diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb index 0bbbe371b01e359e381e43239412d77bf53fb1fb..5b5e414e9c9e1a5325ffce2b5d0bd57067ba2ce3 100644 --- a/module3/exo2/exercice.ipynb +++ b/module3/exo2/exercice.ipynb @@ -1,5 +1,3247 @@ { - "cells": [], + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Incidence de la varicelle" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "import isoweek" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "data_url = \"./incidence-PAY-7.csv\"" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
02021037861060831113713917FRFrance
12021027785954801023812816FRFrance
2202101710531775513307161220FRFrance
3202053711978840615550181323FRFrance
4202052712012828515739181224FRFrance
5202051710564757413554161121FRFrance
6202050770634744938211715FRFrance
720204975026314569078511FRFrance
8202048766834312905410614FRFrance
920204774999296370358511FRFrance
102020467375219635541639FRFrance
112020457369620165376639FRFrance
1220204474391237564077410FRFrance
1320204374376250562477410FRFrance
142020427400019796021639FRFrance
152020417396120995823639FRFrance
16202040720786753481315FRFrance
17202039710492371861213FRFrance
18202038722537823724315FRFrance
19202037715844052763204FRFrance
2020203679191001738102FRFrance
21202035782801694102FRFrance
22202034722723714173306FRFrance
23202033712841772391204FRFrance
24202032726506894611417FRFrance
25202031713031002506204FRFrance
2620203071385752695204FRFrance
272020297841101672102FRFrance
28202028772801515102FRFrance
2920202779861491823102FRFrance
.................................
15431991267176081130423912312042FRFrance
15441991257161691070021638281838FRFrance
15451991247161711007122271281739FRFrance
1546199123711947767116223211329FRFrance
1547199122715452995320951271737FRFrance
1548199121714903897520831261636FRFrance
15491991207190531274225364342345FRFrance
15501991197167391124622232291939FRFrance
15511991187213851388228888382551FRFrance
1552199117713462887718047241632FRFrance
15531991167148571006819646261834FRFrance
1554199115713975978118169251832FRFrance
1555199114712265768416846221430FRFrance
155619911379567604113093171123FRFrance
1557199112710864733114397191325FRFrance
15581991117155741118419964271935FRFrance
15591991107166431137221914292038FRFrance
1560199109713741878018702241533FRFrance
1561199108713289881317765231531FRFrance
1562199107712337807716597221529FRFrance
1563199106710877701314741191226FRFrance
1564199105710442654414340181125FRFrance
15651991047791345631126314820FRFrance
15661991037153871048420290271836FRFrance
15671991027162771104621508292038FRFrance
15681991017155651027120859271836FRFrance
15691990527193751329525455342345FRFrance
15701990517190801380724353342543FRFrance
1571199050711079666015498201228FRFrance
15721990497114302610205FRFrance
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1573 rows × 10 columns

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" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202103 7 8610 6083 11137 13 9 \n", + "1 202102 7 7859 5480 10238 12 8 \n", + "2 202101 7 10531 7755 13307 16 12 \n", + "3 202053 7 11978 8406 15550 18 13 \n", + "4 202052 7 12012 8285 15739 18 12 \n", + "5 202051 7 10564 7574 13554 16 11 \n", + "6 202050 7 7063 4744 9382 11 7 \n", + "7 202049 7 5026 3145 6907 8 5 \n", + "8 202048 7 6683 4312 9054 10 6 \n", + "9 202047 7 4999 2963 7035 8 5 \n", + "10 202046 7 3752 1963 5541 6 3 \n", + "11 202045 7 3696 2016 5376 6 3 \n", + "12 202044 7 4391 2375 6407 7 4 \n", + "13 202043 7 4376 2505 6247 7 4 \n", + "14 202042 7 4000 1979 6021 6 3 \n", + "15 202041 7 3961 2099 5823 6 3 \n", + "16 202040 7 2078 675 3481 3 1 \n", + "17 202039 7 1049 237 1861 2 1 \n", + "18 202038 7 