Russia_preprocess.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "76a17f87-e4c9-409a-83a6-d01fcf9a08a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fe979d0b-308d-4631-9e60-a0e4e2f7a101",
   "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>PopName</th>\n",
       "      <th>Area</th>\n",
       "      <th>Year</th>\n",
       "      <th>YearReg</th>\n",
       "      <th>YearInterval</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>AgeInterval</th>\n",
       "      <th>Lexis</th>\n",
       "      <th>RefCode</th>\n",
       "      <th>Access</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>NoteCode1</th>\n",
       "      <th>NoteCode2</th>\n",
       "      <th>NoteCode3</th>\n",
       "      <th>LDB</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1</td>\n",
       "      <td>1946</td>\n",
       "      <td>1946</td>\n",
       "      <td>1</td>\n",
       "      <td>m</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>RR</td>\n",
       "      <td>1</td>\n",
       "      <td>O</td>\n",
       "      <td>106450.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1</td>\n",
       "      <td>1946</td>\n",
       "      <td>1946</td>\n",
       "      <td>1</td>\n",
       "      <td>m</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>RR</td>\n",
       "      <td>1</td>\n",
       "      <td>O</td>\n",
       "      <td>21379.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1</td>\n",
       "      <td>1946</td>\n",
       "      <td>1946</td>\n",
       "      <td>1</td>\n",
       "      <td>m</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>RR</td>\n",
       "      <td>1</td>\n",
       "      <td>O</td>\n",
       "      <td>8662.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1</td>\n",
       "      <td>1946</td>\n",
       "      <td>1946</td>\n",
       "      <td>1</td>\n",
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       "      <td>5016.000000</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1</td>\n",
       "      <td>1946</td>\n",
       "      <td>1946</td>\n",
       "      <td>1</td>\n",
       "      <td>m</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>RR</td>\n",
       "      <td>1</td>\n",
       "      <td>O</td>\n",
       "      <td>5297.000000</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>17209</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1</td>\n",
       "      <td>2014</td>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>f</td>\n",
       "      <td>99</td>\n",
       "      <td>1</td>\n",
       "      <td>TL</td>\n",
       "      <td>42</td>\n",
       "      <td>O</td>\n",
       "      <td>805.619469</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>17210</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1</td>\n",
       "      <td>2014</td>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>f</td>\n",
       "      <td>99</td>\n",
       "      <td>1</td>\n",
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       "      <td>42</td>\n",
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       "      <td>741.380531</td>\n",
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       "    <tr>\n",
       "      <th>17211</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1</td>\n",
       "      <td>2014</td>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
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       "      <td>100</td>\n",
       "      <td>+</td>\n",
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       "      <td>42</td>\n",
       "      <td>O</td>\n",
       "      <td>2828.000000</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17212</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1</td>\n",
       "      <td>2014</td>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>f</td>\n",
       "      <td>UNK</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "      <td>42</td>\n",
       "      <td>O</td>\n",
       "      <td>912.000000</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17213</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1</td>\n",
       "      <td>2014</td>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>f</td>\n",
       "      <td>TOT</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "      <td>42</td>\n",
       "      <td>O</td>\n",
       "      <td>919364.000000</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>17214 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PopName  Area  Year  YearReg  YearInterval Sex  Age AgeInterval Lexis  \\\n",
       "0         RUS     1  1946     1946             1   m    0           1    RR   \n",
       "1         RUS     1  1946     1946             1   m    1           1    RR   \n",
       "2         RUS     1  1946     1946             1   m    2           1    RR   \n",
       "3         RUS     1  1946     1946             1   m    3           1    RR   \n",
       "4         RUS     1  1946     1946             1   m    4           1    RR   \n",
       "...       ...   ...   ...      ...           ...  ..  ...         ...   ...   \n",
       "17209     RUS     1  2014     2014             1   f   99           1    TL   \n",
       "17210     RUS     1  2014     2014             1   f   99           1    TU   \n",
