From 290d7f286ab23ce3dce2722899b02adbf1171977 Mon Sep 17 00:00:00 2001 From: 7db3512460936f19a53c773a40a4fd70 <7db3512460936f19a53c773a40a4fd70@app-learninglab.inria.fr> Date: Mon, 22 Feb 2021 10:44:35 +0000 Subject: [PATCH] kk --- module2/exo1/toy_notebook_fr.ipynb | 159 -- module3/exo1/analyse-syndrome-grippal.ipynb | 2217 ++++++++++++++++++- 2 files changed, 2180 insertions(+), 196 deletions(-) delete mode 100644 module2/exo1/toy_notebook_fr.ipynb diff --git a/module2/exo1/toy_notebook_fr.ipynb b/module2/exo1/toy_notebook_fr.ipynb deleted file mode 100644 index e0ca20c..0000000 --- a/module2/exo1/toy_notebook_fr.ipynb +++ /dev/null @@ -1,159 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# À propos du calcul de $\\pi$" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## En demandant à la lib maths\n", - "Mon ordinateur m'indique que $\\pi$ vaut *approximativement*" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "3.141592653589793\n" - ] - } - ], - "source": [ - "from math import *\n", - "print(pi)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## En utilisant la méthode des aiguilles de Buffon\n", - "Mais calculé avec la __méthode__ des [aiguilles de Buffon](https://fr.wikipedia.org/wiki/Aiguille_de_Buffon), on obtiendrait comme __approximation__ :\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "text/plain": [ - "3.128911138923655" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import numpy as np\n", - "np.random.seed(seed=42)\n", - "N = 10000\n", - "x = np.random.uniform(size=N, low=0, high=1)\n", - "theta = np.random.uniform(size=N, low=0, high=pi/2)\n", - "2/(sum((x+np.sin(theta))>1)/N)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Avec un argument \"fréquentiel\" de surface\n", - "Sinon, une méthode plus simple à comprendre et ne faisant pas intervenir d'appel à la fonction sinus se base sur le fait que si $X\\sim U(0,1)$ et $Y\\sim U(0,1)$ alors $P[X^2+Y^2\\leq 1] = \\pi/4$ (voir [méthode de Monte Carlo sur Wikipedia](https://fr.wikipedia.org/wiki/M%C3%A9thode_de_Monte-Carlo#D%C3%A9termination_de_la_valeur_de_%CF%80)). Le code suivant illustre ce fait :" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline \n", - "import matplotlib.pyplot as plt\n", - "\n", - "np.random.seed(seed=42)\n", - "N = 1000\n", - "x = np.random.uniform(size=N, low=0, high=1)\n", - "y = np.random.uniform(size=N, low=0, high=1)\n", - "\n", - "accept = (x*x+y*y) <= 1\n", - "reject = np.logical_not(accept)\n", - "\n", - "fig, ax = plt.subplots(1)\n", - "ax.scatter(x[accept], y[accept], c='b', alpha=0.2, edgecolor=None)\n", - "ax.scatter(x[reject], y[reject], c='r', alpha=0.2, edgecolor=None)\n", - "ax.set_aspect('equal')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Il est alors aisé d'obtenir une approximation (pas terrible) de $\\pi$ en comptant combien de fois, en moyenne, $X^2 + Y^2$ est inférieur à 1 :" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "3.112" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "4*np.mean(accept)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/module3/exo1/analyse-syndrome-grippal.ipynb b/module3/exo1/analyse-syndrome-grippal.ipynb index 59d72b5..9938819 100644 --- a/module3/exo1/analyse-syndrome-grippal.ipynb +++ b/module3/exo1/analyse-syndrome-grippal.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -28,10 +28,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 2, + "metadata": {}, "outputs": [], "source": [ "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" @@ -61,9 +59,976 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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320210332181017894.025726.03327.039.0FRFrance
420210231732013906.020734.02621.031.0FRFrance
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620205332122016498.025942.03225.039.0FRFrance
720205231642812285.020571.02519.031.0FRFrance
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102020493129399923.015955.02015.025.0FRFrance
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1820204132787723206.032548.04235.049.0FRFrance
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2020203931981015900.023720.03024.036.0FRFrance
2120203832556221142.029982.03932.046.0FRFrance
2220203731848514649.022321.02822.034.0FRFrance
232020363103907646.013134.01612.020.0FRFrance
24202035399186842.012994.01510.020.0FRFrance
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26202033361063411.08801.095.013.0FRFrance
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.................................
