Co2_project_cleaning.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2e7a2456",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b8a8c60f",
   "metadata": {},
   "outputs": [],
   "source": [
    "co2df = pd.read_csv(\"final_cleaned_data_yearly.csv\",index_col = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "id": "c5ca724a",
   "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>country</th>\n",
       "      <th>year</th>\n",
       "      <th>iso_code</th>\n",
       "      <th>population</th>\n",
       "      <th>gdp</th>\n",
       "      <th>cement_co2</th>\n",
       "      <th>co2</th>\n",
       "      <th>co2_including_luc</th>\n",
       "      <th>coal_co2</th>\n",
       "      <th>cumulative_cement_co2</th>\n",
       "      <th>...</th>\n",
       "      <th>share_global_cumulative_luc_co2</th>\n",
       "      <th>share_global_cumulative_oil_co2</th>\n",
       "      <th>share_global_luc_co2</th>\n",
       "      <th>share_global_oil_co2</th>\n",
       "      <th>share_of_temperature_change_from_ghg</th>\n",
       "      <th>temperature_change_from_ch4</th>\n",
       "      <th>temperature_change_from_co2</th>\n",
       "      <th>temperature_change_from_ghg</th>\n",
       "      <th>temperature_change_from_n2o</th>\n",
       "      <th>output_co2_production</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1949</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7356890</td>\n",
       "      <td>9.421400e+09</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.015</td>\n",
       "      <td>8.039</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.018</td>\n",
       "      <td>...</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.160</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.129</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
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       "      <td>14656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1950</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7480464</td>\n",
       "      <td>9.421400e+09</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.084</td>\n",
       "      <td>8.585</td>\n",
       "      <td>0.021</td>\n",
       "      <td>0.018</td>\n",
       "      <td>...</td>\n",
       "      <td>0.141</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.157</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.129</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>98928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1951</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7571542</td>\n",
       "      <td>9.692280e+09</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.092</td>\n",
       "      <td>9.142</td>\n",
       "      <td>0.026</td>\n",
       "      <td>0.018</td>\n",
       "      <td>...</td>\n",
       "      <td>0.141</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.162</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.129</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.0</td>\n",
       "      <td>190528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1952</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7667534</td>\n",
       "      <td>1.001733e+10</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.092</td>\n",
       "      <td>9.948</td>\n",
       "      <td>0.032</td>\n",
       "      <td>0.018</td>\n",
       "      <td>...</td>\n",
       "      <td>0.141</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.172</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.129</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.0</td>\n",
       "      <td>282128</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1953</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7764549</td>\n",
       "      <td>1.063052e+10</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.106</td>\n",
       "      <td>10.915</td>\n",
       "      <td>0.038</td>\n",
       "      <td>0.018</td>\n",
       "      <td>...</td>\n",
       "      <td>0.142</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.185</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.129</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.0</td>\n",
       "      <td>388384</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       country  year iso_code  population           gdp  cement_co2    co2  \\\n",
       "0  Afghanistan  1949      AFG     7356890  9.421400e+09       0.018  0.015   \n",
       "1  Afghanistan  1950      AFG     7480464  9.421400e+09       0.018  0.084   \n",
       "2  Afghanistan  1951      AFG     7571542  9.692280e+09       0.018  0.092   \n",
       "3  Afghanistan  1952      AFG     7667534  1.001733e+10       0.018  0.092   \n",
       "4  Afghanistan  1953      AFG     7764549  1.063052e+10       0.018  0.106   \n",
       "\n",
       "   co2_including_luc  coal_co2  cumulative_cement_co2  ...  \\\n",
       "0              8.039     0.015                  0.018  ...   \n",
       "1              8.585     0.021                  0.018  ...   \n",
       "2              9.142     0.026                  0.018  ...   \n",
       "3              9.948     0.032                  0.018  ...   \n",
       "4             10.915     0.038                  0.018  ...   \n",
       "\n",
       "   share_global_cumulative_luc_co2  share_global_cumulative_oil_co2  \\\n",
       "0                            0.140                            0.000   \n",
       "1                            0.141                            0.000   \n",
