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Commit e7807342 authored by 2ac5187c3892095c69fae73b3a71c622's avatar 2ac5187c3892095c69fae73b3a71c622
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module3/exo1/analyse-syndrome-grippal.ipynb
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...@@ -9,14 +9,14 @@ ...@@ -9,14 +9,14 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 10,
"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"
] ]
}, },
{ {
...@@ -28,13 +28,12 @@ ...@@ -28,13 +28,12 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 11,
"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\"\n",
"data_path = \"data.csv\""
] ]
}, },
{ {
...@@ -61,11 +60,1056 @@ ...@@ -61,11 +60,1056 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 12,
"metadata": {}, "metadata": {
"outputs": [], "scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Downloading data from : http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\n"
]
},
{
"data": {
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" <th>1856</th>\n",
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" <td>91</td>\n",
" <td>66.0</td>\n",
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" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>1857</th>\n",
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" <th>1858</th>\n",
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" <th>1859</th>\n",
" <td>1860</td>\n",
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" <td>197206</td>\n",
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" <td>357</td>\n",
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" <tr>\n",
" <th>1860</th>\n",
" <td>1861</td>\n",
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" <tr>\n",
" <th>1861</th>\n",
" <td>1862</td>\n",
" <td>198511</td>\n",
" <td>3</td>\n",
" <td>276205</td>\n",
" <td>252399.0</td>\n",
" <td>300011.0</td>\n",
" <td>501</td>\n",
" <td>458.0</td>\n",
" <td>544.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1862</th>\n",
" <td>1863</td>\n",
" <td>198510</td>\n",
" <td>3</td>\n",
" <td>353231</td>\n",
" <td>326279.0</td>\n",
" <td>380183.0</td>\n",
" <td>640</td>\n",
" <td>591.0</td>\n",
" <td>689.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1863</th>\n",
" <td>1864</td>\n",
" <td>198509</td>\n",
" <td>3</td>\n",
" <td>369895</td>\n",
" <td>341109.0</td>\n",
" <td>398681.0</td>\n",
" <td>670</td>\n",
" <td>618.0</td>\n",
" <td>722.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1864</th>\n",
" <td>1865</td>\n",
" <td>198508</td>\n",
" <td>3</td>\n",
" <td>389886</td>\n",
" <td>359529.0</td>\n",
" <td>420243.0</td>\n",
" <td>707</td>\n",
" <td>652.0</td>\n",
" <td>762.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1865</th>\n",
" <td>1866</td>\n",
" <td>198507</td>\n",
" <td>3</td>\n",
" <td>471852</td>\n",
" <td>432599.0</td>\n",
" <td>511105.0</td>\n",
" <td>855</td>\n",
" <td>784.0</td>\n",
" <td>926.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1866</th>\n",
" <td>1867</td>\n",
" <td>198506</td>\n",
" <td>3</td>\n",
" <td>565825</td>\n",
" <td>518011.0</td>\n",
" <td>613639.0</td>\n",
" <td>1026</td>\n",
" <td>939.0</td>\n",
