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6f892419cc99326ee525ed439d8ff5df
mooc-rr
Commits
e84f30e5
Commit
e84f30e5
authored
Feb 28, 2021
by
6f892419cc99326ee525ed439d8ff5df
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analyse-syndrome-grippal.ipynb
module3/exo1/analyse-syndrome-grippal.ipynb
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module3/exo1/analyse-syndrome-grippal.ipynb
View file @
e84f30e5
...
@@ -340,15 +340,2105 @@
...
@@ -340,15 +340,2105 @@
},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count": null,
"execution_count": 6,
"metadata": {
"metadata": {},
"collapsed": true
"outputs": [
},
{
"outputs": [],
"ename": "TypeError",
"evalue": "parser_f() got an unexpected keyword argument 'data_url'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-6-d7294c0df819>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mraw_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata_url\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mskiprows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mraw_data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mTypeError\u001b[0m: parser_f() got an unexpected keyword argument 'data_url'"
]
}
],
"source": [
"source": [
"raw_data = pd.read_csv(data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\", skiprows=1)\n",
"raw_data = pd.read_csv(data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\", skiprows=1)\n",
"raw_data"
"raw_data"
]
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"import isoweek"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\""
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
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" <th>inc_up</th>\n",
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" <td>46.0</td>\n",
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" <td>25726.0</td>\n",
" <td>33</td>\n",
" <td>27.0</td>\n",
" <td>39.0</td>\n",
" <td>FR</td>\n",
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" <th>5</th>\n",
" <td>202102</td>\n",
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" <td>31.0</td>\n",
" <td>FR</td>\n",
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" <th>6</th>\n",
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" <td>3</td>\n",
" <td>21799</td>\n",
" <td>17778.0</td>\n",
" <td>25820.0</td>\n",
" <td>33</td>\n",
" <td>27.0</td>\n",
" <td>39.0</td>\n",
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" <td>France</td>\n",
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" <th>7</th>\n",
" <td>202053</td>\n",
" <td>3</td>\n",
" <td>21220</td>\n",
" <td>16498.0</td>\n",
" <td>25942.0</td>\n",
" <td>32</td>\n",
" <td>25.0</td>\n",
" <td>39.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>202052</td>\n",
" <td>3</td>\n",
" <td>16428</td>\n",
" <td>12285.0</td>\n",
" <td>20571.0</td>\n",
" <td>25</td>\n",
" <td>19.0</td>\n",
" <td>31.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>202051</td>\n",
" <td>3</td>\n",
" <td>21619</td>\n",
" <td>17370.0</td>\n",
" <td>25868.0</td>\n",
" <td>33</td>\n",
" <td>27.0</td>\n",
" <td>39.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>10</th>\n",
" <td>202050</td>\n",
" <td>3</td>\n",
" <td>16845</td>\n",
" <td>13220.0</td>\n",
" <td>20470.0</td>\n",
" <td>26</td>\n",
" <td>20.0</td>\n",
" <td>32.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>202049</td>\n",
" <td>3</td>\n",
" <td>12939</td>\n",
" <td>9923.0</td>\n",
" <td>15955.0</td>\n",
" <td>20</td>\n",
" <td>15.0</td>\n",
" <td>25.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>202048</td>\n",
