From bdf23e1c0ce860271b39f74e859a518885d7c9b3 Mon Sep 17 00:00:00 2001 From: 451defe1a1074031578ff629b9291801 <451defe1a1074031578ff629b9291801@app-learninglab.inria.fr> Date: Wed, 16 Dec 2020 18:08:55 +0000 Subject: [PATCH] Version finale --- module3/exo1/analyse-syndrome-grippal.ipynb | 1512 +++++++- module3/exo1/incidence-PAY-3.csv | 3769 ++++++++++--------- 2 files changed, 3328 insertions(+), 1953 deletions(-) diff --git a/module3/exo1/analyse-syndrome-grippal.ipynb b/module3/exo1/analyse-syndrome-grippal.ipynb index 27bf3b4..a500c08 100644 --- a/module3/exo1/analyse-syndrome-grippal.ipynb +++ b/module3/exo1/analyse-syndrome-grippal.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ @@ -28,7 +28,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -66,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 26, "metadata": {}, "outputs": [ { @@ -78,11 +78,210 @@ }, { "data": { + "text/html": [ + "
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" + ], "text/plain": [ - "1883" + " Unnamed: 0 week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 0 202050 3 18434 13528.0 23340.0 28 21.0 \n", + "1 1 202049 3 13273 10162.0 16384.0 20 15.0 \n", + "2 2 202048 3 13804 10641.0 16967.0 21 16.0 \n", + "3 3 202047 3 19085 15285.0 22885.0 29 23.0 \n", + "4 4 202046 3 24801 20503.0 29099.0 38 31.0 \n", + "5 5 202045 3 42516 36857.0 48175.0 65 56.0 \n", + "6 6 202044 3 44567 38521.0 50613.0 68 59.0 \n", + "7 7 202043 3 43737 37523.0 49951.0 66 57.0 \n", + "8 8 202042 3 35145 29812.0 40478.0 53 45.0 \n", + "9 9 202041 3 27877 23206.0 32548.0 42 35.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 35.0 FR France \n", + "1 25.0 FR France \n", + "2 26.0 FR France \n", + "3 35.0 FR France \n", + "4 45.0 FR France \n", + "5 74.0 FR France \n", + "6 77.0 FR France \n", + "7 75.0 FR France \n", + "8 61.0 FR France \n", + "9 49.0 FR France " ] }, - "execution_count": 11, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -90,15 +289,17 @@ "source": [ "#raw_data = pd.read_csv(data_url, skiprows=1)\n", "#raw_data\n", - "#raw_data.to_csv('incidence-PAY-3.csv')\n", + "#raw_data.to_csv('incidence-PAY-3.csv', header = True)\n", + "\n", "import os\n", "if os.path.isfile('incidence-PAY-3.csv'):\n", - " raw_data = pd.read_csv('incidence-PAY-3.csv', skiprows = 1)\n", + " raw_data = pd.read_csv('incidence-PAY-3.csv')\n", " print('existe')\n", "else:\n", " print(\"n'existe pas\")\n", " raw_data = pd.read_csv(data_url, skiprows = 1)\n", - "len(raw_data)" + "len(raw_data)\n", + "raw_data[:10]" ] }, { @@ -110,7 +311,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 27, "metadata": {}, "outputs": [ { @@ -134,64 +335,1096 @@ " \n", " \n", " \n", + " Unnamed: 0\n", + " week\n", + " indicator\n", + " inc\n", + " inc_low\n", + " inc_up\n", + " inc100\n", + " inc100_low\n", + " inc100_up\n", + " geo_insee\n", + " geo_name\n", + " \n", + " \n", + " \n", + " \n", + " 