" <td>1113.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1867</th>\n",
" <td>1868</td>\n",
" <td>198505</td>\n",
" <td>3</td>\n",
" <td>637302</td>\n",
" <td>592795.0</td>\n",
" <td>681809.0</td>\n",
" <td>1155</td>\n",
" <td>1074.0</td>\n",
" <td>1236.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1868</th>\n",
" <td>1869</td>\n",
" <td>198504</td>\n",
" <td>3</td>\n",
" <td>424937</td>\n",
" <td>390794.0</td>\n",
" <td>459080.0</td>\n",
" <td>770</td>\n",
" <td>708.0</td>\n",
" <td>832.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1869</th>\n",
" <td>1870</td>\n",
" <td>198503</td>\n",
" <td>3</td>\n",
" <td>213901</td>\n",
" <td>174689.0</td>\n",
" <td>253113.0</td>\n",
" <td>388</td>\n",
" <td>317.0</td>\n",
" <td>459.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1870</th>\n",
" <td>1871</td>\n",
" <td>198502</td>\n",
" <td>3</td>\n",
" <td>97586</td>\n",
" <td>80949.0</td>\n",
" <td>114223.0</td>\n",
" <td>177</td>\n",
" <td>147.0</td>\n",
" <td>207.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1871</th>\n",
" <td>1872</td>\n",
" <td>198501</td>\n",
" <td>3</td>\n",
" <td>85489</td>\n",
" <td>65918.0</td>\n",
" <td>105060.0</td>\n",
" <td>155</td>\n",
" <td>120.0</td>\n",
" <td>190.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1872</th>\n",
" <td>1873</td>\n",
" <td>198452</td>\n",
" <td>3</td>\n",
" <td>84830</td>\n",
" <td>60602.0</td>\n",
" <td>109058.0</td>\n",
" <td>154</td>\n",
" <td>110.0</td>\n",
" <td>198.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1873</th>\n",
" <td>1874</td>\n",
" <td>198451</td>\n",
" <td>3</td>\n",
" <td>101726</td>\n",
" <td>80242.0</td>\n",
" <td>123210.0</td>\n",
" <td>185</td>\n",
" <td>146.0</td>\n",
" <td>224.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1874</th>\n",
" <td>1875</td>\n",
" <td>198450</td>\n",
" <td>3</td>\n",
" <td>123680</td>\n",
" <td>101401.0</td>\n",
" <td>145959.0</td>\n",
" <td>225</td>\n",
" <td>184.0</td>\n",
" <td>266.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1875</th>\n",
" <td>1876</td>\n",
" <td>198449</td>\n",
" <td>3</td>\n",
" <td>101073</td>\n",
" <td>81684.0</td>\n",
" <td>120462.0</td>\n",
" <td>184</td>\n",
" <td>149.0</td>\n",
" <td>219.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1876</th>\n",
" <td>1877</td>\n",
" <td>198448</td>\n",
" <td>3</td>\n",
" <td>78620</td>\n",
" <td>60634.0</td>\n",
" <td>96606.0</td>\n",
" <td>143</td>\n",
" <td>110.0</td>\n",
" <td>176.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1877</th>\n",
" <td>1878</td>\n",
" <td>198447</td>\n",
" <td>3</td>\n",
" <td>72029</td>\n",
" <td>54274.0</td>\n",
" <td>89784.0</td>\n",
" <td>131</td>\n",
" <td>99.0</td>\n",
" <td>163.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1878</th>\n",
" <td>1879</td>\n",
" <td>198446</td>\n",
" <td>3</td>\n",
" <td>87330</td>\n",
" <td>67686.0</td>\n",
" <td>106974.0</td>\n",
" <td>159</td>\n",
" <td>123.0</td>\n",
" <td>195.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1879</th>\n",
" <td>1880</td>\n",
" <td>198445</td>\n",
" <td>3</td>\n",
" <td>135223</td>\n",
" <td>101414.0</td>\n",
" <td>169032.0</td>\n",
" <td>246</td>\n",
" <td>184.0</td>\n",
" <td>308.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1880</th>\n",
