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f82c1c4a1227cdba8ff3317d228324d6
mooc-rr
Commits
ea00ac7e
Commit
ea00ac7e
authored
Jan 22, 2024
by
f82c1c4a1227cdba8ff3317d228324d6
Browse files
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deuxieme
parent
1cb25555
Changes
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analyse-syndrome-varicelle-jupyter.ipynb
module3/exo2/analyse-syndrome-varicelle-jupyter.ipynb
+19
-967
No files found.
module3/exo2/analyse-syndrome-varicelle-jupyter.ipynb
View file @
ea00ac7e
...
...
@@ -28,11 +28,11 @@
},
{
"cell_type": "code",
"execution_count": 2
0
,
"execution_count": 2
1
,
"metadata": {},
"outputs": [],
"source": [
"data_url =
\"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"
"
"data_url =
r'D:\\Varicelle\\incidence-PAY-7.csv'
"
]
},
{
...
...
@@ -59,974 +59,26 @@
},
{
"cell_type": "code",
"execution_count":
3
,
"execution_count":
22
,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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" <th>7</th>\n",
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" <td>3</td>\n",
" <td>1506</td>\n",
" <td>239.0</td>\n",
" <td>2773.0</td>\n",
" <td>2</td>\n",
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" <td>4.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>8</th>\n",
" <td>201834</td>\n",
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" <td>1368</td>\n",
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" <td>2620.0</td>\n",
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" <tr>\n",
" <th>9</th>\n",
" <td>201833</td>\n",
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" <td>5.0</td>\n",
" <td>3919.0</td>\n",
" <td>3</td>\n",
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" <td>6.0</td>\n",
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" <td>3495.0</td>\n",
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" <td>201831</td>\n",
" <td>3</td>\n",
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" <td>3854.0</td>\n",
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" <td>6.0</td>\n",
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" <td>6.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <th>13</th>\n",
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" <td>3</td>\n",
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" <td>3650.0</td>\n",
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" <td>3</td>\n",
" <td>1654</td>\n",
" <td>52.0</td>\n",
" <td>3256.0</td>\n",
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" <th>15</th>\n",
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" <td>3</td>\n",
" <td>3269</td>\n",
" <td>1145.0</td>\n",
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" <td>8.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <th>16</th>\n",
" <td>201826</td>\n",
" <td>3</td>\n",
" <td>3758</td>\n",
" <td>1493.0</td>\n",
" <td>6023.0</td>\n",
" <td>6</td>\n",
" <td>3.0</td>\n",
" <td>9.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>17</th>\n",
" <td>201825</td>\n",
" <td>3</td>\n",
" <td>4580</td>\n",
" <td>2220.0</td>\n",
" <td>6940.0</td>\n",
" <td>7</td>\n",
" <td>3.0</td>\n",
" <td>11.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>201824</td>\n",
" <td>3</td>\n",
" <td>3223</td>\n",
" <td>1351.0</td>\n",
" <td>5095.0</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>19</th>\n",
" <td>201823</td>\n",
" <td>3</td>\n",
" <td>1207</td>\n",
" <td>136.0</td>\n",
" <td>2278.0</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>20</th>\n",
" <td>201822</td>\n",
" <td>3</td>\n",
" <td>3202</td>\n",
" <td>1330.0</td>\n",
" <td>5074.0</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>21</th>\n",
" <td>201821</td>\n",
" <td>3</td>\n",
" <td>2537</td>\n",
" <td>763.0</td>\n",
" <td>4311.0</td>\n",
" <td>4</td>\n",
" <td>1.0</td>\n",
" <td>7.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>201820</td>\n",
" <td>3</td>\n",
" <td>2694</td>\n",
" <td>967.0</td>\n",
" <td>4421.0</td>\n",
" <td>4</td>\n",
" <td>1.0</td>\n",
" <td>7.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>201819</td>\n",
" <td>3</td>\n",
" <td>1025</td>\n",
" <td>0.0</td>\n",
" <td>2098.0</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>24</th>\n",
" <td>201818</td>\n",
" <td>3</td>\n",
" <td>3541</td>\n",
" <td>1416.0</td>\n",
" <td>5666.0</td>\n",
" <td>5</td>\n",
" <td>2.0</td>\n",
" <td>8.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>25</th>\n",
" <td>201817</td>\n",
" <td>3</td>\n",
" <td>2573</td>\n",
" <td>1003.0</td>\n",
" <td>4143.0</td>\n",
" <td>4</td>\n",
" <td>2.0</td>\n",
" <td>6.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>201816</td>\n",
" <td>3</td>\n",
" <td>4818</td>\n",
" <td>2724.0</td>\n",
" <td>6912.0</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>27</th>\n",
