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Commit d9ccc6f2 authored by 123bbe3bd54604f74fd95f73d2f93478's avatar 123bbe3bd54604f74fd95f73d2f93478
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premier essai de réponse

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module2/exo2/exercice.ipynb
View file @ d9ccc6f2
{ {
"cells": [], "cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"datas = [14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2, 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0, 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6, 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"14.113000000000001\n",
"4.334094455301447\n",
"2.8\n",
"23.4\n",
"14.5\n"
]
}
],
"source": [
"print(np.average(datas))\n",
"print(np.std(datas, ddof=1))\n",
"print(np.min(datas))\n",
"print(np.max(datas))\n",
"print(np.median(datas))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": { "metadata": {
"kernelspec": { "kernelspec": {
"display_name": "Python 3", "display_name": "Python 3",
...@@ -16,10 +67,9 @@ ...@@ -16,10 +67,9 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.6.3" "version": "3.6.4"
} }
}, },
"nbformat": 4, "nbformat": 4,
"nbformat_minor": 2 "nbformat_minor": 2
} }
module3/exo1/analyse-syndrome-grippal.ipynb
View file @ d9ccc6f2
...@@ -9,14 +9,15 @@ ...@@ -9,14 +9,15 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 1,
"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"
] ]
}, },
{ {
...@@ -28,15 +29,994 @@ ...@@ -28,15 +29,994 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 2,
"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": 8,
"metadata": {},
"outputs": [
{
"data": {
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" <th>1</th>\n",
" <td>202010</td>\n",
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" <td>113304.0</td>\n",
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" <td>110696</td>\n",
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" <td>119326.0</td>\n",
" <td>168</td>\n",
" <td>155.0</td>\n",
" <td>181.0</td>\n",
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" <td>France</td>\n",
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" <th>3</th>\n",
" <td>202008</td>\n",
" <td>3</td>\n",
" <td>143753</td>\n",
" <td>133984.0</td>\n",
" <td>153522.0</td>\n",
" <td>218</td>\n",
" <td>203.0</td>\n",
" <td>233.0</td>\n",
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" <tr>\n",
" <th>4</th>\n",
" <td>202007</td>\n",
" <td>3</td>\n",
" <td>183610</td>\n",
" <td>172812.0</td>\n",
" <td>194408.0</td>\n",
" <td>279</td>\n",
" <td>263.0</td>\n",
" <td>295.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <th>5</th>\n",
" <td>202006</td>\n",
" <td>3</td>\n",
" <td>206669</td>\n",
" <td>195481.0</td>\n",
" <td>217857.0</td>\n",
" <td>314</td>\n",
" <td>297.0</td>\n",
" <td>331.0</td>\n",
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" <td>France</td>\n",
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" <th>6</th>\n",
" <td>202005</td>\n",
" <td>3</td>\n",
" <td>187957</td>\n",
" <td>177445.0</td>\n",
" <td>198469.0</td>\n",
" <td>285</td>\n",
" <td>269.0</td>\n",
" <td>301.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>202004</td>\n",
" <td>3</td>\n",
" <td>122331</td>\n",
" <td>113492.0</td>\n",
" <td>131170.0</td>\n",
" <td>186</td>\n",
" <td>173.0</td>\n",
" <td>199.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>202003</td>\n",
" <td>3</td>\n",
" <td>78413</td>\n",
" <td>71330.0</td>\n",
" <td>85496.0</td>\n",
" <td>119</td>\n",
" <td>108.0</td>\n",
" <td>130.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>9</th>\n",
" <td>202002</td>\n",
" <td>3</td>\n",
" <td>53614</td>\n",
