_dc_not_coded(patient['DEATHCAUSECODE_2']))\n",
    "+ np.array(check_dc_not_coded(patient['DEATHCAUSECODE_UNDERLYING'])))[0]\n",
    "\n",
    "\n",
    "# Drop those rows in place;\n",
    "patient.drop(dc_to_drop, inplace=True)\n",
    "\n",
    "# Check how many rows were dropped\n",
    "patient.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Date format conversion and errors on vital status date\n",
    "The 'VITASTATUSDATA' column contains the time when patients' vital status were recorded but the values are in the type of string. I turned the format of vital status dates into `Pandas Timestamp`, which can be easily compared and calculated. Then I found 31 outliers where the date was on 01/01/1990. These can be blank values in database and thus I decided to drop these entries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1322035, 12)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inconsistent column name\n",
    "This table can be linked to the Systemic Anti-Cancer Therapy (SACT) tables (sim_sact) by an overlapped column 'LINKNUMBER' but the names were different in the two tables, so we changged it to 'LINK_NUMBER' in order to keep consistent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [],
   "source": [
    "# Change the column name to 'LINK_NUMBER' in place.\n",
    "patient.rename(columns={'LINKNUMBER': 'LINK_NUMBER'}, inplace=True)\n",
    "\n",
    "# This line is to check if the name is correctly changed and should return a Series\n",
    "# patient['LINK_NUMBER']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After data cleaning, the table still had 1,322,035 entries."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demographic Information\n",
    "\n",
    "[Ethnicity Category Code](https://www.datadictionary.nhs.uk/data_dictionary/attributes/e/end/ethnic_category_code_de.asp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>PATIENTID</th>\n",
       "      <th>LINK_NUMBER</th>\n",
       "      <th>DEATHCAUSECODE_1A</th>\n",
       "      <th>DEATHCAUSECODE_1B</th>\n",
       "      <th>DEATHCAUSECODE_1C</th>\n",
       "      <th>DEATHCAUSECODE_2</th>\n",
       "      <th>DEATHCAUSECODE_UNDERLYING</th>\n",
       "      <th>DEATHLOCATIONCODE</th>\n",
       "      <th>NEWVITALSTATUS</th>\n",
       "      <th>VITALSTATUSDATE</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SEX</th>\n",
       "      <th>ETHNICITY</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"20\" valign=\"top\">1</th>\n",
       "      <th>0</th>\n",
       "      <td>280</td>\n",
       "      <td>280</td>\n",
       "      <td>42</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>26</td>\n",
       "      <td>43</td>\n",
       "      <td>42</td>\n",
       "      <td>280</td>\n",
       "      <td>280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>516014</td>\n",
       "      <td>516014</td>\n",
       "      <td>144378</td>\n",
       "      <td>43608</td>\n",
       "      <td>8065</td>\n",
       "      <td>64200</td>\n",
       "      <td>143265</td>\n",
       "      <td>144441</td>\n",
       "      <td>516014</td>\n",
       "      <td>516014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>5857</td>\n",
       "      <td>5857</td>\n",
       "      <td>1680</td>\n",
       "      <td>502</td>\n",
       "      <td>77</td>\n",
       "      <td>730</td>\n",
       "      <td>1672</td>\n",
       "      <td>1683</td>\n",
       "      <td>5857</td>\n",
       "      <td>5857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>16831</td>\n",
       "      <td>16831</td>\n",
       "      <td>5027</td>\n",
       "      <td>1516</td>\n",
       "      <td>259</td>\n",
       "      <td>2237</td>\n",
       "      <td>4993</td>\n",
       "      <td>5027</td>\n",
       "      <td>16831</td>\n",
       "      <td>16831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>439</td>\n",
       "      <td>439</td>\n",
       "      <td>153</td>\n",
       "      <td>48</td>\n",
       "      <td>11</td>\n",
       "      <td>59</td>\n",
       "      <td>153</td>\n",
       "      <td>154</td>\n",
       "      <td>439</td>\n",
       "      <td>439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>75</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>25</td>\n",
       "      <td>76</td>\n",
       "      <td>75</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F</th>\n",
       "      <td>327</td>\n",
       "      <td>327</td>\n",
       "      <td>106</td>\n",
       "      <td>33</td>\n",
       "      <td>9</td>\n",
       "      <td>48</td>\n",
       "      <td>104</td>\n",
       "      <td>106</td>\n",
       "      <td>327</td>\n",
       "      <td>327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>G</th>\n",
       "      <td>717</td>\n",
       "      <td>717</td>\n",
       "      <td>233</td>\n",
       "      <td>67</td>\n",
       "      <td>13</td>\n",
       "      <td>106</td>\n",
       "      <td>233</td>\n",
       "      <td>234</td>\n",
       "      <td>717</td>\n",
       "      <td>717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H</th>\n",
       "      <td>4251</td>\n",
       "      <td>4251</td>\n",
       "      <td>1482</td>\n",
       "      <td>449</td>\n",
       "      <td>81</td>\n",
       "      <td>649</td>\n",
       "      <td>1472</td>\n",
       "      <td>1482</td>\n",
       "      <td>4251</td>\n",
       "      <td>4251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>J</th>\n",
       "      <td>2528</td>\n",
       "      <td>2528</td>\n",
       "      <td>989</td>\n",
       "      <td>301</td>\n",
       "      <td>49</td>\n",
       "      <td>393</td>\n",
       "      <td>969</td>\n",
       "      <td>987</td>\n",
       "      <td>2528</td>\n",
       "      <td>2528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>K</th>\n",
       "      <td>800</td>\n",
       "      <td>800</td>\n",
       "      <td>322</td>\n",
       "      <td>110</td>\n",
       "      <td>21</td>\n",
       "      <td>153</td>\n",
       "      <td>322</td>\n",
       "      <td>324</td>\n",
       "      <td>800</td>\n",
       "      <td>800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L</th>\n",
       "      <td>2331</td>\n",
       "      <td>2331</td>\n",
       "      <td>845</td>\n",
       "      <td>247</td>\n",
       "      <td>56</td>\n",
       "      <td>356</td>\n",
       "      <td>831</td>\n",
       "      <td>840</td>\n",
       "      <td>2331</td>\n",
       "      <td>2331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M</th>\n",
       "      <td>4378</td>\n",
       "      <td>4378</td>\n",
       "      <td>1332</td>\n",
       "      <td>390</td>\n",
       "      <td>81</td>\n",
       "      <td>583</td>\n",
       "      <td>1329</td>\n",
       "      <td>1329</td>\n",
       "      <td>4378</td>\n",
       "      <td>4378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N</th>\n",
       "      <td>2531</td>\n",
       "      <td>2531</td>\n",
       "      <td>799</td>\n",
       "      <td>242</td>\n",
       "      <td>57</td>\n",
       "      <td>366</td>\n",
       "      <td>797</td>\n",
       "      <td>796</td>\n",
       "      <td>2531</td>\n",
       "      <td>2531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>P</th>\n",
       "      <td>1452</td>\n",
       "      <td>1452</td>\n",
       "      <td>442</td>\n",
       "      <td>122</td>\n",
       "      <td>26</td>\n",
       "      <td>215</td>\n",
       "      <td>442</td>\n",
       "      <td>443</td>\n",
       "      <td>1452</td>\n",
       "      <td>1452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>823</td>\n",
       "      <td>823</td>\n",
       "      <td>327</td>\n",
       "      <td>110</td>\n",
       "      <td>18</td>\n",
       "      <td>136</td>\n",
       "      <td>324</td>\n",
       "      <td>330</td>\n",
       "      <td>823</td>\n",
       "      <td>823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S</th>\n",
       "      <td>5225</td>\n",
       "      <td>5225</td>\n",
       "      <td>1719</td>\n",
       "      <td>498</td>\n",
       "      <td>107</td>\n",
       "      <td>747</td>\n",
       "      <td>1704</td>\n",
       "      <td>1723</td>\n",
       "      <td>5225</td>\n",
       "      <td>5225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>X</th>\n",
       "      <td>5162</td>\n",
       "      <td>5162</td>\n",
       "      <td>1130</td>\n",
       "      <td>358</td>\n",
       "      <td>72</td>\n",
       "      <td>534</td>\n",
       "      <td>1114</td>\n",
       "      <td>1130</td>\n",
       "      <td>5162</td>\n",
       "      <td>5162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Z</th>\n",
       "      <td>18019</td>\n",
       "      <td>18019</td>\n",
       "      <td>4242</td>\n",
       "      <td>1335</td>\n",
       "      <td>258</td>\n",
       "      <td>1937</td>\n",
       "      <td>4210</td>\n",
       "      <td>4248</td>\n",
       "      <td>18019</td>\n",
       "      <td>18019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"20\" valign=\"top\">2</th>\n",
       "      <th>0</th>\n",
       "      <td>285</td>\n",
       "      <td>285</td>\n",
       "      <td>53</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>285</td>\n",
       "      <td>285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>524162</td>\n",
       "      <td>524162</td>\n",
       "      <td>131943</td>\n",
       "      <td>38037</td>\n",
       "      <td>6885</td>\n",
       "      <td>53993</td>\n",
       "      <td>130997</td>\n",
       "      <td>131962</td>\n",
       "      <td>524162</td>\n",
       "      <td>524162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>5156</td>\n",
       "      <td>5156</td>\n",
       "      <td>1423</td>\n",
       "      <td>429</td>\n",
       "      <td>62</td>\n",
       "      <td>584</td>\n",
       "      <td>1407</td>\n",
       "      <td>1423</td>\n",
       "      <td>5156</td>\n",
       "      <td>5156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>21564</td>\n",
       "      <td>21564</td>\n",
       "      <td>4827</td>\n",
       "      <td>1390</td>\n",
       "      <td>266</td>\n",
       "      <td>1980</td>\n",
       "      <td>4804</td>\n",
       "      <td>4827</td>\n",
       "      <td>21564</td>\n",
       "      <td>21564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>679</td>\n",
