{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# L'incidence de la varicelle" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import isoweek" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
0202312710252706313441151020FRFrance
120231174919288069587410FRFrance
220231074854273169777410FRFrance
3202309770044548946011715FRFrance
42023087817553161103412816FRFrance
5202307765953782940810614FRFrance
62023067959560171317314919FRFrance
720230576237390785679513FRFrance
820230476299397386259612FRFrance
920230376063379883289612FRFrance
102023027657630601009210515FRFrance
112023017815354701083612816FRFrance
1220225275171271776258412FRFrance
1320225176226382286309513FRFrance
142022507659031001008010515FRFrance
1520224975095321269788511FRFrance
1620224874985304369278511FRFrance
1720224776087373384419513FRFrance
182022467303313924674537FRFrance
192022457382717205934639FRFrance
202022447427122316311639FRFrance
2120224375863330284249513FRFrance
222022427377019505590639FRFrance
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2420224074883147282947212FRFrance
25202239720413313751306FRFrance
26202238717714193123315FRFrance
27202237717254992951315FRFrance
28202236710691781960213FRFrance
29202235715814002762204FRFrance
.................................
16561991267176081130423912312042FRFrance
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1660199122715452995320951271737FRFrance
1661199121714903897520831261636FRFrance
16621991207190531274225364342345FRFrance
16631991197167391124622232291939FRFrance
16641991187213851388228888382551FRFrance
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16661991167148571006819646261834FRFrance
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16851990497114302610205FRFrance
\n", "

1686 rows × 10 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202312 7 10252 7063 13441 15 10 \n", "1 202311 7 4919 2880 6958 7 4 \n", "2 202310 7 4854 2731 6977 7 4 \n", "3 202309 7 7004 4548 9460 11 7 \n", "4 202308 7 8175 5316 11034 12 8 \n", "5 202307 7 6595 3782 9408 10 6 \n", "6 202306 7 9595 6017 13173 14 9 \n", "7 202305 7 6237 3907 8567 9 5 \n", "8 202304 7 6299 3973 8625 9 6 \n", "9 202303 7 6063 3798 8328 9 6 \n", "10 202302 7 6576 3060 10092 10 5 \n", "11 202301 7 8153 5470 10836 12 8 \n", "12 202252 7 5171 2717 7625 8 4 \n", "13 202251 7 6226 3822 8630 9 5 \n", "14 202250 7 6590 3100 10080 10 5 \n", "15 202249 7 5095 3212 6978 8 5 \n", "16 202248 7 4985 3043 6927 8 5 \n", "17 202247 7 6087 3733 8441 9 5 \n", "18 202246 7 3033 1392 4674 5 3 \n", "19 202245 7 3827 1720 5934 6 3 \n", "20 202244 7 4271 2231 6311 6 3 \n", "21 202243 7 5863 3302 8424 9 5 \n", "22 202242 7 3770 1950 5590 6 3 \n", "23 202241 7 4177 2219 6135 6 3 \n", "24 202240 7 4883 1472 8294 7 2 \n", "25 202239 7 2041 331 3751 3 0 \n", "26 202238 7 1771 419 3123 3 1 \n", "27 202237 7 1725 499 2951 3 1 \n", "28 202236 7 1069 178 1960 2 1 \n", "29 202235 7 1581 400 2762 2 0 \n", "... ... ... ... ... ... ... ... \n", "1656 199126 7 17608 11304 23912 31 20 \n", "1657 199125 7 16169 10700 21638 28 18 \n", "1658 199124 7 16171 10071 22271 28 17 \n", "1659 199123 7 11947 7671 16223 21 13 \n", "1660 199122 7 15452 9953 20951 27 17 \n", "1661 199121 7 14903 8975 20831 26 16 \n", "1662 199120 7 19053 12742 25364 34 23 \n", "1663 199119 7 16739 11246 22232 29 19 \n", "1664 199118 7 21385 13882 28888 38 25 \n", "1665 199117 7 13462 8877 18047 24 16 \n", "1666 199116 7 14857 10068 19646 26 18 \n", "1667 199115 7 13975 9781 18169 25 18 \n", "1668 199114 7 12265 7684 16846 22 14 \n", "1669 199113 7 9567 6041 13093 17 11 \n", "1670 199112 7 10864 7331 14397 19 13 \n", "1671 199111 7 15574 11184 19964 27 19 \n", "1672 199110 7 16643 11372 21914 29 20 \n", "1673 199109 7 13741 8780 18702 24 15 \n", "1674 199108 7 13289 8813 17765 23 15 \n", "1675 199107 7 12337 8077 16597 22 15 \n", "1676 199106 7 10877 7013 14741 19 12 \n", "1677 199105 7 10442 6544 14340 18 11 \n", "1678 199104 7 7913 4563 11263 14 8 \n", "1679 199103 7 15387 10484 20290 27 18 \n", "1680 199102 7 16277 11046 21508 29 20 \n", "1681 199101 7 15565 10271 20859 27 18 \n", "1682 199052 7 19375 13295 25455 34 23 \n", "1683 199051 7 19080 13807 24353 34 25 \n", "1684 199050 