" <td>47654.0</td>\n",
" <td>59574.0</td>\n",
" <td>81</td>\n",
" <td>72.0</td>\n",
" <td>90.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>10</th>\n",
" <td>202001</td>\n",
" <td>3</td>\n",
" <td>36850</td>\n",
" <td>31608.0</td>\n",
" <td>42092.0</td>\n",
" <td>56</td>\n",
" <td>48.0</td>\n",
" <td>64.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>201952</td>\n",
" <td>3</td>\n",
" <td>28135</td>\n",
" <td>23220.0</td>\n",
" <td>33050.0</td>\n",
" <td>43</td>\n",
" <td>36.0</td>\n",
" <td>50.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>201951</td>\n",
" <td>3</td>\n",
" <td>29786</td>\n",
" <td>25042.0</td>\n",
" <td>34530.0</td>\n",
" <td>45</td>\n",
" <td>38.0</td>\n",
" <td>52.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>201950</td>\n",
" <td>3</td>\n",
" <td>34223</td>\n",
" <td>29156.0</td>\n",
" <td>39290.0</td>\n",
" <td>52</td>\n",
" <td>44.0</td>\n",
" <td>60.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>201949</td>\n",
" <td>3</td>\n",
" <td>25662</td>\n",
" <td>21414.0</td>\n",
" <td>29910.0</td>\n",
" <td>39</td>\n",
" <td>33.0</td>\n",
" <td>45.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>201948</td>\n",
" <td>3</td>\n",
" <td>22367</td>\n",
" <td>18055.0</td>\n",
" <td>26679.0</td>\n",
" <td>34</td>\n",
" <td>27.0</td>\n",
" <td>41.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>201947</td>\n",
" <td>3</td>\n",
" <td>18669</td>\n",
" <td>14759.0</td>\n",
" <td>22579.0</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>17</th>\n",
" <td>201946</td>\n",
" <td>3</td>\n",
" <td>16030</td>\n",
" <td>12567.0</td>\n",
" <td>19493.0</td>\n",
" <td>24</td>\n",
" <td>19.0</td>\n",
" <td>29.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>201945</td>\n",
" <td>3</td>\n",
" <td>10138</td>\n",
" <td>7160.0</td>\n",
" <td>13116.0</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>19</th>\n",
" <td>201944</td>\n",
" <td>3</td>\n",
" <td>7822</td>\n",
" <td>5010.0</td>\n",
" <td>10634.0</td>\n",
" <td>12</td>\n",
" <td>8.0</td>\n",
" <td>16.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>201943</td>\n",
" <td>3</td>\n",
" <td>9487</td>\n",
" <td>6448.0</td>\n",
" <td>12526.0</td>\n",
" <td>14</td>\n",
" <td>9.0</td>\n",
" <td>19.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>201942</td>\n",
" <td>3</td>\n",
" <td>7747</td>\n",
" <td>5243.0</td>\n",
" <td>10251.0</td>\n",
" <td>12</td>\n",
" <td>8.0</td>\n",
" <td>16.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>201941</td>\n",
" <td>3</td>\n",
" <td>7122</td>\n",
" <td>4720.0</td>\n",
" <td>9524.0</td>\n",
" <td>11</td>\n",
" <td>7.0</td>\n",
" <td>15.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>201940</td>\n",
" <td>3</td>\n",
" <td>8505</td>\n",
" <td>5784.0</td>\n",
" <td>11226.0</td>\n",
" <td>13</td>\n",
" <td>9.0</td>\n",
" <td>17.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>201939</td>\n",
" <td>3</td>\n",
" <td>7091</td>\n",
" <td>4462.0</td>\n",
" <td>9720.0</td>\n",
" <td>11</td>\n",
" <td>7.0</td>\n",
" <td>15.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>201938</td>\n",
" <td>3</td>\n",
" <td>4897</td>\n",
" <td>2891.0</td>\n",
" <td>6903.0</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>26</th>\n",
" <td>201937</td>\n",
" <td>3</td>\n",
" <td>3172</td>\n",
" <td>1367.0</td>\n",
" <td>4977.0</td>\n",
" <td>5</td>\n",
" <td>2.0</td>\n",
" <td>8.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>201936</td>\n",
" <td>3</td>\n",
" <td>2295</td>\n",
" <td>728.0</td>\n",
" <td>3862.0</td>\n",
" <td>3</td>\n",
" <td>1.0</td>\n",
" <td>5.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>201935</td>\n",
" <td>3</td>\n",
" <td>1010</td>\n",
" <td>2.0</td>\n",