" <td>3</td>\n",
" <td>13804</td>\n",
" <td>10641.0</td>\n",
" <td>16967.0</td>\n",
" <td>21</td>\n",
" <td>16.0</td>\n",
" <td>26.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>202047</td>\n",
" <td>3</td>\n",
" <td>19085</td>\n",
" <td>15285.0</td>\n",
" <td>22885.0</td>\n",
" <td>29</td>\n",
" <td>23.0</td>\n",
" <td>35.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>202046</td>\n",
" <td>3</td>\n",
" <td>24801</td>\n",
" <td>20503.0</td>\n",
" <td>29099.0</td>\n",
" <td>38</td>\n",
" <td>31.0</td>\n",
" <td>45.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>202045</td>\n",
" <td>3</td>\n",
" <td>42516</td>\n",
" <td>36857.0</td>\n",
" <td>48175.0</td>\n",
" <td>65</td>\n",
" <td>56.0</td>\n",
" <td>74.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>202044</td>\n",
" <td>3</td>\n",
" <td>44567</td>\n",
" <td>38521.0</td>\n",
" <td>50613.0</td>\n",
" <td>68</td>\n",
" <td>59.0</td>\n",
" <td>77.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>202043</td>\n",
" <td>3</td>\n",
" <td>43737</td>\n",
" <td>37523.0</td>\n",
" <td>49951.0</td>\n",
" <td>66</td>\n",
" <td>57.0</td>\n",
" <td>75.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>202042</td>\n",
" <td>3</td>\n",
" <td>35145</td>\n",
" <td>29812.0</td>\n",
" <td>40478.0</td>\n",
" <td>53</td>\n",
" <td>45.0</td>\n",
" <td>61.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>202041</td>\n",
" <td>3</td>\n",
" <td>27877</td>\n",
" <td>23206.0</td>\n",
" <td>32548.0</td>\n",
" <td>42</td>\n",
" <td>35.0</td>\n",
" <td>49.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>202040</td>\n",
" <td>3</td>\n",
" <td>20443</td>\n",
" <td>16381.0</td>\n",
" <td>24505.0</td>\n",
" <td>31</td>\n",
" <td>25.0</td>\n",
" <td>37.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>202039</td>\n",
" <td>3</td>\n",
" <td>19810</td>\n",
" <td>15900.0</td>\n",
" <td>23720.0</td>\n",
" <td>30</td>\n",
" <td>24.0</td>\n",
" <td>36.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>202038</td>\n",
" <td>3</td>\n",
" <td>25562</td>\n",
" <td>21142.0</td>\n",
" <td>29982.0</td>\n",
" <td>39</td>\n",
" <td>32.0</td>\n",
" <td>46.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>202037</td>\n",
" <td>3</td>\n",
" <td>18485</td>\n",
" <td>14649.0</td>\n",
" <td>22321.0</td>\n",
" <td>28</td>\n",
" <td>22.0</td>\n",
" <td>34.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>202036</td>\n",
" <td>3</td>\n",
" <td>10390</td>\n",
" <td>7646.0</td>\n",
" <td>13134.0</td>\n",
" <td>16</td>\n",
" <td>12.0</td>\n",
" <td>20.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>202035</td>\n",
" <td>3</td>\n",
" <td>9918</td>\n",
" <td>6842.0</td>\n",
" <td>12994.0</td>\n",
" <td>15</td>\n",
" <td>10.0</td>\n",
" <td>20.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>202034</td>\n",
" <td>3</td>\n",
" <td>6084</td>\n",
" <td>3090.0</td>\n",
" <td>9078.0</td>\n",
" <td>9</td>\n",
" <td>4.0</td>\n",
" <td>14.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>202033</td>\n",
" <td>3</td>\n",
" <td>6106</td>\n",
" <td>3411.0</td>\n",
" <td>8801.0</td>\n",
" <td>9</td>\n",
" <td>5.0</td>\n",
" <td>13.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>202032</td>\n",
" <td>3</td>\n",
" <td>5918</td>\n",
" <td>3330.0</td>\n",
" <td>8506.0</td>\n",
" <td>9</td>\n",
" <td>5.0</td>\n",
" <td>13.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>202031</td>\n",
" <td>3</td>\n",
" <td>4351</td>\n",
" <td>2269.0</td>\n",
" <td>6433.0</td>\n",
