From 4bed1def580c56255c2da1dced559b382af0b1e6 Mon Sep 17 00:00:00 2001 From: 741dd16a400b6a27c9b4a69b7d9a1349 <741dd16a400b6a27c9b4a69b7d9a1349@app-learninglab.inria.fr> Date: Mon, 12 Dec 2022 17:41:24 +0000 Subject: [PATCH] no commit message --- module3/exo2/exercice.ipynb | 2399 ++++++++++++++++++++++++++++++++++- 1 file changed, 2396 insertions(+), 3 deletions(-) diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb index 0bbbe37..c34680e 100644 --- a/module3/exo2/exercice.ipynb +++ b/module3/exo2/exercice.ipynb @@ -1,5 +1,2399 @@ { - "cells": [], + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Incidence de la varicelle" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + " %matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "import isoweek\n", + "import os\n", + "import requests" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " Les données de l'incidence de la varicelle sont disponibles du site Web du Réseau Sentinelles. Nous les récupérons sous forme d'un fichier en format CSV dont chaque ligne correspond à une semaine de la période demandée. Nous téléchargeons toujours le jeu de données complet, qui commence à la 49ème semaine de l'année 1990 et se termine avec une semaine récente." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "data_url=\"https://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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" + ], + "text/plain": [ + "Empty DataFrame\n", + "Columns: [week, indicator, inc, inc_low, inc_up, inc100, inc100_low, inc100_up, geo_insee, geo_name]\n", + "Index: []" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "raw_data[raw_data.isnull().any(axis=1)] " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nous réalisons toutefois une opération le fichier de toute donnée manquante si le cas se présentait dans l'avenir. Nous travaillerons donc sur le jeu de données nommé `data`." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020224875140312771538511FRFrance
120224776094373784519513FRFrance
22022467303313924674537FRFrance
32022457382717205934639FRFrance
42022447427122316311639FRFrance
520224375863330284249513FRFrance
62022427377019505590639FRFrance
72022417417722196135639FRFrance
820224074883147282947212FRFrance
9202239720413313751306FRFrance
10202238717714193123315FRFrance
11202237717254992951315FRFrance
12202236710691781960213FRFrance
13202235715814002762204FRFrance
14202234722667883744315FRFrance
152022337734001739911026FRFrance
162022327780140861151612618FRFrance
17202231768964170962210614FRFrance
182022307903957701230814919FRFrance
192022297148511006019642221529FRFrance
202022287154711102819914231630FRFrance
212022277211911619826184322440FRFrance
222022267168541280620902251931FRFrance
232022257222461801126481342840FRFrance
242022247224581810526811342741FRFrance
252022237187721487522669282234FRFrance
262022227189161494122891292335FRFrance
272022217203101630724313312537FRFrance
282022207235851900428166362943FRFrance
292022197185931418123005282135FRFrance
.................................
16401991267176081130423912312042FRFrance
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1643199123711947767116223211329FRFrance
1644199122715452995320951271737FRFrance
1645199121714903897520831261636FRFrance
16461991207190531274225364342345FRFrance
16471991197167391124622232291939FRFrance
16481991187213851388228888382551FRFrance
1649199117713462887718047241632FRFrance
16501991167148571006819646261834FRFrance
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1660199106710877701314741191226FRFrance
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16661990527193751329525455342345FRFrance
16671990517190801380724353342543FRFrance
1668199050711079666015498201228FRFrance
16691990497114302610205FRFrance
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1670 rows × 10 columns

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" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202248 7 5140 3127 7153 8 5 \n", + "1 202247 7 6094 3737 8451 9 5 \n", + "2 202246 7 3033 1392 4674 5 3 \n", + "3 202245 7 3827 1720 5934 6 3 \n", + "4 202244 7 4271 2231 6311 6 3 \n", + "5 202243 7 5863 3302 8424 9 5 \n", + "6 202242 7 3770 1950 5590 6 3 \n", + "7 202241 7 4177 2219 6135 6 3 \n", + "8 202240 7 4883 1472 8294 7 2 \n", + "9 202239 7 2041 331 3751 3 0 \n", + "10 202238 7 1771 419 3123 3 1 \n", + "11 202237 7 1725 499 2951 3 1 \n", + "12 202236 7 1069 178 1960 2 1 \n", + "13 202235 7 1581 400 2762 2 0 \n", + "14 202234 7 2266 788 3744 3 1 \n", + "15 202233 7 7340 0 17399 11 0 \n", + "16 202232 7 7801 4086 11516 12 6 \n", + "17 202231 7 6896 4170 9622 10 6 \n", + "18 202230 7 9039 5770 12308 14 9 \n", + "19 202229 7 14851 10060 19642 22 15 \n", + "20 202228 7 15471 11028 19914 23 16 \n", + "21 202227 7 21191 16198 26184 32 24 \n", + "22 202226 7 16854 12806 20902 25 19 \n", + "23 202225 7 22246 18011 26481 34 28 \n", + "24 202224 7 22458 18105 26811 34 27 \n", + "25 202223 7 18772 14875 22669 28 22 \n", + "26 202222 7 18916 14941 22891 29 23 \n", + "27 202221 7 20310 16307 24313 31 25 \n", + "28 202220 7 23585 19004 28166 36 29 \n", + "29 202219 7 18593 14181 23005 28 21 \n", + "... ... ... ... ... ... ... ... \n", + "1640 199126 7 17608 11304 23912 31 20 \n", + "1641 199125 7 16169 10700 21638 28 18 \n", + "1642 199124 7 16171 10071 22271 28 17 \n", + "1643 199123 7 11947 7671 16223 21 13 \n", + "1644 199122 7 15452 9953 20951 27 17 \n", + "1645 199121 7 14903 8975 20831 26 16 \n", + "1646 199120 7 19053 12742 25364 34 23 \n", + "1647 199119 7 16739 11246 22232 29 19 \n", + "1648 199118 7 21385 13882 28888 38 25 \n", + "1649 199117 7 13462 8877 18047 24 16 \n", + "1650 199116 7 14857 10068 19646 26 18 \n", + "1651 199115 7 13975 9781 18169 25 18 \n", + "1652 199114 7 12265 7684 16846 22 14 \n", + "1653 199113 7 9567 6041 13093 17 11 \n", + "1654 199112 7 10864 7331 14397 19 13 \n", + "1655 199111 7 15574 11184 19964 27 19 \n", + "1656 199110 7 16643 11372 21914 29 20 \n", + "1657 199109 7 13741 8780 18702 24 15 \n", + "1658 199108 7 13289 8813 17765 23 15 \n", + "1659 199107 7 12337 8077 16597 22 15 \n", + "1660 199106 7 10877 7013 14741 19 12 \n", + "1661 199105 7 10442 6544 14340 18 11 \n", + "1662 199104 7 7913 4563 11263 14 8 \n", + "1663 199103 7 15387 10484 20290 27 18 \n", + "1664 199102 7 16277 11046 21508 29 20 \n", + "1665 199101 7 15565 10271 20859 27 18 \n", + "1666 199052 7 19375 13295 25455 34 23 \n", + "1667 199051 7 19080 13807 24353 34 25 \n", + "1668 199050 7 11079 6660 15498 20 12 \n", + "1669 199049 7 1143 0 2610 2 0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 11 FR France \n", + "1 13 FR France \n", + "2 7 FR France \n", + "3 9 FR France \n", + "4 9 FR France \n", + "5 13 FR France \n", + "6 9 FR France \n", + "7 9 FR France \n", + "8 12 FR France \n", + "9 6 FR France \n", + "10 5 FR France \n", + "11 5 FR France \n", + "12 3 FR France \n", + "13 4 FR France \n", + "14 5 FR France \n", + "15 26 FR France \n", + "16 18 FR France \n", + "17 14 FR France \n", + "18 19 FR France \n", + "19 29 FR France \n", + "20 30 FR France \n", + "21 40 FR France \n", + "22 31 FR France \n", + "23 40 FR France \n", + "24 41 FR France \n", + "25 34 FR France \n", + "26 35 FR France \n", + "27 37 FR France \n", + "28 43 FR France \n", + "29 35 FR France \n", + "... ... ... ... \n", + "1640 42 FR France \n", + "1641 38 FR France \n", + "1642 39 FR France \n", + "1643 29 FR France \n", + "1644 37 FR France \n", + "1645 36 FR France \n", + "1646 45 FR France \n", + "1647 39 FR France \n", + "1648 51 FR France \n", + "1649 32 FR France \n", + "1650 34 FR France \n", + "1651 32 FR France \n", + "1652 30 FR France \n", + "1653 23 FR France \n", + "1654 25 FR France \n", + "1655 35 FR France \n", + "1656 38 FR France \n", + "1657 33 FR France \n", + "1658 31 FR France \n", + "1659 29 FR France \n", + "1660 26 FR France \n", + "1661 25 FR France \n", + "1662 20 FR France \n", + "1663 36 FR France \n", + "1664 38 FR France \n", + "1665 36 FR France \n", + "1666 45 FR France \n", + "1667 43 FR France \n", + "1668 28 FR France \n", + "1669 5 FR France \n", + "\n", + "[1670 rows x 10 columns]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + " data = raw_data.dropna().copy()\n", + "data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nos données utilisent une convention inhabituelle: le numéro de semaine est collé à l'année, donnant l'impression qu'il s'agit\n", + "de nombre entier. C'est comme ça que Pandas les interprète.\n", + "Un deuxième problème est que Pandas ne comprend pas les numéros de semaine. Il faut lui fournir les dates de début et de fin de semaine. Nous utilisons pour cela la bibliothèque soweek.Comme la conversion des semaines est devenu assez complexe, nous écrivons une petite fonction Python pour cela. Ensuite, nous l'appliquons à tous les points de nos donnés. Les résultats vont dans une nouvelle colonne 'period'." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "def convert_week(year_and_week_int):\n", + " year_and_week_str = str(year_and_week_int)\n", + " year = int(year_and_week_str[:4])\n", + " week = int(year_and_week_str[4:])\n", + " w = isoweek.Week(year, week)\n", + " return pd.Period(w.day(0), 'W')\n", + "\n", + "data['period'] = [convert_week(yw) for yw in data['week']]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Il restent deux petites modifications à faire.Premièrement, nous définissons les périodes d'observation\n", + "comme nouvel index de notre jeux de données. Ceci en fait\n", + "une suite chronologique, ce qui sera pratique par la suite.Deuxièmement, nous trions les points par période, dans\n", + "le sens chronologique." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_data = data.set_index('period').sort_index()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nous vérifions la cohérence des données. Entre la fin d'une période et le début de la période qui suit, la différence temporelle doit être zéro, ou au moins très faible. Nous laissons une \"marge d'erreur\" d'une seconde.\n", + "Nous de détectons aucune erreur." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "periods = sorted_data.index\n", + "for p1, p2 in zip(periods[:-1], periods[1:]):\n", + " delta = p2.to_timestamp() - p1.end_time\n", + " if delta > pd.Timedelta('1s'):\n", + " print(p1, p2)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sorted_data['inc'].plot() " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Un zoom sur les dernières années montrent que les pics épidémiques se situent en hiver. Notons toutefois une différence entre le schéma habituel et celui rencontré en 2020, 2021 et 2022. On peut faire l'hypothèse d'une influence du COVID et des mesures mises en place pour contrecarrer cette pandémie sur l'épidémie de varicelle." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 26, + "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()\n", + "sorted_data['inc'][-600:-200].plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Etude de l'incidence annuelle" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Etant donné que le pic de l'épidémie se situe en hiver, à cheval entre deux années civiles, nous définissons la période de référence entre deux minima de l'incidence, du 1er septembre de l'année $N$ au 1er septembre de l'année $N+1$.\n", + "\n", + "Notre tâche est un peu compliquée par le fait que l'année ne comporte pas un nombre entier de semaines. Nous modifions donc un peu nos périodes de référence: à la place du 1er août de chaque année, nous utilisons le\n", + "premier jour de la semaine qui contient le 1er septembre.\n", + "\n", + "Comme l'incidence de syndrome grippal est très faible en été, cette modification ne risque pas de fausser nos conclusions.\n", + "\n", + "Encore un petit détail: les données commencent an octobre 1990, ce qui rend la première année incomplète. Nous commençons donc l'analyse en 1991." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "first_september_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", + " for y in range(1991,\n", + " sorted_data.index[-1].year)]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "En partant de cette liste des semaines qui contiennent un 1er septembre, nous obtenons nos intervalles d'environ un an comme les périodes entre deux semaines adjacentes dans cette liste. Nous calculons les sommes des incidences hebdomadaires pour toutes ces périodes.\n", + "\n", + "Nous vérifions également que ces périodes contiennent entre 51 et 52 semaines, pour nous protéger contre des éventuelles erreurs dans notre code." + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "year = []\n", + "yearly_incidence = []\n", + "for week1, week2 in zip(first_september_week[:-1],\n", + " first_september_week[1:]):\n", + " one_year = sorted_data['inc'][week1:week2-1]\n", + " assert abs(len(one_year)-52) < 2\n", + " yearly_incidence.append(one_year.sum())\n", + " year.append(week2.year)\n", + "yearly_incidence = pd.Series(data=yearly_incidence, index=year)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Voici les incidences annuelles." + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "yearly_incidence.plot(style='*')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Une liste triée permet de plus facilement répérer les valeurs les plus élevées (à la fin)." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "2020 221186\n", + "2021 376290\n", + "2002 516689\n", + "2018 542312\n", + "2017 551041\n", + "1996 564901\n", + "2019 584066\n", + "2015 604382\n", + "2000 617597\n", + "2001 619041\n", + "2012 624573\n", + "2005 628464\n", + "2006 632833\n", + "2011 642368\n", + "1993 643387\n", + "1995 652478\n", + "1994 661409\n", + "1998 677775\n", + "1997 683434\n", + "2014 685769\n", + "2013 698332\n", + "2007 717352\n", + "2008 749478\n", + "1999 756456\n", + "2003 758363\n", + "2004 777388\n", + "2016 782114\n", + "2010 829911\n", + "1992 832939\n", + "2009 842373\n", + "dtype: int64" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "yearly_incidence.sort_values()" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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