7 11079 6660 15498 20 12 \n", "1685 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 20 FR France \n", "1 10 FR France \n", "2 10 FR France \n", "3 15 FR France \n", "4 16 FR France \n", "5 14 FR France \n", "6 19 FR France \n", "7 13 FR France \n", "8 12 FR France \n", "9 12 FR France \n", "10 15 FR France \n", "11 16 FR France \n", "12 12 FR France \n", "13 13 FR France \n", "14 15 FR France \n", "15 11 FR France \n", "16 11 FR France \n", "17 13 FR France \n", "18 7 FR France \n", "19 9 FR France \n", "20 9 FR France \n", "21 13 FR France \n", "22 9 FR France \n", "23 9 FR France \n", "24 12 FR France \n", "25 6 FR France \n", "26 5 FR France \n", "27 5 FR France \n", "28 3 FR France \n", "29 4 FR France \n", "... ... ... ... \n", "1656 42 FR France \n", "1657 38 FR France \n", "1658 39 FR France \n", "1659 29 FR France \n", "1660 37 FR France \n", "1661 36 FR France \n", "1662 45 FR France \n", "1663 39 FR France \n", "1664 51 FR France \n", "1665 32 FR France \n", "1666 34 FR France \n", "1667 32 FR France \n", "1668 30 FR France \n", "1669 23 FR France \n", "1670 25 FR France \n", "1671 35 FR France \n", "1672 38 FR France \n", "1673 33 FR France \n", "1674 31 FR France \n", "1675 29 FR France \n", "1676 26 FR France \n", "1677 25 FR France \n", "1678 20 FR France \n", "1679 36 FR France \n", "1680 38 FR France \n", "1681 36 FR France \n", "1682 45 FR France \n", "1683 43 FR France \n", "1684 28 FR France \n", "1685 5 FR France \n", "\n", "[1686 rows x 10 columns]" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data_url = \"https://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"\n", "\n", "data_file = \"varicelle.csv\"\n", "\n", "import os\n", "import urllib.request\n", "if not os.path.exists(data_file):\n", " urllib.request.urlretrieve(data_url, data_file)\n", " \n", "raw_data = pd.read_csv(data_file, encoding = 'iso-8859-1', skiprows=1)\n", "raw_data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On vérifie s'il y a une ligne nulle." ] }, { "cell_type": "code", "execution_count": 34, "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": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Pas de problème, à part la première ligne de titres. Il n'est donc pas nécessaire de supprimer les données manquantes." ] }, { "cell_type": "code", "execution_count": 35, "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": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
period
1990-12-03/1990-12-091990497114302610205FRFrance
1990-12-10/1990-12-16199050711079666015498201228FRFrance
1990-12-17/1990-12-231990517190801380724353342543FRFrance
1990-12-24/1990-12-301990527193751329525455342345FRFrance
1990-12-31/1991-01-061991017155651027120859271836FRFrance
1991-01-07/1991-01-131991027162771104621508292038FRFrance
1991-01-14/1991-01-201991037153871048420290271836FRFrance
1991-01-21/1991-01-271991047791345631126314820FRFrance
1991-01-28/1991-02-03199105710442654414340181125FRFrance
1991-02-04/1991-02-10199106710877701314741191226FRFrance
1991-02-11/1991-02-17199107712337807716597221529FRFrance
1991-02-18/1991-02-24199108713289881317765231531FRFrance
1991-02-25/1991-03-03199109713741878018702241533FRFrance
1991-03-04/1991-03-101991107166431137221914292038FRFrance
1991-03-11/1991-03-171991117155741118419964271935FRFrance
1991-03-18/1991-03-24199112710864733114397191325FRFrance
1991-03-25/1991-03-3119911379567604113093171123FRFrance
1991-04-01/1991-04-07199114712265768416846221430FRFrance
1991-04-08/1991-04-14199115713975978118169251832FRFrance
1991-04-15/1991-04-211991167148571006819646261834FRFrance
1991-04-22/1991-04-28199117713462887718047241632FRFrance
1991-04-29/1991-05-051991187213851388228888382551FRFrance
1991-05-06/1991-05-121991197167391124622232291939FRFrance
1991-05-13/1991-05-191991207190531274225364342345FRFrance
1991-05-20/1991-05-26199121714903897520831261636FRFrance
1991-05-27/1991-06-02199122715452995320951271737FRFrance
1991-06-03/1991-06-09199123711947767116223211329FRFrance
1991-06-10/1991-06-161991247161711007122271281739FRFrance
1991-06-17/1991-06-231991257161691070021638281838FRFrance
1991-06-24/1991-06-301991267176081130423912312042FRFrance
.................................