       "      <td>679</td>\n",
       "      <td>140</td>\n",
       "      <td>47</td>\n",
       "      <td>14</td>\n",
       "      <td>57</td>\n",
       "      <td>140</td>\n",
       "      <td>140</td>\n",
       "      <td>679</td>\n",
       "      <td>679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>324</td>\n",
       "      <td>324</td>\n",
       "      <td>76</td>\n",
       "      <td>25</td>\n",
       "      <td>10</td>\n",
       "      <td>30</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>324</td>\n",
       "      <td>324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F</th>\n",
       "      <td>522</td>\n",
       "      <td>522</td>\n",
       "      <td>126</td>\n",
       "      <td>37</td>\n",
       "      <td>7</td>\n",
       "      <td>46</td>\n",
       "      <td>123</td>\n",
       "      <td>126</td>\n",
       "      <td>522</td>\n",
       "      <td>522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>G</th>\n",
       "      <td>1068</td>\n",
       "      <td>1068</td>\n",
       "      <td>261</td>\n",
       "      <td>69</td>\n",
       "      <td>11</td>\n",
       "      <td>102</td>\n",
       "      <td>262</td>\n",
       "      <td>261</td>\n",
       "      <td>1068</td>\n",
       "      <td>1068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H</th>\n",
       "      <td>5290</td>\n",
       "      <td>5290</td>\n",
       "      <td>1414</td>\n",
       "      <td>421</td>\n",
       "      <td>82</td>\n",
       "      <td>572</td>\n",
       "      <td>1407</td>\n",
       "      <td>1419</td>\n",
       "      <td>5290</td>\n",
       "      <td>5290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>J</th>\n",
       "      <td>3032</td>\n",
       "      <td>3032</td>\n",
       "      <td>875</td>\n",
       "      <td>230</td>\n",
       "      <td>52</td>\n",
       "      <td>354</td>\n",
       "      <td>873</td>\n",
       "      <td>876</td>\n",
       "      <td>3032</td>\n",
       "      <td>3032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>K</th>\n",
       "      <td>858</td>\n",
       "      <td>858</td>\n",
       "      <td>237</td>\n",
       "      <td>77</td>\n",
       "      <td>18</td>\n",
       "      <td>100</td>\n",
       "      <td>236</td>\n",
       "      <td>237</td>\n",
       "      <td>858</td>\n",
       "      <td>858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L</th>\n",
       "      <td>2837</td>\n",
       "      <td>2837</td>\n",
       "      <td>698</td>\n",
       "      <td>213</td>\n",
       "      <td>37</td>\n",
       "      <td>292</td>\n",
       "      <td>695</td>\n",
       "      <td>698</td>\n",
       "      <td>2837</td>\n",
       "      <td>2837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M</th>\n",
       "      <td>3875</td>\n",
       "      <td>3875</td>\n",
       "      <td>1084</td>\n",
       "      <td>316</td>\n",
       "      <td>57</td>\n",
       "      <td>415</td>\n",
       "      <td>1084</td>\n",
       "      <td>1085</td>\n",
       "      <td>3875</td>\n",
       "      <td>3875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N</th>\n",
       "      <td>2908</td>\n",
       "      <td>2908</td>\n",
       "      <td>735</td>\n",
       "      <td>213</td>\n",
       "      <td>33</td>\n",
       "      <td>298</td>\n",
       "      <td>728</td>\n",
       "      <td>740</td>\n",
       "      <td>2908</td>\n",
       "      <td>2908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>P</th>\n",
       "      <td>1508</td>\n",
       "      <td>1508</td>\n",
       "      <td>404</td>\n",
       "      <td>111</td>\n",
       "      <td>23</td>\n",
       "      <td>161</td>\n",
       "      <td>402</td>\n",
       "      <td>404</td>\n",
       "      <td>1508</td>\n",
       "      <td>1508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>1412</td>\n",
       "      <td>1412</td>\n",
       "      <td>386</td>\n",
       "      <td>103</td>\n",
       "      <td>16</td>\n",
       "      <td>144</td>\n",
       "      <td>380</td>\n",
       "      <td>386</td>\n",
       "      <td>1412</td>\n",
       "      <td>1412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S</th>\n",
       "      <td>6008</td>\n",
       "      <td>6008</td>\n",
       "      <td>1454</td>\n",
       "      <td>429</td>\n",
       "      <td>68</td>\n",
       "      <td>586</td>\n",
       "      <td>1450</td>\n",
       "      <td>1448</td>\n",
       "      <td>6008</td>\n",
       "      <td>6008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>X</th>\n",
       "      <td>5155</td>\n",
       "      <td>5155</td>\n",
       "      <td>972</td>\n",
       "      <td>335</td>\n",
       "      <td>50</td>\n",
       "      <td>390</td>\n",
       "      <td>969</td>\n",
       "      <td>969</td>\n",
       "      <td>5155</td>\n",
       "      <td>5155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Z</th>\n",
       "      <td>17322</td>\n",
       "      <td>17322</td>\n",
       "      <td>3902</td>\n",
       "      <td>1101</td>\n",
       "      <td>202</td>\n",
       "      <td>1612</td>\n",
       "      <td>3886</td>\n",
       "      <td>3901</td>\n",
       "      <td>17322</td>\n",
       "      <td>17322</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               PATIENTID  LINK_NUMBER  DEATHCAUSECODE_1A  DEATHCAUSECODE_1B  \\\n",
       "SEX ETHNICITY                                                                 \n",
       "1   0                280          280                 42                 10   \n",
       "    8                 21           21                  3                  1   \n",
       "    A             516014       516014             144378              43608   \n",
       "    B               5857         5857               1680                502   \n",
       "    C              16831        16831               5027               1516   \n",
       "    D                439          439                153                 48   \n",
       "    E                219          219                 75                 25   \n",
       "    F                327          327                106                 33   \n",
       "    G                717          717                233                 67   \n",
       "    H               4251         4251               1482                449   \n",
       "    J               2528         2528                989                301   \n",
       "    K                800          800                322                110   \n",
       "    L               2331         2331                845                247   \n",
       "    M               4378         4378               1332                390   \n",
       "    N               2531         2531                799                242   \n",
       "    P               1452         1452                442                122   \n",
       "    R                823          823                327                110   \n",
       "    S               5225         5225               1719                498   \n",
       "    X               5162         5162               1130                358   \n",
       "    Z              18019        18019               4242               1335   \n",
       "2   0                285          285                 53                 12   \n",
       "    8                 20           20                  5                  0   \n",
       "    A             524162       524162             131943              38037   \n",
       "    B               5156         5156               1423                429   \n",
       "    C              21564        21564               4827               1390   \n",
       "    D                679          679                140                 47   \n",
       "    E                324          324                 76                 25   \n",
       "    F                522          522                126                 37   \n",
       "    G               1068         1068                261                 69   \n",
       "    H               5290         5290               1414                421   \n",
       "    J               3032         3032                875                230   \n",
       "    K                858          858                237                 77   \n",
       "    L               2837         2837                698                213   \n",
       "    M               3875         3875               1084                316   \n",
       "    N               2908         2908                735                213   \n",
       "    P               1508         1508                404                111   \n",
       "    R               1412         1412                386                103   \n",
       "    S               6008         6008               1454                429   \n",
       "    X               5155         5155                972                335   \n",
       "    Z              17322        17322               3902               1101   \n",
       "\n",
       "               DEATHCAUSECODE_1C  DEATHCAUSECODE_2  DEATHCAUSECODE_UNDERLYING  \\\n",
       "SEX ETHNICITY                                                                   \n",
       "1   0                          3                26                         43   \n",
       "    8                          0                 2                          3   \n",
       "    A                       8065             64200                     143265   \n",
       "    B                         77               730                       1672   \n",
       "    C                        259              2237                       4993   \n",
       "    D                         11                59                        153   \n",
       "    E                          3                25                         76   \n",
       "    F                          9                48                        104   \n",
       "    G                         13               106                        233   \n",
       "    H                         81               649                       1472   \n",
       "    J                         49               393                        969   \n",
       "    K                         21               153                        322   \n",