       "2                            0.141                            0.000   \n",
       "3                            0.141                            0.001   \n",
       "4                            0.142                            0.001   \n",
       "\n",
       "   share_global_luc_co2  share_global_oil_co2  \\\n",
       "0                 0.160                 0.000   \n",
       "1                 0.157                 0.004   \n",
       "2                 0.162                 0.004   \n",
       "3                 0.172                 0.003   \n",
       "4                 0.185                 0.003   \n",
       "\n",
       "   share_of_temperature_change_from_ghg  temperature_change_from_ch4  \\\n",
       "0                                 0.129                          0.0   \n",
       "1                                 0.129                          0.0   \n",
       "2                                 0.129                          0.0   \n",
       "3                                 0.129                          0.0   \n",
       "4                                 0.129                          0.0   \n",
       "\n",
       "   temperature_change_from_co2  temperature_change_from_ghg  \\\n",
       "0                          0.0                        0.000   \n",
       "1                          0.0                        0.000   \n",
       "2                          0.0                        0.001   \n",
       "3                          0.0                        0.001   \n",
       "4                          0.0                        0.001   \n",
       "\n",
       "   temperature_change_from_n2o  output_co2_production  \n",
       "0                          0.0                  14656  \n",
       "1                          0.0                  98928  \n",
       "2                          0.0                 190528  \n",
       "3                          0.0                 282128  \n",
       "4                          0.0                 388384  \n",
       "\n",
       "[5 rows x 35 columns]"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4108067a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Afghanistan', 'Bangladesh', 'Bhutan', 'India', 'Nepal',\n",
       "       'Pakistan', 'Sri Lanka'], dtype=object)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2df['country'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c0de48c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country                                      0\n",
       "year                                         0\n",
       "iso_code                                     0\n",
       "population                                   0\n",
       "gdp                                          0\n",
       "cement_co2                                   0\n",
       "co2                                          0\n",
       "co2_including_luc                            0\n",
       "coal_co2                                     0\n",
       "cumulative_cement_co2                        0\n",
       "cumulative_co2                               0\n",
       "cumulative_co2_including_luc                 0\n",
       "cumulative_coal_co2                          0\n",
       "cumulative_luc_co2                           0\n",
       "cumulative_oil_co2                           0\n",
       "land_use_change_co2                          0\n",
       "oil_co2                                      0\n",
       "share_global_cement_co2                      0\n",
       "share_global_co2                             0\n",
       "share_global_co2_including_luc               0\n",
       "share_global_coal_co2                        0\n",
       "share_global_cumulative_cement_co2           0\n",
       "share_global_cumulative_co2                  0\n",
       "share_global_cumulative_co2_including_luc    0\n",
       "share_global_cumulative_coal_co2             0\n",
       "share_global_cumulative_luc_co2              0\n",
       "share_global_cumulative_oil_co2              0\n",
       "share_global_luc_co2                         0\n",
       "share_global_oil_co2                         0\n",
       "share_of_temperature_change_from_ghg         0\n",
       "temperature_change_from_ch4                  0\n",
       "temperature_change_from_co2                  0\n",
       "temperature_change_from_ghg                  0\n",
       "temperature_change_from_n2o                  0\n",
       "output_co2_production                        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "421eac95",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(574, 35)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "f7016254",
   "metadata": {},
   "outputs": [],
   "source": [
    "#coun = 'Sri Lanka'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "94e37e3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#co2df.loc[(co2df.country==coun)] = co2df.loc[(co2df.country==coun)].ffill()\n",
    "#co2df.loc[(co2df.country==coun)] = co2df.loc[(co2df.country==coun)].bfill()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "7f634d00",
   "metadata": {},
   "outputs": [],
   "source": [
    "#new_df = co2df.interpolate(method = \"polynomial\",order = 3,limit_direction = 'both')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "177fe59f",
   "metadata": {},
   "outputs": [
    {
