{ "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 urllib" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Les données de l'incidence de la varicelle sont disponibles sur le site Web du [Réseau Sentinelles](http://www.sentiweb.fr/). 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 en 1991 et se termine avec une semaine récente." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "data_url = \"https://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Voici l'explication des colonnes données [sur le site d'origine](https://ns.sentiweb.fr/incidence/csv-schema-v1.json)\n", "\n", "| Nom de colonne | Libellé de colonne |\n", "|----------------|-----------------------------------------------------------------------------------------------------------------------------------|\n", "| week | Semaine calendaire (ISO 8601) |\n", "| indicator | Code de l'indicateur de surveillance |\n", "| inc | Estimation de l'incidence de consultations en nombre de cas |\n", "| inc_low | Estimation de la borne inférieure de l'IC95% du nombre de cas de consultation |\n", "| inc_up | Estimation de la borne supérieure de l'IC95% du nombre de cas de consultation |\n", "| inc100 | Estimation du taux d'incidence du nombre de cas de consultation (en cas pour 100,000 habitants) |\n", "| inc100_low | Estimation de la borne inférieure de l'IC95% du taux d'incidence du nombre de cas de consultation (en cas pour 100,000 habitants) |\n", "| inc100_up | Estimation de la borne supérieure de l'IC95% du taux d'incidence du nombre de cas de consultation (en cas pour 100,000 habitants) |\n", "| geo_insee | Code de la zone géographique concernée (Code INSEE) http://www.insee.fr/fr/methodes/nomenclatures/cog/ |\n", "| geo_name | Libellé de la zone géographique (ce libellé peut être modifié sans préavis) |" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Position du fichier sur le disque dur. S'il existe alors je ne fais rien. Sinon je le télécharge sur le web." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "data_filename = \"analyse-varicelle.csv\"\n", "# Si les données ne sont pas disponibles localement\n", "if not(os.path.exists(data_filename)):\n", " # Alors les télécharger depuis le site officiel\n", " urllib.request.urlretrieve(data_url,data_filename)\n", "# Vérifier que le fichier n'est pas vide\n", "assert os.path.getsize(data_filename)>0" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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520200778959657411344141018FRFrance
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262019387307814164740528FRFrance
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28201936712772632291204FRFrance
29201935792201857102FRFrance
.................................
14991991267176081130423912312042FRFrance
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1504199121714903897520831261636FRFrance
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\n", "

1529 rows × 10 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202012 7 8192 5822 10562 12 8 \n", "1 202011 7 10198 7568 12828 15 11 \n", "2 202010 7 9011 6691 11331 14 10 \n", "3 202009 7 13631 10544 16718 21 16 \n", "4 202008 7 10424 7708 13140 16 12 \n", "5 202007 7 8959 6574 11344 14 10 \n", "6 202006 7 9264 6925 11603 14 10 \n", "7 202005 7 8505 6314 10696 13 10 \n", "8 202004 7 7991 5831 10151 12 9 \n", "9 202003 7 5968 4100 7836 9 6 \n", "10 202002 7 6534 4530 8538 10 7 \n", "11 202001 7 9835 7019 12651 15 11 \n", "12 201952 7 7941 5246 10636 12 8 \n", "13 201951 7 5823 3675 7971 9 6 \n", "14 201950 7 6424 4276 8572 10 7 \n", "15 201949 7 6621 4540 8702 10 7 \n", "16 201948 7 5542 3383 7701 8 5 \n", "17 201947 7 7536 5058 10014 11 7 \n", "18 201946 7 2638 1316 3960 4 2 \n", "19 201945 7 4492 2615 6369 7 4 \n", "20 201944 7 5728 3627 7829 9 6 \n", "21 201943 7 4834 2751 6917 7 4 \n", "22 201942 7 6279 3989 8569 10 7 \n", "23 201941 7 4130 2030 6230 6 3 \n", "24 201940 7 4211 2218 6204 6 3 \n", "25 201939 7 3137 1310 4964 5 2 \n", "26 201938 7 3078 1416 4740 5 2 \n", "27 201937 7 970 162 1778 1 0 \n", "28 201936 7 1277 263 2291 2 0 \n", "29 201935 7 922 0 1857 1 0 \n", "... ... ... ... ... ... ... ... \n", "1499 199126 7 17608 11304 23912 31 20 \n", "1500 199125 7 16169 10700 21638 28 18 \n", "1501 199124 7 