       "    L                         56               356                        831   \n",
       "    M                         81               583                       1329   \n",
       "    N                         57               366                        797   \n",
       "    P                         26               215                        442   \n",
       "    R                         18               136                        324   \n",
       "    S                        107               747                       1704   \n",
       "    X                         72               534                       1114   \n",
       "    Z                        258              1937                       4210   \n",
       "2   0                          5                23                         53   \n",
       "    8                          0                 2                          5   \n",
       "    A                       6885             53993                     130997   \n",
       "    B                         62               584                       1407   \n",
       "    C                        266              1980                       4804   \n",
       "    D                         14                57                        140   \n",
       "    E                         10                30                         75   \n",
       "    F                          7                46                        123   \n",
       "    G                         11               102                        262   \n",
       "    H                         82               572                       1407   \n",
       "    J                         52               354                        873   \n",
       "    K                         18               100                        236   \n",
       "    L                         37               292                        695   \n",
       "    M                         57               415                       1084   \n",
       "    N                         33               298                        728   \n",
       "    P                         23               161                        402   \n",
       "    R                         16               144                        380   \n",
       "    S                         68               586                       1450   \n",
       "    X                         50               390                        969   \n",
       "    Z                        202              1612                       3886   \n",
       "\n",
       "               DEATHLOCATIONCODE  NEWVITALSTATUS  VITALSTATUSDATE  \n",
       "SEX ETHNICITY                                                      \n",
       "1   0                         42             280              280  \n",
       "    8                          3              21               21  \n",
       "    A                     144441          516014           516014  \n",
       "    B                       1683            5857             5857  \n",
       "    C                       5027           16831            16831  \n",
       "    D                        154             439              439  \n",
       "    E                         75             219              219  \n",
       "    F                        106             327              327  \n",
       "    G                        234             717              717  \n",
       "    H                       1482            4251             4251  \n",
       "    J                        987            2528             2528  \n",
       "    K                        324             800              800  \n",
       "    L                        840            2331             2331  \n",
       "    M                       1329            4378             4378  \n",
       "    N                        796            2531             2531  \n",
       "    P                        443            1452             1452  \n",
       "    R                        330             823              823  \n",
       "    S                       1723            5225             5225  \n",
       "    X                       1130            5162             5162  \n",
       "    Z                       4248           18019            18019  \n",
       "2   0                         53             285              285  \n",
       "    8                          5              20               20  \n",
       "    A                     131962          524162           524162  \n",
       "    B                       1423            5156             5156  \n",
       "    C                       4827           21564            21564  \n",
       "    D                        140             679              679  \n",
       "    E                         75             324              324  \n",
       "    F                        126             522              522  \n",
       "    G                        261            1068             1068  \n",
       "    H                       1419            5290             5290  \n",
       "    J                        876            3032             3032  \n",
       "    K                        237             858              858  \n",
       "    L                        698            2837             2837  \n",
       "    M                       1085            3875             3875  \n",
       "    N                        740            2908             2908  \n",
       "    P                        404            1508             1508  \n",
       "    R                        386            1412             1412  \n",
       "    S                       1448            6008             6008  \n",
       "    X                        969            5155             5155  \n",
       "    Z                       3901           17322            17322  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "patient.groupby(['SEX', 'ETHNICITY']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [],
   "source": [
    "# Group the data by sex and ethnicity to see the demographic information of patients.\n",
    "group_a = patient.groupby(['SEX', 'ETHNICITY' ]).count()\n",
    "\n",
    "# The proportion of ethnic groups among male patients\n",
    "m_ethnicity = group_a['PATIENTID'][0:20]\n",
    "m_ethnicity_codes = [x[1] for x in m_ethnicity.index]\n",
    "ethnicity_names = ['', '', 'British', 'Irish', 'Any other White background', 'White and Black Caribbean', 'White and Black African', 'White and Asian', 'Any other mixed background', 'Indian', 'Pakistani', 'Bangladeshi', 'Any other Asian background', 'Caribbean', 'African', 'Any other black background', 'Chinese', 'Any other ethnic group', '', 'Not stated']\n",
    "m_labels = list(zip(m_ethnicity_codes, ethnicity_names))\n",
    "\n",
    "# # The proportion of ethnic groups among non-British male patients\n",
    "m_non_british = m_ethnicity.drop(labels=(1, 'A'))\n",
    "m_non_british_labels = list(zip(m_ethnicity_codes, ethnicity_names))\n",
    "m_non_british_labels.remove(('A', 'British'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1728x1728 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualise the proportion in two pie charts\n",
    "fig1, ax1 = plt.subplots(1, 2, figsize=(24, 24))\n",
    "ax1[0].pie(m_ethnicity, textprops={'fontsize': 8})\n",
    "ax1[1].pie(m_non_british, labels= [x[0] for x in m_non_british_labels])\n",
    "ax1[0].set_title('Proportion of ethnic groups(Male)')\n",
    "ax1[1].set_title('Proportion of ethnic groups(Male, exclude British)')\n",
    "ax1[0].legend(m_labels)\n",
    "ax1[1].legend(m_non_british_labels)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [],
   "source": [
    "# The proportion of ethnic groups among female patients\n",
    "fm_ethnicity = group_a['PATIENTID'][20:40]\n",
    "fm_ethnicity_codes = [x[1] for x in fm_ethnicity.index]\n",
    "fm_labels = list(zip(fm_ethnicity_codes, ethnicity_names))\n",
    "\n",
    "# The proportion of ethnic groups among non-british female patients\n",
    "fm_non_british = fm_ethnicity.drop(labels=(2, 'A'))\n",
    "fm_non_british_labels = list(zip(fm_ethnicity_codes, ethnicity_names))\n",
    "fm_non_british_labels.remove(('A', 'British'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1728x1728 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualise the proportion in two pie charts\n",
    "fig2, ax2 = plt.subplots(1, 2, figsize=(24, 24))\n",
    "ax2[0].pie(fm_ethnicity)\n",
    "ax2[1].pie(fm_non_british, labels=[x[0] for x in fm_non_british_labels])\n",
    "ax2[0].set_title('Proportion of ethnic groups(Female)')\n",
    "ax2[1].set_title('Proportion of ethnic groups(Female, exclude British)')\n",
    "ax2[0].legend(fm_labels)\n",
    "ax2[1].legend(fm_non_british_labels)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [],
   "source": [
    "group_b = patient.groupby('DEATHCAUSECODE_1A').count()\n",
    "# group_b\n",
    "# group_b['PATIENTID'].plot()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "330347"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "patient['DEATHLOCATIONCODE'].value_counts().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## VITAL STATUS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "vital_status = patient.groupby('NEWVITALSTATUS').count()\n",
    "patients_alive = vital_status.iloc[vital_status.index.get_level_values('NEWVITALSTATUS') == 'A'].sum().max()\n",
    "patients_deceased = vital_status.iloc[vital_status.index.get_level_values('NEWVITALSTATUS') == 'D'].sum().max()\n",
    "\n",
    "proportion_of_death = patients_deceased / (patients_deceased + patients_alive)\n",
    "\n",
    "# proportion_of_death.format\n",
    "# vital_status"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Death Location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    138309\n",
       "4     98679\n",
       "2     40280\n",
       "X     28206\n",
       "5     17018\n",
       "6      7146\n",
       "3       709\n",
       "Name: DEATHLOCATIONCODE, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "patient['DEATHLOCATIONCODE'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Death Causes\n",
    "\n",
    "142,407 patients died because of bronchus or lung "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C349 142428\n",
      "G904 1\n"
     ]
