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Commit 671d96c2 authored by 8c2481a10dd33818b61b3592d19a3613's avatar 8c2481a10dd33818b61b3592d19a3613
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feat : adding data for whole China

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module3/exo3/exercice.ipynb
View file @ 671d96c2
...@@ -45,7 +45,7 @@ ...@@ -45,7 +45,7 @@
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...@@ -59,7 +59,7 @@ ...@@ -59,7 +59,7 @@
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...@@ -69,7 +69,7 @@ ...@@ -69,7 +69,7 @@
}, },
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{ {
...@@ -1849,7 +1849,7 @@ ...@@ -1849,7 +1849,7 @@
"[266 rows x 132 columns]" "[266 rows x 132 columns]"
] ]
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"execution_count": 19, "execution_count": 3,
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...@@ -1893,7 +1893,8 @@ ...@@ -1893,7 +1893,8 @@
"Cependant, nous ne sommes pas dépendant de ces données, seul les données relatives au pays suivant nous intéresse. \n", "Cependant, nous ne sommes pas dépendant de ces données, seul les données relatives au pays suivant nous intéresse. \n",
"\n", "\n",
"* Belgique \n", "* Belgique \n",
"* Chine - toutes les provinces sauf Hong-Kong (China), Hong Kong (China, Hong-Kong)\n", "* Chine - toutes les provinces sauf Hong-Kong (China),\n",
"* Hong Kong \n",
"* France métropolitaine\n", "* France métropolitaine\n",
"* Allemagne\n", "* Allemagne\n",
"* Iran\n", "* Iran\n",
...@@ -1915,7 +1916,7 @@ ...@@ -1915,7 +1916,7 @@
}, },
{ {
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"execution_count": 34, "execution_count": 4,
"metadata": {}, "metadata": {},
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{ {
...@@ -2005,7 +2006,7 @@ ...@@ -2005,7 +2006,7 @@
"[1 rows x 132 columns]" "[1 rows x 132 columns]"
] ]
}, },
"execution_count": 34, "execution_count": 4,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
...@@ -2020,7 +2021,7 @@ ...@@ -2020,7 +2021,7 @@
}, },
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{ {
...@@ -2137,7 +2138,7 @@ ...@@ -2137,7 +2138,7 @@
"[2 rows x 132 columns]" "[2 rows x 132 columns]"
] ]
}, },
"execution_count": 35, "execution_count": 5,
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} }
...@@ -2157,6 +2158,1438 @@ ...@@ -2157,6 +2158,1438 @@
"source": [ "source": [
"Les mêmes étapes sont utilisées pour le reste des pays manquants, sauf pour la Chine qui nécessite une opération spécial. (Voir ci-dessous)" "Les mêmes étapes sont utilisées pour le reste des pays manquants, sauf pour la Chine qui nécessite une opération spécial. (Voir ci-dessous)"
] ]
},
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"outputs": [
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"text/plain": [
" Province/State Country/Region Lat Long 1/22/20 1/23/20 \\\n",
"23 NaN Belgium 50.8333 4.0000 0 0 \n",
"116 NaN France 46.2276 2.2137 0 0 \n",
"120 NaN Germany 51.0000 9.0000 0 0 \n",
"133 NaN Iran 32.0000 53.0000 0 0 \n",
"137 NaN Italy 43.0000 12.0000 0 0 \n",
"139 NaN Japan 36.0000 138.0000 2 2 \n",
"143 NaN Korea, South 36.0000 128.0000 1 1 \n",
"169 NaN Netherlands 52.1326 5.2913 0 0 \n",
"184 NaN Portugal 39.3999 -8.2245 0 0 \n",
"201 NaN Spain 40.0000 -4.0000 0 0 \n",
"223 NaN United Kingdom 55.3781 -3.4360 0 0 \n",
"225 NaN US 37.0902 -95.7129 1 1 \n",