" <td>201815</td>\n",
" <td>3</td>\n",
" <td>16311</td>\n",
" <td>12168.0</td>\n",
" <td>20454.0</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>28</th>\n",
" <td>201814</td>\n",
" <td>3</td>\n",
" <td>22666</td>\n",
" <td>18092.0</td>\n",
" <td>27240.0</td>\n",
" <td>35</td>\n",
" <td>28.0</td>\n",
" <td>42.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>201813</td>\n",
" <td>3</td>\n",
" <td>32680</td>\n",
" <td>25536.0</td>\n",
" <td>39824.0</td>\n",
" <td>50</td>\n",
" <td>39.0</td>\n",
" <td>61.0</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>1743</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>1744</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>1745</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>1746</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>1747</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",
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" <tr>\n",
" <th>1748</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>1749</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>1750</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>1751</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>1752</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>1753</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>1754</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>1755</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>1756</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>1757</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>1758</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>1759</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>1760</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>1761</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>1762</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>1763</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>1764</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>1765</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>1766</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>1767</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>1768</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>1769</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>1770</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>1771</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>1772</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>1773 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low \\\n",
"0 201842 3 7832 5145.0 10519.0 12 8.0 \n",
"1 201841 3 8048 5098.0 10998.0 12 8.0 \n",
"2 201840 3 7409 4717.0 10101.0 11 7.0 \n",
"3 201839 3 7174 4235.0 10113.0 11 7.0 \n",
"4 201838 3 6127 3482.0 8772.0 9 5.0 \n",
"5 201837 3 4644 2200.0 7088.0 7 3.0 \n",
"6 201836 3 3215 1349.0 5081.0 5 2.0 \n",
"7 201835 3 1506 239.0 2773.0 2 0.0 \n",
"8 201834 3 1368 116.0 2620.0 2 0.0 \n",
"9 201833 3 1962 5.0 3919.0 3 0.0 \n",
"10 201832 3 1839 183.0 3495.0 3 0.0 \n",
"11 201831 3 2048 242.0 3854.0 3 0.0 \n",
"12 201830 3 1951 202.0 3700.0 3 0.0 \n",
"13 201829 3 1951 252.0 3650.0 3 0.0 \n",
"14 201828 3 1654 52.0 3256.0 3 1.0 \n",
"15 201827 3 3269 1145.0 5393.0 5 2.0 \n",
"16 201826 3 3758 1493.0 6023.0 6 3.0 \n",
"17 201825 3 4580 2220.0 6940.0 7 3.0 \n",
"18 201824 3 3223 1351.0 5095.0 5 2.0 \n",
"19 201823 3 1207 136.0 2278.0 2 0.0 \n",
"20 201822 3 3202 1330.0 5074.0 5 2.0 \n",
"21 201821 3 2537 763.0 4311.0 4 1.0 \n",
"22 201820 3 2694 967.0 4421.0 4 1.0 \n",
"23 201819 3 1025 0.0 2098.0 2 0.0 \n",
"24 201818 3 3541 1416.0 5666.0 5 2.0 \n",
"25 201817 3 2573 1003.0 4143.0 4 2.0 \n",
"26 201816 3 4818 2724.0 6912.0 7 4.0 \n",
"27 201815 3 16311 12168.0 20454.0 25 19.0 \n",
"28 201814 3 22666 18092.0 27240.0 35 28.0 \n",
"29 201813 3 32680 25536.0 39824.0 50 39.0 \n",
"... ... ... ... ... ... ... ... \n",
"1743 198521 3 26096 19621.0 32571.0 47 35.0 \n",
"1744 198520 3 27896 20885.0 34907.0 51 38.0 \n",
"1745 198519 3 43154 32821.0 53487.0 78 59.0 \n",
"1746 198518 3 40555 29935.0 51175.0 74 55.0 \n",
"1747 198517 3 34053 24366.0 43740.0 62 44.0 \n",
"1748 198516 3 50362 36451.0 64273.0 91 66.0 \n",
"1749 198515 3 63881 45538.0 82224.0 116 83.0 \n",
"1750 198514 3 134545 114400.0 154690.0 244 207.0 \n",
"1751 198513 3 197206 176080.0 218332.0 357 319.0 \n",
"1752 198512 3 245240 223304.0 267176.0 445 405.0 \n",
"1753 198511 3 276205 252399.0 300011.0 501 458.0 \n",
"1754 198510 3 353231 326279.0 380183.0 640 591.0 \n",
"1755 198509 3 369895 341109.0 398681.0 670 618.0 \n",
"1756 198508 3 389886 359529.0 420243.0 707 652.0 \n",
"1757 198507 3 471852 432599.0 511105.0 855 784.0 \n",
"1758 198506 3 565825 518011.0 613639.0 1026 939.0 \n",
"1759 198505 3 637302 592795.0 681809.0 1155 1074.0 \n",
"1760 198504 3 424937 390794.0 459080.0 770 708.0 \n",
"1761 198503 3 213901 174689.0 253113.0 388 317.0 \n",