    }
   ],
   "source": [
    "death_causes = {} # Init a dict to store all the death cause codes and how many times.\n",
    "\n",
    "# Define a function to split multiple codes and calculate the numbers of each code.\n",
    "def calculate_death_causes(code):\n",
    "    if type(code) == str:\n",
    "        for i in code.split(','):\n",
    "            if i.strip() not in death_causes and i != '':\n",
    "                death_causes[i.strip()] = 1  # If the death code is not in the dict, put it in and set its number to 1.\n",
    "            elif i != '':\n",
    "                death_causes[i.strip()] += 1 # Otherwise, add 1 to its number.\n",
    "    else:\n",
    "        pass\n",
    "\n",
    "# Apply this function to all the death cause code columns.\n",
    "patient['DEATHCAUSECODE_1A'].map(calculate_death_causes)\n",
    "patient['DEATHCAUSECODE_1B'].map(calculate_death_causes)\n",
    "patient['DEATHCAUSECODE_1C'].map(calculate_death_causes)\n",
    "patient['DEATHCAUSECODE_2'].map(calculate_death_causes)\n",
    "patient['DEATHCAUSECODE_UNDERLYING'].map(calculate_death_causes)\n",
    "\n",
    "# Turn the dict into a Pandas Series Object.\n",
    "death_causes_series = pd.Series(death_causes)\n",
    "\n",
    "print(death_causes_series.idxmax(), death_causes_series.max())\n",
    "print(death_causes_series.idxmin(), death_causes_series.min())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "classified_death_codes = {}\n",
    "\n",
    "for k, v in death_causes.items():\n",
    "    if k[0] not in classified_death_codes.keys():\n",
    "        classified_death_codes[k[0]] = {}\n",
    "\n",
    "for k, v in death_causes.items():\n",
    "    if k[0] in classified_death_codes.keys():\n",
    "        if k[0:3] not in classified_death_codes[k[0]]:\n",
    "            classified_death_codes[k[0]][k[0:3]] = v\n",
    "        elif k[0:3] in classified_death_codes[k[0]]:\n",
    "            classified_death_codes[k[0]][k[0:3]] += v\n",
    "\n",
    "multiindex = [[],[]]\n",
    "death_causes_times = []\n",
    "\n",
    "for k, v in {(i, j): classified_death_codes[i][j] for i in classified_death_codes.keys() for j in classified_death_codes[i].keys()}.items():\n",
    "    multiindex[0].append(k[0])\n",
    "    multiindex[1].append(k[1])\n",
    "    death_causes_times.append(v)\n",
    "\n",
    "death_causes_table = pd.DataFrame(death_causes_times, index=multiindex, columns=['times'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reference\n",
    "[Ethnicity Category Code](https://www.datadictionary.nhs.uk/data_dictionary/attributes/e/end/ethnic_category_code_de.asp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# patient.describe()\n",
    "# patient['DEATHCAUSECODE_1A'][]\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Merge\n",
    "The table of patients registered is linked to the table of tumours registered by `PATIENTID`. I merged the two tables into `merged_av_data` to scrutinise the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>TUMOURID</th>\n",
       "      <th>PATIENTID</th>\n",
       "      <th>DIAGNOSISDATEBEST</th>\n",
       "      <th>SITE_ICD10_O2</th>\n",
       "      <th>SITE_ICD10_O2_3CHAR</th>\n",
       "      <th>MORPH_ICD10_O2</th>\n",
       "      <th>BEHAVIOUR_ICD10_O2</th>\n",
       "      <th>T_BEST</th>\n",
       "      <th>N_BEST</th>\n",
       "      <th>M_BEST</th>\n",
       "      <th>...</th>\n",
       "      <th>LINK_NUMBER</th>\n",
       "      <th>ETHNICITY</th>\n",
       "      <th>DEATHCAUSECODE_1A</th>\n",
       "      <th>DEATHCAUSECODE_1B</th>\n",
       "      <th>DEATHCAUSECODE_1C</th>\n",
       "      <th>DEATHCAUSECODE_2</th>\n",
       "      <th>DEATHCAUSECODE_UNDERLYING</th>\n",
       "      <th>DEATHLOCATIONCODE</th>\n",
       "      <th>NEWVITALSTATUS</th>\n",
       "      <th>VITALSTATUSDATE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10000001</td>\n",
       "      <td>10000001</td>\n",
       "      <td>2015-11-06</td>\n",
       "      <td>C443</td>\n",
       "      <td>C44</td>\n",
       "      <td>8090</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>810000001</td>\n",
       "      <td>A</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A</td>\n",
       "      <td>2017-01-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10000002</td>\n",
       "      <td>10000002</td>\n",
       "      <td>2015-10-06</td>\n",
       "      <td>C449</td>\n",
       "      <td>C44</td>\n",
       "      <td>8090</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>810000002</td>\n",
       "      <td>Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A</td>\n",
       "      <td>2017-01-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10000003</td>\n",
       "      <td>10000003</td>\n",
       "      <td>2013-01-30</td>\n",
       "      <td>C449</td>\n",
       "      <td>C44</td>\n",
       "      <td>8090</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>810000003</td>\n",
       "      <td>A</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A</td>\n",
       "      <td>2017-01-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10000004</td>\n",
       "      <td>10000004</td>\n",
       "      <td>2015-09-15</td>\n",
       "      <td>C449</td>\n",
       "      <td>C44</td>\n",
       "      <td>8090</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>810000004</td>\n",
       "      <td>A</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A</td>\n",
       "      <td>2017-01-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10000005</td>\n",
       "      <td>10000005</td>\n",
       "      <td>2014-11-01</td>\n",
       "      <td>C449</td>\n",
       "      <td>C44</td>\n",
       "      <td>8090</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>810000005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A</td>\n",
       "      <td>2017-01-16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 45 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   TUMOURID  PATIENTID DIAGNOSISDATEBEST SITE_ICD10_O2 SITE_ICD10_O2_3CHAR  \\\n",
       "0  10000001   10000001        2015-11-06          C443                 C44   \n",
       "1  10000002   10000002        2015-10-06          C449                 C44   \n",
       "2  10000003   10000003        2013-01-30          C449                 C44   \n",
       "3  10000004   10000004        2015-09-15          C449                 C44   \n",
       "4  10000005   10000005        2014-11-01          C449                 C44   \n",
       "\n",
       "  MORPH_ICD10_O2 BEHAVIOUR_ICD10_O2 T_BEST N_BEST M_BEST  ... LINK_NUMBER  \\\n",
       "0           8090                  3    NaN    NaN    NaN  ...   810000001   \n",
       "1           8090                  3    NaN    NaN    NaN  ...   810000002   \n",
       "2           8090                  3    NaN    NaN    NaN  ...   810000003   \n",
       "3           8090                  3    NaN    NaN    NaN  ...   810000004   \n",
       "4           8090                  3    NaN    NaN    NaN  ...   810000005   \n",
       "\n",
       "   ETHNICITY DEATHCAUSECODE_1A  DEATHCAUSECODE_1B  DEATHCAUSECODE_1C  \\\n",
       "0          A               NaN                NaN                NaN   \n",
       "1          Z               NaN                NaN                NaN   \n",
       "2          A               NaN                NaN                NaN   \n",
       "3          A               NaN                NaN                NaN   \n",
       "4        NaN               NaN                NaN                NaN   \n",
       "\n",
       "  DEATHCAUSECODE_2  DEATHCAUSECODE_UNDERLYING DEATHLOCATIONCODE  \\\n",
       "0              NaN                        NaN               NaN   \n",
       "1              NaN                        NaN               NaN   \n",
       "2              NaN                        NaN               NaN   \n",
       "3              NaN                        NaN               NaN   \n",
       "4              NaN                        NaN               NaN   \n",
       "\n",
       "  NEWVITALSTATUS  VITALSTATUSDATE  \n",
       "0              A       2017-01-17  \n",
       "1              A       2017-01-14  \n",
       "2              A       2017-01-17  \n",
       "3              A       2017-01-13  \n",
       "4              A       2017-01-16  \n",
       "\n",
       "[5 rows x 45 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge the two tables on 'PATIENTID' column and in 'inner' way.\n",
    "merged_av_data = tumour.merge(patient, on='PATIENTID', how='inner')\n",
    "merged_av_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set the 'PATIENTID' and 'TUMOURID' columns as the index because one patient can get manifold cancers.\n",
    "merged_av_data.set_index(['PATIENTID', 'TUMOURID'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# merged_av_data['T_BEST'].value_counts()\n",
    "merged_av_data.fillna('', inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Age Distribution')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# merged_av_data['AGE']\n",
    "ax = sns.distplot(merged_av_data['AGE'])\n",
    "ax.set_title('Age Distribution')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "# bins = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110]\n",
    "# cats = pd.cut(merged_av_data['AGE'], bins)\n",
    "\n",
    "# age_group = [str(x.left) + ', ' + str(x.right) for x in cats]\n",
    "# merged_av_data['Age Group'] = cats\n",
    "# merged_av_data['Age Group'][0]\n",
    "\n",
    "def calculate_death_rate(group):\n",
    "    g = merged_av_data.loc[(merged_av_data['AGE'] > group[0]) & (merged_av_data['AGE'] <= group[1]), :].groupby('NEWVITALSTATUS').count()\n",
    "    death_rate = g.iloc[g.index.get_level_values('NEWVITALSTATUS') == 'D'].sum().max() / merged_av_data.loc[(merged_av_data['AGE'] > group[0]) & (merged_av_data['AGE'] <= group[1]), :].shape[0]\n",
    "    return death_rate\n",
    "\n",
    "age_groups = np.array([[x*10, (x+1)*10] for x in range(11)])\n",
    "\n",