       "17211     RUS     1  2014     2014             1   f  100           +    RR   \n",
       "17212     RUS     1  2014     2014             1   f  UNK           .     .   \n",
       "17213     RUS     1  2014     2014             1   f  TOT           .     .   \n",
       "\n",
       "       RefCode Access         Deaths NoteCode1 NoteCode2 NoteCode3  LDB  \n",
       "0            1      O  106450.000000         1         2         .    0  \n",
       "1            1      O   21379.000000         1         .         .    0  \n",
       "2            1      O    8662.000000         1         .         .    0  \n",
       "3            1      O    5016.000000         1         .         .    0  \n",
       "4            1      O    5297.000000         1         .         .    0  \n",
       "...        ...    ...            ...       ...       ...       ...  ...  \n",
       "17209       42      O     805.619469         .         .         .    1  \n",
       "17210       42      O     741.380531         .         .         .    1  \n",
       "17211       42      O    2828.000000         .         .         .    1  \n",
       "17212       42      O     912.000000         .         .         .    1  \n",
       "17213       42      O  919364.000000         .         .         .    1  \n",
       "\n",
       "[17214 rows x 16 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('RUSdeath.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2db211d7-1c4b-4815-b658-25afcde429e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PopName          object\n",
       "Area              int64\n",
       "Year              int64\n",
       "YearReg           int64\n",
       "YearInterval      int64\n",
       "Sex              object\n",
       "Age              object\n",
       "AgeInterval      object\n",
       "Lexis            object\n",
       "RefCode           int64\n",
       "Access           object\n",
       "Deaths          float64\n",
       "NoteCode1        object\n",
       "NoteCode2        object\n",
       "NoteCode3        object\n",
       "LDB               int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the dataset\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5bd823c0-495a-45b7-9540-45fa01cc1e78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12',\n",
       "       '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23',\n",
       "       '24', '25', '26', '27', '28', '29', '30', '31', '32', '33', '34',\n",
       "       '35', '36', '37', '38', '39', '40', '41', '42', '43', '44', '45',\n",
       "       '46', '47', '48', '49', '50', '51', '52', '53', '54', '55', '56',\n",
       "       '57', '58', '59', '60', '61', '62', '63', '64', '65', '66', '67',\n",
       "       '68', '69', '70', '71', '72', '73', '74', '75', '76', '77', '78',\n",
       "       '79', '80', '81', '82', '83', '84', '85', '86', '87', '88', '89',\n",
       "       '90', '91', '92', '93', '94', '95', '96', '97', '98', '99', '100',\n",
       "       'UNK', 'TOT'], dtype=object)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Age'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "370f42fc-0774-4788-b7eb-79ce6ff7bb0f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Delete the bad data ('UNK')\n",
    "df = df.drop(df[df['Age'] == 'UNK'].index, axis=0)\n",
    "df = df.drop(df[df['Age'] == 'TOT'].index, axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e30b85cb-5453-47dc-a1b9-9d06042f87a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PopName          object\n",
       "Area              int64\n",
       "Year              int64\n",
       "YearReg           int64\n",
       "YearInterval      int64\n",
       "Sex              object\n",
       "Age              object\n",
       "AgeInterval      object\n",
       "Lexis            object\n",
       "RefCode           int64\n",
       "Access           object\n",
       "Deaths          float64\n",
       "NoteCode1        object\n",
       "NoteCode2        object\n",
       "NoteCode3        object\n",
       "LDB               int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Transfer the data type of Age to int\n",
    "df = df.astype({'Year':'int64'})\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37f10ecb-84b4-4a6c-bab1-05a16623f902",
   "metadata": {},
   "source": [
    "### 2.Treemap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d4351f9e-2409-4326-852f-9ba78ab79ffd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PopName</th>\n",
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       "      <th>Deaths</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>106450.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>21379.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>8662.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>5016.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>5297.000000</td>\n",
       "    </tr>\n",