2253 782 3724 3 1 \n", + "19 202037 7 1584 405 2763 2 0 \n", + "20 202036 7 919 100 1738 1 0 \n", + "21 202035 7 828 0 1694 1 0 \n", + "22 202034 7 2272 371 4173 3 0 \n", + "23 202033 7 1284 177 2391 2 0 \n", + "24 202032 7 2650 689 4611 4 1 \n", + "25 202031 7 1303 100 2506 2 0 \n", + "26 202030 7 1385 75 2695 2 0 \n", + "27 202029 7 841 10 1672 1 0 \n", + "28 202028 7 728 0 1515 1 0 \n", + "29 202027 7 986 149 1823 1 0 \n", + "... ... ... ... ... ... ... ... \n", + "1543 199126 7 17608 11304 23912 31 20 \n", + "1544 199125 7 16169 10700 21638 28 18 \n", + "1545 199124 7 16171 10071 22271 28 17 \n", + "1546 199123 7 11947 7671 16223 21 13 \n", + "1547 199122 7 15452 9953 20951 27 17 \n", + "1548 199121 7 14903 8975 20831 26 16 \n", + "1549 199120 7 19053 12742 25364 34 23 \n", + "1550 199119 7 16739 11246 22232 29 19 \n", + "1551 199118 7 21385 13882 28888 38 25 \n", + "1552 199117 7 13462 8877 18047 24 16 \n", + "1553 199116 7 14857 10068 19646 26 18 \n", + "1554 199115 7 13975 9781 18169 25 18 \n", + "1555 199114 7 12265 7684 16846 22 14 \n", + "1556 199113 7 9567 6041 13093 17 11 \n", + "1557 199112 7 10864 7331 14397 19 13 \n", + "1558 199111 7 15574 11184 19964 27 19 \n", + "1559 199110 7 16643 11372 21914 29 20 \n", + "1560 199109 7 13741 8780 18702 24 15 \n", + "1561 199108 7 13289 8813 17765 23 15 \n", + "1562 199107 7 12337 8077 16597 22 15 \n", + "1563 199106 7 10877 7013 14741 19 12 \n", + "1564 199105 7 10442 6544 14340 18 11 \n", + "1565 199104 7 7913 4563 11263 14 8 \n", + "1566 199103 7 15387 10484 20290 27 18 \n", + "1567 199102 7 16277 11046 21508 29 20 \n", + "1568 199101 7 15565 10271 20859 27 18 \n", + "1569 199052 7 19375 13295 25455 34 23 \n", + "1570 199051 7 19080 13807 24353 34 25 \n", + "1571 199050 7 11079 6660 15498 20 12 \n", + "1572 199049 7 1143 0 2610 2 0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 17 FR France \n", + "1 16 FR France \n", + "2 20 FR France \n", + "3 23 FR France \n", + "4 24 FR France \n", + "5 21 FR France \n", + "6 15 FR France \n", + "7 11 FR France \n", + "8 14 FR France \n", + "9 11 FR France \n", + "10 9 FR France \n", + "11 9 FR France \n", + "12 10 FR France \n", + "13 10 FR France \n", + "14 9 FR France \n", + "15 9 FR France \n", + "16 5 FR France \n", + "17 3 FR France \n", + "18 5 FR France \n", + "19 4 FR France \n", + "20 2 FR France \n", + "21 2 FR France \n", + "22 6 FR France \n", + "23 4 FR France \n", + "24 7 FR France \n", + "25 4 FR France \n", + "26 4 FR France \n", + "27 2 FR France \n", + "28 2 FR France \n", + "29 2 FR France \n", + "... ... ... ... \n", + "1543 42 FR France \n", + "1544 38 FR France \n", + "1545 39 FR France \n", + "1546 29 FR France \n", + "1547 37 FR France \n", + "1548 36 FR France \n", + "1549 45 FR France \n", + "1550 39 FR France \n", + "1551 51 FR France \n", + "1552 32 FR France \n", + "1553 34 FR France \n", + "1554 32 FR France \n", + "1555 30 FR France \n", + "1556 23 FR France \n", + "1557 25 FR France \n", + "1558 35 FR France \n", + "1559 38 FR France \n", + "1560 33 FR France \n", + "1561 31 FR France \n", + "1562 29 FR France \n", + "1563 26 FR France \n", + "1564 25 FR France \n", + "1565 20 FR France \n", + "1566 36 FR France \n", + "1567 38 FR France \n", + "1568 36 FR France \n", + "1569 45 FR France \n", + "1570 43 FR France \n", + "1571 28 FR France \n", + "1572 5 FR France \n", + "\n", + "[1573 rows x 10 columns]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = raw_data.dropna().copy()\n", + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "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": 13, + "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
.................................