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       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>621</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>622</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>623</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>624</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>625 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     country   year  iso_code  population    gdp  cement_co2    co2  \\\n",
       "0      False  False     False       False  False       False  False   \n",
       "1      False  False     False       False  False       False  False   \n",
       "2      False  False     False       False  False       False  False   \n",
       "3      False  False     False       False  False       False  False   \n",
       "4      False  False     False       False  False       False  False   \n",
       "..       ...    ...       ...         ...    ...         ...    ...   \n",
       "620    False  False     False       False  False       False  False   \n",
       "621    False  False     False       False  False       False  False   \n",
       "622    False  False     False       False  False       False  False   \n",
       "623    False  False     False       False  False       False  False   \n",
       "624    False  False     False       False  False       False  False   \n",
       "\n",
       "     co2_including_luc  coal_co2  cumulative_cement_co2  ...  \\\n",
       "0                False     False                  False  ...   \n",
       "1                False     False                  False  ...   \n",
       "2                False     False                  False  ...   \n",
       "3                False     False                  False  ...   \n",
       "4                False     False                  False  ...   \n",
       "..                 ...       ...                    ...  ...   \n",
       "620              False     False                  False  ...   \n",
       "621              False     False                  False  ...   \n",
       "622              False     False                  False  ...   \n",
       "623              False     False                  False  ...   \n",
       "624              False     False                  False  ...   \n",
       "\n",
       "     share_global_cumulative_luc_co2  share_global_cumulative_oil_co2  \\\n",
       "0                              False                            False   \n",
       "1                              False                            False   \n",
       "2                              False                            False   \n",
       "3                              False                            False   \n",
       "4                              False                            False   \n",
       "..                               ...                              ...   \n",
       "620                            False                            False   \n",
       "621                            False                            False   \n",
       "622                            False                            False   \n",
       "623                            False                            False   \n",
       "624                            False                            False   \n",
       "\n",
       "     share_global_luc_co2  share_global_oil_co2  \\\n",
       "0                   False                 False   \n",
       "1                   False                 False   \n",
       "2                   False                 False   \n",
       "3                   False                 False   \n",
       "4                   False                 False   \n",
       "..                    ...                   ...   \n",
       "620                 False                 False   \n",
       "621                 False                 False   \n",
       "622                 False                 False   \n",
       "623                 False                 False   \n",
       "624                 False                 False   \n",
       "\n",
       "     share_of_temperature_change_from_ghg  temperature_change_from_ch4  \\\n",
       "0                                   False                        False   \n",
       "1                                   False                        False   \n",
       "2                                   False                        False   \n",
       "3                                   False                        False   \n",
       "4                                   False                        False   \n",
       "..                                    ...                          ...   \n",
       "620                                 False                        False   \n",
       "621                                 False                        False   \n",
       "622                                 False                        False   \n",
       "623                                 False                        False   \n",
       "624                                 False                        False   \n",
       "\n",
       "     temperature_change_from_co2  temperature_change_from_ghg  \\\n",
       "0                          False                        False   \n",
       "1                          False                        False   \n",
       "2                          False                        False   \n",
       "3                          False                        False   \n",
       "4                          False                        False   \n",
       "..                           ...                          ...   \n",