2022-08-29/2022-09-04202235715814002762204FRFrance
2022-09-05/2022-09-11202236710691781960213FRFrance
2022-09-12/2022-09-18202237717254992951315FRFrance
2022-09-19/2022-09-25202238717714193123315FRFrance
2022-09-26/2022-10-02202239720413313751306FRFrance
2022-10-03/2022-10-0920224074883147282947212FRFrance
2022-10-10/2022-10-162022417417722196135639FRFrance
2022-10-17/2022-10-232022427377019505590639FRFrance
2022-10-24/2022-10-3020224375863330284249513FRFrance
2022-10-31/2022-11-062022447427122316311639FRFrance
2022-11-07/2022-11-132022457382717205934639FRFrance
2022-11-14/2022-11-202022467303313924674537FRFrance
2022-11-21/2022-11-2720224776087373384419513FRFrance
2022-11-28/2022-12-0420224874985304369278511FRFrance
2022-12-05/2022-12-1120224975095321269788511FRFrance
2022-12-12/2022-12-182022507659031001008010515FRFrance
2022-12-19/2022-12-2520225176226382286309513FRFrance
2022-12-26/2023-01-0120225275171271776258412FRFrance
2023-01-02/2023-01-082023017815354701083612816FRFrance
2023-01-09/2023-01-152023027657630601009210515FRFrance
2023-01-16/2023-01-2220230376063379883289612FRFrance
2023-01-23/2023-01-2920230476299397386259612FRFrance
2023-01-30/2023-02-0520230576237390785679513FRFrance
2023-02-06/2023-02-122023067959560171317314919FRFrance
2023-02-13/2023-02-19202307765953782940810614FRFrance
2023-02-20/2023-02-262023087817553161103412816FRFrance
2023-02-27/2023-03-05202309770044548946011715FRFrance
2023-03-06/2023-03-1220231074854273169777410FRFrance
2023-03-13/2023-03-1920231174919288069587410FRFrance
2023-03-20/2023-03-26202312710252706313441151020FRFrance
\n", "

1686 rows × 10 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 \\\n", "period \n", "1990-12-03/1990-12-09 199049 7 1143 0 2610 2 \n", "1990-12-10/1990-12-16 199050 7 11079 6660 15498 20 \n", "1990-12-17/1990-12-23 199051 7 19080 13807 24353 34 \n", "1990-12-24/1990-12-30 199052 7 19375 13295 25455 34 \n", "1990-12-31/1991-01-06 199101 7 15565 10271 20859 27 \n", "1991-01-07/1991-01-13 199102 7 16277 11046 21508 29 \n", "1991-01-14/1991-01-20 199103 7 15387 10484 20290 27 \n", "1991-01-21/1991-01-27 199104 7 7913 4563 11263 14 \n", "1991-01-28/1991-02-03 199105 7 10442 6544 14340 18 \n", "1991-02-04/1991-02-10 199106 7 10877 7013 14741 19 \n", "1991-02-11/1991-02-17 199107 7 12337 8077 16597 22 \n", "1991-02-18/1991-02-24 199108 7 13289 8813 17765 23 \n", "1991-02-25/1991-03-03 199109 7 13741 8780 18702 24 \n", "1991-03-04/1991-03-10 199110 7 16643 11372 21914 29 \n", "1991-03-11/1991-03-17 199111 7 15574 11184 19964 27 \n", "1991-03-18/1991-03-24 199112 7 10864 7331 14397 19 \n", "1991-03-25/1991-03-31 199113 7 9567 6041 13093 17 \n", "1991-04-01/1991-04-07 199114 7 12265 7684 16846 22 \n", "1991-04-08/1991-04-14 199115 7 13975 9781 18169 25 \n", "1991-04-15/1991-04-21 199116 7 14857 10068 19646 26 \n", "1991-04-22/1991-04-28 199117 7 13462 8877 18047 24 \n", "1991-04-29/1991-05-05 199118 7 21385 13882 28888 38 \n", "1991-05-06/1991-05-12 199119 7 16739 11246 22232 29 \n", "1991-05-13/1991-05-19 199120 7 19053 12742 25364 34 \n", "1991-05-20/1991-05-26 199121 7 14903 8975 20831 26 \n", "1991-05-27/1991-06-02 199122 7 15452 9953 20951 27 \n", "1991-06-03/1991-06-09 199123 7 11947 7671 16223 