1648\n", + " 1648\n", + " 198919\n", + " 3\n", + " 0\n", + " NaN\n", + " NaN\n", + " 0\n", + " NaN\n", + " NaN\n", + " FR\n", + " France\n", + " \n", + " \n", + "\n", + "" + ], + "text/plain": [ + " Unnamed: 0 week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "1648 1648 198919 3 0 NaN NaN 0 NaN \n", + "\n", + " inc100_up geo_insee geo_name \n", + "1648 NaN FR France " + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "raw_data[raw_data.isnull().any(axis=1)]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nous éliminons ce point, ce qui n'a pas d'impact fort sur notre analyse qui est assez simple." + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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1875187519850138548965918.0105060.0155120.0190.0FRFrance
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1884 rows × 11 columns

\n", "
" ], "text/plain": [ - " 0 202049 3 13273 10162.0 16384.0 20 15.0 25.0 FR France\n", - "1646 1647 198919 3 0 NaN NaN 0 NaN NaN FR France" + " Unnamed: 0 week indicator inc inc_low inc_up inc100 \\\n", + "0 0 202050 3 18434 13528.0 23340.0 28 \n", + "1 1 202049 3 13273 10162.0 16384.0 20 \n", + "2 2 202048 3 13804 10641.0 16967.0 21 \n", + "3 3 202047 3 19085 15285.0 22885.0 29 \n", + "4 4 202046 3 24801 20503.0 29099.0 38 \n", + "5 5 202045 3 42516 36857.0 48175.0 65 \n", + "6 6 202044 3 44567 38521.0 50613.0 68 \n", + "7 7 202043 3 43737 37523.0 49951.0 66 \n", + "8 8 202042 3 35145 29812.0 40478.0 53 \n", + "9 9 202041 3 27877 23206.0 32548.0 42 \n", + "10 10 202040 3 20443 16381.0 24505.0 31 \n", + "11 11 202039 3 19810 15900.0 23720.0 30 \n", + "12 12 202038 3 25562 21142.0 29982.0 39 \n", + "13 13 202037 3 18485 14649.0 22321.0 28 \n", + "14 14 202036 3 10390 7646.0 13134.0 16 \n", + "15 15 202035 3 9918 6842.0 12994.0 15 \n", + "16 16 202034 3 6084 3090.0 9078.0 9 \n", + "17 17 202033 3 6106 3411.0 8801.0 9 \n", + "18 18 202032 3 5918 3330.0 8506.0 9 \n", + "19 19 202031 3 4351 2269.0 6433.0 7 \n", + "20 20 202030 3 8179 5442.0 10916.0 12 \n", + "21 21 202029 3 8687 5860.0 11514.0 13 \n", + "22 22 202028 3 8340 5701.0 10979.0 13 \n", + "23 23 202027 3 4066 2406.0 5726.0 6 \n", + "24 24 202026 3 4039 2389.0 5689.0 6 \n", + "25 25 202025 3 2853 1488.0 4218.0 4 \n", + "26 26 202024 3 3058 1690.0 4426.0 5 \n", + "27 27 202023 3 4168 2468.0 5868.0 6 \n", + "28 28 202022 3 3580 1947.0 5213.0 5 \n", + "29 29 202021 3 6114 4026.0 8202.0 9 \n", + "... ... ... ... ... ... ... ... \n", + "1855 1855 198521 3 26096 19621.0 32571.0 47 \n", + "1856 1856 198520 3 27896 20885.0 34907.0 51 \n", + "1857 1857 198519 3 43154 32821.0 53487.0 78 \n", + "1858 1858 198518 3 40555 29935.0 51175.0 74 \n", + "1859 1859 198517 3 34053 24366.0 43740.0 62 \n", + "1860 