" <td>2018.0</td>\n",
" <td>2</td>\n",
" <td>0.0</td>\n",
" <td>4.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>201934</td>\n",
" <td>3</td>\n",
" <td>1672</td>\n",
" <td>279.0</td>\n",
" <td>3065.0</td>\n",
" <td>3</td>\n",
" <td>1.0</td>\n",
" <td>5.0</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>1816</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>1817</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>1818</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>1819</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>1820</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>1821</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>1822</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>1823</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>1824</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>1825</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>1826</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>1827</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>1828</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>1829</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>1830</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>1831</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>1832</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>1833</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>1834</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>1835</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>1836</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>1837</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>1838</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>1839</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>1840</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>1841</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>1842</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>1843</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>1844</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>1845</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>1846 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low \\\n",
"0 202011 3 101704 93652.0 109756.0 154 142.0 \n",
"1 202010 3 104977 96650.0 113304.0 159 146.0 \n",
"2 202009 3 110696 102066.0 119326.0 168 155.0 \n",
"3 202008 3 143753 133984.0 153522.0 218 203.0 \n",
"4 202007 3 183610 172812.0 194408.0 279 263.0 \n",
"5 202006 3 206669 195481.0 217857.0 314 297.0 \n",
"6 202005 3 187957 177445.0 198469.0 285 269.0 \n",
"7 202004 3 122331 113492.0 131170.0 186 173.0 \n",
"8 202003 3 78413 71330.0 85496.0 119 108.0 \n",
"9 202002 3 53614 47654.0 59574.0 81 72.0 \n",
"10 202001 3 36850 31608.0 42092.0 56 48.0 \n",
"11 201952 3 28135 23220.0 33050.0 43 36.0 \n",
"12 201951 3 29786 25042.0 34530.0 45 38.0 \n",
"13 201950 3 34223 29156.0 39290.0 52 44.0 \n",
"14 201949 3 25662 21414.0 29910.0 39 33.0 \n",
"15 201948 3 22367 18055.0 26679.0 34 27.0 \n",
"16 201947 3 18669 14759.0 22579.0 28 22.0 \n",
"17 201946 3 16030 12567.0 19493.0 24 19.0 \n",
"18 201945 3 10138 7160.0 13116.0 15 10.0 \n",
"19 201944 3 7822 5010.0 10634.0 12 8.0 \n",
"20 201943 3 9487 6448.0 12526.0 14 9.0 \n",
"21 201942 3 7747 5243.0 10251.0 12 8.0 \n",
"22 201941 3 7122 4720.0 9524.0 11 7.0 \n",
"23 201940 3 8505 5784.0 11226.0 13 9.0 \n",
"24 201939 3 7091 4462.0 9720.0 11 7.0 \n",
"25 201938 3 4897 2891.0 6903.0 7 4.0 \n",
"26 201937 3 3172 1367.0 4977.0 5 2.0 \n",
"27 201936 3 2295 728.0 3862.0 3 1.0 \n",
"28 201935 3 1010 2.0 2018.0 2 0.0 \n",
"29 201934 3 1672 279.0 3065.0 3 1.0 \n",
"... ... ... ... ... ... ... ... \n",
"1816 198521 3 26096 19621.0 32571.0 47 35.0 \n",