21 \n", "1991-06-10/1991-06-16 199124 7 16171 10071 22271 28 \n", "1991-06-17/1991-06-23 199125 7 16169 10700 21638 28 \n", "1991-06-24/1991-06-30 199126 7 17608 11304 23912 31 \n", "... ... ... ... ... ... ... \n", "2022-08-29/2022-09-04 202235 7 1581 400 2762 2 \n", "2022-09-05/2022-09-11 202236 7 1069 178 1960 2 \n", "2022-09-12/2022-09-18 202237 7 1725 499 2951 3 \n", "2022-09-19/2022-09-25 202238 7 1771 419 3123 3 \n", "2022-09-26/2022-10-02 202239 7 2041 331 3751 3 \n", "2022-10-03/2022-10-09 202240 7 4883 1472 8294 7 \n", "2022-10-10/2022-10-16 202241 7 4177 2219 6135 6 \n", "2022-10-17/2022-10-23 202242 7 3770 1950 5590 6 \n", "2022-10-24/2022-10-30 202243 7 5863 3302 8424 9 \n", "2022-10-31/2022-11-06 202244 7 4271 2231 6311 6 \n", "2022-11-07/2022-11-13 202245 7 3827 1720 5934 6 \n", "2022-11-14/2022-11-20 202246 7 3033 1392 4674 5 \n", "2022-11-21/2022-11-27 202247 7 6087 3733 8441 9 \n", "2022-11-28/2022-12-04 202248 7 4985 3043 6927 8 \n", "2022-12-05/2022-12-11 202249 7 5095 3212 6978 8 \n", "2022-12-12/2022-12-18 202250 7 6590 3100 10080 10 \n", "2022-12-19/2022-12-25 202251 7 6226 3822 8630 9 \n", "2022-12-26/2023-01-01 202252 7 5171 2717 7625 8 \n", "2023-01-02/2023-01-08 202301 7 8153 5470 10836 12 \n", "2023-01-09/2023-01-15 202302 7 6576 3060 10092 10 \n", "2023-01-16/2023-01-22 202303 7 6063 3798 8328 9 \n", "2023-01-23/2023-01-29 202304 7 6299 3973 8625 9 \n", "2023-01-30/2023-02-05 202305 7 6237 3907 8567 9 \n", "2023-02-06/2023-02-12 202306 7 9595 6017 13173 14 \n", "2023-02-13/2023-02-19 202307 7 6595 3782 9408 10 \n", "2023-02-20/2023-02-26 202308 7 8175 5316 11034 12 \n", "2023-02-27/2023-03-05 202309 7 7004 4548 9460 11 \n", "2023-03-06/2023-03-12 202310 7 4854 2731 6977 7 \n", "2023-03-13/2023-03-19 202311 7 4919 2880 6958 7 \n", "2023-03-20/2023-03-26 202312 7 10252 7063 13441 15 \n", "\n", " inc100_low inc100_up geo_insee geo_name \n", "period \n", "1990-12-03/1990-12-09 0 5 FR France \n", "1990-12-10/1990-12-16 12 28 FR France \n", "1990-12-17/1990-12-23 25 43 FR France \n", "1990-12-24/1990-12-30 23 45 FR France \n", "1990-12-31/1991-01-06 18 36 FR France \n", "1991-01-07/1991-01-13 20 38 FR France \n", "1991-01-14/1991-01-20 18 36 FR France \n", "1991-01-21/1991-01-27 8 20 FR France \n", "1991-01-28/1991-02-03 11 25 FR France \n", "1991-02-04/1991-02-10 12 26 FR France \n", "1991-02-11/1991-02-17 15 29 FR France \n", "1991-02-18/1991-02-24 15 31 FR France \n", "1991-02-25/1991-03-03 15 33 FR France \n", "1991-03-04/1991-03-10 20 38 FR France \n", "1991-03-11/1991-03-17 19 35 FR France \n", "1991-03-18/1991-03-24 13 25 FR France \n", "1991-03-25/1991-03-31 11 23 FR France \n", "1991-04-01/1991-04-07 14 30 FR France \n", "1991-04-08/1991-04-14 18 32 FR France \n", "1991-04-15/1991-04-21 18 34 FR France \n", "1991-04-22/1991-04-28 16 32 FR France \n", "1991-04-29/1991-05-05 25 51 FR France \n", "1991-05-06/1991-05-12 19 39 FR France \n", "1991-05-13/1991-05-19 23 45 FR France \n", "1991-05-20/1991-05-26 16 36 FR France \n", "1991-05-27/1991-06-02 17 37 FR France \n", "1991-06-03/1991-06-09 13 29 FR France \n", "1991-06-10/1991-06-16 17 39 FR France \n", "1991-06-17/1991-06-23 18 38 FR France \n", "1991-06-24/1991-06-30 20 42 FR