"\n",
" 1/24/20 1/25/20 1/26/20 1/27/20 ... 5/19/20 5/20/20 5/21/20 \\\n",
"23 0 0 0 0 ... 55791 55983 56235 \n",
"116 2 3 3 3 ... 178428 179069 179306 \n",
"120 0 0 0 1 ... 177778 178473 179021 \n",
"133 0 0 0 0 ... 124603 126949 129341 \n",
"137 0 0 0 0 ... 226699 227364 228006 \n",
"139 2 2 4 4 ... 16367 16367 16424 \n",
"143 2 2 3 4 ... 11110 11122 11142 \n",
"169 0 0 0 0 ... 44249 44447 44700 \n",
"184 0 0 0 0 ... 29432 29660 29912 \n",
"201 0 0 0 0 ... 232037 232555 233037 \n",
"223 0 0 0 0 ... 248818 248293 250908 \n",
"225 2 2 5 5 ... 1528568 1551853 1577147 \n",
"\n",
" 5/22/20 5/23/20 5/24/20 5/25/20 5/26/20 5/27/20 5/28/20 \n",
"23 56511 56810 57092 57342 57455 57592 57849 \n",
"116 179645 179964 179859 180166 179887 180044 183309 \n",
"120 179710 179986 180328 180600 181200 181524 182196 \n",
"133 131652 133521 135701 137724 139511 141591 143849 \n",
"137 228658 229327 229858 230158 230555 231139 231732 \n",
"139 16513 16536 16550 16581 16623 16651 16598 \n",
"143 11165 11190 11206 11225 11265 11344 11402 \n",
"169 44888 45064 45236 45445 45578 45768 45950 \n",
"184 30200 30471 30623 30788 31007 31292 31596 \n",
"201 234824 235290 235772 235400 236259 236259 237906 \n",
"223 254195 257154 259559 261184 265227 267240 269127 \n",
"225 1600937 1622612 1643246 1662302 1680913 1699176 1721753 \n",
"\n",
"[12 rows x 132 columns]"
]
},
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}
],
"source": [
"countries_list= list(['China, Hong-Kong', 'Germany', 'Iran', 'Italy', 'Japan', 'Korea, South', 'Netherlands', 'Portugal', 'Spain', 'United Kingdom', 'US'])\n",
"#print(countries_list)\n",
"\n",
"for country in countries_list : \n",
" dataCountries = dataCountries.append(raw_data.loc[(raw_data['Country/Region'] == country) & (raw_data['Province/State'].isnull())])\n",
"\n",
"dataCountries"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"TODO explain"
]
},
{
"cell_type": "code",
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" <th>49</th>\n",
" <td>Anhui</td>\n",
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" <td>31.8257</td>\n",
" <td>117.2264</td>\n",
" <td>1.0</td>\n",
" <td>9.0</td>\n",
" <td>15.0</td>\n",
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" <tr>\n",
" <th>50</th>\n",
" <td>Beijing</td>\n",
" <td>China</td>\n",
" <td>40.1824</td>\n",
" <td>116.4142</td>\n",
" <td>14.0</td>\n",
" <td>22.0</td>\n",
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" <td>41.0</td>\n",
" <td>68.0</td>\n",
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" <tr>\n",
" <th>51</th>\n",
" <td>Chongqing</td>\n",
" <td>China</td>\n",
" <td>30.0572</td>\n",
" <td>107.8740</td>\n",
" <td>6.0</td>\n",
" <td>9.0</td>\n",
" <td>27.0</td>\n",
" <td>57.0</td>\n",
" <td>75.0</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>52</th>\n",
" <td>Fujian</td>\n",
" <td>China</td>\n",
" <td>26.0789</td>\n",
" <td>117.9874</td>\n",
" <td>1.0</td>\n",
" <td>5.0</td>\n",
" <td>10.0</td>\n",
" <td>18.0</td>\n",
" <td>35.0</td>\n",
" <td>59.0</td>\n",
" <td>...</td>\n",
" <td>356.0</td>\n",
" <td>356.0</td>\n",
" <td>356.0</td>\n",
" <td>356.0</td>\n",
" <td>356.0</td>\n",
" <td>356.0</td>\n",
" <td>357.0</td>\n",
" <td>357.0</td>\n",
" <td>358.0</td>\n",
" <td>358.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>53</th>\n",
" <td>Gansu</td>\n",
" <td>China</td>\n",
" <td>37.8099</td>\n",