" <td>7</td>\n",
" <td>4.0</td>\n",
" <td>10.0</td>\n",
" <td>FR</td>\n",
" <td>France</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",
" </tr>\n",
" <tr>\n",
" <th>1865</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1866</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1867</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1868</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1869</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1870</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1871</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1872</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1873</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1874</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1875</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1876</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1877</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1878</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1879</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1880</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1881</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1882</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1883</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1884</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1885</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1886</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1887</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1888</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1889</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1890</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1891</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1892</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1893</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1894</th>\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",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1895 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low \\\n",
"0 202107 3 28994 23212.0 34776.0 44 35.0 \n",
"1 202106 3 23365 19231.0 27499.0 35 29.0 \n",
"2 202105 3 22426 18445.0 26407.0 34 28.0 \n",
"3 202104 3 25804 21491.0 30117.0 39 32.0 \n",
"4 202103 3 21810 17894.0 25726.0 33 27.0 \n",
"5 202102 3 17320 13906.0 20734.0 26 21.0 \n",
"6 202101 3 21799 17778.0 25820.0 33 27.0 \n",
"7 202053 3 21220 16498.0 25942.0 32 25.0 \n",
"8 202052 3 16428 12285.0 20571.0 25 19.0 \n",
"9 202051 3 21619 17370.0 25868.0 33 27.0 \n",
"10 202050 3 16845 13220.0 20470.0 26 20.0 \n",
"11 202049 3 12939 9923.0 15955.0 20 15.0 \n",
"12 202048 3 13804 10641.0 16967.0 21 16.0 \n",
"13 202047 3 19085 15285.0 22885.0 29 23.0 \n",
"14 202046 3 24801 20503.0 29099.0 38 31.0 \n",
"15 202045 3 42516 36857.0 48175.0 65 56.0 \n",
"16 202044 3 44567 38521.0 50613.0 68 59.0 \n",
"17 202043 3 43737 37523.0 49951.0 66 57.0 \n",
"18 202042 3 35145 29812.0 40478.0 53 45.0 \n",
"19 202041 3 27877 23206.0 32548.0 42 35.0 \n",
"20 202040 3 20443 16381.0 24505.0 31 25.0 \n",
"21 202039 3 19810 15900.0 23720.0 30 24.0 \n",
"22 202038 3 25562 21142.0 29982.0 39 32.0 \n",
"23 202037 3 18485 14649.0 22321.0 28 22.0 \n",
"24 202036 3 10390 7646.0 13134.0 16 12.0 \n",
"25 202035 3 9918 6842.0 12994.0 15 10.0 \n",
"26 202034 3 6084 3090.0 9078.0 9 4.0 \n",
"27 202033 3 6106 3411.0 8801.0 9 5.0 \n",
"28 202032 3 5918 3330.0 8506.0 9 5.0 \n",
"29 202031 3 4351 2269.0 6433.0 7 4.0 \n",
"... ... ... ... ... ... ... ... \n",