"1762 198502 3 97586 80949.0 114223.0 177 147.0 \n",
"1763 198501 3 85489 65918.0 105060.0 155 120.0 \n",
"1764 198452 3 84830 60602.0 109058.0 154 110.0 \n",
"1765 198451 3 101726 80242.0 123210.0 185 146.0 \n",
"1766 198450 3 123680 101401.0 145959.0 225 184.0 \n",
"1767 198449 3 101073 81684.0 120462.0 184 149.0 \n",
"1768 198448 3 78620 60634.0 96606.0 143 110.0 \n",
"1769 198447 3 72029 54274.0 89784.0 131 99.0 \n",
"1770 198446 3 87330 67686.0 106974.0 159 123.0 \n",
"1771 198445 3 135223 101414.0 169032.0 246 184.0 \n",
"1772 198444 3 68422 20056.0 116788.0 125 37.0 \n",
"\n",
" inc100_up geo_insee geo_name \n",
"0 16.0 FR France \n",
"1 16.0 FR France \n",
"2 15.0 FR France \n",
"3 15.0 FR France \n",
"4 13.0 FR France \n",
"5 11.0 FR France \n",
"6 8.0 FR France \n",
"7 4.0 FR France \n",
"8 4.0 FR France \n",
"9 6.0 FR France \n",
"10 6.0 FR France \n",
"11 6.0 FR France \n",
"12 6.0 FR France \n",
"13 6.0 FR France \n",
"14 5.0 FR France \n",
"15 8.0 FR France \n",
"16 9.0 FR France \n",
"17 11.0 FR France \n",
"18 8.0 FR France \n",
"19 4.0 FR France \n",
"20 8.0 FR France \n",
"21 7.0 FR France \n",
"22 7.0 FR France \n",
"23 4.0 FR France \n",
"24 8.0 FR France \n",
"25 6.0 FR France \n",
"26 10.0 FR France \n",
"27 31.0 FR France \n",
"28 42.0 FR France \n",
"29 61.0 FR France \n",
"... ... ... ... \n",
"1743 59.0 FR France \n",
"1744 64.0 FR France \n",
"1745 97.0 FR France \n",
"1746 93.0 FR France \n",
"1747 80.0 FR France \n",
"1748 116.0 FR France \n",
"1749 149.0 FR France \n",
"1750 281.0 FR France \n",
"1751 395.0 FR France \n",
"1752 485.0 FR France \n",
"1753 544.0 FR France \n",
"1754 689.0 FR France \n",
"1755 722.0 FR France \n",
"1756 762.0 FR France \n",
"1757 926.0 FR France \n",
"1758 1113.0 FR France \n",
"1759 1236.0 FR France \n",
"1760 832.0 FR France \n",
"1761 459.0 FR France \n",
"1762 207.0 FR France \n",
"1763 190.0 FR France \n",
"1764 198.0 FR France \n",
"1765 224.0 FR France \n",
"1766 266.0 FR France \n",
"1767 219.0 FR France \n",
"1768 176.0 FR France \n",
"1769 163.0 FR France \n",
"1770 195.0 FR France \n",
"1771 308.0 FR France \n",
"1772 213.0 FR France \n",
"\n",
"[1773 rows x 10 columns]"
"ename": "FileNotFoundError",
"evalue": "File b'D:\\\\Varicelle\\\\incidence-PAY-7.csv' does not exist",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-22-95280424b895>\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[0mencoding\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'iso-8859-1'\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;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)\u001b[0m\n\u001b[1;32m 707\u001b[0m skip_blank_lines=skip_blank_lines)\n\u001b[1;32m 708\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 709\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 710\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 711\u001b[0m \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 447\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 448\u001b[0m \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 449\u001b[0;31m \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 450\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 451\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m 816\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 818\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 819\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 820\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m 1047\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'c'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1048\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'c'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1049\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1050\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1051\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'python'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m 1693\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'allow_leading_cols'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex_col\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1694\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1695\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparsers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1696\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1697\u001b[0m \u001b[0;31m# XXX\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.__cinit__\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._setup_parser_source\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mFileNotFoundError\u001b[0m: File b'D:\\\\Varicelle\\\\incidence-PAY-7.csv' does not exist"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
...
...
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