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Commit aba8d83e authored by 335f5f369755e7a506491c0327a7d5ee's avatar 335f5f369755e7a506491c0327a7d5ee
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done with pandas

parent 1524a336
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module3/exo1/analyse-syndrome-grippal.ipynb
View file @ aba8d83e
...@@ -9,14 +9,16 @@ ...@@ -9,14 +9,16 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 21,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"%matplotlib inline\n", "%matplotlib inline\n",
"import matplotlib.pyplot as plt\n", "import matplotlib.pyplot as plt\n",
"import pandas as pd\n", "import pandas as pd\n",
"import isoweek" "import isoweek\n",
"import os.path\n",
"from os import path\n"
] ]
}, },
{ {
...@@ -28,15 +30,42 @@ ...@@ -28,15 +30,42 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 22,
"metadata": { "metadata": {},
"collapsed": true
},
"outputs": [], "outputs": [],
"source": [ "source": [
"data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\""
] ]
}, },
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"file already exist\n"
]
}
],
"source": [
"if not path.exists(\"incidence-PAY-3_downloaded.csv\"):\n",
" print(\"file do not exist , downloading...\")\n",
" #req = requests.get(csv_url)\n",
"\n",
" #url_content = req.content\n",
" #csv_file = open('incidence-PAY-3_downloaded.csv', 'wb')\n",
" #csv_file.write(url_content)\n",
" #csv_file.close()\n",
" pd.read_csv(data_url,encoding='latin-1').to_csv(\"incidence-PAY-3_downloaded.csv\")\n",
" print(\"saved\")\n",
" \n",
"else:\n",
" print(\"file already exist\")"
]
},
{ {
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
...@@ -61,11 +90,1351 @@ ...@@ -61,11 +90,1351 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 24,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
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" <tr>\n",
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" <td>27</td>\n",
" <td>202021</td>\n",
" <td>3</td>\n",
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" <td>8202.0</td>\n",
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" <tr>\n",
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" <td>30</td>\n",
" <td>202018</td>\n",
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" <td>19945.0</td>\n",
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" <td>20.0</td>\n",
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" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1852</th>\n",
" <td>1853</td>\n",
" <td>198521</td>\n",
" <td>3</td>\n",
" <td>26096</td>\n",
" <td>19621.0</td>\n",
" <td>32571.0</td>\n",
" <td>47</td>\n",
" <td>35.0</td>\n",
" <td>59.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1853</th>\n",
" <td>1854</td>\n",
" <td>198520</td>\n",
" <td>3</td>\n",
" <td>27896</td>\n",
" <td>20885.0</td>\n",
" <td>34907.0</td>\n",
" <td>51</td>\n",
" <td>38.0</td>\n",
" <td>64.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1854</th>\n",
" <td>1855</td>\n",
" <td>198519</td>\n",
" <td>3</td>\n",
" <td>43154</td>\n",
" <td>32821.0</td>\n",
" <td>53487.0</td>\n",
" <td>78</td>\n",
" <td>59.0</td>\n",
" <td>97.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1855</th>\n",
" <td>1856</td>\n",
" <td>198518</td>\n",
" <td>3</td>\n",
" <td>40555</td>\n",
" <td>29935.0</td>\n",
" <td>51175.0</td>\n",
" <td>74</td>\n",
" <td>55.0</td>\n",
" <td>93.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1856</th>\n",
" <td>1857</td>\n",
" <td>198517</td>\n",
" <td>3</td>\n",
" <td>34053</td>\n",
" <td>24366.0</td>\n",
" <td>43740.0</td>\n",
" <td>62</td>\n",
" <td>44.0</td>\n",
" <td>80.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1857</th>\n",
" <td>1858</td>\n",
" <td>198516</td>\n",
" <td>3</td>\n",
" <td>50362</td>\n",
" <td>36451.0</td>\n",
" <td>64273.0</td>\n",