"1865 198521 3 26096 19621.0 32571.0 47 35.0 \n",
"1866 198520 3 27896 20885.0 34907.0 51 38.0 \n",
"1867 198519 3 43154 32821.0 53487.0 78 59.0 \n",
"1868 198518 3 40555 29935.0 51175.0 74 55.0 \n",
"1869 198517 3 34053 24366.0 43740.0 62 44.0 \n",
"1870 198516 3 50362 36451.0 64273.0 91 66.0 \n",
"1871 198515 3 63881 45538.0 82224.0 116 83.0 \n",
"1872 198514 3 134545 114400.0 154690.0 244 207.0 \n",
"1873 198513 3 197206 176080.0 218332.0 357 319.0 \n",
"1874 198512 3 245240 223304.0 267176.0 445 405.0 \n",
"1875 198511 3 276205 252399.0 300011.0 501 458.0 \n",
"1876 198510 3 353231 326279.0 380183.0 640 591.0 \n",
"1877 198509 3 369895 341109.0 398681.0 670 618.0 \n",
"1878 198508 3 389886 359529.0 420243.0 707 652.0 \n",
"1879 198507 3 471852 432599.0 511105.0 855 784.0 \n",
"1880 198506 3 565825 518011.0 613639.0 1026 939.0 \n",
"1881 198505 3 637302 592795.0 681809.0 1155 1074.0 \n",
"1882 198504 3 424937 390794.0 459080.0 770 708.0 \n",
"1883 198503 3 213901 174689.0 253113.0 388 317.0 \n",
"1884 198502 3 97586 80949.0 114223.0 177 147.0 \n",
"1885 198501 3 85489 65918.0 105060.0 155 120.0 \n",
"1886 198452 3 84830 60602.0 109058.0 154 110.0 \n",
"1887 198451 3 101726 80242.0 123210.0 185 146.0 \n",
"1888 198450 3 123680 101401.0 145959.0 225 184.0 \n",
"1889 198449 3 101073 81684.0 120462.0 184 149.0 \n",
"1890 198448 3 78620 60634.0 96606.0 143 110.0 \n",
"1891 198447 3 72029 54274.0 89784.0 131 99.0 \n",
"1892 198446 3 87330 67686.0 106974.0 159 123.0 \n",
"1893 198445 3 135223 101414.0 169032.0 246 184.0 \n",
"1894 198444 3 68422 20056.0 116788.0 125 37.0 \n",
"\n",
" inc100_up geo_insee geo_name \n",
"0 53.0 FR France \n",
"1 41.0 FR France \n",
"2 40.0 FR France \n",
"3 46.0 FR France \n",
"4 39.0 FR France \n",
"5 31.0 FR France \n",
"6 39.0 FR France \n",
"7 39.0 FR France \n",
"8 31.0 FR France \n",
"9 39.0 FR France \n",
"10 32.0 FR France \n",
"11 25.0 FR France \n",
"12 26.0 FR France \n",
"13 35.0 FR France \n",
"14 45.0 FR France \n",
"15 74.0 FR France \n",
"16 77.0 FR France \n",
"17 75.0 FR France \n",
"18 61.0 FR France \n",
"19 49.0 FR France \n",
"20 37.0 FR France \n",
"21 36.0 FR France \n",
"22 46.0 FR France \n",
"23 34.0 FR France \n",
"24 20.0 FR France \n",
"25 20.0 FR France \n",
"26 14.0 FR France \n",
"27 13.0 FR France \n",
"28 13.0 FR France \n",
"29 10.0 FR France \n",
"... ... ... ... \n",
"1865 59.0 FR France \n",
"1866 64.0 FR France \n",
"1867 97.0 FR France \n",
"1868 93.0 FR France \n",
"1869 80.0 FR France \n",
"1870 116.0 FR France \n",
"1871 149.0 FR France \n",
"1872 281.0 FR France \n",
"1873 395.0 FR France \n",
"1874 485.0 FR France \n",
"1875 544.0 FR France \n",
"1876 689.0 FR France \n",
"1877 722.0 FR France \n",
"1878 762.0 FR France \n",
"1879 926.0 FR France \n",
"1880 1113.0 FR France \n",
"1881 1236.0 FR France \n",
"1882 832.0 FR France \n",
"1883 459.0 FR France \n",
"1884 207.0 FR France \n",
"1885 190.0 FR France \n",
"1886 198.0 FR France \n",
"1887 224.0 FR France \n",
"1888 266.0 FR France \n",
"1889 219.0 FR France \n",
"1890 176.0 FR France \n",
"1891 163.0 FR France \n",
"1892 195.0 FR France \n",
"1893 308.0 FR France \n",
"1894 213.0 FR France \n",
"\n",
"[1895 rows x 10 columns]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_data = pd.read_csv(data_url, skiprows=1)\n",
"raw_data"
]
},
{
"cell_type": "code",
"execution_count": 10,
"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>week</th>\n",
" <th>indicator</th>\n",
" <th>inc</th>\n",
" <th>inc_low</th>\n",
" <th>inc_up</th>\n",
" <th>inc100</th>\n",