France \n", "... ... ... ... ... \n", "2022-08-29/2022-09-04 0 4 FR France \n", "2022-09-05/2022-09-11 1 3 FR France \n", "2022-09-12/2022-09-18 1 5 FR France \n", "2022-09-19/2022-09-25 1 5 FR France \n", "2022-09-26/2022-10-02 0 6 FR France \n", "2022-10-03/2022-10-09 2 12 FR France \n", "2022-10-10/2022-10-16 3 9 FR France \n", "2022-10-17/2022-10-23 3 9 FR France \n", "2022-10-24/2022-10-30 5 13 FR France \n", "2022-10-31/2022-11-06 3 9 FR France \n", "2022-11-07/2022-11-13 3 9 FR France \n", "2022-11-14/2022-11-20 3 7 FR France \n", "2022-11-21/2022-11-27 5 13 FR France \n", "2022-11-28/2022-12-04 5 11 FR France \n", "2022-12-05/2022-12-11 5 11 FR France \n", "2022-12-12/2022-12-18 5 15 FR France \n", "2022-12-19/2022-12-25 5 13 FR France \n", "2022-12-26/2023-01-01 4 12 FR France \n", "2023-01-02/2023-01-08 8 16 FR France \n", "2023-01-09/2023-01-15 5 15 FR France \n", "2023-01-16/2023-01-22 6 12 FR France \n", "2023-01-23/2023-01-29 6 12 FR France \n", "2023-01-30/2023-02-05 5 13 FR France \n", "2023-02-06/2023-02-12 9 19 FR France \n", "2023-02-13/2023-02-19 6 14 FR France \n", "2023-02-20/2023-02-26 8 16 FR France \n", "2023-02-27/2023-03-05 7 15 FR France \n", "2023-03-06/2023-03-12 4 10 FR France \n", "2023-03-13/2023-03-19 4 10 FR France \n", "2023-03-20/2023-03-26 10 20 FR France \n", "\n", "[1686 rows x 10 columns]" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sorted_data = data.set_index('period').sort_index()\n", "sorted_data" ] }, { "cell_type": "code", "execution_count": 37, "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": [ "Aucun problème." ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "hideOutput": true }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 38, "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'].plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On doit nécessairement changer la ligne ci-dessous, car on s'intéresse a 1er septembre, et que y part de 1991, non plus de 1985." ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [], "source": [ "first_sept_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", " for y in range(1991,\n", " sorted_data.index[-1].year)]" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [], "source": [ "year = []\n", "yearly_incidence = []\n", "for week1, week2 in zip(first_sept_week[:-1],\n", " first_sept_week[1:]):\n", " one_year = sorted_data['inc'][week1:week2-1]\n", " assert abs(len(one_year)-52) < 2 # message d'erreur si la condition n'est pas satisfaite\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": 43, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 43, "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 = pd.Series(index=year, data=yearly_incidence)\n", "yearly_incidence.plot(style='.')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On cherche les épidémies les plus fortes et les plus faibles." ] }, { "cell_type": "code", "execution_count": 47, "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", "2022 641397\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": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.sort_values()" ] }, { "cell_type": "markdown", "metadata": {}, "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 }