" <td>91</td>\n",
" <td>66.0</td>\n",
" <td>116.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1858</th>\n",
" <td>1859</td>\n",
" <td>198515</td>\n",
" <td>3</td>\n",
" <td>63881</td>\n",
" <td>45538.0</td>\n",
" <td>82224.0</td>\n",
" <td>116</td>\n",
" <td>83.0</td>\n",
" <td>149.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1859</th>\n",
" <td>1860</td>\n",
" <td>198514</td>\n",
" <td>3</td>\n",
" <td>134545</td>\n",
" <td>114400.0</td>\n",
" <td>154690.0</td>\n",
" <td>244</td>\n",
" <td>207.0</td>\n",
" <td>281.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1860</th>\n",
" <td>1861</td>\n",
" <td>198513</td>\n",
" <td>3</td>\n",
" <td>197206</td>\n",
" <td>176080.0</td>\n",
" <td>218332.0</td>\n",
" <td>357</td>\n",
" <td>319.0</td>\n",
" <td>395.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1861</th>\n",
" <td>1862</td>\n",
" <td>198512</td>\n",
" <td>3</td>\n",
" <td>245240</td>\n",
" <td>223304.0</td>\n",
" <td>267176.0</td>\n",
" <td>445</td>\n",
" <td>405.0</td>\n",
" <td>485.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1862</th>\n",
" <td>1863</td>\n",
" <td>198511</td>\n",
" <td>3</td>\n",
" <td>276205</td>\n",
" <td>252399.0</td>\n",
" <td>300011.0</td>\n",
" <td>501</td>\n",
" <td>458.0</td>\n",
" <td>544.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1863</th>\n",
" <td>1864</td>\n",
" <td>198510</td>\n",
" <td>3</td>\n",
" <td>353231</td>\n",
" <td>326279.0</td>\n",
" <td>380183.0</td>\n",
" <td>640</td>\n",
" <td>591.0</td>\n",
" <td>689.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1864</th>\n",
" <td>1865</td>\n",
" <td>198509</td>\n",
" <td>3</td>\n",
" <td>369895</td>\n",
" <td>341109.0</td>\n",
" <td>398681.0</td>\n",
" <td>670</td>\n",
" <td>618.0</td>\n",
" <td>722.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1865</th>\n",
" <td>1866</td>\n",
" <td>198508</td>\n",
" <td>3</td>\n",
" <td>389886</td>\n",
" <td>359529.0</td>\n",
" <td>420243.0</td>\n",
" <td>707</td>\n",
" <td>652.0</td>\n",
" <td>762.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1866</th>\n",
" <td>1867</td>\n",
" <td>198507</td>\n",
" <td>3</td>\n",
" <td>471852</td>\n",
" <td>432599.0</td>\n",
" <td>511105.0</td>\n",
" <td>855</td>\n",
" <td>784.0</td>\n",
" <td>926.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1867</th>\n",
" <td>1868</td>\n",
" <td>198506</td>\n",
" <td>3</td>\n",
" <td>565825</td>\n",
" <td>518011.0</td>\n",
" <td>613639.0</td>\n",
" <td>1026</td>\n",
" <td>939.0</td>\n",
" <td>1113.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1868</th>\n",
" <td>1869</td>\n",
" <td>198505</td>\n",
" <td>3</td>\n",
" <td>637302</td>\n",
" <td>592795.0</td>\n",
" <td>681809.0</td>\n",
" <td>1155</td>\n",
" <td>1074.0</td>\n",
" <td>1236.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1869</th>\n",
" <td>1870</td>\n",
" <td>198504</td>\n",
" <td>3</td>\n",
" <td>424937</td>\n",
" <td>390794.0</td>\n",
" <td>459080.0</td>\n",
" <td>770</td>\n",
" <td>708.0</td>\n",
" <td>832.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1870</th>\n",
" <td>1871</td>\n",
" <td>198503</td>\n",
" <td>3</td>\n",
" <td>213901</td>\n",
" <td>174689.0</td>\n",
" <td>253113.0</td>\n",
" <td>388</td>\n",
" <td>317.0</td>\n",
" <td>459.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1871</th>\n",
" <td>1872</td>\n",
" <td>198502</td>\n",
" <td>3</td>\n",
" <td>97586</td>\n",
" <td>80949.0</td>\n",
" <td>114223.0</td>\n",
" <td>177</td>\n",
" <td>147.0</td>\n",
" <td>207.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1872</th>\n",
" <td>1873</td>\n",
" <td>198501</td>\n",
" <td>3</td>\n",
" <td>85489</td>\n",
" <td>65918.0</td>\n",
" <td>105060.0</td>\n",
" <td>155</td>\n",
" <td>120.0</td>\n",
" <td>190.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1873</th>\n",
" <td>1874</td>\n",
" <td>198452</td>\n",
" <td>3</td>\n",