" <th>inc100_low</th>\n",
" <th>inc100_up</th>\n",
" <th>geo_insee</th>\n",
" <th>geo_name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1658</th>\n",
" <td>198919</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n",
"1658 198919 3 0 NaN NaN 0 NaN NaN \n",
"\n",
" geo_insee geo_name \n",
"1658 FR France "
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_data[raw_data.isnull().any(axis=1)]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>week</th>\n",
" <th>indicator</th>\n",
" <th>inc</th>\n",
" <th>inc_low</th>\n",
" <th>inc_up</th>\n",
" <th>inc100</th>\n",
" <th>inc100_low</th>\n",
" <th>inc100_up</th>\n",
" <th>geo_insee</th>\n",
" <th>geo_name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>202107</td>\n",
" <td>3</td>\n",
" <td>28994</td>\n",
" <td>23212.0</td>\n",
" <td>34776.0</td>\n",
" <td>44</td>\n",
" <td>35.0</td>\n",
" <td>53.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>202106</td>\n",
" <td>3</td>\n",
" <td>23365</td>\n",
" <td>19231.0</td>\n",
" <td>27499.0</td>\n",
" <td>35</td>\n",
" <td>29.0</td>\n",
" <td>41.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>202105</td>\n",
" <td>3</td>\n",
" <td>22426</td>\n",
" <td>18445.0</td>\n",
" <td>26407.0</td>\n",
" <td>34</td>\n",
" <td>28.0</td>\n",
" <td>40.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>202104</td>\n",
" <td>3</td>\n",
" <td>25804</td>\n",
" <td>21491.0</td>\n",
" <td>30117.0</td>\n",
" <td>39</td>\n",
" <td>32.0</td>\n",
" <td>46.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>202103</td>\n",
" <td>3</td>\n",
" <td>21810</td>\n",
" <td>17894.0</td>\n",
" <td>25726.0</td>\n",
" <td>33</td>\n",
" <td>27.0</td>\n",
" <td>39.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>202102</td>\n",
" <td>3</td>\n",
" <td>17320</td>\n",
" <td>13906.0</td>\n",
" <td>20734.0</td>\n",
" <td>26</td>\n",
" <td>21.0</td>\n",
" <td>31.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>202101</td>\n",
" <td>3</td>\n",
" <td>21799</td>\n",
" <td>17778.0</td>\n",
" <td>25820.0</td>\n",
" <td>33</td>\n",
" <td>27.0</td>\n",
" <td>39.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>202053</td>\n",
" <td>3</td>\n",
" <td>21220</td>\n",
" <td>16498.0</td>\n",
" <td>25942.0</td>\n",
" <td>32</td>\n",
" <td>25.0</td>\n",
" <td>39.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>202052</td>\n",
" <td>3</td>\n",
" <td>16428</td>\n",
" <td>12285.0</td>\n",
" <td>20571.0</td>\n",
" <td>25</td>\n",
" <td>19.0</td>\n",
" <td>31.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>202051</td>\n",
" <td>3</td>\n",
" <td>21619</td>\n",
" <td>17370.0</td>\n",
" <td>25868.0</td>\n",
" <td>33</td>\n",
" <td>27.0</td>\n",
" <td>39.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>202050</td>\n",
" <td>3</td>\n",
" <td>16845</td>\n",
" <td>13220.0</td>\n",
" <td>20470.0</td>\n",
" <td>26</td>\n",
" <td>20.0</td>\n",
" <td>32.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>202049</td>\n",
" <td>3</td>\n",
" <td>12939</td>\n",
" <td>9923.0</td>\n",
" <td>15955.0</td>\n",
" <td>20</td>\n",
" <td>15.0</td>\n",
" <td>25.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>202048</td>\n",
" <td>3</td>\n",
" <td>13804</td>\n",
" <td>10641.0</td>\n",
" <td>16967.0</td>\n",
" <td>21</td>\n",
" <td>16.0</td>\n",
" <td>26.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>202047</td>\n",
" <td>3</td>\n",
" <td>19085</td>\n",
" <td>15285.0</td>\n",
" <td>22885.0</td>\n",
" <td>29</td>\n",
" <td>23.0</td>\n",
" <td>35.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>202046</td>\n",