       "620                        False                        False   \n",
       "621                        False                        False   \n",
       "622                        False                        False   \n",
       "623                        False                        False   \n",
       "624                        False                        False   \n",
       "\n",
       "     temperature_change_from_n2o  output_co2_production  \n",
       "0                          False                  False  \n",
       "1                          False                  False  \n",
       "2                          False                  False  \n",
       "3                          False                  False  \n",
       "4                          False                  False  \n",
       "..                           ...                    ...  \n",
       "620                        False                  False  \n",
       "621                        False                  False  \n",
       "622                        False                  False  \n",
       "623                        False                  False  \n",
       "624                        False                  False  \n",
       "\n",
       "[625 rows x 35 columns]"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "3e8c30ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "#co2df.to_csv(\"final_cleaned_data_yearly.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "e62ab0d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country                                      0\n",
       "year                                         0\n",
       "iso_code                                     0\n",
       "population                                   0\n",
       "gdp                                          0\n",
       "cement_co2                                   0\n",
       "co2                                          0\n",
       "co2_including_luc                            0\n",
       "coal_co2                                     0\n",
       "cumulative_cement_co2                        0\n",
       "cumulative_co2                               0\n",
       "cumulative_co2_including_luc                 0\n",
       "cumulative_coal_co2                          0\n",
       "cumulative_luc_co2                           0\n",
       "cumulative_oil_co2                           0\n",
       "land_use_change_co2                          0\n",
       "oil_co2                                      0\n",
       "share_global_cement_co2                      0\n",
       "share_global_co2                             0\n",
       "share_global_co2_including_luc               0\n",
       "share_global_coal_co2                        0\n",
       "share_global_cumulative_cement_co2           0\n",
       "share_global_cumulative_co2                  0\n",
       "share_global_cumulative_co2_including_luc    0\n",
       "share_global_cumulative_coal_co2             0\n",
       "share_global_cumulative_luc_co2              0\n",
       "share_global_cumulative_oil_co2              0\n",
       "share_global_luc_co2                         0\n",
       "share_global_oil_co2                         0\n",
       "share_of_temperature_change_from_ghg         0\n",
       "temperature_change_from_ch4                  0\n",
       "temperature_change_from_co2                  0\n",
       "temperature_change_from_ghg                  0\n",
       "temperature_change_from_n2o                  0\n",
       "output_co2_production                        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "id": "411f36de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      1949\n",
       "1      1950\n",
       "2      1951\n",
       "3      1952\n",
       "4      1953\n",
       "       ... \n",
       "569    2017\n",
       "570    2018\n",
       "571    2019\n",
       "572    2020\n",
       "573    2021\n",
       "Name: year, Length: 574, dtype: int64"
      ]
     },
     "execution_count": 233,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2df['year']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "ce90a6db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2021, 1, 1, 0, 0)"
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input = '2021'\n",
    "format = '%Y'\n",
    " \n",
    "# convert from string format to datetime format\n",
    "c = datetime.strptime(input, format)\n",
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "id": "cbb8471f",
   "metadata": {},
   "outputs": [],
   "source": [
    "co2df['year'] = pd.to_datetime(co2df['year'], format='%Y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "id": "d155d3a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "co2df = co2df.set_index('year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "id": "d2e6bbe7",
   "metadata": {},
   "outputs": [],
   "source": [
    "l = ['Afghanistan', 'Bangladesh', 'Bhutan', 'India', 'Nepal',\n",
    "       'Pakistan', 'Sri Lanka']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "id": "b3145da8",
   "metadata": {},
   "outputs": [],
   "source": [
    "afgh = co2df.loc[(co2df.country=='Afghanistan')].resample('M').ffill()\n",
    "bang = co2df.loc[(co2df.country=='Bangladesh')].resample('M').ffill()\n",
    "bhutan = co2df.loc[(co2df.country=='Bhutan')].resample('M').ffill()\n",
    "india = co2df.loc[(co2df.country=='India')].resample('M').ffill()\n",
    "nepal = co2df.loc[(co2df.country=='Nepal')].resample('M').ffill()\n",