    "death_rate_by_age_group = pd.DataFrame(data={'AGE GROUP': [str(group) for group in age_groups], 'DEATH RATE': [calculate_death_rate(group) for group in age_groups]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Death Rate by Age Group')"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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fAAAboPABALABCh8AABug8AEAsAEKHwAAG6DwAQCwAQofAAAboPABALABCh8AABug8AEAsAEKHwAAG6DwAQCwAQofAAAboPABALABCh8AABug8AEAsAEKHwBsJCsn19bLtzMPVz54bGys5s+fr6ysLPXv3199+vTJN339+vWaPXu2jDG66aab9MILL+jaa69VTEyMXn75ZV133XWSpLvvvlsjRoxwZVQAsAVP90qauPzrMlv+5HtblNmy7c5lhZ+QkKCZM2dq5cqV8vLyUq9evdS8eXPVqVNHkpSSkqJJkybpo48+kr+/v1599VXNnj1b48eP1969exUdHa0uXbq4Kh4AALbisl36W7duVYsWLVStWjX5+PgoJCREq1evtqZnZWVp0qRJ8vf3lyTVrVtXf/zxhyRp7969iomJUUREhEaNGqXTp0+7KiYAALbgssJPTEyUr6+vNezn56eEhARruHr16urQoYMkKT09XW+++aY17OvrqyeeeEKrVq3SDTfcoClTprgqJgAAtuCyXfrGmALj3NzcCow7c+aMHn30UdWrV0/dunWTJM2dO9eaPnDgQOuDgLP27dtn3W7SpEmR5nWVnTt3lnUEACgXfxP5e1g2XFb4/v7+iouLs4YTExPl5+eX7z6JiYl66KGH1KJFCz311FOSzn0A+Oijj9S/f39J5z44eHgULWZgYKC8vb2L9x8oYeXhTQYA5QF/D0tWRkZGvg1dR1y2S79ly5batm2bkpOTlZaWprVr1yooKMianpOToyFDhig0NFRPP/20tfXv4+OjhQsXavfu3ZKk//znPwoODnZVTABAOZJdDn62Vx4yuIJLt/BHjBihfv36KSsrSz179lSDBg00aNAgDR06VH/++ad++OEH5eTkaM2aNZLObZk/99xzmjVrliZNmqT09HTdeuutmj59uqtiAgDKEQ/3Snr1i+/KNMOw0EZlunxXcenv8MPDwxUeHp5v3IIFCyRJ9evX1/79+wudr2nTpvr4449dGQ0AAFvhTHsAANgAhQ8AgA1Q+ABQQrKyc8o6QrnIgPLJpcfwAcBOPD3c9cTbG8o0w+wBd5fp8lF+sYUPAIANUPgAANgAhQ8AgA1Q+AAA2ACFDwCADVD4AADYAIUPAIANUPgAANgAhQ8AgA1Q+AAA2ACFDwCADVD4AADYAIUPAIANUPgAANgAhQ8AgA1Q+AAA2ACFDwCADVD4AADYAIVfDmRkZtp6+QAA1/Mo6wCQvL289O/IqDJb/pZVi8ts2QCA0sEWPgAANkDhA6gwMrNzbL18oDjYpQ+gwvDycFef11aX2fKXDO1UZstG+ZGTmyv3SmW7vXw5GSh8AACKwL1SJb23aX+ZZujXul6R52GXPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANuDSwo+NjVVYWJiCg4O1ZMmSAtPXr1+vyMhIRURE6NFHH9Xp06clSfHx8erTp486deqkRx55RGfPnnVlTAAArnguK/yEhATNnDlTS5cu1apVq7Rs2TL98ssv1vSUlBRNmjRJb775pj755BPVrVtXs2fPliRNnjxZvXv31urVqxUYGKh58+a5KiaA/y8zO6esI5SLDMCVysNVD7x161a1aNFC1apVkySFhIRo9erVevzxxyVJWVlZmjRpkvz9/SVJdevWVWxsrLKysrRjxw7NnTtXktS9e3f17dtXo0ePdlVUAJK8PNwV9lxMmWb4/OmuZbp84Ermsi38xMRE+fr6WsN+fn5KSEiwhqtXr64OHTpIktLT0/Xmm2+qQ4cOOnnypKpWrSoPj3OfRXx9ffPNBwAAis5lW/jGmALj3NzcCow7c+aMHn30UdWrV0/dunUrtNwLm+9i9u3bZ91u0qRJkeZ1lZ07dzqcVh4yXiwf7KE8vA6liv1eKQ/5pPKfsbznkyp+xsK4rPD9/f0VFxdnDScmJsrPzy/ffRITE/XQQw+pRYsWeuqppyRJNWrUUEpKinJycuTu7q6kpKQC811KYGCgvL29i/+fKEHl5QXiSHnPB/so76/F8p5PKv8Zy3s+qWJlzMjIyLeh64jLdum3bNlS27ZtU3JystLS0rR27VoFBQVZ03NycjRkyBCFhobq6aeftrbiPT091bRpU33++eeSpJiYmHzzAQCAonPpFv6IESPUr18/ZWVlqWfPnmrQoIEGDRqkoUOH6s8//9QPP/ygnJwcrVmzRtK5LfPnnntOEydOVHR0tObPn68bbrhBM2bMcFVMAABswWWFL0nh4eEKDw/PN27BggWSpPr162v//v2FzlezZk0tXrzYldEAALAVzrQHAIANUPgAANgAhQ8AgA1Q+AAA2ACFDwCADVD4AADYAIUPAIANUPgAANiAw8LPzs52OJOjE+YAAIDyyWHh33PPPdbtZ599Nt+0cePGuS4RAAAocQ4L//zL23777bcOpwEAgPLPYeFf7Br0Rb0+PQAAKFtObeEDAICK7bK28AEAQMXi8PK4+/fvV+PGjSVJ6enp1m1jjDIzM0snHQAAKBEOC3/9+vWlmQMAALiQw8JfunSpRo8eXZpZAACAizg8hr9169bSzAEAAFyIU+sCAGADDnfp//rrrwoPD3c4Y2xsrEsCAQCAkuew8P39/TVhwoTSzAIAAFzEYeFfddVVatasWWlmAQAALsKZ9gAAsAGHhb948eJCx6enp2vp0qUuCwQAAEqew8K/+uqr8w0nJCTo5ZdfVlBQkN555x2XBwMAACXH4TH8PLt379aiRYu0du1aubm5adKkSeratWtpZAMAACXE4Rb+559/rl69emnw4MGqXr26li5dKl9fX/Xo0UPu7u6lmREAABSTwy38kSNHKiIiQvPmzVONGjUkcQU9AAAqKodb+PPmzdOpU6fUrl07DR8+XBs2bOCb+wAAVFAOC79du3Z68803FRsbq5tuuknjxo1TQkKC5syZo1OnTpVmRgAAUEyXPJd+rVq1NGrUKG3cuFHPP/+8Nm/erLZt25ZGNgAAUEIu+S39PF5eXoqMjFRkZKT279/vykwAAKCEOdzCP3bsmJ588kk9++yzSktLkySlpKTohRdeUM+ePUstIAAAKD6Hhf/UU0+pevXqSkpK0htvvKG4uDiFhoZqy5YtWrhwYWlmBAAAxeRwl/6ff/6p9957T+np6erevbuWL1+u/v37a8CAAfLwcPpIAAAAKAccNrePj48kqXLlyjp9+rSmT5+uVq1alVowAABQci75LX1Juu666yh7AAAqMIeFf/5Z9TiVLgAAFZvDXfoHDhxQ48aNJZ27JG7ebWOM3Nzc9O2335ZOQgAAUGwOC3/dunWlmQMAALiQw8KvWbNmaeYAAAAu5NSX9gAAQMVG4QMAYAMUPgAANuDwGP7UqVMvOuP48eNLPAwAAHANh1v41apVs/6tXr0633C1atVKMyMAACgmh1v4jz/+uHV7/fr1+YYBAEDF4tQx/PPPugcAACoevrQHAIANUPgAANiAw2P4d9xxh7Urn3PpA8WXmZUtL0+Hb7krfvkAypbDd/+nn35amjmAK56Xp4c6jl1QZstf++KgMls2gLLnsPCXLl2q0aNHl2YWAADgIg6P4W/durXYDx4bG6uwsDAFBwdryZIlDu83duxYrVy50hqOiYlRq1atFBkZqcjISM2cObPYWQAAsDOXHdBLSEjQzJkztXLlSnl5ealXr15q3ry56tSpk+8+EydO1LZt29S8eXNr/N69exUdHa0uXbq4Kh4AALbisPB//fVXhYeHO5wxNjb2og+8detWtWjRwjorX0hIiFavXp3vBD6xsbFq3759gTP37d27V0eOHNGbb76pgIAATZgwQddee61T/yEAAFCQw8L39/fXhAkTLvuBExMT5evraw37+flpz549+e4zcOBASdLOnTvzjff19dXgwYPVoEEDzZgxQ1OmTNErr7xy2VkAALA7h4V/1VVXqVmzZpf9wMaYAuOcPWPf3LlzrdsDBw5Uhw4dirTsffv2WbebNGlSpHld5cIPNecrDxkvlg8lo7w/z+Uhn1T+M5b3fFL5z1je80kVP2NhHBZ+YYVdFP7+/oqLi7OGExMT5efnd8n5zpw5o48++kj9+/e3cnh4FO2rBoGBgfL29i7SPK5WXl4gjpT3fCgZFeF5Lu8Zy3s+qfxnLO/5pIqVMSMjI9+GriMOv6W/ePHiQsenp6dr6dKll3zgli1batu2bUpOTlZaWprWrl2roKCgS87n4+OjhQsXavfu3ZKk//znPwoODr7kfAAAwDGHm85XX311vuGEhAQtXrxYy5cv17XXXqvevXtf9IH9/f01YsQI9evXT1lZWerZs6caNGigQYMGaejQoapfv36h87m7u2vWrFmaNGmS0tPTdeutt2r69OmX8V8DAAB5LrmvfPfu3Vq0aJHWrl0rNzc3TZo0SV27dnXqwcPDwwt803/BgoJnGps2bVq+4aZNm+rjjz92ahkAAODSHO7S//zzz9WrVy8NHjxY1atX19KlS+Xr66sePXrI3d29NDMCAIBicriFP3LkSEVERGjevHmqUaOGJOe/ZQ8AAMoXh1v48+bN06lTp9SuXTsNHz5cGzZsKPY39wEAQNlwWPjt2rXTm2++qdjYWN10000aN26cEhISNGfOHJ06dao0MwIAgGJyWPh5atWqpVGjRmnjxo16/vnntXnzZrVt27Y0sgEAgBLi9BltvLy8rKvX7d+/35WZAABACXO4hR8dHW3dvvAncuPHj3ddIgAAUOIcFv6BAwes2++9916+adnZ2a5LBAAASpzDwj//G/kXfjufn+cBAFCxXPJLexIFDwBAReew8Cl5AACuHA6/pX/06FENGTKkwG1JOnbsmOuTAQCAEuOw8J9++mnrdkhISL5pFw4DAIDyzWHhd+vWrTRzAAAAF7roiXfWrVunhQsX6qefflKVKlUUEBCgAQMGKCgoqLTyAQCAEuCw8GNiYjRv3jwNHTpU9erVk5ubm/bs2aOpU6dq1KhR6tixY2nmBAAAxeCw8BcvXqx3331XN954ozWudu3aatSokZ566ikKHwCACsThz/KysrLylX2e2267TRkZGS4NBQAASpbDwnd3d3c404Vn3gMAAOWbU2faAwAAFZvDY/gHDhxQ48aNC4w3xigzM9OloQAAQMlyWPjr1q0rzRwAAMCFHBZ+zZo1SzMHAABwIY7hAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANuDSwo+NjVVYWJiCg4O1ZMkSh/cbO3asVq5caQ3Hx8erT58+6tSpkx555BGdPXvWlTFxBcjMyrb18gHgUjxc9cAJCQmaOXOmVq5cKS8vL/Xq1UvNmzdXnTp18t1n4sSJ2rZtm5o3b26Nnzx5snr37q3OnTtr7ty5mjdvnkaPHu2qqLgCeHl6qN2jL5TZ8r+aN67Mlg0AznDZFv7WrVvVokULVatWTT4+PgoJCdHq1avz3Sc2Nlbt27dXaGioNS4rK0s7duxQSEiIJKl79+4F5gMAAEXjsi38xMRE+fr6WsN+fn7as2dPvvsMHDhQkrRz505r3MmTJ1W1alV5eJyL5uvrq4SEBFfFBADAFlxW+MaYAuPc3NxcNt/59u3bZ91u0qRJkeZ1lfM/1FyoPGS8WL6KoCKsw/KesTzkk8p/xvKeTyr/Gct7PqniZyyMywrf399fcXFx1nBiYqL8/PwuOV+NGjWUkpKinJwcubu7Kykpyan5zhcYGChvb+8iZ3al8vICcaS856sIKsI6JGPxlfd8UvnPWN7zSRUrY0ZGRr4NXUdcdgy/ZcuW2rZtmzSW7kQAAByLSURBVJKTk5WWlqa1a9cqKCjokvN5enqqadOm+vzzzyVJMTExTs0HAAAcc1nh+/v7a8SIEerXr5+6du2qLl26qEGDBho0aJD27t170XknTpyo5cuXKywsTHFxcRo+fLirYgIAYAsu26UvSeHh4QoPD883bsGCBQXuN23atHzDNWvW1OLFi10ZDQAAW+FMewAA2ACFDwCADVD4AADYAIUPAIANUPgAANgAhQ8AgA1Q+AAA2ACFDwCADVD4AADYAIUPAIANUPgAANgAhQ8AgA1Q+AAA2ACFDwCADVD4AADYAIUPAIANUPgAANgAhQ8AgA1Q+AAA2ACFDwCADVD4AADYAIUPAIANUPgAANgAhQ8AgA1Q+AAA2ACFDwCADVD4AADYAIUPAIANUPgAANgAhQ8AgA1Q+AAA2ACFDwCADVD4AADYAIUPAIANUPgAANgAhQ8AgA1Q+AAA2ACFDwCADVD4AADYAIUPAIANUPgAANgAhQ8AgA1Q+AAA2ACFDwCADVD4AADYAIUPAIANUPgAANgAhQ8AgA1Q+AAA2ACFDwCADVD4AADYAIUPAIANUPgAANiASws/NjZWYWFhCg4O1pIlSwpM//HHH9WjRw+FhITo6aefVnZ2tiQpJiZGrVq1UmRkpCIjIzVz5kxXxgQA4Irn4aoHTkhI0MyZM7Vy5Up5eXmpV69eat68uerUqWPdZ/To0Zo6daoaNWqkp556SsuXL1fv3r21d+9eRUdHq0uXLq6KBwCArbhsC3/r1q1q0aKFqlWrJh8fH4WEhGj16tXW9N9//13p6elq1KiRJKl79+7W9L179yomJkYREREaNWqUTp8+7aqYAADYgsu28BMTE+Xr62sN+/n5ac+ePQ6n+/r6KiEhwbo9ePBgNWjQQDNmzNCUKVP0yiuvOL3sffv2WbebNGlSnP9Gidm5c6fDaeUh48XyVQQVYR2W94zlIZ9U/jOW93xS+c9Y3vNJFT9jYVxW+MaYAuPc3Nycmj537lxr3MCBA9WhQ4ciLTswMFDe3t5FmsfVyssLxJHynq8iqAjrkIzFV97zSeU/Y3nPJ1WsjBkZGfk2dB1x2S59f39/HT9+3BpOTEyUn5+fw+lJSUny8/PTmTNn9O6771rjjTHy8HDZ5xIAAGzBZYXfsmVLbdu2TcnJyUpLS9PatWsVFBRkTa9Zs6a8vb2tXRIxMTEKCgqSj4+PFi5cqN27d0uS/vOf/yg4ONhVMQEAsAWXbTr7+/trxIgR6tevn7KystSzZ081aNBAgwYN0tChQ1W/fn29/PLLGj9+vM6ePat//vOf6tevn9zd3TVr1ixNmjRJ6enpuvXWWzV9+nRXxQQAwBZcuq88PDxc4eHh+cYtWLDAul2vXj19+OGHBeZr2rSpPv74Y1dGAwDAVjjTHgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4eOSMjKzyjpCucgAABUZp7DDJXl7eapN1MgyzbBx8YwyXT4AVHRs4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA2QOEDAGADFD4AADZA4QMAYAMUPgAANkDhAwBgAxQ+AAA24NLCj42NVVhYmIKDg7VkyZIC03/88Uf16NFDISEhevrpp5WdnS1Jio+PV58+fdSpUyc98sgjOnv2rCtjAgBwxXNZ4SckJGjmzJlaunSpVq1apWXLlumXX37Jd5/Ro0drwoQJWrNmjYwxWr58uSRp8uTJ6t27t1avXq3AwEDNmzfPVTEBALAFD1c98NatW9WiRQtVq1ZNkhQSEqLVq1fr8ccflyT9/vvvSk9PV6NGjSRJ3bt312uvvaZ77rlHO3bs0Ny5c63xffv21ejRoy+5TGOMJCkzMzPf+BrVq5XY/+tyZGRkXPI+Na69phSSFM6ZfNWvuaoUkjjmVMaqlUshSeGcySdJ1Xy8XJzEMWcyVqviXgpJHHMm4zXeZXck0pl8VT3dSiGJY85krOKyv/yX5kw+70qmFJI45kxGT7fcUkji2PkZ8zovrwMdcTOXusdleuONN5SamqoRI0ZIklasWKE9e/bo2WeflSTt2rVL06dP1/vvvy9JOnLkiAYPHqzFixerZ8+e+t///idJys7OVqNGjbRv375LLvPMmTP66aefXPHfAQCgXAsICNDVV1/tcLrLPucV9jnCzc3tktMvNd/FXHXVVQoICJCnp6fT8wAAUJEZY5SVlaWrrrr4nliXFb6/v7/i4uKs4cTERPn5+eWbfvz4cWs4KSlJfn5+qlGjhlJSUpSTkyN3d3drvDMqVap00U83AABciSpXvvQhTZcdDGvZsqW2bdum5ORkpaWlae3atQoKCrKm16xZU97e3tq5c6ckKSYmRkFBQfL09FTTpk31+eef5xsPAAAun8uO4Uvnfpb3xhtvKCsrSz179tSgQYM0aNAgDR06VPXr19f+/fs1fvx4nT17Vv/85z/1wgsvyMvLS7///ruio6N14sQJ3XDDDZoxY4auvfZaV8UEAOCK59LCBwAA5QNn2gMAwAYofAAAbIDCBwDABih8AABswBaFv337dt1xxx3q379/gWlbt25VeHi4OnbsqJkzZ170ccaOHauVK1daw4Vd5CcuLk5hYWFq167dZWfLysrSAw88oO3bt1vjHF1o6Hw7d+5Ujx49FBkZqQceeEC///67JOmvv/7S4MGDFRoaqj59+igpKUm//fabIiMjVbdu3SJnXLZsmbp06aLw8HCNGzfOOq2jMxnj4uLUvXt3hYeHa8iQITp9+nSxM16Yb+nSpercubPCwsL04osvWidzciZfnh9++EGBgYHWcGZmpkaPHq3Q0FB169ZNBw8eVHp6uiIjIxUYGKhjx44VKWOeJUuWKCoqyhp25sJRO3bsUPPmzRUZGanIyEiNGzeu2OuwsIzjxo1Tx44dreWsW7dOknPvmV9//VVRUVGKiIjQQw89ZD3PxXnPXJhv165duvfee9W5c2eNHDnS6dfhiRMnrP9TZGSk2rVrpzvuuKPE1+HGjRvzLadFixZ6+OGHncooSceOHVOfPn0UGRmpqKgo6/1cnNfihetw8+bNioiIUJcuXTRmzBhrHTrzOjx8+LD69u2r8PBwRUVF6dChQ5LOnQTmxRdfVKdOnRQWFmb99DoqKkp33HFHvr9rF/vbvHLlSoWFhSk8PFxTp069rIurffjhh4qOjraGC1t3jjJv375dt99+u26//XYrc1H+NhcnZ54tW7bogQcesIaLsm4LZWzg66+/Nn379i0wPi0tzbRp08b89ttvJisrywwYMMBs2LChwP3+/PNP8/DDD5sGDRqYjz76yBo/ePBg8+mnnxpjjJkzZ46ZPn26McaYo0ePmrZt215WtoMHD5r77rvP1K9f33z99dfW+M6dO5tdu3YZY4wZN26cWbJkSYHHatu2rfnxxx+NMcasWLHCDBkyxBhjzOTJk80bb7xhjDHm448/NsOGDbPmCQgIKFLGX3/91QQHB5szZ86Y3NxcM2bMGPPOO+84nbFDhw7m559/NsYY89JLL5lXXnml2BnPz/fbb7+Z4OBgc/bsWZOdnW3uu+8+s2nTJqfzGWNMamqque+++/Itd+HChWbChAnGGGO++eYb07NnT2ta27ZtzdGjR53OmOfnn382rVu3zjfe0WvqfG+99ZZ5/fXXC4wvyefZGGO6dOliEhIS8t3HmfdMbm6u6dixo9m4caMx5tzznPf/KM575vx8Z86cMf/+97+t1/uIESOs59PZ59kYY3Jyckzfvn3NJ598Yowp+XWYJzEx0bRv394cOnTI6YyjRo2yxr/33nvmySefNMYU77V4Yb6goCDzyy+/GGOMeeKJJ8zy5cuNMc69Dnv16mX9Pdy1a5eJiIgwxhjzxRdfmEGDBpmcnBzz66+/mg4dOpisrCxjjDF9+/bN93fN0fo6ePCgad26tfX6mzhxonn77bedzpaenm5eeukl06hRIzN27FhrvKN1V1jmLVu2mL59+1qZi/q3uTg5c3JyzFtvvWWaNWuWb/0UZd0WxhZb+I7s2bNHt9xyi2rVqiUPDw+Fh4dr9erVBe4XGxur9u3bKzQ01BqXlZWlHTt2KCQkRNK5i/wUNm9Rffjhhxo4cKAaNmxojSvsQkMXLiszM1PDhg1TvXr1JEl169bVH3/8IUnasGGDwsPDJUldunTR//73P2VlZV1WPi8vL02aNElVq1aVm5ubAgICFB8f71RGSfr8889Vp04dZWVlKSEhQddcc02JZqxVq5Y+++wz+fj46K+//lJKSoquueYap/NJ0rRp0wpscWzYsEERERGSpDvvvFMnT55UfHx8kfPlyczM1DPPPKNhw4ZZ45x9Te3du1dbtmxR165dNWTIEJc8z6mpqYqPj9eECRMUHh6u1157Tbm5uU69Z77//nv5+PhYJ8waMmSI+vTpU6LvmS1btqhRo0bW6338+PEKDg4u0vMsSR999JGqVKlirbeSXIfnmz59unr16qVbb73V6Yy5ublKSUmRJKWlpVlnUivJ12JOTo51ZtOMjAx5e3s7/Tz9+OOP6tSpkySpUaNGSkxM1NGjR7Vx40aFhYWpUqVKuu2223TjjTdq165dRcp14MABNWrUyDrLatu2bbV+/Xqns+3YsUO5ubkFLrrmaN