" <td>84830</td>\n",
" <td>60602.0</td>\n",
" <td>109058.0</td>\n",
" <td>154</td>\n",
" <td>110.0</td>\n",
" <td>198.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1874</th>\n",
" <td>1875</td>\n",
" <td>198451</td>\n",
" <td>3</td>\n",
" <td>101726</td>\n",
" <td>80242.0</td>\n",
" <td>123210.0</td>\n",
" <td>185</td>\n",
" <td>146.0</td>\n",
" <td>224.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1875</th>\n",
" <td>1876</td>\n",
" <td>198450</td>\n",
" <td>3</td>\n",
" <td>123680</td>\n",
" <td>101401.0</td>\n",
" <td>145959.0</td>\n",
" <td>225</td>\n",
" <td>184.0</td>\n",
" <td>266.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1876</th>\n",
" <td>1877</td>\n",
" <td>198449</td>\n",
" <td>3</td>\n",
" <td>101073</td>\n",
" <td>81684.0</td>\n",
" <td>120462.0</td>\n",
" <td>184</td>\n",
" <td>149.0</td>\n",
" <td>219.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1877</th>\n",
" <td>1878</td>\n",
" <td>198448</td>\n",
" <td>3</td>\n",
" <td>78620</td>\n",
" <td>60634.0</td>\n",
" <td>96606.0</td>\n",
" <td>143</td>\n",
" <td>110.0</td>\n",
" <td>176.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1878</th>\n",
" <td>1879</td>\n",
" <td>198447</td>\n",
" <td>3</td>\n",
" <td>72029</td>\n",
" <td>54274.0</td>\n",
" <td>89784.0</td>\n",
" <td>131</td>\n",
" <td>99.0</td>\n",
" <td>163.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1879</th>\n",
" <td>1880</td>\n",
" <td>198446</td>\n",
" <td>3</td>\n",
" <td>87330</td>\n",
" <td>67686.0</td>\n",
" <td>106974.0</td>\n",
" <td>159</td>\n",
" <td>123.0</td>\n",
" <td>195.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1880</th>\n",
" <td>1881</td>\n",
" <td>198445</td>\n",
" <td>3</td>\n",
" <td>135223</td>\n",
" <td>101414.0</td>\n",
" <td>169032.0</td>\n",
" <td>246</td>\n",
" <td>184.0</td>\n",
" <td>308.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1881</th>\n",
" <td>1882</td>\n",
" <td>198444</td>\n",
" <td>3</td>\n",
" <td>68422</td>\n",
" <td>20056.0</td>\n",
" <td>116788.0</td>\n",
" <td>125</td>\n",
" <td>37.0</td>\n",
" <td>213.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1882 rows × 15 columns</p>\n",
"</div>"
],
"text/plain": [
" 0 week indicator inc inc_low inc_up inc100 inc100_low \\\n",
"0 1 202047 3 19180 15348.0 23012.0 29 23.0 \n",
"1 2 202046 3 24801 20503.0 29099.0 38 31.0 \n",
"2 3 202045 3 42516 36857.0 48175.0 65 56.0 \n",
"3 4 202044 3 44567 38521.0 50613.0 68 59.0 \n",
"4 5 202043 3 43737 37523.0 49951.0 66 57.0 \n",
"5 6 202042 3 35145 29812.0 40478.0 53 45.0 \n",
"6 7 202041 3 27877 23206.0 32548.0 42 35.0 \n",
"7 8 202040 3 20443 16381.0 24505.0 31 25.0 \n",
"8 9 202039 3 19810 15900.0 23720.0 30 24.0 \n",
"9 10 202038 3 25562 21142.0 29982.0 39 32.0 \n",
"10 11 202037 3 18485 14649.0 22321.0 28 22.0 \n",
"11 12 202036 3 10390 7646.0 13134.0 16 12.0 \n",
"12 13 202035 3 9918 6842.0 12994.0 15 10.0 \n",
"13 14 202034 3 6084 3090.0 9078.0 9 4.0 \n",
"14 15 202033 3 6106 3411.0 8801.0 9 5.0 \n",
"15 16 202032 3 5918 3330.0 8506.0 9 5.0 \n",
"16 17 202031 3 4351 2269.0 6433.0 7 4.0 \n",
"17 18 202030 3 8179 5442.0 10916.0 12 8.0 \n",
"18 19 202029 3 8687 5860.0 11514.0 13 9.0 \n",
"19 20 202028 3 8340 5701.0 10979.0 13 9.0 \n",
"20 21 202027 3 4066 2406.0 5726.0 6 3.0 \n",
"21 22 202026 3 4039 2389.0 5689.0 6 3.0 \n",
"22 23 202025 3 2853 1488.0 4218.0 4 2.0 \n",
"23 24 202024 3 3058 1690.0 4426.0 5 3.0 \n",
"24 25 202023 3 4168 2468.0 5868.0 6 3.0 \n",
"25 26 202022 3 3580 1947.0 5213.0 5 3.0 \n",
"26 27 202021 3 6114 4026.0 8202.0 9 6.0 \n",
"27 28 202020 3 9315 6775.0 11855.0 14 10.0 \n",
"28 29 202019 3 11679 8722.0 14636.0 18 14.0 \n",
"29 30 202018 3 16398 12851.0 19945.0 25 20.0 \n",
"... ... ... ... ... ... ... ... ... \n",
"1852 1853 198521 3 26096 19621.0 32571.0 47 35.0 \n",
"1853 1854 198520 3 27896 20885.0 34907.0 51 38.0 \n",