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1894 rows × 10 columns

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" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202106 3 23816 18867.0 28765.0 36 29.0 \n", + "1 202105 3 22491 18436.0 26546.0 34 28.0 \n", + "2 202104 3 25804 21491.0 30117.0 39 32.0 \n", + "3 202103 3 21810 17894.0 25726.0 33 27.0 \n", + "4 202102 3 17320 13906.0 20734.0 26 21.0 \n", + "5 202101 3 21799 17778.0 25820.0 33 27.0 \n", + "6 202053 3 21220 16498.0 25942.0 32 25.0 \n", + "7 202052 3 16428 12285.0 20571.0 25 19.0 \n", + "8 202051 3 21619 17370.0 25868.0 33 27.0 \n", + "9 202050 3 16845 13220.0 20470.0 26 20.0 \n", + "10 202049 3 12939 9923.0 15955.0 20 15.0 \n", + "11 202048 3 13804 10641.0 16967.0 21 16.0 \n", + "12 202047 3 19085 15285.0 22885.0 29 23.0 \n", + "13 202046 3 24801 20503.0 29099.0 38 31.0 \n", + "14 202045 3 42516 36857.0 48175.0 65 56.0 \n", + "15 202044 3 44567 38521.0 50613.0 68 59.0 \n", + "16 202043 3 43737 37523.0 49951.0 66 57.0 \n", + "17 202042 3 35145 29812.0 40478.0 53 45.0 \n", + "18 202041 3 27877 23206.0 32548.0 42 35.0 \n", + "19 202040 3 20443 16381.0 24505.0 31 25.0 \n", + "20 202039 3 19810 15900.0 23720.0 30 24.0 \n", + "21 202038 3 25562 21142.0 29982.0 39 32.0 \n", + "22 202037 3 18485 14649.0 22321.0 28 22.0 \n", + "23 202036 3 10390 7646.0 13134.0 16 12.0 \n", + "24 202035 3 9918 6842.0 12994.0 15 10.0 \n", + "25 202034 3 6084 3090.0 9078.0 9 4.0 \n", + "26 202033 3 6106 3411.0 8801.0 9 5.0 \n", + "27 202032 3 5918 3330.0 8506.0 9 5.0 \n", + "28 202031 3 4351 2269.0 6433.0 7 4.0 \n", + "29 202030 3 8179 5442.0 10916.0 12 8.0 \n", + "... ... ... ... ... ... ... ... \n", + "1864 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "1865 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "1866 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "1867 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "1868 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "1869 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "1870 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "1871 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "1872 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1873 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1874 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1875 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1876 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1877 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1878 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1879 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1880 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1881 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1882 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1883 