" <td>1881</td>\n",
" <td>198444</td>\n",
" <td>3</td>\n",
" <td>68422</td>\n",
" <td>20056.0</td>\n",
" <td>116788.0</td>\n",
" <td>125</td>\n",
" <td>37.0</td>\n",
" <td>213.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1881 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" 0 202047 3 21191 16469.0 25913.0 32 25.0 39.0 FR \\\n",
"0 1 202046 3 25103 20716.0 29490.0 38 31.0 45.0 FR \n",
"1 2 202045 3 42516 36857.0 48175.0 65 56.0 74.0 FR \n",
"2 3 202044 3 44567 38521.0 50613.0 68 59.0 77.0 FR \n",
"3 4 202043 3 43737 37523.0 49951.0 66 57.0 75.0 FR \n",
"4 5 202042 3 35145 29812.0 40478.0 53 45.0 61.0 FR \n",
"5 6 202041 3 27877 23206.0 32548.0 42 35.0 49.0 FR \n",
"6 7 202040 3 20443 16381.0 24505.0 31 25.0 37.0 FR \n",
"7 8 202039 3 19810 15900.0 23720.0 30 24.0 36.0 FR \n",
"8 9 202038 3 25562 21142.0 29982.0 39 32.0 46.0 FR \n",
"9 10 202037 3 18485 14649.0 22321.0 28 22.0 34.0 FR \n",
"10 11 202036 3 10390 7646.0 13134.0 16 12.0 20.0 FR \n",
"11 12 202035 3 9918 6842.0 12994.0 15 10.0 20.0 FR \n",
"12 13 202034 3 6084 3090.0 9078.0 9 4.0 14.0 FR \n",
"13 14 202033 3 6106 3411.0 8801.0 9 5.0 13.0 FR \n",
"14 15 202032 3 5918 3330.0 8506.0 9 5.0 13.0 FR \n",
"15 16 202031 3 4351 2269.0 6433.0 7 4.0 10.0 FR \n",
"16 17 202030 3 8179 5442.0 10916.0 12 8.0 16.0 FR \n",
"17 18 202029 3 8687 5860.0 11514.0 13 9.0 17.0 FR \n",
"18 19 202028 3 8340 5701.0 10979.0 13 9.0 17.0 FR \n",
"19 20 202027 3 4066 2406.0 5726.0 6 3.0 9.0 FR \n",
"20 21 202026 3 4039 2389.0 5689.0 6 3.0 9.0 FR \n",
"21 22 202025 3 2853 1488.0 4218.0 4 2.0 6.0 FR \n",
"22 23 202024 3 3058 1690.0 4426.0 5 3.0 7.0 FR \n",
"23 24 202023 3 4168 2468.0 5868.0 6 3.0 9.0 FR \n",
"24 25 202022 3 3580 1947.0 5213.0 5 3.0 7.0 FR \n",
"25 26 202021 3 6114 4026.0 8202.0 9 6.0 12.0 FR \n",
"26 27 202020 3 9315 6775.0 11855.0 14 10.0 18.0 FR \n",
"27 28 202019 3 11679 8722.0 14636.0 18 14.0 22.0 FR \n",
"28 29 202018 3 16398 12851.0 19945.0 25 20.0 30.0 FR \n",
"29 30 202017 3 18082 14454.0 21710.0 27 21.0 33.0 FR \n",
"... ... ... .. ... ... ... ... ... ... .. \n",
"1851 1852 198521 3 26096 19621.0 32571.0 47 35.0 59.0 FR \n",
"1852 1853 198520 3 27896 20885.0 34907.0 51 38.0 64.0 FR \n",
"1853 1854 198519 3 43154 32821.0 53487.0 78 59.0 97.0 FR \n",
"1854 1855 198518 3 40555 29935.0 51175.0 74 55.0 93.0 FR \n",
"1855 1856 198517 3 34053 24366.0 43740.0 62 44.0 80.0 FR \n",
"1856 1857 198516 3 50362 36451.0 64273.0 91 66.0 116.0 FR \n",
"1857 1858 198515 3 63881 45538.0 82224.0 116 83.0 149.0 FR \n",
"1858 1859 198514 3 134545 114400.0 154690.0 244 207.0 281.0 FR \n",
"1859 1860 198513 3 197206 176080.0 218332.0 357 319.0 395.0 FR \n",
"1860 1861 198512 3 245240 223304.0 267176.0 445 405.0 485.0 FR \n",
"1861 1862 198511 3 276205 252399.0 300011.0 501 458.0 544.0 FR \n",
"1862 1863 198510 3 353231 326279.0 380183.0 640 591.0 689.0 FR \n",
"1863 1864 198509 3 369895 341109.0 398681.0 670 618.0 722.0 FR \n",
"1864 1865 198508 3 389886 359529.0 420243.0 707 652.0 762.0 FR \n",
"1865 1866 198507 3 471852 432599.0 511105.0 855 784.0 926.0 FR \n",
"1866 1867 198506 3 565825 518011.0 613639.0 1026 939.0 1113.0 FR \n",
"1867 1868 198505 3 637302 592795.0 681809.0 1155 1074.0 1236.0 FR \n",