"1854 1855 198519 3 43154 32821.0 53487.0 78 59.0 \n",
"1855 1856 198518 3 40555 29935.0 51175.0 74 55.0 \n",
"1856 1857 198517 3 34053 24366.0 43740.0 62 44.0 \n",
"1857 1858 198516 3 50362 36451.0 64273.0 91 66.0 \n",
"1858 1859 198515 3 63881 45538.0 82224.0 116 83.0 \n",
"1859 1860 198514 3 134545 114400.0 154690.0 244 207.0 \n",
"1860 1861 198513 3 197206 176080.0 218332.0 357 319.0 \n",
"1861 1862 198512 3 245240 223304.0 267176.0 445 405.0 \n",
"1862 1863 198511 3 276205 252399.0 300011.0 501 458.0 \n",
"1863 1864 198510 3 353231 326279.0 380183.0 640 591.0 \n",
"1864 1865 198509 3 369895 341109.0 398681.0 670 618.0 \n",
"1865 1866 198508 3 389886 359529.0 420243.0 707 652.0 \n",
"1866 1867 198507 3 471852 432599.0 511105.0 855 784.0 \n",
"1867 1868 198506 3 565825 518011.0 613639.0 1026 939.0 \n",
"1868 1869 198505 3 637302 592795.0 681809.0 1155 1074.0 \n",
"1869 1870 198504 3 424937 390794.0 459080.0 770 708.0 \n",
"1870 1871 198503 3 213901 174689.0 253113.0 388 317.0 \n",
"1871 1872 198502 3 97586 80949.0 114223.0 177 147.0 \n",
"1872 1873 198501 3 85489 65918.0 105060.0 155 120.0 \n",
"1873 1874 198452 3 84830 60602.0 109058.0 154 110.0 \n",
"1874 1875 198451 3 101726 80242.0 123210.0 185 146.0 \n",
"1875 1876 198450 3 123680 101401.0 145959.0 225 184.0 \n",
"1876 1877 198449 3 101073 81684.0 120462.0 184 149.0 \n",
"1877 1878 198448 3 78620 60634.0 96606.0 143 110.0 \n",
"1878 1879 198447 3 72029 54274.0 89784.0 131 99.0 \n",
"1879 1880 198446 3 87330 67686.0 106974.0 159 123.0 \n",
"1880 1881 198445 3 135223 101414.0 169032.0 246 184.0 \n",
"1881 1882 198444 3 68422 20056.0 116788.0 125 37.0 \n",
"\n",
" inc100_up geo_insee geo_name Unnamed: 11 Unnamed: 12 Unnamed: 13 \\\n",
"0 35.0 FR France NaN NaN NaN \n",
"1 45.0 FR France NaN NaN NaN \n",
"2 74.0 FR France NaN NaN NaN \n",
"3 77.0 FR France NaN NaN NaN \n",
"4 75.0 FR France NaN NaN NaN \n",
"5 61.0 FR France NaN NaN NaN \n",
"6 49.0 FR France NaN NaN NaN \n",
"7 37.0 FR France NaN NaN NaN \n",
"8 36.0 FR France NaN NaN NaN \n",
"9 46.0 FR France NaN NaN NaN \n",
"10 34.0 FR France NaN NaN NaN \n",
"11 20.0 FR France NaN NaN NaN \n",
"12 20.0 FR France NaN NaN NaN \n",
"13 14.0 FR France NaN NaN NaN \n",
"14 13.0 FR France NaN NaN NaN \n",
"15 13.0 FR France NaN NaN NaN \n",
"16 10.0 FR France NaN NaN NaN \n",
"17 16.0 FR France NaN NaN NaN \n",
"18 17.0 FR France NaN NaN NaN \n",
"19 17.0 FR France NaN NaN NaN \n",
"20 9.0 FR France NaN NaN NaN \n",
"21 9.0 FR France NaN NaN NaN \n",
"22 6.0 FR France NaN NaN NaN \n",
"23 7.0 FR France NaN NaN NaN \n",
"24 9.0 FR France NaN NaN NaN \n",
"25 7.0 FR France NaN NaN NaN \n",
"26 12.0 FR France NaN NaN NaN \n",
"27 18.0 FR France NaN NaN NaN \n",
"28 22.0 FR France NaN NaN NaN \n",
"29 30.0 FR France NaN NaN NaN \n",
"... ... ... ... ... ... ... \n",
"1852 59.0 FR France NaN NaN NaN \n",
"1853 64.0 FR France NaN NaN NaN \n",
"1854 97.0 FR France NaN NaN NaN \n",
"1855 93.0 FR France NaN NaN NaN \n",
"1856 80.0 FR France NaN NaN NaN \n",
"1857 116.0 FR France NaN NaN NaN \n",
"1858 149.0 FR France NaN NaN NaN \n",
"1859 281.0 FR France NaN NaN NaN \n",
"1860 395.0 FR France NaN NaN NaN \n",
"1861 485.0 FR France NaN NaN NaN \n",
"1862 544.0 FR France NaN NaN NaN \n",
"1863 689.0 FR France NaN NaN NaN \n",
"1864 722.0 FR France NaN NaN NaN \n",
"1865 762.0 FR France NaN NaN NaN \n",
"1866 926.0 FR France NaN NaN NaN \n",
"1867 1113.0 FR France NaN NaN NaN \n",
"1868 1236.0 FR France NaN NaN NaN \n",
"1869 832.0 FR France NaN NaN NaN \n",
"1870 459.0 FR France NaN NaN NaN \n",
"1871 207.0 FR France NaN NaN NaN \n",
"1872 190.0 FR France NaN NaN NaN \n",
"1873 198.0 FR France NaN NaN NaN \n",
"1874 224.0 FR France NaN NaN NaN \n",
"1875 266.0 FR France NaN NaN NaN \n",
"1876 219.0 FR France NaN NaN NaN \n",
"1877 176.0 FR France NaN NaN NaN \n",
"1878 163.0 FR France NaN NaN NaN \n",