"1817 198520 3 27896 20885.0 34907.0 51 38.0 \n",
"1818 198519 3 43154 32821.0 53487.0 78 59.0 \n",
"1819 198518 3 40555 29935.0 51175.0 74 55.0 \n",
"1820 198517 3 34053 24366.0 43740.0 62 44.0 \n",
"1821 198516 3 50362 36451.0 64273.0 91 66.0 \n",
"1822 198515 3 63881 45538.0 82224.0 116 83.0 \n",
"1823 198514 3 134545 114400.0 154690.0 244 207.0 \n",
"1824 198513 3 197206 176080.0 218332.0 357 319.0 \n",
"1825 198512 3 245240 223304.0 267176.0 445 405.0 \n",
"1826 198511 3 276205 252399.0 300011.0 501 458.0 \n",
"1827 198510 3 353231 326279.0 380183.0 640 591.0 \n",
"1828 198509 3 369895 341109.0 398681.0 670 618.0 \n",
"1829 198508 3 389886 359529.0 420243.0 707 652.0 \n",
"1830 198507 3 471852 432599.0 511105.0 855 784.0 \n",
"1831 198506 3 565825 518011.0 613639.0 1026 939.0 \n",
"1832 198505 3 637302 592795.0 681809.0 1155 1074.0 \n",
"1833 198504 3 424937 390794.0 459080.0 770 708.0 \n",
"1834 198503 3 213901 174689.0 253113.0 388 317.0 \n",
"1835 198502 3 97586 80949.0 114223.0 177 147.0 \n",
"1836 198501 3 85489 65918.0 105060.0 155 120.0 \n",
"1837 198452 3 84830 60602.0 109058.0 154 110.0 \n",
"1838 198451 3 101726 80242.0 123210.0 185 146.0 \n",
"1839 198450 3 123680 101401.0 145959.0 225 184.0 \n",
"1840 198449 3 101073 81684.0 120462.0 184 149.0 \n",
"1841 198448 3 78620 60634.0 96606.0 143 110.0 \n",
"1842 198447 3 72029 54274.0 89784.0 131 99.0 \n",
"1843 198446 3 87330 67686.0 106974.0 159 123.0 \n",
"1844 198445 3 135223 101414.0 169032.0 246 184.0 \n",
"1845 198444 3 68422 20056.0 116788.0 125 37.0 \n",
"\n",
" inc100_up geo_insee geo_name \n",
"0 166.0 FR France \n",
"1 172.0 FR France \n",
"2 181.0 FR France \n",
"3 233.0 FR France \n",
"4 295.0 FR France \n",
"5 331.0 FR France \n",
"6 301.0 FR France \n",
"7 199.0 FR France \n",
"8 130.0 FR France \n",
"9 90.0 FR France \n",
"10 64.0 FR France \n",
"11 50.0 FR France \n",
"12 52.0 FR France \n",
"13 60.0 FR France \n",
"14 45.0 FR France \n",
"15 41.0 FR France \n",
"16 34.0 FR France \n",
"17 29.0 FR France \n",
"18 20.0 FR France \n",
"19 16.0 FR France \n",
"20 19.0 FR France \n",
"21 16.0 FR France \n",
"22 15.0 FR France \n",
"23 17.0 FR France \n",
"24 15.0 FR France \n",
"25 10.0 FR France \n",
"26 8.0 FR France \n",
"27 5.0 FR France \n",
"28 4.0 FR France \n",
"29 5.0 FR France \n",
"... ... ... ... \n",
"1816 59.0 FR France \n",
"1817 64.0 FR France \n",
"1818 97.0 FR France \n",
"1819 93.0 FR France \n",
"1820 80.0 FR France \n",
"1821 116.0 FR France \n",
"1822 149.0 FR France \n",
"1823 281.0 FR France \n",
"1824 395.0 FR France \n",
"1825 485.0 FR France \n",
"1826 544.0 FR France \n",
"1827 689.0 FR France \n",
"1828 722.0 FR France \n",
"1829 762.0 FR France \n",
"1830 926.0 FR France \n",
"1831 1113.0 FR France \n",
"1832 1236.0 FR France \n",
"1833 832.0 FR France \n",
"1834 459.0 FR France \n",
"1835 207.0 FR France \n",
"1836 190.0 FR France \n",
"1837 198.0 FR France \n",
"1838 224.0 FR France \n",
"1839 266.0 FR France \n",
"1840 219.0 FR France \n",
"1841 176.0 FR France \n",
"1842 163.0 FR France \n",
"1843 195.0 FR France \n",
"1844 308.0 FR France \n",
"1845 213.0 FR France \n",
"\n",
"[1846 rows x 10 columns]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"if os.path.exists('datas_sentinelle.csv') == True:\n",
" raw_data = pd.read_csv('datas_sentinelle.csv', skiprows=1)\n",
"else:\n",
" data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"\n",
" raw_data = pd.read_csv(data_url, skiprows=1)\n",
"raw_data"
]
},
{ {
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
...@@ -364,7 +1344,7 @@ ...@@ -364,7 +1344,7 @@
"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,
......
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