16171 10071 22271 28 17 \n", "1502 199123 7 11947 7671 16223 21 13 \n", "1503 199122 7 15452 9953 20951 27 17 \n", "1504 199121 7 14903 8975 20831 26 16 \n", "1505 199120 7 19053 12742 25364 34 23 \n", "1506 199119 7 16739 11246 22232 29 19 \n", "1507 199118 7 21385 13882 28888 38 25 \n", "1508 199117 7 13462 8877 18047 24 16 \n", "1509 199116 7 14857 10068 19646 26 18 \n", "1510 199115 7 13975 9781 18169 25 18 \n", "1511 199114 7 12265 7684 16846 22 14 \n", "1512 199113 7 9567 6041 13093 17 11 \n", "1513 199112 7 10864 7331 14397 19 13 \n", "1514 199111 7 15574 11184 19964 27 19 \n", "1515 199110 7 16643 11372 21914 29 20 \n", "1516 199109 7 13741 8780 18702 24 15 \n", "1517 199108 7 13289 8813 17765 23 15 \n", "1518 199107 7 12337 8077 16597 22 15 \n", "1519 199106 7 10877 7013 14741 19 12 \n", "1520 199105 7 10442 6544 14340 18 11 \n", "1521 199104 7 7913 4563 11263 14 8 \n", "1522 199103 7 15387 10484 20290 27 18 \n", "1523 199102 7 16277 11046 21508 29 20 \n", "1524 199101 7 15565 10271 20859 27 18 \n", "1525 199052 7 19375 13295 25455 34 23 \n", "1526 199051 7 19080 13807 24353 34 25 \n", "1527 199050 7 11079 6660 15498 20 12 \n", "1528 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 16 FR France \n", "1 19 FR France \n", "2 18 FR France \n", "3 26 FR France \n", "4 20 FR France \n", "5 18 FR France \n", "6 18 FR France \n", "7 16 FR France \n", "8 15 FR France \n", "9 12 FR France \n", "10 13 FR France \n", "11 19 FR France \n", "12 16 FR France \n", "13 12 FR France \n", "14 13 FR France \n", "15 13 FR France \n", "16 11 FR France \n", "17 15 FR France \n", "18 6 FR France \n", "19 10 FR France \n", "20 12 FR France \n", "21 10 FR France \n", "22 13 FR France \n", "23 9 FR France \n", "24 9 FR France \n", "25 8 FR France \n", "26 8 FR France \n", "27 2 FR France \n", "28 4 FR France \n", "29 2 FR France \n", "... ... ... ... \n", "1499 42 FR France \n", "1500 38 FR France \n", "1501 39 FR France \n", "1502 29 FR France \n", "1503 37 FR France \n", "1504 36 FR France \n", "1505 45 FR France \n", "1506 39 FR France \n", "1507 51 FR France \n", "1508 32 FR France \n", "1509 34 FR France \n", "1510 32 FR France \n", "1511 30 FR France \n", "1512 23 FR France \n", "1513 25 FR France \n", "1514 35 FR France \n", "1515 38 FR France \n", "1516 33 FR France \n", "1517 31 FR France \n", "1518 29 FR France \n", "1519 26 FR France \n", "1520 25 FR France \n", "1521 20 FR France \n", "1522 36 FR France \n", "1523 38 FR France \n", "1524 36 FR France \n", "1525 45 FR France \n", "1526 43 FR France \n", "1527 28 FR France \n", "1528 5 FR France \n", "\n", "[1529 rows x 10 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = pd.read_csv(data_filename, skiprows=1)\n", "raw_data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Y a-t-il des points manquants dans ce jeux de données ? Non, il n'y pas de points manquants. (2020-04-05T19:59:00)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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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": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nous éliminons ces points manquants du jeu de données." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
02020127819258221056212816FRFrance
1202011710198756812828151119FRFrance
220201079011669111331141018FRFrance
32020097136311054416718211626FRFrance
4202008710424770813140161220FRFrance
520200778959657411344141018FRFrance
620200679264692511603141018FRFrance
720200578505631410696131016FRFrance
82020047799158311015112915FRFrance
920200375968410078369612FRFrance
10202002765344530853810713FRFrance
1120200179835701912651151119FRFrance
122019527794152461063612816FRFrance
1320195175823367579719612FRFrance
14201950764244276857210713FRFrance
15201949766214540870210713FRFrance
1620194875542338377018511FRFrance
172019477753650581001411715FRFrance
182019467263813163960426FRFrance
1920194574492261563697410FRFrance
2020194475728362778299612FRFrance
2120194374834275169177410FRFrance
22201942762793989856910713FRFrance
232019417413020306230639FRFrance
242019407421122186204639FRFrance
252019397313713104964528FRFrance
262019387307814164740528FRFrance
2720193779701621778102FRFrance
28201936712772632291204FRFrance
29201935792201857102FRFrance
.................................