0Vlvnnn3/ON29R/jYXN+fBgwd18OBB69ozeYq7bm1d+ImJifL19bWG/fz8lJCQUOB+AwcO1D333JNv3MmTJ1W1alV5eJw7O7Gvr2+h8xbVmDFj1KFDh4vmLGxZXl5eioyMlHTuD8WcOXOsxzl/fg8PD1WtWlXJycmXla9mzZpq2bKlJCk5OVlLlixR+/btncooSZ6enjpw4IDatGmj7du3q3PnziWe0dPTU8uXL1eHDh3k6+urevXqOZ3vyy+/VHp6uvWHLE9h8//555+XlU+SXnnlFfXo0UM33XSTNc7Z19TVV1+tfv36KSYmRm3atLEuUFWS6/DEiRNq0aKFnn/+eS1fvlxxcXH68MMPnXrP/Pbbb7r++us1duxYhYeHa+LEifLx8SnR98yRI0fk4+Ojxx57TOHh4Zo9e7auueYap59n6VzZzZ8/X08++aQ1riTXYZ7Dhw/rm2++Ub9+/Qos42IZhw0bpnfffVetW7fW22+/rUGDBjmc/3Jfi5MmTVJUVJRat26tkydPqlOnTk4/T//85z/12WefSZK2bdumU6dOKSkpqcBp1C8nX7169bR792798ccfysnJ0erVq3X8+HGns7Vq1UpjxowpcLpZR+uusMwXPu9F+dtc3Jz/+Mc/9NxzzxU44Vxx162tC98U40I9xZm3qIqyrMzMTI0aNUrZ2dnW8cLCVKpUvKc+ISFBDzzwgHr06KHmzZsXKWPdunW1detWPfroo1ZZlXTGe++9V9u3b9f111+vOXPmOJUvKSlJ8+fP14QJE5xaxuXm27Jli/744w/16NEj33hn1+GUKVOsPzz333+/fvnlF505c6ZEM9aqVUtz587VddddpypVqigqKkobN250KmN2dra++eYb9e3bV7GxsapVq5amTZtWou+ZnJwcbd68WdHR0YqJiVFaWprefPPNIi1j06ZNuu222y55bL6475Vly5apd+/e8vI6d2lkZzOOHTtWU6ZM0aZNmzR58mQ9/vjjDi9/ejkZk5KS9PLLL+vTTz/V5s2b1bBhQ73wwgtO55s2bZrWrl2riIgIbdmyRfXq1ZOnp2eh8xc132233aYnn3xSjzzyiPr06aO6des6fOzi/t2tVKnSZWd2lMdV/VDcdWvrwr/wAj4Xfnq6mPMv8iOpSBf5KW5OR8s6e/asBg4cqOzsbM2fP1+enp6Szm2F5c2fnZ2tlJQUVatW7bLzHDx4UPfff7+6deumxx57zOmMGRkZWr9+vTUcERGhAwcOlGjGP/74w/oii4eHhzp37qwDBw44lW/Dhg06deqU9UUpSYqMjFRKSor8/PyUlJR00fmd9emnn+rnn39WZGSkxo8fr3379mn48OFOvaZyc3M1f/586z55PDw8SvR5PnDggNasWWMNG2Pk4eHh1HvG19dXt9xyi+rXry/p3K7xPXv2lOh75vrrr1fDhg1Vq1Ytubu7KzQ0VHv27HH6vSJJ69evV1hYWL5xJf1ekc7tNTp/Oc5kTE5O1q+//mp9sAsJCVFSUpJOnjxZYq/FuLg4BQQE6Oabb1alSpV077336ptvvnH6ecrOztbcuXP1ySefaOTIkfr999910003yd/fv9j5MjIy1KBBA8XExOiDDz7QjTfeqFq1ahX7NeRo3RWW2Znn3ZmLwF1Ozostrzjr1taF37BhQx06dEhHjhxRTk6OPv30U6cv1FOaF/lxdKGhC40ePVq33HKLXn31VWtrQpLatGmjmJgYSeeOoTdt2tT6MFBUKSkpeuihhzRs2DANGDCgSBk9PDw0efJk7du3T5L0xRdfqHHjxiWa8cyZMxo9erT++usvGWO0Zs0aNWnSxKl899xzj9avX69Vq1Zp1apVkqRVq1apatWqatOmjTUuLi5O3t7euvHGG4ucT5JeeOEFffHFF1q1apWmTp2qwMBAzZo1y6nXVKVKlbRu3TqrjGNiYtSwYUNVqVKlRJ9nY4yef/55nT59WllZWVq2bJmCg4Odes/ccccdSk5O1v79+yVJX331lf71r3+V6HumVatW+v77763vL/z3v//Vv/71L6ffK5L03XffqWnTpvnGleQ6lM4Vd3p6umrVqmWNcyZj9erV5e3tbV1xdOfOnbrqqqtUo0aNEnstBgQEaM+ePVZhffnll6pfv77Tz9PMmTP15ZdfSpJWrFihwMBAVa9eXUFBQYqNjVVOTo6OHDmiw4cPWx/+nJWamqoHHnhAKSkpyszM1OLFixUWFlbs15CjdVdY5r///e+XfLzSvghccdetyy6PWxF4e3tr2rRpeuKJJ5SRkaE2bdoUOHZ7MRMnTlR0dLTmz59vXeTHVV5++eV8FxrKOx6Y54cfftCXX36pOnXqqGvXrpLOfZpdsGCBhg0bpujoaHXu3FlXX321Xn755cvO8eGHH+r48eN6++239fbbb0uS2rVrp2HDhl0yo7u7u2bOnKlnnnlGOTk58vf313PPPSdJJZYxICBAgwcPVq9eveTu7q6mTZvqwQcflHTpdXgxUVFReuaZZ9S5c2d5eXlp+vTpl5XvUpx5Tb344ouaMGGC5s6dqxo1alhZSvJ5rlevngYPHqz7779f2dnZ6tixo7p06SJJl3zPVK5cWXPnztX48eOVlpamv/3tb1bGknrP3HDDDZoyZYqGDBmijIwM3X777Ro7dqwk55/no0eP6m9/+1u+cSW5DqVzP627cBnOZHRzc9OcOXP07LPPKj09XVdddZVmz54tqeRei7Vr19awYcPUr18/ubu765ZbbtGUKVMkOfc8jRo1SmPHjtWcOXPk7++vF154QZLUqVMn7dmzx/py3HPPPefUpVvPV716dT3++OO67777lJ2dbf0M2Nlsjjhad4VldvaDnqPn0hX9UOx1e9Hv8F8hHP30w1WK87O80lacnxqVlqL8LK8sXO7P8kpTeX+ei/qzvLJQ3tehMUX/WV5pc/ZneeVBXjZnfu5WHvCzvPPs27ev0JM7lLS4uDgNHjy4SPOUVrbz5Z1MxFnlPWNZ5Ms72UliYqJT9y/v61Aqm4xFec+wDgtXlNdiWeSTzm1d5x3OKw95nBEXF2cdVinPHK3bC3F5XAAAbMA2W/gAANgZhQ8AgA1Q+AAA2ICtf5YHXCmysrLUtm1b1a1bV2+99Va+aStWrNDy5cuVkpKirKws1apVS8OHD7fOCR4dHa0tW7aoRo0a+ebr0aNHoT9pS0tL0+uvv67169fLzc1NqampatKkiUaPHm2dBKRdu3by9PRU5cqV5ebmpszMTFWqVEljxoyxfo+cnZ2tBQsWKDY21joLWbNmzTRs2DDrpCdRUVHWFcfyJCcn66677tKBAwd07NgxBQcHKyAgwJpujFG/fv3Us2fP4q5W4IpC4QNXgHXr1qlu3br6/vvvdfDgQdWuXVuSNGPGDO3YsUOzZs1SzZo1JZ077/nDDz+slStXWids6d+/vx566KFLLicnJ0cDBw5UnTp1tGLFCvn4+Cg3N1cLFy7UoEGDFBMTY5X3yy+/nO+kIKtXr9ZTTz2lzZs3S5JGjhwpT09PLV26VNWqVVNWVpbeffdd3Xffffroo49UtWpVp/7vlStXtk6mIp077XOXLl0UGBhoXVwHALv0gSvC+++/rw4dOigsLEyLFi2SJB0/flyLFi3Sq6++apW9JN11112Kjo5WWlpakZezfv16nTlzxrogjnTu7H+DBw9W586dHV7z2xijY8eOWRcD2bVrl7777ju9+OKL1ta8p6enBg0apL///e/64IMPipwtj7+/v2655RYdPnz4sh8DuBKxhQ9UcL/88ou+++47zZ49W//6178UFRWlESNG6LvvvlPt2rULPdd23tkY87z77rv65JNP8o2bPn16gQvLxMXFqWXLloVesOPC39KPGjVKlStX1qlTp2SMUatWrfT6669LOlf4jRo1sq4mdr6WLVtq69atGjhwoHMr4AK7du3Sb7/9lu8ypgAofKDCe//993X33XerWrVqqlatmm666SYtW7bM2q2fJyUlRX369JF07lzloaGhGjlypCTnd+kbY/Jd9evrr7+2Tql6+vRpTZw4UW3btpX0f7v0jx49qgcffFC1a9fOd0757OzsQpeRmZlpLaOwK4wZY/J94Mg76Yx07pBD9erV9dJLL+mGG2645P8HsBMKH6jAUlNTFRMTI29vb7Vr107SuWJfsmSJPvjgAx06dEgnT55U9erVVbVqVetY9+zZs3Xy5MkiL69x48b5vhTYokUL6zGjoqKUkZFRYJ5atWpp+vTpioqKUtOmTdWwYUM1btxYb7/9ttLS0lSlSpV899++fbvuvPNOSefOqX7q1Kl8048fP57vSmYXHsMHUDiO4QMVWGxsrKpXr65Nmzbpq6++0ldffaX169crNTVVO3fuVL9+/TRs2DDFx8db88THx+vbb7+9rGuod+zYUT4+PnruuefyHa/fvXu3jh49Knd390Lna9y4sbp166bJkycrNzdXjRo1UrNmzRQdHa3Tp09LOrd1Pn/+fB0+fFi9evWSdO7qYCtXrtSZM2ckndsrsGTJErVp06bI2QG7YwsfqMDef/99Pfjgg/mK9pprrlFUVJQWLVqkjz76SJ988olGjRql1NRUZWdny8vLS2FhYdbufanwY/gNGza0rp6Wx8PDQwsXLtTChQvVt29fGWOUnp6uG264QWPGjLGu316YkSNHKjQ0VMuWLdP999+vl156Se+884769u0r6dyu/ObNm+uDDz7Q1VdfLUnq3r27EhMT1bt3b1WqVEnp6elq3ry5xo8fX+x1B9gN59IHAMAG2KUPAIANUPgAANgAhQ8AgA1Q+AAA2ACFDwCADVD4AADYAIUPAIANUPgAANjA/wPGDQeCyAvC8wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x1152 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p1 = plt.figure(figsize=(8,16),dpi=72)\n",
    "ax_death_by_age = p1.add_subplot(2,1,1)\n",
    "ax_death_by_age = sns.barplot(x='AGE GROUP', y='DEATH RATE', data=death_rate_by_age_group, palette='Blues_d', orient='H')\n",
    "ax_death_by_age.set_title('Death Rate by Age Group')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Type of cancer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>Code</th>\n",
       "      <th>Description</th>\n",
       "      <th>Amount</th>\n",
       "      <th>Death Rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td></td>\n",
       "      <td>None</td>\n",
       "      <td>461</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>C00</td>\n",
       "      <td>Malignant neoplasm of lip</td>\n",
       "      <td>662</td>\n",
       "      <td>0.120846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>C01</td>\n",
       "      <td>Malignant neoplasm of base of tongue</td>\n",
       "      <td>2383</td>\n",
       "      <td>0.234578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>C02</td>\n",
       "      <td>Malignant neoplasm of other and unspecified pa...</td>\n",
       "      <td>3655</td>\n",
       "      <td>0.268673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>C03</td>\n",
       "      <td>Malignant neoplasm of gum</td>\n",
       "      <td>1084</td>\n",
       "      <td>0.298893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>C04</td>\n",
       "      <td>Malignant neoplasm of floor of mouth</td>\n",
       "      <td>1372</td>\n",
       "      <td>0.285714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>C05</td>\n",
       "      <td>Malignant neoplasm of palate</td>\n",
       "      <td>1055</td>\n",
       "      <td>0.199052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>C06</td>\n",
       "      <td>Malignant neoplasm of other and unspecified pa...</td>\n",
       "      <td>1591</td>\n",
       "      <td>0.318039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>C07</td>\n",
       "      <td>Malignant neoplasm of parotid gland</td>\n",
       "      <td>1287</td>\n",
       "      <td>0.164724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>C08</td>\n",
       "      <td>Malignant neoplasm of other and unspecified ma...</td>\n",
       "      <td>309</td>\n",
       "      <td>0.216828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>C09</td>\n",
       "      <td>Malignant neoplasm of tonsil</td>\n",
       "      <td>4138</td>\n",
       "      <td>0.166022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>C10</td>\n",
       "      <td>Malignant neoplasm of oropharynx</td>\n",
       "      <td>702</td>\n",
       "      <td>0.373219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>C11</td>\n",
       "      <td>Malignant neoplasm of nasopharynx</td>\n",
       "      <td>582</td>\n",
       "      <td>0.295533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>C12</td>\n",
       "      <td>Malignant neoplasm of pyriform sinus</td>\n",
       "      <td>826</td>\n",
       "      <td>0.412833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>C13</td>\n",
       "      <td>Malignant neoplasm of hypopharynx</td>\n",
       "      <td>652</td>\n",
       "      <td>0.420245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>C14</td>\n",
       "      <td>Malignant neoplasm of other and ill-defined si...</td>\n",
       "      <td>263</td>\n",
       "      <td>0.349810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>C15</td>\n",
       "      <td>Malignant neoplasm of oesophagus</td>\n",
       "      <td>20996</td>\n",
       "      <td>0.617499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>C16</td>\n",
       "      <td>Malignant neoplasm of stomach</td>\n",
       "      <td>15298</td>\n",
       "      <td>0.592953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>C17</td>\n",
       "      <td>Malignant neoplasm of small intestine</td>\n",
       "      <td>3706</td>\n",
       "      <td>0.337561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>C18</td>\n",
       "      <td>Malignant neoplasm of colon</td>\n",
       "      <td>65825</td>\n",
       "      <td>0.317357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>C19</td>\n",
       "      <td>Malignant neoplasm of rectosigmoid junction</td>\n",
       "      <td>5317</td>\n",
       "      <td>0.300733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>C20</td>\n",
       "      <td>Malignant neoplasm of rectum</td>\n",
       "      <td>27163</td>\n",
       "      <td>0.258845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>C21</td>\n",
       "      <td>Malignant neoplasm of anus and anal canal</td>\n",
       "      <td>3300</td>\n",
       "      <td>0.228485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>C22</td>\n",
       "      <td>Malignant neoplasm of liver and intrahepatic b...</td>\n",
       "      <td>12532</td>\n",
       "      <td>0.679301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>C23</td>\n",
       "      <td>Malignant neoplasm of gallbladder</td>\n",
       "      <td>2120</td>\n",
       "      <td>0.713208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>C24</td>\n",
       "      <td>Malignant neoplasm of other and unspecified pa...</td>\n",
       "      <td>2433</td>\n",
       "      <td>0.600493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>C25</td>\n",
       "      <td>Malignant neoplasm of pancreas</td>\n",
       "      <td>21344</td>\n",