"1879 195.0 FR France NaN NaN NaN \n",
"1880 308.0 FR France NaN NaN NaN \n",
"1881 213.0 FR France NaN NaN NaN \n",
"\n",
" Unnamed: 14 \n",
"0 NaN \n",
"1 NaN \n",
"2 NaN \n",
"3 NaN \n",
"4 NaN \n",
"5 NaN \n",
"6 NaN \n",
"7 NaN \n",
"8 NaN \n",
"9 NaN \n",
"10 NaN \n",
"11 NaN \n",
"12 NaN \n",
"13 NaN \n",
"14 NaN \n",
"15 NaN \n",
"16 NaN \n",
"17 NaN \n",
"18 NaN \n",
"19 NaN \n",
"20 NaN \n",
"21 NaN \n",
"22 NaN \n",
"23 NaN \n",
"24 NaN \n",
"25 NaN \n",
"26 NaN \n",
"27 NaN \n",
"28 NaN \n",
"29 NaN \n",
"... ... \n",
"1852 NaN \n",
"1853 NaN \n",
"1854 NaN \n",
"1855 NaN \n",
"1856 NaN \n",
"1857 NaN \n",
"1858 NaN \n",
"1859 NaN \n",
"1860 NaN \n",
"1861 NaN \n",
"1862 NaN \n",
"1863 NaN \n",
"1864 NaN \n",
"1865 NaN \n",
"1866 NaN \n",
"1867 NaN \n",
"1868 NaN \n",
"1869 NaN \n",
"1870 NaN \n",
"1871 NaN \n",
"1872 NaN \n",
"1873 NaN \n",
"1874 NaN \n",
"1875 NaN \n",
"1876 NaN \n",
"1877 NaN \n",
"1878 NaN \n",
"1879 NaN \n",
"1880 NaN \n",
"1881 NaN \n",
"\n",
"[1882 rows x 15 columns]"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data = pd.read_csv(\"incidence-PAY-3_downloaded.csv\", skiprows=1)\n",
"raw_data" "raw_data"
] ]
}, },
...@@ -78,9 +1447,1349 @@ ...@@ -78,9 +1447,1349 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 25,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"data": {
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" <tr>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <tr>\n",
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" <td>6433.0</td>\n",
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" <tr>\n",
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" <td>10916.0</td>\n",
" <td>12</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <tr>\n",
" <th>18</th>\n",
" <td>19</td>\n",
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" <td>5860.0</td>\n",
" <td>11514.0</td>\n",
" <td>13</td>\n",
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" <td>17.0</td>\n",
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" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <tr>\n",
" <th>19</th>\n",
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" <td>10979.0</td>\n",
" <td>13</td>\n",
" <td>9.0</td>\n",
" <td>17.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <tr>\n",
" <th>20</th>\n",
" <td>21</td>\n",
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" <td>6</td>\n",
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" <td>9.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <tr>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <tr>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <tr>\n",
" <th>23</th>\n",
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" <td>7.0</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
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" <td>202023</td>\n",
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" <td>3.0</td>\n",
" <td>9.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <th>25</th>\n",
" <td>26</td>\n",
" <td>202022</td>\n",
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" <td>1947.0</td>\n",
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" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>27</td>\n",
" <td>202021</td>\n",
" <td>3</td>\n",
" <td>6114</td>\n",
" <td>4026.0</td>\n",
" <td>8202.0</td>\n",
" <td>9</td>\n",
" <td>6.0</td>\n",
" <td>12.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>28</td>\n",
" <td>202020</td>\n",
" <td>3</td>\n",
" <td>9315</td>\n",
" <td>6775.0</td>\n",
" <td>11855.0</td>\n",
" <td>14</td>\n",
" <td>10.0</td>\n",
" <td>18.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>29</td>\n",
" <td>202019</td>\n",
" <td>3</td>\n",
" <td>11679</td>\n",
" <td>8722.0</td>\n",
" <td>14636.0</td>\n",
" <td>18</td>\n",
" <td>14.0</td>\n",
" <td>22.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>30</td>\n",