    "pakistan = co2df.loc[(co2df.country=='Pakistan')].resample('M').ffill()\n",
    "srilanka = co2df.loc[(co2df.country=='Sri Lanka')].resample('M').ffill()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "id": "872908ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "final_monthly_data = pd.concat([afgh,bang,bhutan,india,nepal,pakistan,srilanka])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "id": "9567a9ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "final_monthly_data.to_csv(\"input_data_clean_monthly.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "id": "314656e2",
   "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>country</th>\n",
       "      <th>iso_code</th>\n",
       "      <th>population</th>\n",
       "      <th>gdp</th>\n",
       "      <th>cement_co2</th>\n",
       "      <th>co2</th>\n",
       "      <th>co2_including_luc</th>\n",
       "      <th>coal_co2</th>\n",
       "      <th>cumulative_cement_co2</th>\n",
       "      <th>cumulative_co2</th>\n",
       "      <th>...</th>\n",
       "      <th>share_global_cumulative_luc_co2</th>\n",
       "      <th>share_global_cumulative_oil_co2</th>\n",
       "      <th>share_global_luc_co2</th>\n",
       "      <th>share_global_oil_co2</th>\n",
       "      <th>share_of_temperature_change_from_ghg</th>\n",
       "      <th>temperature_change_from_ch4</th>\n",
       "      <th>temperature_change_from_co2</th>\n",
       "      <th>temperature_change_from_ghg</th>\n",
       "      <th>temperature_change_from_n2o</th>\n",
       "      <th>output_co2_production</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</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",
       "      <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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1949-01-31</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7356890</td>\n",
       "      <td>9.421400e+09</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.015</td>\n",
       "      <td>8.039</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.015</td>\n",
       "      <td>...</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.160</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.129</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1949-02-28</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7356890</td>\n",
       "      <td>9.421400e+09</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.015</td>\n",
       "      <td>8.039</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.015</td>\n",
       "      <td>...</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.160</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.129</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1949-03-31</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7356890</td>\n",
       "      <td>9.421400e+09</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.015</td>\n",
       "      <td>8.039</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.015</td>\n",
       "      <td>...</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.160</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.129</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1949-04-30</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7356890</td>\n",
       "      <td>9.421400e+09</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.015</td>\n",
       "      <td>8.039</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.015</td>\n",
       "      <td>...</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.160</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.129</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1949-05-31</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7356890</td>\n",
       "      <td>9.421400e+09</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.015</td>\n",
       "      <td>8.039</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.015</td>\n",
       "      <td>...</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.160</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.129</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-30</th>\n",
       "      <td>Sri Lanka</td>\n",
       "      <td>LKA</td>\n",
       "      <td>21715076</td>\n",
       "      <td>2.530000e+11</td>\n",
       "      <td>1.511</td>\n",
       "      <td>21.704</td>\n",
       "      <td>31.743</td>\n",
       "      <td>6.335</td>\n",
       "      <td>24.931</td>\n",
       "      <td>500.266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.379</td>\n",
       "      <td>0.071</td>\n",
       "      <td>0.247</td>\n",
       "      <td>0.124</td>\n",
       "      <td>0.100</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.0</td>\n",
       "      <td>500266000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-31</th>\n",
       "      <td>Sri Lanka</td>\n",
       "      <td>LKA</td>\n",
       "      <td>21715076</td>\n",
       "      <td>2.530000e+11</td>\n",
       "      <td>1.511</td>\n",
       "      <td>21.704</td>\n",
       "      <td>31.743</td>\n",
       "      <td>6.335</td>\n",
       "      <td>24.931</td>\n",
       "      <td>500.266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.379</td>\n",
       "      <td>0.071</td>\n",
       "      <td>0.247</td>\n",
       "      <td>0.124</td>\n",
       "      <td>0.100</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.0</td>\n",
       "      <td>500266000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-30</th>\n",
       "      <td>Sri Lanka</td>\n",