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       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>17207</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>1020.916080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17208</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>931.083920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17209</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>805.619469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17210</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>741.380531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17211</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>2828.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16938 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PopName  Year         Deaths\n",
       "0         RUS  1946  106450.000000\n",
       "1         RUS  1946   21379.000000\n",
       "2         RUS  1946    8662.000000\n",
       "3         RUS  1946    5016.000000\n",
       "4         RUS  1946    5297.000000\n",
       "...       ...   ...            ...\n",
       "17207     RUS  2014    1020.916080\n",
       "17208     RUS  2014     931.083920\n",
       "17209     RUS  2014     805.619469\n",
       "17210     RUS  2014     741.380531\n",
       "17211     RUS  2014    2828.000000\n",
       "\n",
       "[16938 rows x 3 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#2.1 filter the data we need (Year 1940-2019)\n",
    "df2 = df[(df['Year'] >= 1940) & (df['Year'] <= 2019)][['PopName', 'Year', 'Deaths']]\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bab6f42f-e445-458e-a169-4df9b740cb00",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PopName</th>\n",
       "      <th>Year</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>YearGroup</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>106450.000000</td>\n",
       "      <td>1940s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>21379.000000</td>\n",
       "      <td>1940s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>8662.000000</td>\n",
       "      <td>1940s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>5016.000000</td>\n",
       "      <td>1940s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>5297.000000</td>\n",
       "      <td>1940s</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>17207</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>1020.916080</td>\n",
       "      <td>2010s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17208</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>931.083920</td>\n",
       "      <td>2010s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17209</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>805.619469</td>\n",
       "      <td>2010s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17210</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>741.380531</td>\n",
       "      <td>2010s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17211</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>2828.000000</td>\n",
       "      <td>2010s</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16938 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PopName  Year         Deaths YearGroup\n",
       "0         RUS  1946  106450.000000     1940s\n",
       "1         RUS  1946   21379.000000     1940s\n",
       "2         RUS  1946    8662.000000     1940s\n",
       "3         RUS  1946    5016.000000     1940s\n",
       "4         RUS  1946    5297.000000     1940s\n",
       "...       ...   ...            ...       ...\n",
       "17207     RUS  2014    1020.916080     2010s\n",
       "17208     RUS  2014     931.083920     2010s\n",
       "17209     RUS  2014     805.619469     2010s\n",
       "17210     RUS  2014     741.380531     2010s\n",
       "17211     RUS  2014    2828.000000     2010s\n",
       "\n",
       "[16938 rows x 4 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#2.2 Categorize the year into 8 groups\n",
    "bins = [1940, 1949, 1959, 1969, 1979, 1989, 1999, 2009, 2019]\n",
    "labels = ['1940s', '1950s', '1960s', '1970s','1980s','1990s','2000s', '2010s']\n",
    "df2['YearGroup'] = pd.cut(df2['Year'],bins=bins,labels=labels, include_lowest=True)\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6f3d3694-6263-416d-9f8e-d5dd5e112a7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>4.677599e+06</td>\n",
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       "      <th>1</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>21379.000000</td>\n",
       "      <td>1940s</td>\n",
       "      <td>4.677599e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>8662.000000</td>\n",
       "      <td>1940s</td>\n",
       "      <td>4.677599e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>5016.000000</td>\n",
       "      <td>1940s</td>\n",
       "      <td>4.677599e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>5297.000000</td>\n",
       "      <td>1940s</td>\n",
       "      <td>4.677599e+06</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17207</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>1020.916080</td>\n",
       "      <td>2010s</td>\n",
       "      <td>9.579022e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17208</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>931.083920</td>\n",
       "      <td>2010s</td>\n",
       "      <td>9.579022e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17209</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>805.619469</td>\n",