" <td>101.0583</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>4.0</td>\n",
" <td>7.0</td>\n",
" <td>14.0</td>\n",
" <td>...</td>\n",
" <td>139.0</td>\n",
" <td>139.0</td>\n",
" <td>139.0</td>\n",
" <td>139.0</td>\n",
" <td>139.0</td>\n",
" <td>139.0</td>\n",
" <td>139.0</td>\n",
" <td>139.0</td>\n",
" <td>139.0</td>\n",
" <td>139.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>54</th>\n",
" <td>Guangdong</td>\n",
" <td>China</td>\n",
" <td>23.3417</td>\n",
" <td>113.4244</td>\n",
" <td>26.0</td>\n",
" <td>32.0</td>\n",
" <td>53.0</td>\n",
" <td>78.0</td>\n",
" <td>111.0</td>\n",
" <td>151.0</td>\n",
" <td>...</td>\n",
" <td>1590.0</td>\n",
" <td>1590.0</td>\n",
" <td>1590.0</td>\n",
" <td>1591.0</td>\n",
" <td>1592.0</td>\n",
" <td>1592.0</td>\n",
" <td>1592.0</td>\n",
" <td>1592.0</td>\n",
" <td>1592.0</td>\n",
" <td>1592.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55</th>\n",
" <td>Guangxi</td>\n",
" <td>China</td>\n",
" <td>23.8298</td>\n",
" <td>108.7881</td>\n",
" <td>2.0</td>\n",
" <td>5.0</td>\n",
" <td>23.0</td>\n",
" <td>23.0</td>\n",
" <td>36.0</td>\n",
" <td>46.0</td>\n",
" <td>...</td>\n",
" <td>254.0</td>\n",
" <td>254.0</td>\n",
" <td>254.0</td>\n",
" <td>254.0</td>\n",
" <td>254.0</td>\n",
" <td>254.0</td>\n",
" <td>254.0</td>\n",
" <td>254.0</td>\n",
" <td>254.0</td>\n",
" <td>254.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>56</th>\n",
" <td>Guizhou</td>\n",
" <td>China</td>\n",
" <td>26.8154</td>\n",
" <td>106.8748</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>5.0</td>\n",
" <td>7.0</td>\n",
" <td>...</td>\n",
" <td>147.0</td>\n",
" <td>147.0</td>\n",
" <td>147.0</td>\n",
" <td>147.0</td>\n",
" <td>147.0</td>\n",
" <td>147.0</td>\n",
" <td>147.0</td>\n",
" <td>147.0</td>\n",
" <td>147.0</td>\n",
" <td>147.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>57</th>\n",
" <td>Hainan</td>\n",
" <td>China</td>\n",
" <td>19.1959</td>\n",
" <td>109.7453</td>\n",
" <td>4.0</td>\n",
" <td>5.0</td>\n",
" <td>8.0</td>\n",
" <td>19.0</td>\n",
" <td>22.0</td>\n",
" <td>33.0</td>\n",
" <td>...</td>\n",
" <td>169.0</td>\n",
" <td>169.0</td>\n",
" <td>169.0</td>\n",
" <td>169.0</td>\n",
" <td>169.0</td>\n",
" <td>169.0</td>\n",
" <td>169.0</td>\n",
" <td>169.0</td>\n",
" <td>169.0</td>\n",
" <td>169.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>58</th>\n",
" <td>Hebei</td>\n",
" <td>China</td>\n",
" <td>39.5490</td>\n",
" <td>116.1306</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>8.0</td>\n",
" <td>13.0</td>\n",
" <td>18.0</td>\n",
" <td>...</td>\n",
" <td>328.0</td>\n",
" <td>328.0</td>\n",
" <td>328.0</td>\n",
" <td>328.0</td>\n",
" <td>328.0</td>\n",
" <td>328.0</td>\n",
" <td>328.0</td>\n",
" <td>328.0</td>\n",
" <td>328.0</td>\n",
" <td>328.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>59</th>\n",
" <td>Heilongjiang</td>\n",
" <td>China</td>\n",
" <td>47.8620</td>\n",
" <td>127.7615</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>4.0</td>\n",
" <td>9.0</td>\n",
" <td>15.0</td>\n",
" <td>21.0</td>\n",
" <td>...</td>\n",
" <td>945.0</td>\n",
" <td>945.0</td>\n",
" <td>945.0</td>\n",
" <td>945.0</td>\n",
" <td>945.0</td>\n",
" <td>945.0</td>\n",
" <td>945.0</td>\n",
" <td>945.0</td>\n",
" <td>945.0</td>\n",
" <td>945.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60</th>\n",
" <td>Henan</td>\n",
" <td>China</td>\n",