14991991267176081130423912312042FRFrance
15001991257161691070021638281838FRFrance
15011991247161711007122271281739FRFrance
1502199123711947767116223211329FRFrance
1503199122715452995320951271737FRFrance
1504199121714903897520831261636FRFrance
15051991207190531274225364342345FRFrance
15061991197167391124622232291939FRFrance
15071991187213851388228888382551FRFrance
1508199117713462887718047241632FRFrance
15091991167148571006819646261834FRFrance
1510199115713975978118169251832FRFrance
1511199114712265768416846221430FRFrance
151219911379567604113093171123FRFrance
1513199112710864733114397191325FRFrance
15141991117155741118419964271935FRFrance
15151991107166431137221914292038FRFrance
1516199109713741878018702241533FRFrance
1517199108713289881317765231531FRFrance
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1519199106710877701314741191226FRFrance
1520199105710442654414340181125FRFrance
15211991047791345631126314820FRFrance
15221991037153871048420290271836FRFrance
15231991027162771104621508292038FRFrance
15241991017155651027120859271836FRFrance
15251990527193751329525455342345FRFrance
15261990517190801380724353342543FRFrance
1527199050711079666015498201228FRFrance
15281990497114302610205FRFrance
\n", "

1529 rows × 10 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202012 7 8192 5822 10562 12 8 \n", "1 202011 7 10198 7568 12828 15 11 \n", "2 202010 7 9011 6691 11331 14 10 \n", "3 202009 7 13631 10544 16718 21 16 \n", "4 202008 7 10424 7708 13140 16 12 \n", "5 202007 7 8959 6574 11344 14 10 \n", "6 202006 7 9264 6925 11603 14 10 \n", "7 202005 7 8505 6314 10696 13 10 \n", "8 202004 7 7991 5831 10151 12 9 \n", "9 202003 7 5968 4100 7836 9 6 \n", "10 202002 7 6534 4530 8538 10 7 \n", "11 202001 7 9835 7019 12651 15 11 \n", "12 201952 7 7941 5246 10636 12 8 \n", "13 201951 7 5823 3675 7971 9 6 \n", "14 201950 7 6424 4276 8572 10 7 \n", "15 201949 7 6621 4540 8702 10 7 \n", "16 201948 7 5542 3383 7701 8 5 \n", "17 201947 7 7536 5058 10014 11 7 \n", "18 201946 7 2638 1316 3960 4 2 \n", "19 201945 7 4492 2615 6369 7 4 \n", "20 201944 7 5728 3627 7829 9 6 \n", "21 201943 7 4834 2751 6917 7 4 \n", "22 201942 7 6279 3989 8569 10 7 \n", "23 201941 7 4130 2030 6230 6 3 \n", "24 201940 7 4211 2218 6204 6 3 \n", "25 201939 7 3137 1310 4964 5 2 \n", "26 201938 7 3078 1416 4740 5 2 \n", "27 201937 7 970 162 1778 1 0 \n", "28 201936 7 1277 263 2291 2 0 \n", "29 201935 7 922 0 1857 1 0 \n", "... ... ... ... ... ... ... ... \n", "1499 199126 7 17608 11304 23912 31 20 \n", "1500 199125 7 16169 10700 21638 28 18 \n", "1501 199124 7 16171 10071 22271 28 17 \n", "1502 199123 7 11947 7671 16223 21 13 \n", "1503 199122 7 15452 9953 20951 27 17 \n", "1504 199121 7 14903 8975 20831 26 16 \n", "1505 199120 7 19053 12742 25364 34 23 \n", "1506 199119 7 16739 11246 22232 29 19 \n", "1507 199118 7 21385 13882 28888 38 25 \n", "1508 199117 7 13462 8877 18047 24 16 \n", "1509 199116 7 14857 10068 19646 26 18 \n", "1510 199115 7 13975 9781 18169 25 18 \n", "1511 199114 7 12265 7684 16846 22 14 \n", "1512 199113 7 9567 6041 13093 17 11 \n", "1513 199112 7 10864 7331 14397 19 13 \n", "1514 199111 7 15574 11184 19964 27 19 \n", "1515 199110 7 16643 11372 21914 29 20 \n", "1516 199109 7 13741 8780 18702 24 15 \n", "1517 199108 7 13289 8813 17765 23 15 \n", "1518 199107 7 12337 8077 16597 22 15 \n", "1519 199106 7 10877 7013 14741 19 12 \n", "1520 199105 7 10442 6544 14340 18 11 \n", "1521 199104 7 7913 4563 11263 14 8 \n", "1522 199103 7 15387 10484 20290 27 18 \n", "1523 199102 7 16277 11046 21508 29 20 \n", "1524 199101 7 15565 10271 20859 27 18 \n", "1525 199052 7 19375 13295 25455 34 23 \n", "1526 199051 7 19080 13807 24353 34 25 \n", "1527 199050 7 11079 6660 15498 20 12 \n", "1528 