{ "cells": [ { "cell_type": "markdown", "metadata": { "hideCode": true, "hidePrompt": true }, "source": [ "# Incidence de la varicelle" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "hideCode": true, "hidePrompt": true }, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import isoweek" ] }, { "cell_type": "markdown", "metadata": { "hideCode": true, "hidePrompt": true }, "source": [ "On télécharge les données depuis le site Web du Réseau Sentinelle sous format csv. " ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "hideCode": true, "hidePrompt": true }, "outputs": [], "source": [ "data_url = \"https://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "hideCode": true, "hidePrompt": true }, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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12021367344117305152528FRFrance
22021357256211074017426FRFrance
3202134714293782480204FRFrance
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52021327410818956321639FRFrance
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72021307719041911018911616FRFrance
8202129768004109949110614FRFrance
92021287973402173115033FRFrance
102021277902643161373614721FRFrance
112021267728441081046011616FRFrance
1220212579351654012162141018FRFrance
13202124712034893715131181323FRFrance
1420212379116642011812141018FRFrance
1520212274817275268827410FRFrance
1620212176092345887269513FRFrance
172021207748546011036911715FRFrance
18202119766544370893810713FRFrance
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2020211774686287864947410FRFrance
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2720211079056645211660141018FRFrance
28202109710988793814038171222FRFrance
29202108711281836114201171321FRFrance
.................................
15771991267176081130423912312042FRFrance
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1580199123711947767116223211329FRFrance
1581199122715452995320951271737FRFrance
1582199121714903897520831261636FRFrance
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15841991197167391124622232291939FRFrance
15851991187213851388228888382551FRFrance
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16061990497114302610205FRFrance
\n", "

1607 rows × 10 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202137 7 1984 761 3207 3 1 \n", "1 202136 7 3441 1730 5152 5 2 \n", "2 202135 7 2562 1107 4017 4 2 \n", "3 202134 7 1429 378 2480 2 0 \n", "4 202133 7 3829 1830 5828 6 3 \n", "5 202132 7 4108 1895 6321 6 3 \n", "6 202131 7 4793 2301 7285 7 3 \n", "7 202130 7 7190 4191 10189 11 6 \n", "8 202129 7 6800 4109 9491 10 6 \n", "9 202128 7 9734 0 21731 15 0 \n", "10 202127 7 9026 4316 13736 14 7 \n", "11 202126 7 7284 4108 10460 11 6 \n", "12 202125 7 9351 6540 12162 14 10 \n", "13 202124 7 12034 8937 15131 18 13 \n", "14 202123 7 9116 6420 11812 14 10 \n", "15 202122 7 4817 2752 6882 7 4 \n", "16 202121 7 6092 3458 8726 9 5 \n", "17 202120 7 7485 4601 10369 11 7 \n", "18 202119 7 6654 4370 8938 10 7 \n", "19 202118 7 3912 2110 5714 6 3 \n", "20 202117 7 4686 2878 6494 7 4 \n", "21 202116 7 4780 2891 6669 7 4 \n", "22 202115 7 11215 7627 14803 17 12 \n", "23 202114 7 11197 7994 14400 17 12 \n", "24 202113 7 9714 6289 13139 15 10 \n", "25 202112 7 11520 8415 14625 17 12 \n", "26 202111 7 9386 6678 12094 14 10 \n", "27 202110 7 9056 6452 11660 14 10 \n", "28 202109 7 10988 7938 14038 17 12 \n", "29 202108 7 11281 8361 14201 17 13 \n", "... ... ... ... ... ... ... ... \n", "1577 199126 7 17608 11304 23912 31 20 \n", "1578 199125 7 16169 10700 21638 28 18 \n", "1579 199124 7 16171 10071 22271 28 17 \n", "1580 199123 7 11947 7671 16223 21 13 \n", "1581 199122 7 15452 9953 20951 27 17 \n", "1582 199121 7 14903 8975 20831 26 16 \n", "1583 199120 7 19053 12742 25364 34 23 \n", "1584 199119 7 16739 11246 22232 29 19 \n", "1585 199118 7 21385 13882 28888 38 25 \n", "1586 199117 7 13462 8877 18047 24 16 \n", "1587 199116 7 14857 10068 19646 26 18 \n", "1588 199115 7 13975 9781 18169 25 18 \n", "1589 199114 7 12265 7684 16846 22 14 \n", "1590 199113 7 9567 6041 13093 17 11 \n", "1591 199112 7 10864 7331 14397 19 13 \n", "1592 199111 7 15574 11184 19964 27 19 \n", "1593 199110 7 16643 11372 21914 29 20 \n", "1594 199109 7 13741 8780 18702 24 15 \n", "1595 199108 7 13289 8813 17765 23 15 \n", "1596 199107 7 12337 8077 16597 22 15 \n", "1597 199106 7 10877 7013 14741 19 12 \n", "1598 199105 7 10442 6544 14340 18 11 \n", "1599 199104 7 7913 4563 11263 14 8 \n", "1600 199103 7 15387 10484 20290 27 18 \n", "1601 199102 7 16277 11046 21508 29 20 \n", "1602 199101 7 15565 10271 20859 27 18 \n", "1603 199052 7 19375 13295 25455 34 23 \n", "1604 199051 7 19080 13807 24353 34 25 \n", "1605 199050 7 11079 6660 15498 20 12 \n", "1606 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 5 FR France \n", "1 8 FR France \n", "2 6 FR France \n", "3 4 FR France \n", "4 9 FR France \n", "5 9 FR France \n", "6 11 FR France \n", "7 16 FR France \n", "8 14 FR France \n", "9 33 FR France \n", "10 21 FR France \n", "11 16 FR France \n", "12 18 FR France \n", "13 23 FR France \n", "14 18 FR France \n", "15 10 FR France \n", "16 13 FR France \n", "17 15 FR