" <td>33.8820</td>\n",
" <td>113.6140</td>\n",
" <td>5.0</td>\n",
" <td>5.0</td>\n",
" <td>9.0</td>\n",
" <td>32.0</td>\n",
" <td>83.0</td>\n",
" <td>128.0</td>\n",
" <td>...</td>\n",
" <td>1276.0</td>\n",
" <td>1276.0</td>\n",
" <td>1276.0</td>\n",
" <td>1276.0</td>\n",
" <td>1276.0</td>\n",
" <td>1276.0</td>\n",
" <td>1276.0</td>\n",
" <td>1276.0</td>\n",
" <td>1276.0</td>\n",
" <td>1276.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>61</th>\n",
" <td>Hong Kong</td>\n",
" <td>China</td>\n",
" <td>22.3000</td>\n",
" <td>114.2000</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>5.0</td>\n",
" <td>8.0</td>\n",
" <td>8.0</td>\n",
" <td>...</td>\n",
" <td>1055.0</td>\n",
" <td>1055.0</td>\n",
" <td>1055.0</td>\n",
" <td>1065.0</td>\n",
" <td>1065.0</td>\n",
" <td>1065.0</td>\n",
" <td>1065.0</td>\n",
" <td>1065.0</td>\n",
" <td>1066.0</td>\n",
" <td>1066.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>62</th>\n",
" <td>Hubei</td>\n",
" <td>China</td>\n",
" <td>30.9756</td>\n",
" <td>112.2707</td>\n",
" <td>444.0</td>\n",
" <td>444.0</td>\n",
" <td>549.0</td>\n",
" <td>761.0</td>\n",
" <td>1058.0</td>\n",
" <td>1423.0</td>\n",
" <td>...</td>\n",
" <td>68135.0</td>\n",
" <td>68135.0</td>\n",
" <td>68135.0</td>\n",
" <td>68135.0</td>\n",
" <td>68135.0</td>\n",
" <td>68135.0</td>\n",
" <td>68135.0</td>\n",
" <td>68135.0</td>\n",
" <td>68135.0</td>\n",
" <td>68135.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>63</th>\n",
" <td>Hunan</td>\n",
" <td>China</td>\n",
" <td>27.6104</td>\n",
" <td>111.7088</td>\n",
" <td>4.0</td>\n",
" <td>9.0</td>\n",
" <td>24.0</td>\n",
" <td>43.0</td>\n",
" <td>69.0</td>\n",
" <td>100.0</td>\n",
" <td>...</td>\n",
" <td>1019.0</td>\n",
" <td>1019.0</td>\n",
" <td>1019.0</td>\n",
" <td>1019.0</td>\n",
" <td>1019.0</td>\n",
" <td>1019.0</td>\n",
" <td>1019.0</td>\n",
" <td>1019.0</td>\n",
" <td>1019.0</td>\n",
" <td>1019.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>64</th>\n",
" <td>Inner Mongolia</td>\n",
" <td>China</td>\n",
" <td>44.0935</td>\n",
" <td>113.9448</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>7.0</td>\n",
" <td>7.0</td>\n",
" <td>11.0</td>\n",
" <td>...</td>\n",
" <td>216.0</td>\n",
" <td>216.0</td>\n",
" <td>216.0</td>\n",
" <td>217.0</td>\n",
" <td>217.0</td>\n",
" <td>227.0</td>\n",
" <td>232.0</td>\n",
" <td>232.0</td>\n",
" <td>232.0</td>\n",
" <td>232.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>65</th>\n",
" <td>Jiangsu</td>\n",
" <td>China</td>\n",
" <td>32.9711</td>\n",
" <td>119.4550</td>\n",
" <td>1.0</td>\n",
" <td>5.0</td>\n",
" <td>9.0</td>\n",
" <td>18.0</td>\n",
" <td>33.0</td>\n",
" <td>47.0</td>\n",
" <td>...</td>\n",
" <td>653.0</td>\n",
" <td>653.0</td>\n",
" <td>653.0</td>\n",
" <td>653.0</td>\n",
" <td>653.0</td>\n",
" <td>653.0</td>\n",
" <td>653.0</td>\n",
" <td>653.0</td>\n",
" <td>653.0</td>\n",
" <td>653.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>66</th>\n",
" <td>Jiangxi</td>\n",
" <td>China</td>\n",
" <td>27.6140</td>\n",
" <td>115.7221</td>\n",
" <td>2.0</td>\n",
" <td>7.0</td>\n",
" <td>18.0</td>\n",
" <td>18.0</td>\n",
" <td>36.0</td>\n",
" <td>72.0</td>\n",
" <td>...</td>\n",
" <td>937.0</td>\n",
" <td>937.0</td>\n",
" <td>937.0</td>\n",
" <td>937.0</td>\n",
" <td>937.0</td>\n",
" <td>937.0</td>\n",
" <td>937.0</td>\n",
" <td>937.0</td>\n",
" <td>937.0</td>\n",