       "      <td>2010s</td>\n",
       "      <td>9.579022e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17210</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>741.380531</td>\n",
       "      <td>2010s</td>\n",
       "      <td>9.579022e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17211</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2014</td>\n",
       "      <td>2828.000000</td>\n",
       "      <td>2010s</td>\n",
       "      <td>9.579022e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16938 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PopName  Year         Deaths YearGroup  Total_Deaths\n",
       "0         RUS  1946  106450.000000     1940s  4.677599e+06\n",
       "1         RUS  1946   21379.000000     1940s  4.677599e+06\n",
       "2         RUS  1946    8662.000000     1940s  4.677599e+06\n",
       "3         RUS  1946    5016.000000     1940s  4.677599e+06\n",
       "4         RUS  1946    5297.000000     1940s  4.677599e+06\n",
       "...       ...   ...            ...       ...           ...\n",
       "17207     RUS  2014    1020.916080     2010s  9.579022e+06\n",
       "17208     RUS  2014     931.083920     2010s  9.579022e+06\n",
       "17209     RUS  2014     805.619469     2010s  9.579022e+06\n",
       "17210     RUS  2014     741.380531     2010s  9.579022e+06\n",
       "17211     RUS  2014    2828.000000     2010s  9.579022e+06\n",
       "\n",
       "[16938 rows x 5 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#2.3 Group and calculate the total deaths in each group of year (Treemap)\n",
    "group = df2.groupby(['YearGroup'])\n",
    "df2['Total_Deaths'] = group['Deaths'].transform('sum')\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "23c2382d-9e39-4626-80f6-91db75ec784e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [PopName, Year, Deaths, YearGroup, Total_Deaths]\n",
       "Index: []"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2[df2.isna().any(axis=1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7edf1a89-6d49-44cb-b4cf-ef8b026ff31a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Year</th>\n",
       "      <th>Total_Deaths</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>1940s</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>824</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1950s</td>\n",
       "      <td>9.634787e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2884</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1960s</td>\n",
       "      <td>9.663970e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4944</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1970s</td>\n",
       "      <td>1.284553e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7004</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1980s</td>\n",
       "      <td>1.556478e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9064</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1990s</td>\n",
       "      <td>1.992745e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11124</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2000s</td>\n",
       "      <td>2.196557e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15184</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2010s</td>\n",
       "      <td>9.579022e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Country   Year  Total_Deaths\n",
       "0         RUS  1940s  4.677599e+06\n",
       "824       RUS  1950s  9.634787e+06\n",
       "2884      RUS  1960s  9.663970e+06\n",
       "4944      RUS  1970s  1.284553e+07\n",
       "7004      RUS  1980s  1.556478e+07\n",
       "9064      RUS  1990s  1.992745e+07\n",
       "11124     RUS  2000s  2.196557e+07\n",
       "15184     RUS  2010s  9.579022e+06"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#2.4 Drop duplicates\n",
    "df2 = df2.drop_duplicates('YearGroup')\n",
    "df2 = df2.drop(['Year','Deaths'],axis=1)\n",
    "df2 = df2.rename({'PopName':'Country', 'YearGroup':'Year'}, axis=1)\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5f1e2995-ce4a-47fb-9872-a48ca9d52ec9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>0</th>\n",
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       "      <th>1</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>495443</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>442311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>654199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>1079548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14858</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2015</td>\n",
       "      <td>13281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14859</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2015</td>\n",
       "      <td>6897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14860</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2015</td>\n",
       "      <td>4994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14861</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2015</td>\n",
       "      <td>4263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14862</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2015</td>\n",