"1868 1869 198504 3 424937 390794.0 459080.0 770 708.0 832.0 FR \n",
"1869 1870 198503 3 213901 174689.0 253113.0 388 317.0 459.0 FR \n",
"1870 1871 198502 3 97586 80949.0 114223.0 177 147.0 207.0 FR \n",
"1871 1872 198501 3 85489 65918.0 105060.0 155 120.0 190.0 FR \n",
"1872 1873 198452 3 84830 60602.0 109058.0 154 110.0 198.0 FR \n",
"1873 1874 198451 3 101726 80242.0 123210.0 185 146.0 224.0 FR \n",
"1874 1875 198450 3 123680 101401.0 145959.0 225 184.0 266.0 FR \n",
"1875 1876 198449 3 101073 81684.0 120462.0 184 149.0 219.0 FR \n",
"1876 1877 198448 3 78620 60634.0 96606.0 143 110.0 176.0 FR \n",
"1877 1878 198447 3 72029 54274.0 89784.0 131 99.0 163.0 FR \n",
"1878 1879 198446 3 87330 67686.0 106974.0 159 123.0 195.0 FR \n",
"1879 1880 198445 3 135223 101414.0 169032.0 246 184.0 308.0 FR \n",
"1880 1881 198444 3 68422 20056.0 116788.0 125 37.0 213.0 FR \n",
"\n",
" France \n",
"0 France \n",
"1 France \n",
"2 France \n",
"3 France \n",
"4 France \n",
"5 France \n",
"6 France \n",
"7 France \n",
"8 France \n",
"9 France \n",
"10 France \n",
"11 France \n",
"12 France \n",
"13 France \n",
"14 France \n",
"15 France \n",
"16 France \n",
"17 France \n",
"18 France \n",
"19 France \n",
"20 France \n",
"21 France \n",
"22 France \n",
"23 France \n",
"24 France \n",
"25 France \n",
"26 France \n",
"27 France \n",
"28 France \n",
"29 France \n",
"... ... \n",
"1851 France \n",
"1852 France \n",
"1853 France \n",
"1854 France \n",
"1855 France \n",
"1856 France \n",
"1857 France \n",
"1858 France \n",
"1859 France \n",
"1860 France \n",
"1861 France \n",
"1862 France \n",
"1863 France \n",
"1864 France \n",
"1865 France \n",
"1866 France \n",
"1867 France \n",
"1868 France \n",
"1869 France \n",
"1870 France \n",
"1871 France \n",
"1872 France \n",
"1873 France \n",
"1874 France \n",
"1875 France \n",
"1876 France \n",
"1877 France \n",
"1878 France \n",
"1879 France \n",
"1880 France \n",
"\n",
"[1881 rows x 11 columns]"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"raw_data = pd.read_csv(data_url, skiprows=1)\n", "try :\n",
" open(data_path)\n",
"except IOError:\n",
" print(\"Downloading data from : \" + data_url)\n",
" pd.read_csv(data_url, skiprows=1).to_csv(data_path)\n",
" \n",
" \n",
"raw_data = pd.read_csv(data_path, skiprows=1)\n",
"raw_data" "raw_data"
] ]
}, },
...@@ -73,6 +1117,16 @@ ...@@ -73,6 +1117,16 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"Si le fichier `data.csv` n'existe pas alors on télécharge le csv depuis l'url `data_url`"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\n",
"Y a-t-il des points manquants dans ce jeux de données ? Oui, la semaine 19 de l'année 1989 n'a pas de valeurs associées." "Y a-t-il des points manquants dans ce jeux de données ? Oui, la semaine 19 de l'année 1989 n'a pas de valeurs associées."
] ]
}, },
...@@ -364,7 +1418,7 @@ ...@@ -364,7 +1418,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.6.1" "version": "3.6.4"
} }
}, },
"nbformat": 4, "nbformat": 4,
......
module3/exo1/data.csv 0 → 100644
View file @ e7807342
This source diff could not be displayed because it is too large. You can view the blob instead.
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