       "      <td>LKA</td>\n",
       "      <td>21715076</td>\n",
       "      <td>2.530000e+11</td>\n",
       "      <td>1.511</td>\n",
       "      <td>21.704</td>\n",
       "      <td>31.743</td>\n",
       "      <td>6.335</td>\n",
       "      <td>24.931</td>\n",
       "      <td>500.266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.379</td>\n",
       "      <td>0.071</td>\n",
       "      <td>0.247</td>\n",
       "      <td>0.124</td>\n",
       "      <td>0.100</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.0</td>\n",
       "      <td>500266000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>Sri Lanka</td>\n",
       "      <td>LKA</td>\n",
       "      <td>21715076</td>\n",
       "      <td>2.530000e+11</td>\n",
       "      <td>1.511</td>\n",
       "      <td>21.704</td>\n",
       "      <td>31.743</td>\n",
       "      <td>6.335</td>\n",
       "      <td>24.931</td>\n",
       "      <td>500.266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.379</td>\n",
       "      <td>0.071</td>\n",
       "      <td>0.247</td>\n",
       "      <td>0.124</td>\n",
       "      <td>0.100</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.0</td>\n",
       "      <td>500266000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-31</th>\n",
       "      <td>Sri Lanka</td>\n",
       "      <td>LKA</td>\n",
       "      <td>21773438</td>\n",
       "      <td>2.530000e+11</td>\n",
       "      <td>1.511</td>\n",
       "      <td>20.781</td>\n",
       "      <td>30.637</td>\n",
       "      <td>6.077</td>\n",
       "      <td>26.442</td>\n",
       "      <td>521.047</td>\n",
       "      <td>...</td>\n",
       "      <td>0.379</td>\n",
       "      <td>0.071</td>\n",
       "      <td>0.250</td>\n",
       "      <td>0.111</td>\n",
       "      <td>0.099</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.0</td>\n",
       "      <td>521046900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6943 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                country iso_code  population           gdp  cement_co2  \\\n",
       "year                                                                     \n",
       "1949-01-31  Afghanistan      AFG     7356890  9.421400e+09       0.018   \n",
       "1949-02-28  Afghanistan      AFG     7356890  9.421400e+09       0.018   \n",
       "1949-03-31  Afghanistan      AFG     7356890  9.421400e+09       0.018   \n",
       "1949-04-30  Afghanistan      AFG     7356890  9.421400e+09       0.018   \n",
       "1949-05-31  Afghanistan      AFG     7356890  9.421400e+09       0.018   \n",
       "...                 ...      ...         ...           ...         ...   \n",
       "2020-09-30    Sri Lanka      LKA    21715076  2.530000e+11       1.511   \n",
       "2020-10-31    Sri Lanka      LKA    21715076  2.530000e+11       1.511   \n",
       "2020-11-30    Sri Lanka      LKA    21715076  2.530000e+11       1.511   \n",
       "2020-12-31    Sri Lanka      LKA    21715076  2.530000e+11       1.511   \n",
       "2021-01-31    Sri Lanka      LKA    21773438  2.530000e+11       1.511   \n",
       "\n",
       "               co2  co2_including_luc  coal_co2  cumulative_cement_co2  \\\n",
       "year                                                                     \n",
       "1949-01-31   0.015              8.039     0.015                  0.018   \n",
       "1949-02-28   0.015              8.039     0.015                  0.018   \n",
       "1949-03-31   0.015              8.039     0.015                  0.018   \n",
       "1949-04-30   0.015              8.039     0.015                  0.018   \n",
       "1949-05-31   0.015              8.039     0.015                  0.018   \n",
       "...            ...                ...       ...                    ...   \n",
       "2020-09-30  21.704             31.743     6.335                 24.931   \n",
       "2020-10-31  21.704             31.743     6.335                 24.931   \n",
       "2020-11-30  21.704             31.743     6.335                 24.931   \n",
       "2020-12-31  21.704             31.743     6.335                 24.931   \n",
       "2021-01-31  20.781             30.637     6.077                 26.442   \n",
       "\n",
       "            cumulative_co2  ...  share_global_cumulative_luc_co2  \\\n",
       "year                        ...                                    \n",
       "1949-01-31           0.015  ...                            0.140   \n",
       "1949-02-28           0.015  ...                            0.140   \n",
       "1949-03-31           0.015  ...                            0.140   \n",
       "1949-04-30           0.015  ...                            0.140   \n",
       "1949-05-31           0.015  ...                            0.140   \n",
       "...                    ...  ...                              ...   \n",
       "2020-09-30         500.266  ...                            0.379   \n",
       "2020-10-31         500.266  ...                            0.379   \n",
       "2020-11-30         500.266  ...                            0.379   \n",
       "2020-12-31         500.266  ...                            0.379   \n",
       "2021-01-31         521.047  ...                            0.379   \n",
       "\n",
       "            share_global_cumulative_oil_co2  share_global_luc_co2  \\\n",
       "year                                                                \n",