" <td>202018</td>\n",
" <td>3</td>\n",
" <td>16398</td>\n",
" <td>12851.0</td>\n",
" <td>19945.0</td>\n",
" <td>25</td>\n",
" <td>20.0</td>\n",
" <td>30.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</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",
" </tr>\n",
" <tr>\n",
" <th>1852</th>\n",
" <td>1853</td>\n",
" <td>198521</td>\n",
" <td>3</td>\n",
" <td>26096</td>\n",
" <td>19621.0</td>\n",
" <td>32571.0</td>\n",
" <td>47</td>\n",
" <td>35.0</td>\n",
" <td>59.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1853</th>\n",
" <td>1854</td>\n",
" <td>198520</td>\n",
" <td>3</td>\n",
" <td>27896</td>\n",
" <td>20885.0</td>\n",
" <td>34907.0</td>\n",
" <td>51</td>\n",
" <td>38.0</td>\n",
" <td>64.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1854</th>\n",
" <td>1855</td>\n",
" <td>198519</td>\n",
" <td>3</td>\n",
" <td>43154</td>\n",
" <td>32821.0</td>\n",
" <td>53487.0</td>\n",
" <td>78</td>\n",
" <td>59.0</td>\n",
" <td>97.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1855</th>\n",
" <td>1856</td>\n",
" <td>198518</td>\n",
" <td>3</td>\n",
" <td>40555</td>\n",
" <td>29935.0</td>\n",
" <td>51175.0</td>\n",
" <td>74</td>\n",
" <td>55.0</td>\n",
" <td>93.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1856</th>\n",
" <td>1857</td>\n",
" <td>198517</td>\n",
" <td>3</td>\n",
" <td>34053</td>\n",
" <td>24366.0</td>\n",
" <td>43740.0</td>\n",
" <td>62</td>\n",
" <td>44.0</td>\n",
" <td>80.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1857</th>\n",
" <td>1858</td>\n",
" <td>198516</td>\n",
" <td>3</td>\n",
" <td>50362</td>\n",
" <td>36451.0</td>\n",
" <td>64273.0</td>\n",
" <td>91</td>\n",
" <td>66.0</td>\n",
" <td>116.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1858</th>\n",
" <td>1859</td>\n",
" <td>198515</td>\n",
" <td>3</td>\n",
" <td>63881</td>\n",
" <td>45538.0</td>\n",
" <td>82224.0</td>\n",
" <td>116</td>\n",
" <td>83.0</td>\n",
" <td>149.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1859</th>\n",
" <td>1860</td>\n",
" <td>198514</td>\n",
" <td>3</td>\n",
" <td>134545</td>\n",
" <td>114400.0</td>\n",
" <td>154690.0</td>\n",
" <td>244</td>\n",
" <td>207.0</td>\n",
" <td>281.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1860</th>\n",
" <td>1861</td>\n",
" <td>198513</td>\n",
" <td>3</td>\n",
" <td>197206</td>\n",
" <td>176080.0</td>\n",
" <td>218332.0</td>\n",
" <td>357</td>\n",
" <td>319.0</td>\n",
" <td>395.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1861</th>\n",
" <td>1862</td>\n",
" <td>198512</td>\n",
" <td>3</td>\n",
" <td>245240</td>\n",
" <td>223304.0</td>\n",
" <td>267176.0</td>\n",
" <td>445</td>\n",
" <td>405.0</td>\n",
" <td>485.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1862</th>\n",
" <td>1863</td>\n",
" <td>198511</td>\n",
" <td>3</td>\n",
" <td>276205</td>\n",
" <td>252399.0</td>\n",
" <td>300011.0</td>\n",
" <td>501</td>\n",
" <td>458.0</td>\n",
" <td>544.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1863</th>\n",
" <td>1864</td>\n",
" <td>198510</td>\n",
" <td>3</td>\n",
" <td>353231</td>\n",
" <td>326279.0</td>\n",
" <td>380183.0</td>\n",
" <td>640</td>\n",
" <td>591.0</td>\n",
" <td>689.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1864</th>\n",
" <td>1865</td>\n",
" <td>198509</td>\n",
" <td>3</td>\n",
" <td>369895</td>\n",
" <td>341109.0</td>\n",
" <td>398681.0</td>\n",
" <td>670</td>\n",
" <td>618.0</td>\n",
" <td>722.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1865</th>\n",
" <td>1866</td>\n",
" <td>198508</td>\n",
" <td>3</td>\n",
" <td>389886</td>\n",
" <td>359529.0</td>\n",
" <td>420243.0</td>\n",
" <td>707</td>\n",
" <td>652.0</td>\n",
" <td>762.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1866</th>\n",
" <td>1867</td>\n",
" <td>198507</td>\n",
" <td>3</td>\n",
" <td>471852</td>\n",
" <td>432599.0</td>\n",