" <td>3</td>\n",
" <td>24801</td>\n",
" <td>20503.0</td>\n",
" <td>29099.0</td>\n",
" <td>38</td>\n",
" <td>31.0</td>\n",
" <td>45.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>202045</td>\n",
" <td>3</td>\n",
" <td>42516</td>\n",
" <td>36857.0</td>\n",
" <td>48175.0</td>\n",
" <td>65</td>\n",
" <td>56.0</td>\n",
" <td>74.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>202044</td>\n",
" <td>3</td>\n",
" <td>44567</td>\n",
" <td>38521.0</td>\n",
" <td>50613.0</td>\n",
" <td>68</td>\n",
" <td>59.0</td>\n",
" <td>77.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>202043</td>\n",
" <td>3</td>\n",
" <td>43737</td>\n",
" <td>37523.0</td>\n",
" <td>49951.0</td>\n",
" <td>66</td>\n",
" <td>57.0</td>\n",
" <td>75.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>202042</td>\n",
" <td>3</td>\n",
" <td>35145</td>\n",
" <td>29812.0</td>\n",
" <td>40478.0</td>\n",
" <td>53</td>\n",
" <td>45.0</td>\n",
" <td>61.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>202041</td>\n",
" <td>3</td>\n",
" <td>27877</td>\n",
" <td>23206.0</td>\n",
" <td>32548.0</td>\n",
" <td>42</td>\n",
" <td>35.0</td>\n",
" <td>49.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>202040</td>\n",
" <td>3</td>\n",
" <td>20443</td>\n",
" <td>16381.0</td>\n",
" <td>24505.0</td>\n",
" <td>31</td>\n",
" <td>25.0</td>\n",
" <td>37.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>202039</td>\n",
" <td>3</td>\n",
" <td>19810</td>\n",
" <td>15900.0</td>\n",
" <td>23720.0</td>\n",
" <td>30</td>\n",
" <td>24.0</td>\n",
" <td>36.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>202038</td>\n",
" <td>3</td>\n",
" <td>25562</td>\n",
" <td>21142.0</td>\n",
" <td>29982.0</td>\n",
" <td>39</td>\n",
" <td>32.0</td>\n",
" <td>46.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>202037</td>\n",
" <td>3</td>\n",
" <td>18485</td>\n",
" <td>14649.0</td>\n",
" <td>22321.0</td>\n",
" <td>28</td>\n",
" <td>22.0</td>\n",
" <td>34.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>202036</td>\n",
" <td>3</td>\n",
" <td>10390</td>\n",
" <td>7646.0</td>\n",
" <td>13134.0</td>\n",
" <td>16</td>\n",
" <td>12.0</td>\n",
" <td>20.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>202035</td>\n",
" <td>3</td>\n",
" <td>9918</td>\n",
" <td>6842.0</td>\n",
" <td>12994.0</td>\n",
" <td>15</td>\n",
" <td>10.0</td>\n",
" <td>20.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>202034</td>\n",
" <td>3</td>\n",
" <td>6084</td>\n",
" <td>3090.0</td>\n",
" <td>9078.0</td>\n",
" <td>9</td>\n",
" <td>4.0</td>\n",
" <td>14.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>202033</td>\n",
" <td>3</td>\n",
" <td>6106</td>\n",
" <td>3411.0</td>\n",
" <td>8801.0</td>\n",
" <td>9</td>\n",
" <td>5.0</td>\n",
" <td>13.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>202032</td>\n",
" <td>3</td>\n",
" <td>5918</td>\n",
" <td>3330.0</td>\n",
" <td>8506.0</td>\n",
" <td>9</td>\n",
" <td>5.0</td>\n",
" <td>13.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>202031</td>\n",
" <td>3</td>\n",
" <td>4351</td>\n",
" <td>2269.0</td>\n",
" <td>6433.0</td>\n",
" <td>7</td>\n",
" <td>4.0</td>\n",
" <td>10.0</td>\n",
" <td>FR</td>\n",
" <td>France</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",
" </tr>\n",
" <tr>\n",