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1884 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1885 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1886 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1887 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1888 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1889 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1890 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1891 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1892 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "1893 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 43.0 FR France \n", + "1 40.0 FR France \n", + "2 46.0 FR France \n", + "3 39.0 FR France \n", + "4 31.0 FR France \n", + "5 39.0 FR France \n", + "6 39.0 FR France \n", + "7 31.0 FR France \n", + "8 39.0 FR France \n", + "9 32.0 FR France \n", + "10 25.0 FR France \n", + "11 26.0 FR France \n", + "12 35.0 FR France \n", + "13 45.0 FR France \n", + "14 74.0 FR France \n", + "15 77.0 FR France \n", + "16 75.0 FR France \n", + "17 61.0 FR France \n", + "18 49.0 FR France \n", + "19 37.0 FR France \n", + "20 36.0 FR France \n", + "21 46.0 FR France \n", + "22 34.0 FR France \n", + "23 20.0 FR France \n", + "24 20.0 FR France \n", + "25 14.0 FR France \n", + "26 13.0 FR France \n", + "27 13.0 FR France \n", + "28 10.0 FR France \n", + "29 16.0 FR France \n", + "... ... ... ... \n", + "1864 59.0 FR France \n", + "1865 64.0 FR France \n", + "1866 97.0 FR France \n", + "1867 93.0 FR France \n", + "1868 80.0 FR France \n", + "1869 116.0 FR France \n", + "1870 149.0 FR France \n", + "1871 281.0 FR France \n", + "1872 395.0 FR France \n", + "1873 485.0 FR France \n", + "1874 544.0 FR France \n", + "1875 689.0 FR France \n", + "1876 722.0 FR France \n", + "1877 762.0 FR France \n", + "1878 926.0 FR France \n", + "1879 1113.0 FR France \n", + "1880 1236.0 FR France \n", + "1881 832.0 FR France \n", + "1882 459.0 FR France \n", + "1883 207.0 FR France \n", + "1884 190.0 FR France \n", + "1885 198.0 FR France \n", + "1886 224.0 FR France \n", + "1887 266.0 FR France \n", + "1888 219.0 FR France \n", + "1889 176.0 FR France \n", + "1890 163.0 FR France \n", + "1891 195.0 FR France \n", + "1892 308.0 FR France \n", + "1893 213.0 FR France \n", + "\n", + "[1894 rows x 10 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data" @@ -78,9 +1043,73 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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1886198451310172680242.0123210.0185146.0224.0FRFrance
18871984503123680101401.0145959.0225184.0266.0FRFrance
1888198449310107381684.0120462.0184149.0219.0FRFrance
188919844837862060634.096606.0143110.0176.0FRFrance
189019844737202954274.089784.013199.0163.0FRFrance