       "      <td>10316</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14863 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PopName  Year  Population\n",
       "0         RUS  1946      703018\n",
       "1         RUS  1946      495443\n",
       "2         RUS  1946      442311\n",
       "3         RUS  1946      654199\n",
       "4         RUS  1946     1079548\n",
       "...       ...   ...         ...\n",
       "14858     RUS  2015       13281\n",
       "14859     RUS  2015        6897\n",
       "14860     RUS  2015        4994\n",
       "14861     RUS  2015        4263\n",
       "14862     RUS  2015       10316\n",
       "\n",
       "[14863 rows x 3 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#3.1 Population dataset\n",
    "df_pop = pd.read_csv('RUSpop.csv')\n",
    "df_pop = df_pop[(df_pop['Year'] >= 1940) & (df_pop['Year'] <= 2019)][['PopName', 'Year', 'Population']]\n",
    "df_pop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cca172ba-8844-48d4-be29-cba259966849",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1946</td>\n",
       "      <td>1079548</td>\n",
       "      <td>1940s</td>\n",
       "      <td>790932680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14858</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2015</td>\n",
       "      <td>13281</td>\n",
       "      <td>2010s</td>\n",
       "      <td>1719483416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14859</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2015</td>\n",
       "      <td>6897</td>\n",
       "      <td>2010s</td>\n",
       "      <td>1719483416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14860</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2015</td>\n",
       "      <td>4994</td>\n",
       "      <td>2010s</td>\n",
       "      <td>1719483416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14861</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2015</td>\n",
       "      <td>4263</td>\n",
       "      <td>2010s</td>\n",
       "      <td>1719483416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14862</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2015</td>\n",
       "      <td>10316</td>\n",
       "      <td>2010s</td>\n",
       "      <td>1719483416</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14863 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PopName  Year  Population YearGroup   Total_Pop\n",
       "0         RUS  1946      703018     1940s   790932680\n",
       "1         RUS  1946      495443     1940s   790932680\n",
       "2         RUS  1946      442311     1940s   790932680\n",
       "3         RUS  1946      654199     1940s   790932680\n",
       "4         RUS  1946     1079548     1940s   790932680\n",
       "...       ...   ...         ...       ...         ...\n",
       "14858     RUS  2015       13281     2010s  1719483416\n",
       "14859     RUS  2015        6897     2010s  1719483416\n",
       "14860     RUS  2015        4994     2010s  1719483416\n",
       "14861     RUS  2015        4263     2010s  1719483416\n",
       "14862     RUS  2015       10316     2010s  1719483416\n",
       "\n",
       "[14863 rows x 5 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#3.2 Categorize the year into 8 groups\n",
    "bins = [1940, 1949, 1959, 1969, 1979, 1989, 1999, 2009, 2019]\n",
    "labels = ['1940s', '1950s', '1960s', '1970s','1980s','1990s','2000s', '2010s']\n",
    "df_pop['YearGroup'] = pd.cut(df_pop['Year'],bins=bins,labels=labels, include_lowest=True)\n",
    "\n",
    "#3.3 Group and calculate the total population in each group of year (Treemap)\n",
    "group = df_pop.groupby(['YearGroup'])\n",
    "df_pop['Total_Pop'] = group['Population'].transform('sum')\n",
    "df_pop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b35abde2-67a0-4d7b-b17c-7c05e930e49e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Year</th>\n",
       "      <th>Total_Deaths</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
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      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Country, Year, Total_Deaths]\n",
       "Index: []"
      ]
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     "execution_count": 15,
     "metadata": {},
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    }
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   "source": [
    "df2[df2.isna().any(axis=1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "67b8d5d7-a971-40ed-b0a3-67e21b1ad86a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Total_Pop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1940s</td>\n",
       "      <td>790932680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>816</th>\n",
       "      <td>1950s</td>\n",
       "      <td>2429924948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3062</th>\n",
       "      <td>1970s</td>\n",
       "      <td>3203912971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5274</th>\n",
       "      <td>1980s</td>\n",
       "      <td>3139841144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7520</th>\n",
       "      <td>1990s</td>\n",
       "      <td>5019199950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10987</th>\n",
       "      <td>2000s</td>\n",