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 16 FR France \n", "1 19 FR France \n", "2 18 FR France \n", "3 26 FR France \n", "4 20 FR France \n", "5 18 FR France \n", "6 18 FR France \n", "7 16 FR France \n", "8 15 FR France \n", "9 12 FR France \n", "10 13 FR France \n", "11 19 FR France \n", "12 16 FR France \n", "13 12 FR France \n", "14 13 FR France \n", "15 13 FR France \n", "16 11 FR France \n", "17 15 FR France \n", "18 6 FR France \n", "19 10 FR France \n", "20 12 FR France \n", "21 10 FR France \n", "22 13 FR France \n", "23 9 FR France \n", "24 9 FR France \n", "25 8 FR France \n", "26 8 FR France \n", "27 2 FR France \n", "28 4 FR France \n", "29 2 FR France \n", "... ... ... ... \n", "1499 42 FR France \n", "1500 38 FR France \n", "1501 39 FR France \n", "1502 29 FR France \n", "1503 37 FR France \n", "1504 36 FR France \n", "1505 45 FR France \n", "1506 39 FR France \n", "1507 51 FR France \n", "1508 32 FR France \n", "1509 34 FR France \n", "1510 32 FR France \n", "1511 30 FR France \n", "1512 23 FR France \n", "1513 25 FR France \n", "1514 35 FR France \n", "1515 38 FR France \n", "1516 33 FR France \n", "1517 31 FR France \n", "1518 29 FR France \n", "1519 26 FR France \n", "1520 25 FR France \n", "1521 20 FR France \n", "1522 36 FR France \n", "1523 38 FR France \n", "1524 36 FR France \n", "1525 45 FR France \n", "1526 43 FR France \n", "1527 28 FR France \n", "1528 5 FR France \n", "\n", "[1529 rows x 10 columns]" ] }, "execution_count": 8, "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 de nombre entier. C'est comme ça que Pandas les interprète.\n", "\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 isoweek.\n", "\n", "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": 9, "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.\n", "\n", "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.\n", "\n", "Deuxièmement, nous trions les points par période, dans\n", "le sens chronologique." ] }, { "cell_type": "code", "execution_count": 11, "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\n", "le début de la période qui suit, la différence temporelle doit être\n", "zéro, ou au moins très faible. Nous laissons une \"marge d'erreur\"\n", "d'une seconde." ] }, { "cell_type": "code", "execution_count": 13, "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": "markdown", "metadata": {}, "source": [ "Il n'y a pas d'incohérence à noter. (2020-04-05T20:12:00)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Le prétraitement des données est terminé, nous pouvons commencer l'exploration." ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 41, "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": [ "Les données sont trés oscillantes au cours du temps. Nous allons décomposer cette série chronologique comme une somme de séries afin d'avoir une interprétation plus éclairée." ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from statsmodels.tsa.seasonal import seasonal_decompose\n", "# freq = 52 car 52 semaines par an\n", "result = seasonal_decompose(sorted_data['inc'],model=\"additive\", freq=52)\n", "result.plot()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Un zoom sur les dernières années montre mieux la situation des pics en hiver. Le creux des incidences se trouve en été." ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 44, "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()" ] }, { "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 août de l'année 𝑁\n", "au 1er août de l'année 𝑁+1\n", "\n", ".\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 premier jour de la semaine qui contient le 1er août.\n", "\n", "Comme l'incidence de la varicelle est très faible en été, cette modification ne risque pas de fausser nos conclusions.