       "1949-01-31                            0.000                 0.160   \n",
       "1949-02-28                            0.000                 0.160   \n",
       "1949-03-31                            0.000                 0.160   \n",
       "1949-04-30                            0.000                 0.160   \n",
       "1949-05-31                            0.000                 0.160   \n",
       "...                                     ...                   ...   \n",
       "2020-09-30                            0.071                 0.247   \n",
       "2020-10-31                            0.071                 0.247   \n",
       "2020-11-30                            0.071                 0.247   \n",
       "2020-12-31                            0.071                 0.247   \n",
       "2021-01-31                            0.071                 0.250   \n",
       "\n",
       "            share_global_oil_co2  share_of_temperature_change_from_ghg  \\\n",
       "year                                                                     \n",
       "1949-01-31                 0.000                                 0.129   \n",
       "1949-02-28                 0.000                                 0.129   \n",
       "1949-03-31                 0.000                                 0.129   \n",
       "1949-04-30                 0.000                                 0.129   \n",
       "1949-05-31                 0.000                                 0.129   \n",
       "...                          ...                                   ...   \n",
       "2020-09-30                 0.124                                 0.100   \n",
       "2020-10-31                 0.124                                 0.100   \n",
       "2020-11-30                 0.124                                 0.100   \n",
       "2020-12-31                 0.124                                 0.100   \n",
       "2021-01-31                 0.111                                 0.099   \n",
       "\n",
       "            temperature_change_from_ch4  temperature_change_from_co2  \\\n",
       "year                                                                   \n",
       "1949-01-31                        0.000                        0.000   \n",
       "1949-02-28                        0.000                        0.000   \n",
       "1949-03-31                        0.000                        0.000   \n",
       "1949-04-30                        0.000                        0.000   \n",
       "1949-05-31                        0.000                        0.000   \n",
       "...                                 ...                          ...   \n",
       "2020-09-30                        0.001                        0.001   \n",
       "2020-10-31                        0.001                        0.001   \n",
       "2020-11-30                        0.001                        0.001   \n",
       "2020-12-31                        0.001                        0.001   \n",
       "2021-01-31                        0.001                        0.001   \n",
       "\n",
       "            temperature_change_from_ghg  temperature_change_from_n2o  \\\n",
       "year                                                                   \n",
       "1949-01-31                        0.000                          0.0   \n",
       "1949-02-28                        0.000                          0.0   \n",
       "1949-03-31                        0.000                          0.0   \n",
       "1949-04-30                        0.000                          0.0   \n",
       "1949-05-31                        0.000                          0.0   \n",
       "...                                 ...                          ...   \n",
       "2020-09-30                        0.002                          0.0   \n",
       "2020-10-31                        0.002                          0.0   \n",
       "2020-11-30                        0.002                          0.0   \n",
       "2020-12-31                        0.002                          0.0   \n",
       "2021-01-31                        0.002                          0.0   \n",
       "\n",
       "            output_co2_production  \n",
       "year                               \n",
       "1949-01-31                  14656  \n",
       "1949-02-28                  14656  \n",
       "1949-03-31                  14656  \n",
       "1949-04-30                  14656  \n",
       "1949-05-31                  14656  \n",
       "...                           ...  \n",
       "2020-09-30              500266000  \n",
       "2020-10-31              500266000  \n",
       "2020-11-30              500266000  \n",
       "2020-12-31              500266000  \n",
       "2021-01-31              521046900  \n",
       "\n",
       "[6943 rows x 34 columns]"
      ]
     },
     "execution_count": 246,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_monthly_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6adeb4c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "mnc = co2df.loc[(co2df.country=='Afghanistan')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "71b7e2df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    " \n",
    "timeseries = mnc[[\"output_co2_production\"]].values.astype('float32')\n",
    " \n",
    "plt.plot(timeseries)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d61abb24",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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