       "      <td>0.761666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>C26</td>\n",
       "      <td>Malignant neoplasm of other and ill-defined di...</td>\n",
       "      <td>756</td>\n",
       "      <td>0.767196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>C30</td>\n",
       "      <td>Malignant neoplasm of nasal cavity and middle ear</td>\n",
       "      <td>801</td>\n",
       "      <td>0.283396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>C31</td>\n",
       "      <td>Malignant neoplasm of accessory sinuses</td>\n",
       "      <td>413</td>\n",
       "      <td>0.411622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>C95</td>\n",
       "      <td>Leukaemia of unspecified cell type</td>\n",
       "      <td>402</td>\n",
       "      <td>0.373134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>C96</td>\n",
       "      <td>Other and unspecified malignant neoplasms of l...</td>\n",
       "      <td>184</td>\n",
       "      <td>0.336957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>D00</td>\n",
       "      <td>Carcinoma in situ of oral cavity, oesophagus a...</td>\n",
       "      <td>2553</td>\n",
       "      <td>0.137094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>D01</td>\n",
       "      <td>Carcinoma in situ of other and unspecified dig...</td>\n",
       "      <td>9229</td>\n",
       "      <td>0.083866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>D02</td>\n",
       "      <td>Carcinoma in situ of middle ear and respirator...</td>\n",
       "      <td>1051</td>\n",
       "      <td>0.111323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>D03</td>\n",
       "      <td>Melanoma in situ</td>\n",
       "      <td>17123</td>\n",
       "      <td>0.029142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>D04</td>\n",
       "      <td>Carcinoma in situ of skin</td>\n",
       "      <td>647</td>\n",
       "      <td>0.123648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>D05</td>\n",
       "      <td>Carcinoma in situ of breast</td>\n",
       "      <td>19777</td>\n",
       "      <td>0.013905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>D06</td>\n",
       "      <td>Carcinoma in situ of cervix uteri</td>\n",
       "      <td>76678</td>\n",
       "      <td>0.001500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>D07</td>\n",
       "      <td>Carcinoma in situ of other and unspecified gen...</td>\n",
       "      <td>6931</td>\n",
       "      <td>0.025393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>D09</td>\n",
       "      <td>Carcinoma in situ of other and unspecified sites</td>\n",
       "      <td>25193</td>\n",
       "      <td>0.084230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>D13</td>\n",
       "      <td>Benign neoplasm of other and ill-defined parts...</td>\n",
       "      <td>13</td>\n",
       "      <td>0.307692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>D15</td>\n",
       "      <td>Benign neoplasm of other and unspecified intra...</td>\n",
       "      <td>45</td>\n",
       "      <td>0.244444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>D27</td>\n",
       "      <td>Benign neoplasm of ovary</td>\n",
       "      <td>10</td>\n",
       "      <td>0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>D29</td>\n",
       "      <td>Benign neoplasm of male genital organs</td>\n",
       "      <td>75</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>D32</td>\n",
       "      <td>Benign neoplasm of meninges</td>\n",
       "      <td>6087</td>\n",
       "      <td>0.176113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>D33</td>\n",
       "      <td>Benign neoplasm of brain and other parts of ce...</td>\n",
       "      <td>2185</td>\n",
       "      <td>0.042563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>D35</td>\n",
       "      <td>Benign neoplasm of other and unspecified endoc...</td>\n",
       "      <td>2407</td>\n",
       "      <td>0.051101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>D37</td>\n",
       "      <td>Neoplasm of uncertain or unknown behaviour of ...</td>\n",
       "      <td>3205</td>\n",
       "      <td>0.138846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>D38</td>\n",
       "      <td>Neoplasm of uncertain or unknown behaviour of ...</td>\n",
       "      <td>491</td>\n",
       "      <td>0.250509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>D39</td>\n",
       "      <td>Neoplasm of uncertain or unknown behaviour of ...</td>\n",
       "      <td>1044</td>\n",
       "      <td>0.193487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>D40</td>\n",
       "      <td>Neoplasm of uncertain or unknown behaviour of ...</td>\n",
       "      <td>196</td>\n",
       "      <td>0.255102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>D41</td>\n",
       "      <td>Neoplasm of uncertain or unknown behaviour of ...</td>\n",
       "      <td>6453</td>\n",
       "      <td>0.103208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>D42</td>\n",
       "      <td>Neoplasm of uncertain or unknown behaviour of ...</td>\n",
       "      <td>735</td>\n",
       "      <td>0.087075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>D43</td>\n",
       "      <td>Neoplasm of uncertain or unknown behaviour of ...</td>\n",
       "      <td>1481</td>\n",
       "      <td>0.295071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>D44</td>\n",
       "      <td>Neoplasm of uncertain or unknown behaviour of ...</td>\n",
       "      <td>678</td>\n",
       "      <td>0.092920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>D45</td>\n",
       "      <td>Polycythaemia vera</td>\n",
       "      <td>1379</td>\n",
       "      <td>0.171864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>D46</td>\n",
       "      <td>Myelodysplastic syndromes</td>\n",
       "      <td>6869</td>\n",
       "      <td>0.480565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>D47</td>\n",
       "      <td>Other neoplasms of uncertain or unknown behavi...</td>\n",
       "      <td>5922</td>\n",
       "      <td>0.189801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>D48</td>\n",
       "      <td>Neoplasm of uncertain or unknown behaviour of ...</td>\n",
       "      <td>3039</td>\n",
       "      <td>0.070418</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>116 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Code                                        Description  Amount  Death Rate\n",
       "91                                                    None     461         NaN\n",
       "82  C00                          Malignant neoplasm of lip     662    0.120846\n",
       "52  C01               Malignant neoplasm of base of tongue    2383    0.234578\n",
       "44  C02  Malignant neoplasm of other and unspecified pa...    3655    0.268673\n",
       "68  C03                          Malignant neoplasm of gum    1084    0.298893\n",
       "..  ...                                                ...     ...         ...\n",
       "81  D44  Neoplasm of uncertain or unknown behaviour of ...     678    0.092920\n",
       "65  D45                                 Polycythaemia vera    1379    0.171864\n",
       "30  D46                          Myelodysplastic syndromes    6869    0.480565\n",
       "35  D47  Other neoplasms of uncertain or unknown behavi...    5922    0.189801\n",
       "48  D48  Neoplasm of uncertain or unknown behaviour of ...    3039    0.070418\n",
       "\n",
       "[116 rows x 4 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def match_neoplasms_3CHAR(site_code_3CHAR):\n",
    "    if site_code_3CHAR != \"\":\n",
    "        return icd_codes_3char.loc[icd_codes_3char['Code'] == [re.search(site_code_3CHAR, icd_code).string for icd_code in icd_codes_3char['Code'].values if re.search(site_code_3CHAR, icd_code) != None][0], 'Description'].values[0]\n",
    "    \n",
    "def death_rate_by_site_3char(site_code_3char):\n",
    "    if site_code_3char != \"\":\n",
    "        g = merged_av_data[merged_av_data['SITE_ICD10_O2_3CHAR'] == site_code_3char].groupby('NEWVITALSTATUS').count()\n",
    "        death_rate = g.iloc[g.index.get_level_values('NEWVITALSTATUS') == 'D'].sum().max() / g.iloc[:, :].sum().max()\n",
    "        return death_rate\n",
    "\n",
    "types_of_cancer_3char = pd.DataFrame({\n",
    "    'Code': merged_av_data['SITE_ICD10_O2_3CHAR'].value_counts().index,\n",
    "    'Description': [match_neoplasms_3CHAR(x) for x in list(merged_av_data['SITE_ICD10_O2_3CHAR'].value_counts().index.to_numpy())],\n",
    "    'Amount': merged_av_data['SITE_ICD10_O2_3CHAR'].value_counts().values,\n",
    "    'Death Rate': [death_rate_by_site_3char(x) for x in list(merged_av_data['SITE_ICD10_O2_3CHAR'].value_counts().index.to_numpy())]\n",
    "})\n",
    "\n",
    "types_of_cancer_3char.sort_values('Code')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "    \n",
    "# def calculate_death_rate(group):\n",
    "#     g = merged_av_data.loc[(merged_av_data['AGE'] > group[0]) & (merged_av_data['AGE'] <= group[1]), :].groupby('NEWVITALSTATUS').count()\n",
    "#     death_rate = g.iloc[g.index.get_level_values('NEWVITALSTATUS') == 'D'].sum().max() / merged_av_data.loc[(merged_av_data['AGE'] > group[0]) & (merged_av_data['AGE'] <= group[1]), :].shape[0]\n",
    "#     return death_rate\n",
    "\n",
    "# g.iloc[g.index.get_level_values('NEWVITALSTATUS') == 'D'].sum().max()\n",
    "# g['NEWVITALSTATUS']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TNM Staging"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PATIENTID  TUMOURID \n",
       "10000001   10000001       \n",
       "10000002   10000002       \n",
       "10000003   10000003       \n",
       "10000004   10000004       \n",
       "10000005   10000005       \n",
       "                        ..\n",
       "220039666  220051512     1\n",
       "220044010  220051679      \n",
       "220045545  220051740      \n",
       "220046812  220051825      \n",
       "220048063  220051877    1a\n",
       "Name: T_BEST, Length: 1402749, dtype: object"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# def convert_staging(stages):\n",
    "#     for stage in stages:\n",
    "#     filter(str.isdigit, )\n",
    "\n",
    "# merged_av_data['T_BEST'].value_counts()\n",
    "merged_av_data['T_BEST']\n",
    "\n",