2020-06-29/2020-07-0520202779861491823102FRFrance
2020-07-06/2020-07-12202028772801515102FRFrance
2020-07-13/2020-07-192020297841101672102FRFrance
2020-07-20/2020-07-2620203071385752695204FRFrance
2020-07-27/2020-08-02202031713031002506204FRFrance
2020-08-03/2020-08-09202032726506894611417FRFrance
2020-08-10/2020-08-16202033712841772391204FRFrance
2020-08-17/2020-08-23202034722723714173306FRFrance
2020-08-24/2020-08-30202035782801694102FRFrance
2020-08-31/2020-09-0620203679191001738102FRFrance
2020-09-07/2020-09-13202037715844052763204FRFrance
2020-09-14/2020-09-20202038722537823724315FRFrance
2020-09-21/2020-09-27202039710492371861213FRFrance
2020-09-28/2020-10-04202040720786753481315FRFrance
2020-10-05/2020-10-112020417396120995823639FRFrance
2020-10-12/2020-10-182020427400019796021639FRFrance
2020-10-19/2020-10-2520204374376250562477410FRFrance
2020-10-26/2020-11-0120204474391237564077410FRFrance
2020-11-02/2020-11-082020457369620165376639FRFrance
2020-11-09/2020-11-152020467375219635541639FRFrance
2020-11-16/2020-11-2220204774999296370358511FRFrance
2020-11-23/2020-11-29202048766834312905410614FRFrance
2020-11-30/2020-12-0620204975026314569078511FRFrance
2020-12-07/2020-12-13202050770634744938211715FRFrance
2020-12-14/2020-12-20202051710564757413554161121FRFrance
2020-12-21/2020-12-27202052712012828515739181224FRFrance
2020-12-28/2021-01-03202053711978840615550181323FRFrance
2021-01-04/2021-01-10202101710531775513307161220FRFrance
2021-01-11/2021-01-172021027785954801023812816FRFrance
2021-01-18/2021-01-242021037861060831113713917FRFrance
\n", + "

1573 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", + "2020-06-29/2020-07-05 202027 7 986 149 1823 1 \n", + "2020-07-06/2020-07-12 202028 7 728 0 1515 1 \n", + "2020-07-13/2020-07-19 202029 7 841 10 1672 1 \n", + "2020-07-20/2020-07-26 202030 7 1385 75 2695 2 \n", + "2020-07-27/2020-08-02 202031 7 1303 100 2506 2 \n", + "2020-08-03/2020-08-09 202032 7 2650 689 4611 4 \n", + "2020-08-10/2020-08-16 202033 7 1284 177 2391 2 \n", + "2020-08-17/2020-08-23 202034 7 2272 371 4173 3 \n", + "2020-08-24/2020-08-30 202035 7 828 0 1694 1 \n", + "2020-08-31/2020-09-06 202036 7 919 100 1738 1 \n", + "2020-09-07/2020-09-13 202037 7 1584 405 2763 2 \n", + "2020-09-14/2020-09-20 202038 7 2253 782 3724 3 \n", + "2020-09-21/2020-09-27 202039 7 1049 237 1861 2 \n", + "2020-09-28/2020-10-04 202040 7 2078 675 3481 3 \n", + "2020-10-05/2020-10-11 202041 7 3961 2099 5823 6 \n", + "2020-10-12/2020-10-18 202042 7 4000 1979 6021 6 \n", + "2020-10-19/2020-10-25 202043 7 4376 2505 6247 7 \n", + "2020-10-26/2020-11-01 202044 7 4391 2375 6407 7 \n", + "2020-11-02/2020-11-08 202045 7 3696 2016 5376 6 \n", + "2020-11-09/2020-11-15 202046 7 