France \n", "18 13 FR France \n", "19 9 FR France \n", "20 10 FR France \n", "21 10 FR France \n", "22 22 FR France \n", "23 22 FR France \n", "24 20 FR France \n", "25 22 FR France \n", "26 18 FR France \n", "27 18 FR France \n", "28 22 FR France \n", "29 21 FR France \n", "... ... ... ... \n", "1577 42 FR France \n", "1578 38 FR France \n", "1579 39 FR France \n", "1580 29 FR France \n", "1581 37 FR France \n", "1582 36 FR France \n", "1583 45 FR France \n", "1584 39 FR France \n", "1585 51 FR France \n", "1586 32 FR France \n", "1587 34 FR France \n", "1588 32 FR France \n", "1589 30 FR France \n", "1590 23 FR France \n", "1591 25 FR France \n", "1592 35 FR France \n", "1593 38 FR France \n", "1594 33 FR France \n", "1595 31 FR France \n", "1596 29 FR France \n", "1597 26 FR France \n", "1598 25 FR France \n", "1599 20 FR France \n", "1600 36 FR France \n", "1601 38 FR France \n", "1602 36 FR France \n", "1603 45 FR France \n", "1604 43 FR France \n", "1605 28 FR France \n", "1606 5 FR France \n", "\n", "[1607 rows x 10 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data" ] }, { "cell_type": "markdown", "metadata": { "hideCode": true, "hidePrompt": true }, "source": [ "Cherchons les points manquants dans ce jeu de données ? Visiblement aucune sinon une ligne apparaitrait. Fort bien, ca me fait du travail en moins. " ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "hideCode": true, "hidePrompt": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
\n", "
" ], "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": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] }, { "cell_type": "markdown", "metadata": { "hideCode": true, "hidePrompt": true }, "source": [ "Voilà le code qui permettrait d'enlever les données sans valeurs: data = raw_data.dropna().copy()\n", "data" ] }, { "cell_type": "markdown", "metadata": { "hideCode": true, "hidePrompt": true }, "source": [ "Les données utilisent une convention inhabituelle pour définir le temps qu'il va falloir corriger si nous voulons travailler avec pandas sur ce jeu de données. " ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "hideCode": true, "hidePrompt": true }, "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", "raw_data['period'] = [convert_week(yw) for yw in raw_data['week']]" ] }, { "cell_type": "markdown", "metadata": { "hideCode": true, "hidePrompt": true }, "source": [ "Fixons la période de temps comme index et ordonnons par chronologie" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "hideCode": true, "hidePrompt": true }, "outputs": [], "source": [ "sorted_data = raw_data.set_index('period').sort_index()" ] }, { "cell_type": "markdown", "metadata": { "hideCode": true, "hidePrompt": true }, "source": [ "La il faut vérifier que les périodes ont toutes la même durée, du coup on reprend le code du MOOC:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "hideCode": true, "hidePrompt": true }, "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": 12, "metadata": { "hideCode": true, "hidePrompt": true }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sorted_data['inc'][-200:].plot()" ] }, { "cell_type": "markdown", "metadata": { "hideCode": true, "hidePrompt": true }, "source": [ "Dans l'entrée 12 j'ai simplement recopié un code qui permet d'avoir une vue d'ensemble sur les données. Etant donné que nous travaillons avec un jeu de donné qui commence en 1991 un zoom sur les dernières années ne fait pas de mal." ] }, { "cell_type": "markdown", "metadata": { "hideCode": true, "hidePrompt": true }, "source": [ "Ceci est fait dans l'entrée 13 en ne prenant que les 200 dernières valeurs du jeu de données de la colonne inc." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Etude de l'incidence annuelle" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On peut voir que le pic de l'épidémie se situe en hiver mais commence à la fin de l'été / début de l'automne, du coup nou allons créer des sous périodes d'une durée d'un an en commencant au 1er septembre comme cela nous est demandé dans l'exercice. " ] }, { "cell_type": "code", "execution_count": 16, "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": [ "Maintenant il faut s'assurer que ces périodes n'ont pas des durées anormales et soient comprise entre 51 et 52 semaines. " ] }, { "cell_type": "code", "execution_count": 17, "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": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "yearly_incidence.plot(style='*')" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2020 221186\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": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.sort_values()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Les questions du MOOC sont les suivants: \n", "1) Quelle est l'année avec la plus forte incidence et 2) celle avec la plus faible. \n", "Simple je n'ai qu'à prendre la dernière et la première valeurs de la liste ci-dessus que sont 2009 et 2020. \n", "\n", "J'ai réussi, Djudjul c'est un thug. Bravo mon vieux. " ] } ], "metadata": { "hide_code_all_hidden": true, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 }