" <td>511105.0</td>\n",
" <td>855</td>\n",
" <td>784.0</td>\n",
" <td>926.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1867</th>\n",
" <td>1868</td>\n",
" <td>198506</td>\n",
" <td>3</td>\n",
" <td>565825</td>\n",
" <td>518011.0</td>\n",
" <td>613639.0</td>\n",
" <td>1026</td>\n",
" <td>939.0</td>\n",
" <td>1113.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1868</th>\n",
" <td>1869</td>\n",
" <td>198505</td>\n",
" <td>3</td>\n",
" <td>637302</td>\n",
" <td>592795.0</td>\n",
" <td>681809.0</td>\n",
" <td>1155</td>\n",
" <td>1074.0</td>\n",
" <td>1236.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1869</th>\n",
" <td>1870</td>\n",
" <td>198504</td>\n",
" <td>3</td>\n",
" <td>424937</td>\n",
" <td>390794.0</td>\n",
" <td>459080.0</td>\n",
" <td>770</td>\n",
" <td>708.0</td>\n",
" <td>832.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1870</th>\n",
" <td>1871</td>\n",
" <td>198503</td>\n",
" <td>3</td>\n",
" <td>213901</td>\n",
" <td>174689.0</td>\n",
" <td>253113.0</td>\n",
" <td>388</td>\n",
" <td>317.0</td>\n",
" <td>459.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1871</th>\n",
" <td>1872</td>\n",
" <td>198502</td>\n",
" <td>3</td>\n",
" <td>97586</td>\n",
" <td>80949.0</td>\n",
" <td>114223.0</td>\n",
" <td>177</td>\n",
" <td>147.0</td>\n",
" <td>207.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1872</th>\n",
" <td>1873</td>\n",
" <td>198501</td>\n",
" <td>3</td>\n",
" <td>85489</td>\n",
" <td>65918.0</td>\n",
" <td>105060.0</td>\n",
" <td>155</td>\n",
" <td>120.0</td>\n",
" <td>190.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1873</th>\n",
" <td>1874</td>\n",
" <td>198452</td>\n",
" <td>3</td>\n",
" <td>84830</td>\n",
" <td>60602.0</td>\n",
" <td>109058.0</td>\n",
" <td>154</td>\n",
" <td>110.0</td>\n",
" <td>198.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1874</th>\n",
" <td>1875</td>\n",
" <td>198451</td>\n",
" <td>3</td>\n",
" <td>101726</td>\n",
" <td>80242.0</td>\n",
" <td>123210.0</td>\n",
" <td>185</td>\n",
" <td>146.0</td>\n",
" <td>224.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1875</th>\n",
" <td>1876</td>\n",
" <td>198450</td>\n",
" <td>3</td>\n",
" <td>123680</td>\n",
" <td>101401.0</td>\n",
" <td>145959.0</td>\n",
" <td>225</td>\n",
" <td>184.0</td>\n",
" <td>266.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1876</th>\n",
" <td>1877</td>\n",
" <td>198449</td>\n",
" <td>3</td>\n",
" <td>101073</td>\n",
" <td>81684.0</td>\n",
" <td>120462.0</td>\n",
" <td>184</td>\n",
" <td>149.0</td>\n",
" <td>219.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1877</th>\n",
" <td>1878</td>\n",
" <td>198448</td>\n",
" <td>3</td>\n",
" <td>78620</td>\n",
" <td>60634.0</td>\n",
" <td>96606.0</td>\n",
" <td>143</td>\n",
" <td>110.0</td>\n",
" <td>176.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1878</th>\n",
" <td>1879</td>\n",
" <td>198447</td>\n",
" <td>3</td>\n",
" <td>72029</td>\n",
" <td>54274.0</td>\n",
" <td>89784.0</td>\n",
" <td>131</td>\n",
" <td>99.0</td>\n",
" <td>163.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1879</th>\n",
" <td>1880</td>\n",
" <td>198446</td>\n",
" <td>3</td>\n",
" <td>87330</td>\n",
" <td>67686.0</td>\n",
" <td>106974.0</td>\n",
" <td>159</td>\n",
" <td>123.0</td>\n",
" <td>195.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1880</th>\n",
" <td>1881</td>\n",
" <td>198445</td>\n",
" <td>3</td>\n",
" <td>135223</td>\n",
" <td>101414.0</td>\n",
" <td>169032.0</td>\n",
" <td>246</td>\n",
" <td>184.0</td>\n",
" <td>308.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1881</th>\n",
" <td>1882</td>\n",
" <td>198444</td>\n",
" <td>3</td>\n",
" <td>68422</td>\n",
" <td>20056.0</td>\n",
" <td>116788.0</td>\n",
" <td>125</td>\n",
" <td>37.0</td>\n",
" <td>213.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1882 rows × 15 columns</p>\n",
"</div>"
],
"text/plain": [