" <td>937.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>67</th>\n",
" <td>Jilin</td>\n",
" <td>China</td>\n",
" <td>43.6661</td>\n",
" <td>126.1923</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>6.0</td>\n",
" <td>...</td>\n",
" <td>151.0</td>\n",
" <td>151.0</td>\n",
" <td>151.0</td>\n",
" <td>154.0</td>\n",
" <td>155.0</td>\n",
" <td>155.0</td>\n",
" <td>155.0</td>\n",
" <td>155.0</td>\n",
" <td>155.0</td>\n",
" <td>155.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>68</th>\n",
" <td>Liaoning</td>\n",
" <td>China</td>\n",
" <td>41.2956</td>\n",
" <td>122.6085</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>17.0</td>\n",
" <td>21.0</td>\n",
" <td>27.0</td>\n",
" <td>...</td>\n",
" <td>149.0</td>\n",
" <td>149.0</td>\n",
" <td>149.0</td>\n",
" <td>149.0</td>\n",
" <td>149.0</td>\n",
" <td>149.0</td>\n",
" <td>149.0</td>\n",
" <td>149.0</td>\n",
" <td>149.0</td>\n",
" <td>149.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>69</th>\n",
" <td>Macau</td>\n",
" <td>China</td>\n",
" <td>22.1667</td>\n",
" <td>113.5500</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>5.0</td>\n",
" <td>6.0</td>\n",
" <td>...</td>\n",
" <td>45.0</td>\n",
" <td>45.0</td>\n",
" <td>45.0</td>\n",
" <td>45.0</td>\n",
" <td>45.0</td>\n",
" <td>45.0</td>\n",
" <td>45.0</td>\n",
" <td>45.0</td>\n",
" <td>45.0</td>\n",
" <td>45.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>70</th>\n",
" <td>Ningxia</td>\n",
" <td>China</td>\n",
" <td>37.2692</td>\n",
" <td>106.1655</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>7.0</td>\n",
" <td>...</td>\n",
" <td>75.0</td>\n",
" <td>75.0</td>\n",
" <td>75.0</td>\n",
" <td>75.0</td>\n",
" <td>75.0</td>\n",
" <td>75.0</td>\n",
" <td>75.0</td>\n",
" <td>75.0</td>\n",
" <td>75.0</td>\n",
" <td>75.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>71</th>\n",
" <td>Qinghai</td>\n",
" <td>China</td>\n",
" <td>35.7452</td>\n",
" <td>95.9956</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>6.0</td>\n",
" <td>...</td>\n",
" <td>18.0</td>\n",
" <td>18.0</td>\n",
" <td>18.0</td>\n",
" <td>18.0</td>\n",
" <td>18.0</td>\n",
" <td>18.0</td>\n",
" <td>18.0</td>\n",
" <td>18.0</td>\n",
" <td>18.0</td>\n",
" <td>18.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>72</th>\n",
" <td>Shaanxi</td>\n",
" <td>China</td>\n",
" <td>35.1917</td>\n",
" <td>108.8701</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>5.0</td>\n",
" <td>15.0</td>\n",
" <td>22.0</td>\n",
" <td>35.0</td>\n",
" <td>...</td>\n",
" <td>308.0</td>\n",
" <td>308.0</td>\n",
" <td>308.0</td>\n",
" <td>308.0</td>\n",
" <td>308.0</td>\n",
" <td>308.0</td>\n",
" <td>308.0</td>\n",
" <td>308.0</td>\n",
" <td>308.0</td>\n",
" <td>308.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>73</th>\n",
" <td>Shandong</td>\n",
" <td>China</td>\n",
" <td>36.3427</td>\n",
" <td>118.1498</td>\n",
" <td>2.0</td>\n",
" <td>6.0</td>\n",
" <td>15.0</td>\n",
" <td>27.0</td>\n",
" <td>46.0</td>\n",
" <td>75.0</td>\n",
" <td>...</td>\n",
" <td>788.0</td>\n",
" <td>788.0</td>\n",
" <td>788.0</td>\n",
" <td>788.0</td>\n",
" <td>788.0</td>\n",
" <td>788.0</td>\n",
" <td>788.0</td>\n",
" <td>788.0</td>\n",
" <td>788.0</td>\n",
" <td>788.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>74</th>\n",
" <td>Shanghai</td>\n",
" <td>China</td>\n",
" <td>31.2020</td>\n",
" <td>121.4491</td>\n",
" <td>9.0</td>\n",