    "\n",
    "\n",
    "# # merged_av_data[['T_BEST', 'N_BEST', 'M_BEST']] = merged_av_data[['T_BEST', 'N_BEST', 'M_BEST']].astype(str)\n",
    "# # merged_av_data['M_BEST'].value_counts().index\n",
    "# # merged_av_data[(merged_av_data['M_BEST'] != '0' and merged_av_data['M_BEST'] != str(0.0))]\n",
    "# # type(merged_av_data.iloc[merged_av_data.index.get_level_values('PATIENTID') == 10000018]['M_BEST'][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>TUMOURID</th>\n",
       "      <th>PATIENTID</th>\n",
       "      <th>DIAGNOSISDATEBEST</th>\n",
       "      <th>SITE_ICD10_O2</th>\n",
       "      <th>SITE_ICD10_O2_3CHAR</th>\n",
       "      <th>MORPH_ICD10_O2</th>\n",
       "      <th>BEHAVIOUR_ICD10_O2</th>\n",
       "      <th>T_BEST</th>\n",
       "      <th>N_BEST</th>\n",
       "      <th>M_BEST</th>\n",
       "      <th>...</th>\n",
       "      <th>PERFORMANCESTATUS</th>\n",
       "      <th>CNS</th>\n",
       "      <th>ACE27</th>\n",
       "      <th>GLEASON_PRIMARY</th>\n",
       "      <th>GLEASON_SECONDARY</th>\n",
       "      <th>GLEASON_TERTIARY</th>\n",
       "      <th>GLEASON_COMBINED</th>\n",
       "      <th>DATE_FIRST_SURGERY</th>\n",
       "      <th>LATERALITY</th>\n",
       "      <th>QUINTILE_2015</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>816073</th>\n",
       "      <td>60035351</td>\n",
       "      <td>60035351</td>\n",
       "      <td>2013-07-22</td>\n",
       "      <td>C183</td>\n",
       "      <td>C18</td>\n",
       "      <td>8140</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2013-07-22</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>845745</th>\n",
       "      <td>60066711</td>\n",
       "      <td>60035351</td>\n",
       "      <td>2013-07-22</td>\n",
       "      <td>C20</td>\n",
       "      <td>C45</td>\n",
       "      <td>8070</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>Y2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2013-07-22</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>847728</th>\n",
       "      <td>60068814</td>\n",
       "      <td>60035351</td>\n",
       "      <td>2013-07-22</td>\n",
       "      <td>C187</td>\n",
       "      <td>C18</td>\n",
       "      <td>8140</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>847878</th>\n",
       "      <td>60069008</td>\n",
       "      <td>60035351</td>\n",
       "      <td>2013-07-22</td>\n",
       "      <td>C19</td>\n",
       "      <td>C18</td>\n",
       "      <td>8210</td>\n",
       "      <td>3</td>\n",
       "      <td>3a</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2013-07-22</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>847891</th>\n",
       "      <td>60069026</td>\n",
       "      <td>60035351</td>\n",
       "      <td>2013-08-20</td>\n",
       "      <td>D010</td>\n",
       "      <td>C18</td>\n",
       "      <td>8140</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2013-08-20</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>847892</th>\n",
       "      <td>60069028</td>\n",
       "      <td>60035351</td>\n",
       "      <td>2014-03-09</td>\n",
       "      <td>C509</td>\n",
       "      <td>C64</td>\n",
       "      <td>8130</td>\n",
       "      <td>3</td>\n",
       "      <td>1b</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2014-05-09</td>\n",
       "      <td>L</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        TUMOURID  PATIENTID DIAGNOSISDATEBEST SITE_ICD10_O2  \\\n",
       "816073  60035351   60035351        2013-07-22          C183   \n",
       "845745  60066711   60035351        2013-07-22           C20   \n",
       "847728  60068814   60035351        2013-07-22          C187   \n",
       "847878  60069008   60035351        2013-07-22           C19   \n",
       "847891  60069026   60035351        2013-08-20          D010   \n",
       "847892  60069028   60035351        2014-03-09          C509   \n",
       "\n",
       "       SITE_ICD10_O2_3CHAR MORPH_ICD10_O2 BEHAVIOUR_ICD10_O2 T_BEST N_BEST  \\\n",
       "816073                 C18           8140                  3    NaN    NaN   \n",
       "845745                 C45           8070                  3    NaN    NaN   \n",
       "847728                 C18           8140                  3      1      2   \n",
       "847878                 C18           8210                  3     3a      0   \n",
       "847891                 C18           8140                  3      2      0   \n",
       "847892                 C64           8130                  3     1b      0   \n",
       "\n",
       "       M_BEST  ... PERFORMANCESTATUS  CNS ACE27  GLEASON_PRIMARY  \\\n",
       "816073      1  ...               NaN  NaN   NaN              NaN   \n",
       "845745    NaN  ...                 0   Y2     0              NaN   \n",
       "847728      0  ...               NaN  NaN   NaN              NaN   \n",
       "847878      0  ...               NaN   99   NaN              NaN   \n",
       "847891      0  ...               NaN  NaN   NaN              NaN   \n",
       "847892      0  ...                 3  NaN   NaN              NaN   \n",
       "\n",
       "        GLEASON_SECONDARY GLEASON_TERTIARY  GLEASON_COMBINED  \\\n",
       "816073                NaN              NaN               NaN   \n",
       "845745                NaN              NaN               NaN   \n",
       "847728                NaN              NaN               NaN   \n",
       "847878                NaN              NaN               NaN   \n",
       "847891                NaN              NaN               NaN   \n",
       "847892                NaN              NaN               NaN   \n",
       "\n",
       "       DATE_FIRST_SURGERY LATERALITY  QUINTILE_2015  \n",
       "816073         2013-07-22          8              4  \n",
       "845745         2013-07-22          8              4  \n",
       "847728                NaN          8              4  \n",
       "847878         2013-07-22          8              4  \n",
       "847891         2013-08-20          8              4  \n",
       "847892         2014-05-09          L              4  \n",
       "\n",
       "[6 rows x 34 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# tumour[tumour['PATIENTID' == 210004664]]\n",
    "tumour['PATIENTID'].value_counts()\n",
    "tumour[tumour['PATIENTID'] == 60035351]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# tumour_reindex.iloc[tumour_reindex.index.get_level_values('PATIENTID') == 60035351]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# tumour.groupby('SITE_ICD10_O2').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1322035, 12)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "patient.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1402817, 34)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tumour.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1402749, 43)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_av_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1402749"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(merged_av_data.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "\"None of ['PATIENTID', 'TUMOURID'] are in the columns\"",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-41-1be2d915c584>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmerged_av_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmerged_av_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'PATIENTID'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'TUMOURID'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36mset_index\u001b[0;34m(self, keys, drop, append, inplace, verify_integrity)\u001b[0m\n\u001b[1;32m   4389\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4390\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mmissing\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4391\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"None of {} are in the columns\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmissing\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4392\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4393\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: \"None of ['PATIENTID', 'TUMOURID'] are in the columns\""
     ]
    }
   ],
   "source": [
    "# merged_av_data = merged_av_data.set_index(['PATIENTID', 'TUMOURID'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# merged_av_data.iloc[merged_av_data.index.get_level_values('PATIENTID') == 60035351][['AGE', 'DIAGNOSISDATEBEST']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_av_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tumour.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_av_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_av_data['DATE_FIRST_SURGERY'] = pd.to_datetime(merged_av_data['DATE_FIRST_SURGERY'])\n",
    "merged_av_data['DIAGNOSISDATEBEST'] = pd.to_datetime(merged_av_data['DIAGNOSISDATEBEST'])\n",
    "\n",
    "# (merged_av_data['DATE_FIRST_SURGERY'] - merged_av_data['DIAGNOSISDATEBEST']).value_counts() < pd.Timedelta('0 days 00:00:00')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_av_data['DATE_FIRST_SURGERY']\n",
    "merged_av_data['DIAGNOSISDATEBEST']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "       867097\n",
       "0      396681\n",
       "1       80765\n",
       "1b      36196\n",
       "1a      14767\n",
       "0.0      6388\n",
       "1c        574\n",
       "X         236\n",
       "1.0        42\n",
       "2           2\n",
       "1e          1\n",
       "Name: M_BEST, dtype: int64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# merged_av_data.groupby(['SEX_y', 'NEWVITALSTATUS']).count().iloc\n",
    "merged_av_data['M_BEST'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "86167"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_av_data[(merged_av_data['M_BEST'] != 0.0) & (merged_av_data['M_BEST'] != '0') & (merged_av_data['M_BEST'] != '')].groupby('NEWVITALSTATUS').count().iloc[1][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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   "display_name": "Python 3",
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   "codemirror_mode": {
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  "pycharm": {
   "stem_cell": {
    "cell_type": "raw",
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 },
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