" 0 week indicator inc inc_low inc_up inc100 inc100_low \\\n",
"0 1 202047 3 19180 15348.0 23012.0 29 23.0 \n",
"1 2 202046 3 24801 20503.0 29099.0 38 31.0 \n",
"2 3 202045 3 42516 36857.0 48175.0 65 56.0 \n",
"3 4 202044 3 44567 38521.0 50613.0 68 59.0 \n",
"4 5 202043 3 43737 37523.0 49951.0 66 57.0 \n",
"5 6 202042 3 35145 29812.0 40478.0 53 45.0 \n",
"6 7 202041 3 27877 23206.0 32548.0 42 35.0 \n",
"7 8 202040 3 20443 16381.0 24505.0 31 25.0 \n",
"8 9 202039 3 19810 15900.0 23720.0 30 24.0 \n",
"9 10 202038 3 25562 21142.0 29982.0 39 32.0 \n",
"10 11 202037 3 18485 14649.0 22321.0 28 22.0 \n",
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"29 30 202018 3 16398 12851.0 19945.0 25 20.0 \n",
"... ... ... ... ... ... ... ... ... \n",
"1852 1853 198521 3 26096 19621.0 32571.0 47 35.0 \n",
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"1854 1855 198519 3 43154 32821.0 53487.0 78 59.0 \n",
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"1857 1858 198516 3 50362 36451.0 64273.0 91 66.0 \n",
"1858 1859 198515 3 63881 45538.0 82224.0 116 83.0 \n",
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"1861 1862 198512 3 245240 223304.0 267176.0 445 405.0 \n",
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"1863 1864 198510 3 353231 326279.0 380183.0 640 591.0 \n",
"1864 1865 198509 3 369895 341109.0 398681.0 670 618.0 \n",
"1865 1866 198508 3 389886 359529.0 420243.0 707 652.0 \n",
"1866 1867 198507 3 471852 432599.0 511105.0 855 784.0 \n",
"1867 1868 198506 3 565825 518011.0 613639.0 1026 939.0 \n",
"1868 1869 198505 3 637302 592795.0 681809.0 1155 1074.0 \n",
"1869 1870 198504 3 424937 390794.0 459080.0 770 708.0 \n",
"1870 1871 198503 3 213901 174689.0 253113.0 388 317.0 \n",
"1871 1872 198502 3 97586 80949.0 114223.0 177 147.0 \n",
"1872 1873 198501 3 85489 65918.0 105060.0 155 120.0 \n",
"1873 1874 198452 3 84830 60602.0 109058.0 154 110.0 \n",
"1874 1875 198451 3 101726 80242.0 123210.0 185 146.0 \n",
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"1876 1877 198449 3 101073 81684.0 120462.0 184 149.0 \n",
"1877 1878 198448 3 78620 60634.0 96606.0 143 110.0 \n",
"1878 1879 198447 3 72029 54274.0 89784.0 131 99.0 \n",
"1879 1880 198446 3 87330 67686.0 106974.0 159 123.0 \n",
"1880 1881 198445 3 135223 101414.0 169032.0 246 184.0 \n",
"1881 1882 198444 3 68422 20056.0 116788.0 125 37.0 \n",
"\n",
" inc100_up geo_insee geo_name Unnamed: 11 Unnamed: 12 Unnamed: 13 \\\n",
"0 35.0 FR France NaN NaN NaN \n",
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"9 46.0 FR France NaN NaN NaN \n",
"10 34.0 FR France NaN NaN NaN \n",
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"21 9.0 FR France NaN NaN NaN \n",
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"... ... ... ... ... ... ... \n",
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"1854 97.0 FR France NaN NaN NaN \n",
"1855 93.0 FR France NaN NaN NaN \n",
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"1862 544.0 FR France NaN NaN NaN \n",
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"1864 722.0 FR France NaN NaN NaN \n",
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"\n",
" Unnamed: 14 \n",
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"... ... \n",
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"\n",
"[1882 rows x 15 columns]"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"raw_data[raw_data.isnull().any(axis=1)]" "raw_data[raw_data.isnull().any(axis=1)]"
] ]
...@@ -364,7 +3073,7 @@ ...@@ -364,7 +3073,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.6.1" "version": "3.6.4"
} }
}, },
"nbformat": 4, "nbformat": 4,
......
module3/exo1/incidence-PAY-3_downloaded.csv 0 → 100644
View file @ aba8d83e
This source diff could not be displayed because it is too large. You can view the blob instead.
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