\n", "\n", "Encore un petit détail: Nous éliminons la première année qui pourrait ne pas contenir 12 mois." ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[Period('1991-07-29/1991-08-04', 'W-SUN'),\n", " Period('1992-07-27/1992-08-02', 'W-SUN'),\n", " Period('1993-07-26/1993-08-01', 'W-SUN'),\n", " Period('1994-08-01/1994-08-07', 'W-SUN'),\n", " Period('1995-07-31/1995-08-06', 'W-SUN'),\n", " Period('1996-07-29/1996-08-04', 'W-SUN'),\n", " Period('1997-07-28/1997-08-03', 'W-SUN'),\n", " Period('1998-07-27/1998-08-02', 'W-SUN'),\n", " Period('1999-07-26/1999-08-01', 'W-SUN'),\n", " Period('2000-07-31/2000-08-06', 'W-SUN'),\n", " Period('2001-07-30/2001-08-05', 'W-SUN'),\n", " Period('2002-07-29/2002-08-04', 'W-SUN'),\n", " Period('2003-07-28/2003-08-03', 'W-SUN'),\n", " Period('2004-07-26/2004-08-01', 'W-SUN'),\n", " Period('2005-08-01/2005-08-07', 'W-SUN'),\n", " Period('2006-07-31/2006-08-06', 'W-SUN'),\n", " Period('2007-07-30/2007-08-05', 'W-SUN'),\n", " Period('2008-07-28/2008-08-03', 'W-SUN'),\n", " Period('2009-07-27/2009-08-02', 'W-SUN'),\n", " Period('2010-07-26/2010-08-01', 'W-SUN'),\n", " Period('2011-08-01/2011-08-07', 'W-SUN'),\n", " Period('2012-07-30/2012-08-05', 'W-SUN'),\n", " Period('2013-07-29/2013-08-04', 'W-SUN'),\n", " Period('2014-07-28/2014-08-03', 'W-SUN'),\n", " Period('2015-07-27/2015-08-02', 'W-SUN'),\n", " Period('2016-08-01/2016-08-07', 'W-SUN'),\n", " Period('2017-07-31/2017-08-06', 'W-SUN'),\n", " Period('2018-07-30/2018-08-05', 'W-SUN'),\n", " Period('2019-07-29/2019-08-04', 'W-SUN')]" ] }, "execution_count": 70, "metadata": {}, "output_type": "execute_result" } ], "source": [ "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", " for y in range(1991,\n", " sorted_data.index[-1].year)]\n", "first_august_week" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "En partant de cette liste des semaines qui contiennent un 1er août, 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. Nous commençons donc l'analyse en 1991" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [], "source": [ "year = []\n", "yearly_incidence = []\n", "for week1, week2 in zip(first_august_week[:-1],\n", " first_august_week[1:]):\n", " one_year = sorted_data['inc'][week1:week2-1]\n", " if not abs(len(one_year)-52) < 2:\n", " raise Exception(\"Mauvaise taille de semaines : \",len(one_year))\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": 76, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 76, "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).\n" ] }, { "cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2010 848236\n", "2009 822819\n", "1992 821558\n", "1999 784963\n", "2016 780645\n", "2003 770211\n", "2008 745701\n", "2004 736266\n", "2013 708874\n", "2007 701566\n", "1994 682920\n", "1997 679308\n", "2014 673458\n", "1998 660316\n", "2006 657482\n", "2005 654308\n", "1993 653058\n", "2001 650660\n", "1995 648598\n", "2011 645042\n", "2012 620315\n", "2015 613286\n", "2000 605096\n", "2019 584926\n", "2017 557449\n", "1996 553859\n", "2018 543281\n", "2002 502271\n", "dtype: int64" ] }, "execution_count": 80, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.sort_values(ascending=False)" ] }, { "cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [ { "ename": "SyntaxError", "evalue": "unexpected EOF while parsing (, line 1)", "output_type": "error", "traceback": [ "\u001b[0;36m File \u001b[0;32m\"\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m print(\"min : {}\".format(min(yearly_incidence))\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m unexpected EOF while parsing\n" ] } ], "source": [] } ], "metadata": { "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 }