" <th>1865</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1866</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1867</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1868</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1869</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1870</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1871</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1872</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1873</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1874</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1875</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1876</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1877</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1878</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1879</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1880</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1881</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1882</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1883</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1884</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1885</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1886</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1887</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1888</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1889</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1890</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1891</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1892</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1893</th>\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",
" </tr>\n",
" <tr>\n",
" <th>1894</th>\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",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1894 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low \\\n",
"0 202107 3 28994 23212.0 34776.0 44 35.0 \n",
"1 202106 3 23365 19231.0 27499.0 35 29.0 \n",
"2 202105 3 22426 18445.0 26407.0 34 28.0 \n",
"3 202104 3 25804 21491.0 30117.0 39 32.0 \n",
"4 202103 3 21810 17894.0 25726.0 33 27.0 \n",
"5 202102 3 17320 13906.0 20734.0 26 21.0 \n",
"6 202101 3 21799 17778.0 25820.0 33 27.0 \n",
"7 202053 3 21220 16498.0 25942.0 32 25.0 \n",
"8 202052 3 16428 12285.0 20571.0 25 19.0 \n",
"9 202051 3 21619 17370.0 25868.0 33 27.0 \n",
"10 202050 3 16845 13220.0 20470.0 26 20.0 \n",
"11 202049 3 12939 9923.0 15955.0 20 15.0 \n",
"12 202048 3 13804 10641.0 16967.0 21 16.0 \n",
"13 202047 3 19085 15285.0 22885.0 29 23.0 \n",
"14 202046 3 24801 20503.0 29099.0 38 31.0 \n",
"15 202045 3 42516 36857.0 48175.0 65 56.0 \n",
"16 202044 3 44567 38521.0 50613.0 68 59.0 \n",
"17 202043 3 43737 37523.0 49951.0 66 57.0 \n",
"18 202042 3 35145 29812.0 40478.0 53 45.0 \n",
"19 202041 3 27877 23206.0 32548.0 42 35.0 \n",
"20 202040 3 20443 16381.0 24505.0 31 25.0 \n",
"21 202039 3 19810 15900.0 23720.0 30 24.0 \n",
"22 202038 3 25562 21142.0 29982.0 39 32.0 \n",
"23 202037 3 18485 14649.0 22321.0 28 22.0 \n",
"24 202036 3 10390 7646.0 13134.0 16 12.0 \n",
"25 202035 3 9918 6842.0 12994.0 15 10.0 \n",
"26 202034 3 6084 3090.0 9078.0 9 4.0 \n",
"27 202033 3 6106 3411.0 8801.0 9 5.0 \n",
"28 202032 3 5918 3330.0 8506.0 9 5.0 \n",
"29 202031 3 4351 2269.0 6433.0 7 4.0 \n",
"... ... ... ... ... ... ... ... \n",
"1865 198521 3 26096 19621.0 32571.0 47 35.0 \n",
"1866 198520 3 27896 20885.0 34907.0 51 38.0 \n",
"1867 198519 3 43154 32821.0 53487.0 78 59.0 \n",
"1868 198518 3 40555 29935.0 51175.0 74 55.0 \n",
"1869 198517 3 34053 24366.0 43740.0 62 44.0 \n",
"1870 198516 3 50362 36451.0 64273.0 91 66.0 \n",
"1871 198515 3 63881 45538.0 82224.0 116 83.0 \n",
"1872 198514 3 134545 114400.0 154690.0 244 207.0 \n",