" <td>16.0</td>\n",
" <td>20.0</td>\n",
" <td>33.0</td>\n",
" <td>40.0</td>\n",
" <td>53.0</td>\n",
" <td>...</td>\n",
" <td>666.0</td>\n",
" <td>666.0</td>\n",
" <td>666.0</td>\n",
" <td>667.0</td>\n",
" <td>668.0</td>\n",
" <td>668.0</td>\n",
" <td>669.0</td>\n",
" <td>670.0</td>\n",
" <td>671.0</td>\n",
" <td>671.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75</th>\n",
" <td>Shanxi</td>\n",
" <td>China</td>\n",
" <td>37.5777</td>\n",
" <td>112.2922</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>6.0</td>\n",
" <td>9.0</td>\n",
" <td>13.0</td>\n",
" <td>...</td>\n",
" <td>198.0</td>\n",
" <td>198.0</td>\n",
" <td>198.0</td>\n",
" <td>198.0</td>\n",
" <td>198.0</td>\n",
" <td>198.0</td>\n",
" <td>198.0</td>\n",
" <td>198.0</td>\n",
" <td>198.0</td>\n",
" <td>198.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>76</th>\n",
" <td>Sichuan</td>\n",
" <td>China</td>\n",
" <td>30.6171</td>\n",
" <td>102.7103</td>\n",
" <td>5.0</td>\n",
" <td>8.0</td>\n",
" <td>15.0</td>\n",
" <td>28.0</td>\n",
" <td>44.0</td>\n",
" <td>69.0</td>\n",
" <td>...</td>\n",
" <td>561.0</td>\n",
" <td>561.0</td>\n",
" <td>561.0</td>\n",
" <td>563.0</td>\n",
" <td>563.0</td>\n",
" <td>564.0</td>\n",
" <td>564.0</td>\n",
" <td>564.0</td>\n",
" <td>564.0</td>\n",
" <td>564.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>77</th>\n",
" <td>Tianjin</td>\n",
" <td>China</td>\n",
" <td>39.3054</td>\n",
" <td>117.3230</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>8.0</td>\n",
" <td>10.0</td>\n",
" <td>14.0</td>\n",
" <td>23.0</td>\n",
" <td>...</td>\n",
" <td>192.0</td>\n",
" <td>192.0</td>\n",
" <td>192.0</td>\n",
" <td>192.0</td>\n",
" <td>192.0</td>\n",
" <td>192.0</td>\n",
" <td>192.0</td>\n",
" <td>192.0</td>\n",
" <td>192.0</td>\n",
" <td>192.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>78</th>\n",
" <td>Tibet</td>\n",
" <td>China</td>\n",
" <td>31.6927</td>\n",
" <td>88.0924</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>79</th>\n",
" <td>Xinjiang</td>\n",
" <td>China</td>\n",
" <td>41.1129</td>\n",
" <td>85.2401</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>5.0</td>\n",
" <td>...</td>\n",
" <td>76.0</td>\n",
" <td>76.0</td>\n",
" <td>76.0</td>\n",
" <td>76.0</td>\n",
" <td>76.0</td>\n",
" <td>76.0</td>\n",
" <td>76.0</td>\n",
" <td>76.0</td>\n",
" <td>76.0</td>\n",
" <td>76.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>80</th>\n",
" <td>Yunnan</td>\n",
" <td>China</td>\n",
" <td>24.9740</td>\n",
" <td>101.4870</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>5.0</td>\n",
" <td>11.0</td>\n",
" <td>16.0</td>\n",
" <td>26.0</td>\n",
" <td>...</td>\n",
" <td>185.0</td>\n",
" <td>185.0</td>\n",
" <td>185.0</td>\n",
" <td>185.0</td>\n",
" <td>185.0</td>\n",
" <td>185.0</td>\n",
" <td>185.0</td>\n",
" <td>185.0</td>\n",
" <td>185.0</td>\n",
" <td>185.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>81</th>\n",
" <td>Zhejiang</td>\n",
" <td>China</td>\n",
" <td>29.1832</td>\n",
" <td>120.0934</td>\n",
" <td>10.0</td>\n",
" <td>27.0</td>\n",
" <td>43.0</td>\n",
" <td>62.0</td>\n",
" <td>104.0</td>\n",
" <td>128.0</td>\n",
" <td>...</td>\n",
" <td>1268.0</td>\n",
" <td>1268.0</td>\n",
" <td>1268.0</td>\n",
" <td>1268.0</td>\n",
" <td>1268.0</td>\n",
" <td>1268.0</td>\n",
" <td>1268.0</td>\n",
" <td>1268.0</td>\n",
" <td>1268.0</td>\n",