1860 198516 3 50362 36451.0 64273.0 91 \n", + "1861 1861 198515 3 63881 45538.0 82224.0 116 \n", + "1862 1862 198514 3 134545 114400.0 154690.0 244 \n", + "1863 1863 198513 3 197206 176080.0 218332.0 357 \n", + "1864 1864 198512 3 245240 223304.0 267176.0 445 \n", + "1865 1865 198511 3 276205 252399.0 300011.0 501 \n", + "1866 1866 198510 3 353231 326279.0 380183.0 640 \n", + "1867 1867 198509 3 369895 341109.0 398681.0 670 \n", + "1868 1868 198508 3 389886 359529.0 420243.0 707 \n", + "1869 1869 198507 3 471852 432599.0 511105.0 855 \n", + "1870 1870 198506 3 565825 518011.0 613639.0 1026 \n", + "1871 1871 198505 3 637302 592795.0 681809.0 1155 \n", + "1872 1872 198504 3 424937 390794.0 459080.0 770 \n", + "1873 1873 198503 3 213901 174689.0 253113.0 388 \n", + "1874 1874 198502 3 97586 80949.0 114223.0 177 \n", + "1875 1875 198501 3 85489 65918.0 105060.0 155 \n", + "1876 1876 198452 3 84830 60602.0 109058.0 154 \n", + "1877 1877 198451 3 101726 80242.0 123210.0 185 \n", + "1878 1878 198450 3 123680 101401.0 145959.0 225 \n", + "1879 1879 198449 3 101073 81684.0 120462.0 184 \n", + "1880 1880 198448 3 78620 60634.0 96606.0 143 \n", + "1881 1881 198447 3 72029 54274.0 89784.0 131 \n", + "1882 1882 198446 3 87330 67686.0 106974.0 159 \n", + "1883 1883 198445 3 135223 101414.0 169032.0 246 \n", + "1884 1884 198444 3 68422 20056.0 116788.0 125 \n", + "\n", + " inc100_low inc100_up geo_insee geo_name \n", + "0 21.0 35.0 FR France \n", + "1 15.0 25.0 FR France \n", + "2 16.0 26.0 FR France \n", + "3 23.0 35.0 FR France \n", + "4 31.0 45.0 FR France \n", + "5 56.0 74.0 FR France \n", + "6 59.0 77.0 FR France \n", + "7 57.0 75.0 FR France \n", + "8 45.0 61.0 FR France \n", + "9 35.0 49.0 FR France \n", + "10 25.0 37.0 FR France \n", + "11 24.0 36.0 FR France \n", + "12 32.0 46.0 FR France \n", + "13 22.0 34.0 FR France \n", + "14 12.0 20.0 FR France \n", + "15 10.0 20.0 FR France \n", + "16 4.0 14.0 FR France \n", + "17 5.0 13.0 FR France \n", + "18 5.0 13.0 FR France \n", + "19 4.0 10.0 FR France \n", + "20 8.0 16.0 FR France \n", + "21 9.0 17.0 FR France \n", + "22 9.0 17.0 FR France \n", + "23 3.0 9.0 FR France \n", + "24 3.0 9.0 FR France \n", + "25 2.0 6.0 FR France \n", + "26 3.0 7.0 FR France \n", + "27 3.0 9.0 FR France \n", + "28 3.0 7.0 FR France \n", + "29 6.0 12.0 FR France \n", + "... ... ... ... ... \n", + "1855 35.0 59.0 FR France \n", + "1856 38.0 64.0 FR France \n", + "1857 59.0 97.0 FR France \n", + "1858 55.0 93.0 FR France \n", + "1859 44.0 80.0 FR France \n", + "1860 66.0 116.0 FR France \n", + "1861 83.0 149.0 FR France \n", + "1862 207.0 281.0 FR France \n", + "1863 319.0 395.0 FR France \n", + "1864 405.0 485.0 FR France \n", + "1865 458.0 544.0 FR France \n", + "1866 591.0 689.0 FR France \n", + "1867 618.0 722.0 FR France \n", + "1868 652.0 762.0 FR