189119844638733067686.0106974.0159123.0195.0FRFrance
18921984453135223101414.0169032.0246184.0308.0FRFrance
189319844436842220056.0116788.012537.0213.0FRFrance
\n", + "

1893 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202106 3 23816 18867.0 28765.0 36 29.0 \n", + "1 202105 3 22491 18436.0 26546.0 34 28.0 \n", + "2 202104 3 25804 21491.0 30117.0 39 32.0 \n", + "3 202103 3 21810 17894.0 25726.0 33 27.0 \n", + "4 202102 3 17320 13906.0 20734.0 26 21.0 \n", + "5 202101 3 21799 17778.0 25820.0 33 27.0 \n", + "6 202053 3 21220 16498.0 25942.0 32 25.0 \n", + "7 202052 3 16428 12285.0 20571.0 25 19.0 \n", + "8 202051 3 21619 17370.0 25868.0 33 27.0 \n", + "9 202050 3 16845 13220.0 20470.0 26 20.0 \n", + "10 202049 3 12939 9923.0 15955.0 20 15.0 \n", + "11 202048 3 13804 10641.0 16967.0 21 16.0 \n", + "12 202047 3 19085 15285.0 22885.0 29 23.0 \n", + "13 202046 3 24801 20503.0 29099.0 38 31.0 \n", + "14 202045 3 42516 36857.0 48175.0 65 56.0 \n", + "15 202044 3 44567 38521.0 50613.0 68 59.0 \n", + "16 202043 3 43737 37523.0 49951.0 66 57.0 \n", + "17 202042 3 35145 29812.0 40478.0 53 45.0 \n", + "18 202041 3 27877 23206.0 32548.0 42 35.0 \n", + "19 202040 3 20443 16381.0 24505.0 31 25.0 \n", + "20 202039 3 19810 15900.0 23720.0 30 24.0 \n", + "21 202038 3 25562 21142.0 29982.0 39 32.0 \n", + "22 202037 3 18485 14649.0 22321.0 28 22.0 \n", + "23 202036 3 10390 7646.0 13134.0 16 12.0 \n", + "24 202035 3 9918 6842.0 12994.0 15 10.0 \n", + "25 202034 3 6084 3090.0 9078.0 9 4.0 \n", + "26 202033 3 6106 3411.0 8801.0 9 5.0 \n", + "27 202032 3 5918 3330.0 8506.0 9 5.0 \n", + "28 202031 3 4351 2269.0 6433.0 7 4.0 \n", + "29 202030 3 8179 5442.0 10916.0 12 8.0 \n", + "... ... ... ... ... ... ... ... \n", + "1864 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "1865 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "1866 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "1867 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "1868 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "1869 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "1870 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "1871 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "1872 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1873 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1874 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1875 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1876 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1877 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1878 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1879 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1880 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1881 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1882 