"1873 198513 3 197206 176080.0 218332.0 357 319.0 \n",
"1874 198512 3 245240 223304.0 267176.0 445 405.0 \n",
"1875 198511 3 276205 252399.0 300011.0 501 458.0 \n",
"1876 198510 3 353231 326279.0 380183.0 640 591.0 \n",
"1877 198509 3 369895 341109.0 398681.0 670 618.0 \n",
"1878 198508 3 389886 359529.0 420243.0 707 652.0 \n",
"1879 198507 3 471852 432599.0 511105.0 855 784.0 \n",
"1880 198506 3 565825 518011.0 613639.0 1026 939.0 \n",
"1881 198505 3 637302 592795.0 681809.0 1155 1074.0 \n",
"1882 198504 3 424937 390794.0 459080.0 770 708.0 \n",
"1883 198503 3 213901 174689.0 253113.0 388 317.0 \n",
"1884 198502 3 97586 80949.0 114223.0 177 147.0 \n",
"1885 198501 3 85489 65918.0 105060.0 155 120.0 \n",
"1886 198452 3 84830 60602.0 109058.0 154 110.0 \n",
"1887 198451 3 101726 80242.0 123210.0 185 146.0 \n",
"1888 198450 3 123680 101401.0 145959.0 225 184.0 \n",
"1889 198449 3 101073 81684.0 120462.0 184 149.0 \n",
"1890 198448 3 78620 60634.0 96606.0 143 110.0 \n",
"1891 198447 3 72029 54274.0 89784.0 131 99.0 \n",
"1892 198446 3 87330 67686.0 106974.0 159 123.0 \n",
"1893 198445 3 135223 101414.0 169032.0 246 184.0 \n",
"1894 198444 3 68422 20056.0 116788.0 125 37.0 \n",
"\n",
" inc100_up geo_insee geo_name \n",
"0 53.0 FR France \n",
"1 41.0 FR France \n",
"2 40.0 FR France \n",
"3 46.0 FR France \n",
"4 39.0 FR France \n",
"5 31.0 FR France \n",
"6 39.0 FR France \n",
"7 39.0 FR France \n",
"8 31.0 FR France \n",
"9 39.0 FR France \n",
"10 32.0 FR France \n",
"11 25.0 FR France \n",
"12 26.0 FR France \n",
"13 35.0 FR France \n",
"14 45.0 FR France \n",
"15 74.0 FR France \n",
"16 77.0 FR France \n",
"17 75.0 FR France \n",
"18 61.0 FR France \n",
"19 49.0 FR France \n",
"20 37.0 FR France \n",
"21 36.0 FR France \n",
"22 46.0 FR France \n",
"23 34.0 FR France \n",
"24 20.0 FR France \n",
"25 20.0 FR France \n",
"26 14.0 FR France \n",
"27 13.0 FR France \n",
"28 13.0 FR France \n",
"29 10.0 FR France \n",
"... ... ... ... \n",
"1865 59.0 FR France \n",
"1866 64.0 FR France \n",
"1867 97.0 FR France \n",
"1868 93.0 FR France \n",
"1869 80.0 FR France \n",
"1870 116.0 FR France \n",
"1871 149.0 FR France \n",
"1872 281.0 FR France \n",
"1873 395.0 FR France \n",
"1874 485.0 FR France \n",
"1875 544.0 FR France \n",
"1876 689.0 FR France \n",
"1877 722.0 FR France \n",
"1878 762.0 FR France \n",
"1879 926.0 FR France \n",
"1880 1113.0 FR France \n",
"1881 1236.0 FR France \n",
"1882 832.0 FR France \n",
"1883 459.0 FR France \n",
"1884 207.0 FR France \n",
"1885 190.0 FR France \n",
"1886 198.0 FR France \n",
"1887 224.0 FR France \n",
"1888 266.0 FR France \n",
"1889 219.0 FR France \n",
"1890 176.0 FR France \n",
"1891 163.0 FR France \n",
"1892 195.0 FR France \n",
"1893 308.0 FR France \n",
"1894 213.0 FR France \n",
"\n",
"[1894 rows x 10 columns]"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data = raw_data.dropna().copy()\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"def convert_week(year_and_week_int):\n",
" year_and_week_str = str(year_and_week_int)\n",
" year = int(year_and_week_str[:4])\n",
" week = int(year_and_week_str[4:])\n",
" w = isoweek.Week(year, week)\n",
" return pd.Period(w.day(0), 'W')\n",
"\n",
"data['period'] = [convert_week(yw) for yw in data['week']]"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"sorted_data = data.set_index('period').sort_index()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
}
],
],
"metadata": {
"metadata": {
...
...
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