" <td>1268.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>NaN</td>\n",
" <td>China</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>548.0</td>\n",
" <td>643.0</td>\n",
" <td>920.0</td>\n",
" <td>1406.0</td>\n",
" <td>2075.0</td>\n",
" <td>2877.0</td>\n",
" <td>...</td>\n",
" <td>84063.0</td>\n",
" <td>84063.0</td>\n",
" <td>84063.0</td>\n",
" <td>84081.0</td>\n",
" <td>84084.0</td>\n",
" <td>84095.0</td>\n",
" <td>84102.0</td>\n",
" <td>84103.0</td>\n",
" <td>84106.0</td>\n",
" <td>84106.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>34 rows × 132 columns</p>\n",
"</div>"
],
"text/plain": [
" Province/State Country/Region Lat Long 1/22/20 1/23/20 \\\n",
"49 Anhui China 31.8257 117.2264 1.0 9.0 \n",
"50 Beijing China 40.1824 116.4142 14.0 22.0 \n",
"51 Chongqing China 30.0572 107.8740 6.0 9.0 \n",
"52 Fujian China 26.0789 117.9874 1.0 5.0 \n",
"53 Gansu China 37.8099 101.0583 0.0 2.0 \n",
"54 Guangdong China 23.3417 113.4244 26.0 32.0 \n",
"55 Guangxi China 23.8298 108.7881 2.0 5.0 \n",
"56 Guizhou China 26.8154 106.8748 1.0 3.0 \n",
"57 Hainan China 19.1959 109.7453 4.0 5.0 \n",
"58 Hebei China 39.5490 116.1306 1.0 1.0 \n",
"59 Heilongjiang China 47.8620 127.7615 0.0 2.0 \n",
"60 Henan China 33.8820 113.6140 5.0 5.0 \n",
"61 Hong Kong China 22.3000 114.2000 0.0 2.0 \n",
"62 Hubei China 30.9756 112.2707 444.0 444.0 \n",
"63 Hunan China 27.6104 111.7088 4.0 9.0 \n",
"64 Inner Mongolia China 44.0935 113.9448 0.0 0.0 \n",
"65 Jiangsu China 32.9711 119.4550 1.0 5.0 \n",
"66 Jiangxi China 27.6140 115.7221 2.0 7.0 \n",
"67 Jilin China 43.6661 126.1923 0.0 1.0 \n",
"68 Liaoning China 41.2956 122.6085 2.0 3.0 \n",
"69 Macau China 22.1667 113.5500 1.0 2.0 \n",
"70 Ningxia China 37.2692 106.1655 1.0 1.0 \n",
"71 Qinghai China 35.7452 95.9956 0.0 0.0 \n",
"72 Shaanxi China 35.1917 108.8701 0.0 3.0 \n",
"73 Shandong China 36.3427 118.1498 2.0 6.0 \n",
"74 Shanghai China 31.2020 121.4491 9.0 16.0 \n",
"75 Shanxi China 37.5777 112.2922 1.0 1.0 \n",
"76 Sichuan China 30.6171 102.7103 5.0 8.0 \n",
"77 Tianjin China 39.3054 117.3230 4.0 4.0 \n",
"78 Tibet China 31.6927 88.0924 0.0 0.0 \n",
"79 Xinjiang China 41.1129 85.2401 0.0 2.0 \n",
"80 Yunnan China 24.9740 101.4870 1.0 2.0 \n",
"81 Zhejiang China 29.1832 120.0934 10.0 27.0 \n",
"1 NaN China NaN NaN 548.0 643.0 \n",
"\n",
" 1/24/20 1/25/20 1/26/20 1/27/20 ... 5/19/20 5/20/20 5/21/20 \\\n",
"49 15.0 39.0 60.0 70.0 ... 991.0 991.0 991.0 \n",
"50 36.0 41.0 68.0 80.0 ... 593.0 593.0 593.0 \n",
"51 27.0 57.0 75.0 110.0 ... 579.0 579.0 579.0 \n",
"52 10.0 18.0 35.0 59.0 ... 356.0 356.0 356.0 \n",
"53 2.0 4.0 7.0 14.0 ... 139.0 139.0 139.0 \n",
"54 53.0 78.0 111.0 151.0 ... 1590.0 1590.0 1590.0 \n",
"55 23.0 23.0 36.0 46.0 ... 254.0 254.0 254.0 \n",
"56 3.0 4.0 5.0 7.0 ... 147.0 147.0 147.0 \n",
"57 8.0 19.0 22.0 33.0 ... 169.0 169.0 169.0 \n",
"58 2.0 8.0 13.0 18.0 ... 328.0 328.0 328.0 \n",
"59 4.0 9.0 15.0 21.0 ... 945.0 945.0 945.0 \n",
"60 9.0 32.0 83.0 128.0 ... 1276.0 1276.0 1276.0 \n",
"61 2.0 5.0 8.0 8.0 ... 1055.0 1055.0 1055.0 \n",
"62 549.0 761.0 1058.0 1423.0 ... 68135.0 68135.0 68135.0 \n",
"63 24.0 43.0 69.0 100.0 ... 1019.0 1019.0 1019.0 \n",
"64 1.0 7.0 7.0 11.0 ... 216.0 216.0 216.0 \n",
"65 9.0 18.0 33.0 47.0 ... 653.0 653.0 653.0 \n",
"66 18.0 18.0 36.0 72.0 ... 937.0 937.0 937.0 \n",
"67 3.0 4.0 4.0 6.0 ... 151.0 151.0 151.0 \n",
"68 4.0 17.0 21.0 27.0 ... 149.0 149.0 149.0 \n",