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1883 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1884 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1885 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1886 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1887 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1888 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1889 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1890 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1891 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1892 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "1893 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 43.0 FR France \n", + "1 40.0 FR France \n", + "2 46.0 FR France \n", + "3 39.0 FR France \n", + "4 31.0 FR France \n", + "5 39.0 FR France \n", + "6 39.0 FR France \n", + "7 31.0 FR France \n", + "8 39.0 FR France \n", + "9 32.0 FR France \n", + "10 25.0 FR France \n", + "11 26.0 FR France \n", + "12 35.0 FR France \n", + "13 45.0 FR France \n", + "14 74.0 FR France \n", + "15 77.0 FR France \n", + "16 75.0 FR France \n", + "17 61.0 FR France \n", + "18 49.0 FR France \n", + "19 37.0 FR France \n", + "20 36.0 FR France \n", + "21 46.0 FR France \n", + "22 34.0 FR France \n", + "23 20.0 FR France \n", + "24 20.0 FR France \n", + "25 14.0 FR France \n", + "26 13.0 FR France \n", + "27 13.0 FR France \n", + "28 10.0 FR France \n", + "29 16.0 FR France \n", + "... ... ... ... \n", + "1864 59.0 FR France \n", + "1865 64.0 FR France \n", + "1866 97.0 FR France \n", + "1867 93.0 FR France \n", + "1868 80.0 FR France \n", + "1869 116.0 FR France \n", + "1870 149.0 FR France \n", + "1871 281.0 FR France \n", + "1872 395.0 FR France \n", + "1873 485.0 FR France \n", + "1874 544.0 FR France \n", + "1875 689.0 FR France \n", + "1876 722.0 FR France \n", + "1877 762.0 FR France \n", + "1878 926.0 FR France \n", + "1879 1113.0 FR France \n", + "1880 1236.0 FR France \n", + "1881 832.0 FR France \n", + "1882 459.0 FR France \n", + "1883 207.0 FR France \n", + "1884 190.0 FR France \n", + "1885 198.0 FR France \n", + "1886 224.0 FR France \n", + "1887 266.0 FR France \n", + "1888 219.0 FR France \n", + "1889 176.0 FR France \n", + "1890 163.0 FR France \n", + "1891 195.0 FR France \n", + "1892 308.0 FR France \n", + "1893 213.0 FR France \n", + "\n", + "[1893 rows x 10 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "data = raw_data.dropna().copy()\n", "data" @@ -122,7 +2118,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -152,10 +2148,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 7, + "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" @@ -179,9 +2173,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "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", @@ -199,9 +2201,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "sorted_data['inc'][-200:].plot()" ] @@ -252,10 +2300,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 11, + "metadata": {}, "outputs": [], "source": [ "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", @@ -274,7 +2320,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -298,9 +2344,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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lbpS0XdIrkhaW0udKeiHPrcqtgMntgh/M9I2SZpbKLJPUna9lpfRZmbc7yx7bmEtiA9WoZZT9fQofjZ8OR3vPzNpLPT2Ug8D8iHhP0jjgbyVVtu69PSL+tJxZ0myKLXzPBqYBT0j6RG4DvBpYDjwLPA4sotgG+EpgX0ScIWkpcBvwJUmTgJuBDiCALZIei4h9mef2iFgr6btZx+rBXwobrHIgWHnxpwZcvt5P4aPx0+Fo7ZlZe+q3hxKF9/Lbcfmq9QCwxcDaiDgYEa8C24F5kqYCEyJiQxQPELsHWFIqsyaPHwYuyt7LQqAzInoyiHQCi/Lc/MxLlq3UZcPkrJvWMfOGn3Dfxp1EFIFg5g0/4ayb1vVfuMSfwmsbjT0za091zaFIOgbYApwB/O+I2CjpM8C1kq4AuoCv5h/96RQ9kIpdmfZ+Hlenk19fA4iIXknvAJPL6VVlJgNvR0RvH3XZMHnm+guPuEf7QPhTeG2jsWdm7amuVV4RcSgi5gAzKHob51AML30cmAPsBr6V2dVXFTXSB1OmVl2HkbRcUpekrr179/aVxQapkYHAn8JHHj+iZPQZ0CqviHhb0tPAovLciaTvAz/Ob3cBp5aKzQDeyPQZfaSXy+ySNBY4EejJ9E9XlXkaeAs4SdLY7KWU66pu853AnVA8vn4gP6/1r1H7cPhT+MhztHNr1n763Q9F0hTg/QwmxwM/pZgQ3xIRuzPPHwLnRcRSSWcD9wPzKCblfwacGRGHJG0G/iuwkWJS/n9FxOOSrgE+FRFfyUn5346I381J+S3Ab2Zzfg7MjYgeSX8F/LA0Kf+LiPhOrZ/F+6GYDT3vcT/y1LsfSj09lKnAmpxHGQM8FBE/lnSvpDkUQ007gC8DRMQ2SQ8BLwG9wDW5wgvgKuBu4HiK1V2V2du7gHslbafomSzNunok3Qpszny3RERPHq8A1kpaCWzNOsysyRo1t2btp9+AEhG/AM7tI/3yGmX+BPiTPtK7gF8Zz4iIA8AXj1DXD4Af9JH+/yh6QWbWQrzIYvTynfJm1nDe43508p7yZmZWk/eUNzOzYeWAYmZmDeGAYmZmDeGAYmZmDeGAYmZmDeGAYmZmDeGAYmZmDeGAYmZmDeGAYmZmDeGAYjaEvCeIjSYOKGZDqLwniNlI54dDmg2B6j1B7tu4k/s27vSeIDaiuYdiNgSeuf5CvjBnGuPHFf/Fxo8bw+I503hmxYVNbpnZ0HFAMRsC3hPERiMHFBtRWmkSvLInyCNXX8Bl553O3vcONrtJZkOq34AiabykTZKel7RN0h9n+iRJnZK68+vEUpkbJW2X9IqkhaX0uZJeyHOrJCnTj5P0YKZvlDSzVGZZvke3pGWl9FmZtzvLHtuYS2LtrJUmwb93eQcrl5zD7GkTWLnkHL53eb/bSZi1tX432Mo/+h+JiPckjQP+FrgO+G2gJyK+IekGYGJErJA0G3iAYnveacATwCci4pCkTVn2WeBxYFVErJN0NfAbEfEVSUuBiyPiS5ImAV1AB8Xe9VuAuRGxL/et/1FErJX0XeD5iFhd62fxBlsjV/UkeIUnwc2OXsM22IrCe/ntuHwFsBhYk+lrgCV5vBhYGxEHI+JVYDswT9JUYEJEbIgiit1TVaZS18PARRnIFgKdEdETEfuATmBRnpufeavf30YhT4IPr1YaWrTWUdcciqRjJD0H7KH4A78ROCUidgPk15Mz+3TgtVLxXZk2PY+r0w8rExG9wDvA5Bp1TQbezrzVdVW3fbmkLklde/furefHtTbkSfDh1UpDi9Y66roPJSIOAXMknQQ8IumcGtnVVxU10gdTplZdhydG3AncCcWQV195bGSoTIJfOu807t+0k73+9Nxwvr/GahnQjY0R8bakp4FFwJuSpkbE7hzO2pPZdgGnlorNAN7I9Bl9pJfL7JI0FjgR6Mn0T1eVeRp4CzhJ0tjspZTrslGqPOm9ckmtzzw2WM9cfyErH3+Zn277Jw68/wHjx41h4dm/ztc+98lmN81aQD2rvKZkzwRJxwP/Gfgl8BhQWXW1DHg0jx8DlubKrVnAmcCmHBbbL+n8nAO5oqpMpa5LgCdznmU9sEDSxFxFtgBYn+eeyrzV729mQ8RDi1ZLPT2UqcAaScdQBKCHIuLHkjYAD0m6EtgJfBEgIrblCqyXgF7gmhwyA7gKuBs4HliXL4C7gHslbafomSzNunok3Qpszny3RERPHq8A1kpaCWzNOsxsiHlo0Y6k32XDI8lQLhve8+4Brn1gK3dceq4/rZk1UDv+32rHNtfSsGXDVh+vejEbGu34f6sd29wI7qEcJd9QZzY02vH/Vju2uR7uoQwT31BnNjTa8f9WO7a5kRxQjtJAVr347mJrB63ye9qOK8rasc2N5IDSAPU+VXa0jqtae2ml39N2fGJzO7a5UTyHMgxG6riqjSz+PbUj8RxKCxnt46rWHvx72npaZfixXg4ow6Cdx1Xb7RfaBq+df09HqlYafqzHgJ7lZYPXrncXl3+hV178qWY3x4ZYu/6ejjTt+hBOz6FYnzyebtY8e949cMSHcDajx+g5FDsqHk83a552HX70kJf1qV1/oc1GinYcfnRAsSNqx19os5GiHff38RzKKDbSnohqZkPDcyjWr3Zbkmhmrc1DXqNQuy5JbDXu4Zkdrp4tgE+V9JSklyVtk3Rdpn9d0uuSnsvXZ0tlbpS0XdIrkhaW0udKeiHPrcqtgMntgh/M9I2SZpbKLJPUna9lpfRZmbc7yx7bmEsy8nkFV2O4h2d2uHp6KL3AVyPi55JOALZI6sxzt0fEn5YzS5pNsYXv2cA04AlJn8htgFcDy4FngceBRRTbAF8J7IuIMyQtBW4DviRpEnAz0AFEvvdjEbEv89weEWslfTfrWD34SzF6eAXX0XEPz6xv/fZQImJ3RPw8j/cDLwPTaxRZDKyNiIMR8SqwHZgnaSowISI2RLES4B5gSanMmjx+GLgoey8Lgc6I6Mkg0gksynPzMy9ZtlKX1WE0PxH1aLmHZ9a3Ac2h5FDUucBG4ALgWklXAF0UvZh9FMHm2VKxXZn2fh5Xp5NfXwOIiF5J7wCTy+lVZSYDb0dEbx91WR3acUliq3APz6xvda/ykvRR4IfAH0TEuxTDSx8H5gC7gW9VsvZRPGqkD6ZMrbqq271cUpekrr179/aVxWzA3MMz+1V19VAkjaMIJn8ZET8CiIg3S+e/D/w4v90FnFoqPgN4I9Nn9JFeLrNL0ljgRKAn0z9dVeZp4C3gJEljs5dSruswEXEncCcU96HU8/Oa9cc9PLNfVc8qLwF3AS9HxLdL6VNL2S4GXszjx4CluXJrFnAmsCkidgP7JZ2fdV4BPFoqU1nBdQnwZM6zrAcWSJooaSKwAFif557KvGTZSl1mZtYE9fRQLgAuB16Q9Fym/RHwXyTNoRhq2gF8GSAitkl6CHiJYoXYNbnCC+Aq4G7geIrVXesy/S7gXknbKXomS7OuHkm3Apsz3y0R0ZPHK4C1klYCW7MOMzNrEj96xczMavKjV8zMbFg5oJiZNcFI3F7bAcVsFBmJf8Ta1Uh8dI8fDmk2ipT/iK28+FPNbs6oNJIf3eNJebNRoPqPWMVI+CPWbhq5X/xwPfHak/Jm9q/8/LHW0chH97TasJmHvMyabDg+Zfr5Y63laLfXbtVhMwcUsyYbrnmNo/0jZo1ztI/ueeb6C484bNZMDihmTTLcnzL9/LGRo1V7nJ5DMWsSz2s0zmhcDt2KT7x2D8WsSVr1U2Y7Go3LoVuxx+mAYtZEntc4Oq06OT1a+T4UM2tbjbynw47M96GY2YjnYcPW4iEvM2trHjZsHR7yMjMbwRpx46yHvMzMbFgfz1LPnvKnSnpK0suStkm6LtMnSeqU1J1fJ5bK3Chpu6RXJC0spc+V9EKeW5V7y5P7zz+Y6RslzSyVWZbv0S1pWSl9VubtzrLHNuaSmJm1v7NuWsfMG37CfRt3ElGsgJt5w08466Z1/RcepHp6KL3AVyPik8D5wDWSZgM3AD+LiDOBn+X35LmlwNnAIuA7ko7JulYDy4Ez87Uo068E9kXEGcDtwG1Z1yTgZuA8YB5wcylw3Qbcnu+/L+swMzOac+NsvwElInZHxM/zeD/wMjAdWAysyWxrgCV5vBhYGxEHI+JVYDswT9JUYEJEbIhi4uaeqjKVuh4GLsrey0KgMyJ6ImIf0AksynPzM2/1+5uZjXrNWAE3oFVeORR1LrAROCUidkMRdCSdnNmmA8+Wiu3KtPfzuDq9Uua1rKtX0jvA5HJ6VZnJwNsR0dtHXWZmxvCvgKs7oEj6KPBD4A8i4t2c/ugzax9pUSN9MGVq1XV4Y6TlFMNsnHbaaX1lMTMbkYb78Sx1rfKSNI4imPxlRPwok9/MYSzy655M3wWcWio+A3gj02f0kX5YGUljgROBnhp1vQWclHmr6zpMRNwZER0R0TFlypR6flwzMxuEelZ5CbgLeDkivl069RhQWXW1DHi0lL40V27Noph835TDY/slnZ91XlFVplLXJcCTOc+yHlggaWJOxi8A1ue5pzJv9fubmVkT1DPkdQFwOfCCpOcy7Y+AbwAPSboS2Al8ESAitkl6CHiJYoXYNRFxKMtdBdwNHA+syxcUAeteSdspeiZLs64eSbcCmzPfLRHRk8crgLWSVgJbsw4zM2sS3ylvZmY1+U55aymjcQMks9HGAcWGxXA+/sHMmsNPG7Yh5Q2QzEYP91BsSHnfdLPRwwHFhpQ3QDIbPTzkZUPOGyCZjQ5eNmxmZjV52bCZmQ0rBxQzM2sIB5QRyjcSmtlwc0AZoXwjoZkNN6/yGmF8I6GZNYt7KCOMbyQ0GzwPFR8dB5QRxjcSmg2eh4qPjoe8RiDfSGg2MB4qbgzf2Ghmo96edw+w8vGX+em2f+LA+x8wftwYFp7963ztc590754G3tgo6QeS9kh6sZT2dUmvS3ouX58tnbtR0nZJr0haWEqfK+mFPLcqtwEmtwp+MNM3SppZKrNMUne+lpXSZ2Xe7ix7bD0XxcysLx4qbox65lDuBhb1kX57RMzJ1+MAkmZTbN97dpb5jqRjMv9qYDnFHvNnluq8EtgXEWcAtwO3ZV2TgJuB84B5wM25rzyZ5/aIOBPYl3WYmQ1aZaj4kasv4LLzTmfveweb3aS20+8cSkT8TbnX0I/FwNqIOAi8mnvEz5O0A5gQERsAJN0DLKHYU34x8PUs/zBwR/ZeFgKdlT3kJXUCiyStBeYDl2aZNVl+dZ1tNDP7Fd+7/MMRnZVLzmliS9rX0azyulbSL3JIrNJzmA68VsqzK9Om53F1+mFlIqIXeAeYXKOuycDbmbe6LjMza5LBBpTVwMeBOcBu4FuZrj7yRo30wZSpVdevkLRcUpekrr179x4pm5mZHaVBBZSIeDMiDkXEB8D3KeY4oOgtnFrKOgN4I9Nn9JF+WBlJY4ETgZ4adb0FnJR5q+vqq613RkRHRHRMmTJloD+qmZnVaVABRdLU0rcXA5UVYI8BS3Pl1iyKyfdNEbEb2C/p/JwfuQJ4tFSmsoLrEuDJKNYyrwcWSJqYQ2oLgPV57qnMS5at1GVmZk3S76S8pAeATwMfk7SLYuXVpyXNoRhq2gF8GSAitkl6CHgJ6AWuiYhDWdVVFCvGjqeYjF+X6XcB9+YEfg/FKjEiokfSrcDmzHdLZYIeWAGslbQS2Jp1mJlZE/nGRjMzq6neGxtHVUCRtBf4xz5OfYxibqaduM1Dr93aC27zcGm3Nh9te0+PiH4noUdVQDkSSV31RN9W4jYPvXZrL7jNw6Xd2jxc7fXThs3MrCEcUMzMrCEcUAp3NrsBg+A2D712ay+4zcOl3do8LO31HIqZmTWEeyhmZtYQIzKgHGEPl38raUPuyfJ/JE3I9HGS1mT6y5JuLJV5Ovd1qez7cnKLtPlYSX+R6c9L+nSpTJ/7zrR4m4flOks6VdJT+e+8TdJ1mT5JUmfur9NZetjpgPf3afE2t+R1ljQ5878n6Y6qulryOvfT5iG/zoNo729J2pLXcouk+aW6GneNI2LEvYD/CPwm8GIpbTPwn/L494Fb8/hSikfuA/waxZ3/M/P7p4GOFmzzNcBf5PHJwBZgTH6ruEO0AAADpklEQVS/Cfh3FA/RXAd8pg3aPCzXGZgK/GYenwD8PTAb+CZwQ6bfANyWx7OB54HjgFnAPwDHDOd1bnCbW/U6fwT498BXgDuq6mrV61yrzUN+nQfR3nOBaXl8DvD6UFzjEdlDiYi/oXiMS9lZwN/kcSfwO5XswEdUPGzyeOBfgHeHo51lA2zzbOBnWW4P8DbQoeIZaxMiYkMUvymVfWdats1D1ba+RMTuiPh5Hu8HXqbY+mAxxb465NfKNfvX/X0i4lWgsr/PsF3nRrV5KNrWqDZHxD9HxN8CB8r1tPJ1PlKbh8sg2rs1IioP0d0GjFfxzMWGXuMRGVCO4EXgC3n8RT58kvHDwD9TPIZ/J/Cn8eEzwwD+Irut/2Moh4+O4Ehtfh5YLGmsiodwzs1ztfadGS4DbXPFsF5nFZvGnQtsBE6J4gGm5NfKEMVg9vcZMkfZ5opWvM5H0srXuT/Ddp0H0d7fAbZGsRFiQ6/xaAoovw9cI2kLRRfxXzJ9HnAImEYxRPBVSf8mz10WEZ8C/kO+Lh/eJh+xzT+g+IfvAv4M+L8UD+Mc0F4xQ2SgbYZhvs6SPgr8EPiDiKjVG23InjyN0IA2Q+te5yNW0Udaq1znWobtOg+0vZLOpthC/cuVpD6yDfoaj5qAEhG/jIgFETEXeIBibBmKOZS/joj3cyjm78ihmIh4Pb/uB+5n+IcO+mxzRPRGxB9GxJyIWAycBHRTe9+ZVm3zsF5nSeMo/gP+ZUT8KJPfzK5/ZZhlT6YPZn+fVm1zK1/nI2nl63xEw3WdB9peSTOAR4ArIqLy96+h13jUBJTKSgtJY4CbgO/mqZ3AfBU+ApwP/DKHZj6WZcYBn+fDfV+a2mZJv5ZtRdJvAb0R8VLU3nemJds8nNc5r8ldwMsR8e3SqfKePOX9dQazv09LtrnFr3OfWvw6H6meYbnOA22vpJOAnwA3RsTfVTI3/BoPdja/lV8Un4x3A+9TROArgesoVkL8PfANPryp86PAX1FMVL0E/Pf4cBXHFuAXee5/kqtlWqDNM4FXKCbinqB4Emilng6KX+B/AO6olGnVNg/ndaZYlRP5Xs/l67PAZIoFA935dVKpzNfyWr5CafXLcF3nRrW5Da7zDooFHu/l79LsNrjOv9Lm4brOA20vxYe7fy7lfQ44udHX2HfKm5lZQ4yaIS8zMxtaDihmZtYQDihmZtYQDihmZtYQDihmZtYQDihmZtYQDihmZtYQDihmZtYQ/x/rFzgxQKYDrwAAAABJRU5ErkJggg==\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "yearly_incidence.plot(style='*')" ] @@ -314,9 +2383,55 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2014 1600941\n", + "1991 1659249\n", + "1995 1840410\n", + "2020 2042389\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": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "yearly_incidence.sort_values()" ] @@ -331,9 +2446,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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