3752 1963 5541 6 \n", + "2020-11-16/2020-11-22 202047 7 4999 2963 7035 8 \n", + "2020-11-23/2020-11-29 202048 7 6683 4312 9054 10 \n", + "2020-11-30/2020-12-06 202049 7 5026 3145 6907 8 \n", + "2020-12-07/2020-12-13 202050 7 7063 4744 9382 11 \n", + "2020-12-14/2020-12-20 202051 7 10564 7574 13554 16 \n", + "2020-12-21/2020-12-27 202052 7 12012 8285 15739 18 \n", + "2020-12-28/2021-01-03 202053 7 11978 8406 15550 18 \n", + "2021-01-04/2021-01-10 202101 7 10531 7755 13307 16 \n", + "2021-01-11/2021-01-17 202102 7 7859 5480 10238 12 \n", + "2021-01-18/2021-01-24 202103 7 8610 6083 11137 13 \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", + "2020-06-29/2020-07-05 0 2 FR France \n", + "2020-07-06/2020-07-12 0 2 FR France \n", + "2020-07-13/2020-07-19 0 2 FR France \n", + "2020-07-20/2020-07-26 0 4 FR France \n", + "2020-07-27/2020-08-02 0 4 FR France \n", + "2020-08-03/2020-08-09 1 7 FR France \n", + "2020-08-10/2020-08-16 0 4 FR France \n", + "2020-08-17/2020-08-23 0 6 FR France \n", + "2020-08-24/2020-08-30 0 2 FR France \n", + "2020-08-31/2020-09-06 0 2 FR France \n", + "2020-09-07/2020-09-13 0 4 FR France \n", + "2020-09-14/2020-09-20 1 5 FR France \n", + "2020-09-21/2020-09-27 1 3 FR France \n", + "2020-09-28/2020-10-04 1 5 FR France \n", + "2020-10-05/2020-10-11 3 9 FR France \n", + "2020-10-12/2020-10-18 3 9 FR France \n", + "2020-10-19/2020-10-25 4 10 FR France \n", + "2020-10-26/2020-11-01 4 10 FR France \n", + "2020-11-02/2020-11-08 3 9 FR France \n", + "2020-11-09/2020-11-15 3 9 FR France \n", + "2020-11-16/2020-11-22 5 11 FR France \n", + "2020-11-23/2020-11-29 6 14 FR France \n", + "2020-11-30/2020-12-06 5 11 FR France \n", + "2020-12-07/2020-12-13 7 15 FR France \n", + "2020-12-14/2020-12-20 11 21 FR France \n", + "2020-12-21/2020-12-27 12 24 FR France \n", + "2020-12-28/2021-01-03 13 23 FR France \n", + "2021-01-04/2021-01-10 12 20 FR France \n", + "2021-01-11/2021-01-17 8 16 FR France \n", + "2021-01-18/2021-01-24 9 17 FR France \n", + "\n", + "[1573 rows x 10 columns]" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted_data = data.set_index('period').sort_index()\n", + "sorted_data" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "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": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "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": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "first_august_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": 15, + "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", + " 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": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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