"69 2.0 2.0 5.0 6.0 ... 45.0 45.0 45.0 \n",
"70 2.0 3.0 4.0 7.0 ... 75.0 75.0 75.0 \n",
"71 0.0 1.0 1.0 6.0 ... 18.0 18.0 18.0 \n",
"72 5.0 15.0 22.0 35.0 ... 308.0 308.0 308.0 \n",
"73 15.0 27.0 46.0 75.0 ... 788.0 788.0 788.0 \n",
"74 20.0 33.0 40.0 53.0 ... 666.0 666.0 666.0 \n",
"75 1.0 6.0 9.0 13.0 ... 198.0 198.0 198.0 \n",
"76 15.0 28.0 44.0 69.0 ... 561.0 561.0 561.0 \n",
"77 8.0 10.0 14.0 23.0 ... 192.0 192.0 192.0 \n",
"78 0.0 0.0 0.0 0.0 ... 1.0 1.0 1.0 \n",
"79 2.0 3.0 4.0 5.0 ... 76.0 76.0 76.0 \n",
"80 5.0 11.0 16.0 26.0 ... 185.0 185.0 185.0 \n",
"81 43.0 62.0 104.0 128.0 ... 1268.0 1268.0 1268.0 \n",
"1 920.0 1406.0 2075.0 2877.0 ... 84063.0 84063.0 84063.0 \n",
"\n",
" 5/22/20 5/23/20 5/24/20 5/25/20 5/26/20 5/27/20 5/28/20 \n",
"49 991.0 991.0 991.0 991.0 991.0 991.0 991.0 \n",
"50 593.0 593.0 593.0 593.0 593.0 593.0 593.0 \n",
"51 579.0 579.0 579.0 579.0 579.0 579.0 579.0 \n",
"52 356.0 356.0 356.0 357.0 357.0 358.0 358.0 \n",
"53 139.0 139.0 139.0 139.0 139.0 139.0 139.0 \n",
"54 1591.0 1592.0 1592.0 1592.0 1592.0 1592.0 1592.0 \n",
"55 254.0 254.0 254.0 254.0 254.0 254.0 254.0 \n",
"56 147.0 147.0 147.0 147.0 147.0 147.0 147.0 \n",
"57 169.0 169.0 169.0 169.0 169.0 169.0 169.0 \n",
"58 328.0 328.0 328.0 328.0 328.0 328.0 328.0 \n",
"59 945.0 945.0 945.0 945.0 945.0 945.0 945.0 \n",
"60 1276.0 1276.0 1276.0 1276.0 1276.0 1276.0 1276.0 \n",
"61 1065.0 1065.0 1065.0 1065.0 1065.0 1066.0 1066.0 \n",
"62 68135.0 68135.0 68135.0 68135.0 68135.0 68135.0 68135.0 \n",
"63 1019.0 1019.0 1019.0 1019.0 1019.0 1019.0 1019.0 \n",
"64 217.0 217.0 227.0 232.0 232.0 232.0 232.0 \n",
"65 653.0 653.0 653.0 653.0 653.0 653.0 653.0 \n",
"66 937.0 937.0 937.0 937.0 937.0 937.0 937.0 \n",
"67 154.0 155.0 155.0 155.0 155.0 155.0 155.0 \n",
"68 149.0 149.0 149.0 149.0 149.0 149.0 149.0 \n",
"69 45.0 45.0 45.0 45.0 45.0 45.0 45.0 \n",
"70 75.0 75.0 75.0 75.0 75.0 75.0 75.0 \n",
"71 18.0 18.0 18.0 18.0 18.0 18.0 18.0 \n",
"72 308.0 308.0 308.0 308.0 308.0 308.0 308.0 \n",
"73 788.0 788.0 788.0 788.0 788.0 788.0 788.0 \n",
"74 667.0 668.0 668.0 669.0 670.0 671.0 671.0 \n",
"75 198.0 198.0 198.0 198.0 198.0 198.0 198.0 \n",
"76 563.0 563.0 564.0 564.0 564.0 564.0 564.0 \n",
"77 192.0 192.0 192.0 192.0 192.0 192.0 192.0 \n",
"78 1.0 1.0 1.0 1.0 1.0 1.0 1.0 \n",
"79 76.0 76.0 76.0 76.0 76.0 76.0 76.0 \n",
"80 185.0 185.0 185.0 185.0 185.0 185.0 185.0 \n",
"81 1268.0 1268.0 1268.0 1268.0 1268.0 1268.0 1268.0 \n",
"1 84081.0 84084.0 84095.0 84102.0 84103.0 84106.0 84106.0 \n",
"\n",
"[34 rows x 132 columns]"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# For china the data have to be summed between region in order to get the results for the whole country.\n",
"dataChina = raw_data.loc[(raw_data['Country/Region'] == 'China')]\n",
"\n",
"#print(dataChina)\n",
"\n",
"#let's use df.sum() to sum rows \n",
"col_list= list(dataChina)\n",
"col_list.remove(\"Province/State\")\n",
"col_list.remove(\"Country/Region\")\n",
"col_list.remove(\"Lat\")\n",
"col_list.remove(\"Long\")\n",
"\n",
"\n",
"\n",
"for col in col_list: \n",
" dataChina.at['1', col] = dataChina[col].sum()\n",
"\n",
"\n",
"dataChina.at['1', \"Country/Region\"] = \"China\"\n",
"\n",
"dataChina"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
} }
], ],
"metadata": { "metadata": {
......
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