France \n", + "1869 784.0 926.0 FR France \n", + "1870 939.0 1113.0 FR France \n", + "1871 1074.0 1236.0 FR France \n", + "1872 708.0 832.0 FR France \n", + "1873 317.0 459.0 FR France \n", + "1874 147.0 207.0 FR France \n", + "1875 120.0 190.0 FR France \n", + "1876 110.0 198.0 FR France \n", + "1877 146.0 224.0 FR France \n", + "1878 184.0 266.0 FR France \n", + "1879 149.0 219.0 FR France \n", + "1880 110.0 176.0 FR France \n", + "1881 99.0 163.0 FR France \n", + "1882 123.0 195.0 FR France \n", + "1883 184.0 308.0 FR France \n", + "1884 37.0 213.0 FR France \n", + "\n", + "[1884 rows x 11 columns]" ] }, - "execution_count": 12, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], - "source": [ - "raw_data[raw_data.isnull().any(axis=1)]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Nous éliminons ce point, ce qui n'a pas d'impact fort sur notre analyse qui est assez simple." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "data = raw_data.dropna().copy()\n", "data" @@ -217,7 +1450,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ @@ -247,10 +1480,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 30, + "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" @@ -274,9 +1505,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1989-05-01/1989-05-07 1989-05-15/1989-05-21\n" + ] + } + ], "source": [ "periods = sorted_data.index\n", "for p1, p2 in zip(periods[:-1], periods[1:]):\n", @@ -294,9 +1533,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "yearly_incidence.plot(style='*')" ] @@ -409,9 +1715,54 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 37, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2014 1600941\n", + "1991 1659249\n", + "1995 1840410\n", + "2012 2175217\n", + "2003 2234584\n", + "2019 2254386\n", + "2006 2307352\n", + "2017 2321583\n", + "2001 2529279\n", + "1992 2574578\n", + "1993 2703886\n", + "2018 2705325\n", + "1988 2765617\n", + "2007 2780164\n", + "1987 2855570\n", + "2016 2856393\n", + "2011 2857040\n", + "2008 2973918\n", + "1998 3034904\n", + "2002 3125418\n", + "2009 3444020\n", + "1994 3514763\n", + "1996 3539413\n", + "2004 3567744\n", + "1997 3620066\n", + "2015 3654892\n", + "2000 3826372\n", + "2005 3835025\n", + "1999 3908112\n", + "2010 4111392\n", + "2013 4182691\n", + "1986 5115251\n", + "1990 5235827\n", + "1989 5466192\n", + "dtype: int64" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "yearly_incidence.sort_values()" ] @@ -426,9 +1777,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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d+cp0xdwBPK3t/qHAnb2NY2Zm3SpT2K8HDpf0DEl7A68D/rE/sczMrKqOu2IiYo+kdwJfAZYAn4mIm7uY94LdNTVqcjZodj5nq67J+ZytukXP1/HBUzMze2LwladmZplxYTczy4wLu5lZZp6QhV3Sakmr684xG0nPlPQeSSfUnWWmJmeDZudztuqanK/J2aB6vidUYZe0RtLVwBXAxyW9pO5M7ST9R+BrpO/SeZukt9cc6ReanA2anc/ZqmtyviZngy7zRUSj/4B9226/FvhEcfvNwD8AQ8V91ZDtBOAZ0/MHPgCcVtx/EfAlYLiOfE3O1vR8zpZnviZn63W+Rm6xSzpA0l9JuhX4hKTDikG/A/youD0G/BA4Y/ppi5jvKEnfA/4b8FlJJ0Rq7aOAQwAi4jrgm8BbFjNfk7M1PZ+z5Zmvydn6la+RhR04EdiXtGCPAB+QtJy0W/JqgIh4GLgYeElx/7F+hZF0qKQD2h46BbgkIl5K+oB5g6TDgQun8xUuA46WtE+/8jU5W9PzOVue+ZqcbbHy1VbYlSyV9FZJX5d0lqRnFYOfDTwSEXuAPwN+CpwGfBV4iqRfK8a7FfixpOP6lPFISV8GvgF8WNL01xT/P2C/4vYXgbuAdaRP1Ce37WHcR/p2y+f9KmVrej5nyzNfk7Mtdr7aCnuxq/GbwJuAjwH7AH9TDL4LuLv4ZPoxaWGeRWqA7/P41wIvA+4tHu8JSSva7j4fuCMi1gBXAp8oHr8PeFjS/hFxH/CvwFOLHN8E3luMtzfwc2B77tmans/Z8szX5Gx15lu0wi7pOEkflXR6cV/AkcAVEfGliPgYcJikFwM7SJ9gRxZP3wYMFI/9BfAqSa8mfSgMAt/tMtuTJJ0v6Xpgo6SDinxDwLWSFBH/CNwvaR1pT2H/YjjF/YOBx0h7GAdL+hvgImBPRNydY7am53O26pqcr8nZmpJvUQq7pOcAfwk8APyepPcW814NPFAsNMD5wBtIhXoP8OLi8RtIR4wfiohrgA3A6cDxwH+PiMfaplHFS4v5vYp0UOJs4ADSl50dUuxdAFxQ5Pt2sSyvBIiIbxXTWBoR24AzgZuB/xkRb6E7Tc7W9HzOlme+JmdrRr65Tpep+kfasj6DtNuxtHjsT4Gzitst4JPAycDLga+0PfdppF0VSIX8RtKvMB0D/G/gKW3jlj4dqWjYM4GrSd05q4rHvwi8u7j9DGBjMfxYUn/YkrZl+0kxndWkPYl3Ap8FPgWs6KLdGput6fmcza+r2+7f//V0i13S80kHOH8b+CDwvmLQDtJvpkL65LkW+F3gn4FDJD1X0rJI/ek7JL0kIq4kfd3lR4FLgYsi4t+m5xVFy5R0EvAa4EPAcaS+fUhn20zvHfwY+Drwyoi4nvSJO1LMcwq4Djg2InYAbyR1Bd0FvC8iHiwbqG1P49VNyzaD266axrUbuO26yfZEaLsyP433SyS9EDgc+GpE/IS0NX5rRJwu6QXAOZJawDjwnyTtFxEPSfou8HukczQvBP4A+KSk3cAkcHsxi78CLoyIXSUyKSJC0rGk3ZyvA1sinR7568BtEXGlpNtJV6++AtgK/I6kVRFxj6R/BR6U9HTgz4HTJB1M+tWoe0m7TkTEBDBRod1apL2aB4CPA3cDz6w7m9uuWrYnQru57fJru/mU2mJXskzSmyTdSOrYPxCYLrw/B7YXW983kHYtjgMe4vFTeAAeJe2CHELaKr+J1L9+NXBPRNwBaau8YlF/KfAZ0lHllwMfKUZ5DLhV0vKIuL3I91zSi3Un6XzS6eVYQmqfS4qMpwJrgc1R8RxXSSslfbaY5u3AuRFxt6S9SJ/kdWZbUrTdb5J2BRvTdsV6NyDpfBrWdsU8Q9IwzVzn9pG0oqFtd0DD225A0r6SLqBhbbegTvprgBXAi4vbBxbBPjnLeGeRLoNdXdw/mdSffhjpKwCuLh7fl9QNs6rtuccAe3eSZ8Y89wPexuNb/suAPwLeUQx/EvC9YvqnkPq71hTDTiqWZVVxexJYSerf/3J7HmCvLrJdRLpibIDUtXRm2zjTxyHeCfyPxcrW9rqeQVrZ1pMO8DSl7aazXVqsVwc1rO32B7aQfkkM4D1NaLcZ+b4M/HVx/2PA2+puO9J74s2k9/8lTWu7tnxXAn9fPNaY9a7TvwW32CWdDdwGbJE0GBH3k/qF7iz6xl+jxy8Q+hbpAOj0hUbXkg6iPhQRFwA/lfQ50kHRW4Bf9CFFxI0R8chCeWZkOwS4HBgGPkc6QPFa0l7CnmK6PyUdeH03qe/rYB4/jfIa0rn0j0TE5cCnSVeznkc6Yv1oW75Sn6ozsv0d8PYi263AEZI2FltRv690wdUVpD2Yvmcr8q0gvblOIF0/8ArScY9jSVtKdbZde7bNpLMFXku6huE36m67wnLStRfPkrSKtM4vKaZZS7vNkm9v0rr2VFIXx9GSPlJX20laRjrGdjLw8Yj43WLQMW3TrK3tZuT7WERMb3FPAkfV2XaldfAJNkzavfhb4D3FY8eSitYdRfALgU3FsHOAD7c9/3rgmOL2PqRTgI7txacSaeV9Udv900lbJm8Gvt32+FOBO4vb7yBdtvuk4vlfAp7eNu6qPmV7E+lI968Df1/8vR74X6Rz+RctW9v0Dmy7/Z9Jb6ZT6267WbL9MemUsWc2qO3eTOprfT/wVtKBtOvrbrdZ8r2PtMezqgltR9oDO3XGY6cA1zWh7ebI9/QiQ+3rXcfL0cGCTp+acwowXtxeRtqaWlncP4y0tX4saRfwYtKW1j+RPqn26Uv41Mcl+MVvt76Ax7t77iWdMzo97tcoCi1p9+mrxTh/skjZjgG+Mb3ito23jHRw+YTi/jn9zjYj5wGk4xs7gQ8X9+8FButqu1my3VXMdwVFN19dbdf2er6F1M32WuALxWP31N1uc+QbKx5rP124lvWO1EVxK7CpmP8HivpxH3BwA9a59nxXkb6Y69C617vSy1FigZ9MulDoOcX9pTOGnw+cPL0CkboezqRPRX2OlfkCHj9f/nPAR4vbv0ba43h62wtzNG1fCbxI2d7R/lhx+5Ci7Z672NnaMvwh6XzbzaR+7W8WbzjV2XYzsp1HOq3s2U1oO9JXRi8h9aFeTdoyvgl4f93r3Cz5/pl0htkLGtJ2XyHtgT2NtBV8FmnDsCnrXHu+L5Au/T+8CW3X6d900emIpE8BP4uIDcX9vUjnXb4DeA5wSpTsJ+8VSYeS+rTeFRG3Kn2h2GiRazXwnejNVWXdZHt7RNxWPHYMqVtqXZHtD+vI1k7pOoQzSW+yI0kr66HU2HZt2Y4mvdn+nHSW1UnU1HaSBkjdHPuQ2uk3SBeenE3aUj6cGtttlnyHk45P/BbpmNfLSO1Xy3qn4rTn4vbzSO/Ta0mX1Ne+zs3IdzTpSvdzSd80W9t6V0bZ89g3A+cWBxmOJK3Ex5NelLPrKuqFYyjOgZd0Bqn//2xSF9IPIp1+WXe2HxXZbietHHtIW/E31pit3b2kg4Dvi4i/k3QacHND8t1P6ie+ifS6LqO+tttDOnviUdKW+s9J6/8k8N4GtNtc+R6W9BpSwa9tvZsumoX7Sced3h8RFzag7Wbme4C08boN+K/Uu951rOwW++tIB0ofJn3j2JURcUufspUi6VrSwbXtpHNIPxQR36s1VGFGtruADQ1qt5WkLbg3kL7/fjNwXkQ8Ou8TF8Es2T4dEZvqTfXLigtPpvuy76o7z0xFvpOBz0Y666TuPPuQfnPhjaQ96r8EPhXpa7prN0u+zRHxZ/WmKqfjwi7puaTzOS8mHSzq2VfldqvYg/ggaUv485GuWmuEJmcDkLSU1P3yMClfk17XxmaDdFEX8FiU2TpaRE3OJ+lM0mm1n2va6wrNz7eQUlvsZmbWfE39aTwzM6vIhd3MLDMu7GZmmXFhNzPLjAu7mVlmXNjNzDLjwm5mlpn/D0QBdzhJVkBDAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "yearly_incidence.hist(xrot=20)" ] diff --git a/module3/exo1/incidence-PAY-3.csv b/module3/exo1/incidence-PAY-3.csv index fb2ce8d..c88fb85 100644 --- a/module3/exo1/incidence-PAY-3.csv +++ b/module3/exo1/incidence-PAY-3.csv @@ -1,1885 +1,1886 @@ ,week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name -0,202049,3,13273,10162.0,16384.0,20,15.0,25.0,FR,France -1,202048,3,13804,10641.0,16967.0,21,16.0,26.0,FR,France -2,202047,3,19085,15285.0,22885.0,29,23.0,35.0,FR,France -3,202046,3,24801,20503.0,29099.0,38,31.0,45.0,FR,France -4,202045,3,42516,36857.0,48175.0,65,56.0,74.0,FR,France -5,202044,3,44567,38521.0,50613.0,68,59.0,77.0,FR,France -6,202043,3,43737,37523.0,49951.0,66,57.0,75.0,FR,France -7,202042,3,35145,29812.0,40478.0,53,45.0,61.0,FR,France -8,202041,3,27877,23206.0,32548.0,42,35.0,49.0,FR,France 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-1703,198815,3,70616,61754.0,79478.0,126,110.0,142.0,FR,France -1704,198814,3,123868,113211.0,134525.0,222,203.0,241.0,FR,France -1705,198813,3,193710,181519.0,205901.0,347,325.0,369.0,FR,France -1706,198812,3,283445,268834.0,298056.0,507,481.0,533.0,FR,France -1707,198811,3,316175,300858.0,331492.0,566,539.0,593.0,FR,France -1708,198810,3,235142,222004.0,248280.0,421,397.0,445.0,FR,France -1709,198809,3,135564,125263.0,145865.0,243,225.0,261.0,FR,France -1710,198808,3,87753,78449.0,97057.0,157,140.0,174.0,FR,France -1711,198807,3,77099,68423.0,85775.0,138,122.0,154.0,FR,France -1712,198806,3,69349,61502.0,77196.0,124,110.0,138.0,FR,France -1713,198805,3,72705,64952.0,80458.0,130,116.0,144.0,FR,France -1714,198804,3,72818,64944.0,80692.0,130,116.0,144.0,FR,France -1715,198803,3,68869,60922.0,76816.0,123,109.0,137.0,FR,France -1716,198802,3,59743,51907.0,67579.0,107,93.0,121.0,FR,France -1717,198801,3,60929,52573.0,69285.0,109,94.0,124.0,FR,France 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