       "      <td>3758377804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13639</th>\n",
       "      <td>2010s</td>\n",
       "      <td>1719483416</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Year   Total_Pop\n",
       "0      1940s   790932680\n",
       "816    1950s  2429924948\n",
       "3062   1970s  3203912971\n",
       "5274   1980s  3139841144\n",
       "7520   1990s  5019199950\n",
       "10987  2000s  3758377804\n",
       "13639  2010s  1719483416"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#3.4 Drop duplicates\n",
    "df_pop = df_pop.drop_duplicates('YearGroup')\n",
    "df_pop = df_pop.drop(['PopName','Year','Population'],axis=1)\n",
    "df_pop = df_pop.rename({'YearGroup':'Year'}, axis=1)\n",
    "df_pop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "20984a08-7ba9-44e2-b818-76dfebb3ea55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Year</th>\n",
       "      <th>Total_Deaths</th>\n",
       "      <th>Total_Pop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1940s</td>\n",
       "      <td>4.677599e+06</td>\n",
       "      <td>790932680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1950s</td>\n",
       "      <td>9.634787e+06</td>\n",
       "      <td>2429924948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1970s</td>\n",
       "      <td>1.284553e+07</td>\n",
       "      <td>3203912971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1980s</td>\n",
       "      <td>1.556478e+07</td>\n",
       "      <td>3139841144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1990s</td>\n",
       "      <td>1.992745e+07</td>\n",
       "      <td>5019199950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2000s</td>\n",
       "      <td>2.196557e+07</td>\n",
       "      <td>3758377804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2010s</td>\n",
       "      <td>9.579022e+06</td>\n",
       "      <td>1719483416</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Country   Year  Total_Deaths   Total_Pop\n",
       "0     RUS  1940s  4.677599e+06   790932680\n",
       "1     RUS  1950s  9.634787e+06  2429924948\n",
       "2     RUS  1970s  1.284553e+07  3203912971\n",
       "3     RUS  1980s  1.556478e+07  3139841144\n",
       "4     RUS  1990s  1.992745e+07  5019199950\n",
       "5     RUS  2000s  2.196557e+07  3758377804\n",
       "6     RUS  2010s  9.579022e+06  1719483416"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#4. merge 2 datasets\n",
    "ru = pd.merge(df2, df_pop, on='Year', how='inner')\n",
    "ru"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c1b7dec9-0fd2-4869-90c8-31ea298d1872",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Year</th>\n",
       "      <th>Total_Deaths</th>\n",
       "      <th>Total_Pop</th>\n",
       "      <th>Death_Rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1940s</td>\n",
       "      <td>4.677599e+06</td>\n",
       "      <td>790932680</td>\n",
       "      <td>5.914029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1950s</td>\n",
       "      <td>9.634787e+06</td>\n",
       "      <td>2429924948</td>\n",
       "      <td>3.965055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1970s</td>\n",
       "      <td>1.284553e+07</td>\n",
       "      <td>3203912971</td>\n",
       "      <td>4.009325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1980s</td>\n",
       "      <td>1.556478e+07</td>\n",
       "      <td>3139841144</td>\n",
       "      <td>4.957186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RUS</td>\n",
       "      <td>1990s</td>\n",
       "      <td>1.992745e+07</td>\n",
       "      <td>5019199950</td>\n",
       "      <td>3.970244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2000s</td>\n",
       "      <td>2.196557e+07</td>\n",
       "      <td>3758377804</td>\n",
       "      <td>5.844428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>RUS</td>\n",
       "      <td>2010s</td>\n",
       "      <td>9.579022e+06</td>\n",
       "      <td>1719483416</td>\n",
       "      <td>5.570872</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Country   Year  Total_Deaths   Total_Pop  Death_Rate\n",
       "0     RUS  1940s  4.677599e+06   790932680    5.914029\n",
       "1     RUS  1950s  9.634787e+06  2429924948    3.965055\n",
       "2     RUS  1970s  1.284553e+07  3203912971    4.009325\n",
       "3     RUS  1980s  1.556478e+07  3139841144    4.957186\n",
       "4     RUS  1990s  1.992745e+07  5019199950    3.970244\n",
       "5     RUS  2000s  2.196557e+07  3758377804    5.844428\n",
       "6     RUS  2010s  9.579022e+06  1719483416    5.570872"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ru['Death_Rate'] = ru[['Total_Deaths','Total_Pop']].apply(lambda x: x['Total_Deaths'] / x['Total_Pop']* 1000 ,axis=1)\n",
    "ru"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "1d89b9f3-f348-4aa2-82cd-1d45b927fede",
   "metadata": {},
   "outputs": [],
   "source": [
    "ru.to_csv('D:/Users/Lenovo/Desktop/COMP4037 Research Methods/CW2_Data Visualization/Data/Russia rate.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cff8e74e-32c0-4733-95bb-e87bdd1a6f3d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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