diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb index 0bbbe371b01e359e381e43239412d77bf53fb1fb..4326776c725bf7e2d1b1a698059854bef951c91d 100644 --- a/module3/exo2/exercice.ipynb +++ b/module3/exo2/exercice.ipynb @@ -1,5 +1,3283 @@ { - "cells": [], + "cells": [ + { + "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 numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020220679777691612638151119FRFrance
1202205710851779713905161121FRFrance
220220479547672112373141018FRFrance
32022037139721068017264211626FRFrance
42022027849560261096413917FRFrance
52022017137931059716989211626FRFrance
6202152713239961116867201525FRFrance
7202151713326962917023201426FRFrance
82021507141281031217944211527FRFrance
92021497136741036916979211626FRFrance
10202148711549850314595171222FRFrance
11202147711419837614462171222FRFrance
122021467821657241070812816FRFrance
1320214578965646811462141018FRFrance
142021447873656361183613818FRFrance
152021437814551641112612717FRFrance
162021427944360371284914919FRFrance
172021417402122395803639FRFrance
1820214074441245464287410FRFrance
192021397229110563526315FRFrance
2020213874325226763837410FRFrance
21202137719647543174315FRFrance
222021367344117305152528FRFrance
232021357256211074017426FRFrance
24202134714293782480204FRFrance
252021337382918305828639FRFrance
262021327410818956321639FRFrance
2720213174793230172857311FRFrance
282021307719041911018911616FRFrance
29202129768004109949110614FRFrance
.................................
15981991267176081130423912312042FRFrance
15991991257161691070021638281838FRFrance
16001991247161711007122271281739FRFrance
1601199123711947767116223211329FRFrance
1602199122715452995320951271737FRFrance
1603199121714903897520831261636FRFrance
16041991207190531274225364342345FRFrance
16051991197167391124622232291939FRFrance
16061991187213851388228888382551FRFrance
1607199117713462887718047241632FRFrance
16081991167148571006819646261834FRFrance
1609199115713975978118169251832FRFrance
1610199114712265768416846221430FRFrance
161119911379567604113093171123FRFrance
1612199112710864733114397191325FRFrance
16131991117155741118419964271935FRFrance
16141991107166431137221914292038FRFrance
1615199109713741878018702241533FRFrance
1616199108713289881317765231531FRFrance
1617199107712337807716597221529FRFrance
1618199106710877701314741191226FRFrance
1619199105710442654414340181125FRFrance
16201991047791345631126314820FRFrance
16211991037153871048420290271836FRFrance
16221991027162771104621508292038FRFrance
16231991017155651027120859271836FRFrance
16241990527193751329525455342345FRFrance
16251990517190801380724353342543FRFrance
1626199050711079666015498201228FRFrance
16271990497114302610205FRFrance
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1628 rows × 10 columns

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202136 7 3441 1730 5152 5 2 \n", + "23 202135 7 2562 1107 4017 4 2 \n", + "24 202134 7 1429 378 2480 2 0 \n", + "25 202133 7 3829 1830 5828 6 3 \n", + "26 202132 7 4108 1895 6321 6 3 \n", + "27 202131 7 4793 2301 7285 7 3 \n", + "28 202130 7 7190 4191 10189 11 6 \n", + "29 202129 7 6800 4109 9491 10 6 \n", + "... ... ... ... ... ... ... ... \n", + "1598 199126 7 17608 11304 23912 31 20 \n", + "1599 199125 7 16169 10700 21638 28 18 \n", + "1600 199124 7 16171 10071 22271 28 17 \n", + "1601 199123 7 11947 7671 16223 21 13 \n", + "1602 199122 7 15452 9953 20951 27 17 \n", + "1603 199121 7 14903 8975 20831 26 16 \n", + "1604 199120 7 19053 12742 25364 34 23 \n", + "1605 199119 7 16739 11246 22232 29 19 \n", + "1606 199118 7 21385 13882 28888 38 25 \n", + "1607 199117 7 13462 8877 18047 24 16 \n", + "1608 199116 7 14857 10068 19646 26 18 \n", + "1609 199115 7 13975 9781 18169 25 18 \n", + "1610 199114 7 12265 7684 16846 22 14 \n", + "1611 199113 7 9567 6041 13093 17 11 \n", + "1612 199112 7 10864 7331 14397 19 13 \n", + "1613 199111 7 15574 11184 19964 27 19 \n", + "1614 199110 7 16643 11372 21914 29 20 \n", + "1615 199109 7 13741 8780 18702 24 15 \n", + "1616 199108 7 13289 8813 17765 23 15 \n", + "1617 199107 7 12337 8077 16597 22 15 \n", + "1618 199106 7 10877 7013 14741 19 12 \n", + "1619 199105 7 10442 6544 14340 18 11 \n", + "1620 199104 7 7913 4563 11263 14 8 \n", + "1621 199103 7 15387 10484 20290 27 18 \n", + "1622 199102 7 16277 11046 21508 29 20 \n", + "1623 199101 7 15565 10271 20859 27 18 \n", + "1624 199052 7 19375 13295 25455 34 23 \n", + "1625 199051 7 19080 13807 24353 34 25 \n", + "1626 199050 7 11079 6660 15498 20 12 \n", + "1627 199049 7 1143 0 2610 2 0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 19 FR France \n", + "1 21 FR France \n", + "2 18 FR France \n", + "3 26 FR France \n", + "4 17 FR France \n", + "5 26 FR France \n", + "6 25 FR France \n", + "7 26 FR France \n", + "8 27 FR France \n", + "9 26 FR France \n", + "10 22 FR France \n", + "11 22 FR France \n", + "12 16 FR France \n", + "13 18 FR France \n", + "14 18 FR France \n", + "15 17 FR France \n", + "16 19 FR France \n", + "17 9 FR France \n", + "18 10 FR France \n", + "19 5 FR France \n", + "20 10 FR France \n", + "21 5 FR France \n", + "22 8 FR France \n", + "23 6 FR France \n", + "24 4 FR France \n", + "25 9 FR France \n", + "26 9 FR France \n", + "27 11 FR France \n", + "28 16 FR France \n", + "29 14 FR France \n", + "... ... ... ... \n", + "1598 42 FR France \n", + "1599 38 FR France \n", + "1600 39 FR France \n", + "1601 29 FR France \n", + "1602 37 FR France \n", + "1603 36 FR France \n", + "1604 45 FR France \n", + "1605 39 FR France \n", + "1606 51 FR France \n", + "1607 32 FR France \n", + "1608 34 FR France \n", + "1609 32 FR France \n", + "1610 30 FR France \n", + "1611 23 FR France \n", + "1612 25 FR France \n", + "1613 35 FR France \n", + "1614 38 FR France \n", + "1615 33 FR France \n", + "1616 31 FR France \n", + "1617 29 FR France \n", + "1618 26 FR France \n", + "1619 25 FR France \n", + "1620 20 FR France \n", + "1621 36 FR France \n", + "1622 38 FR France \n", + "1623 36 FR France \n", + "1624 45 FR France \n", + "1625 43 FR France \n", + "1626 28 FR France \n", + "1627 5 FR France \n", + "\n", + "[1628 rows x 10 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + " data = raw_data.dropna().copy()\n", + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "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": 7, + "metadata": {}, + "outputs": [ + { + "data": { + 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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
.................................
2021-07-19/2021-07-25202129768004109949110614FRFrance
2021-07-26/2021-08-012021307719041911018911616FRFrance
2021-08-02/2021-08-0820213174793230172857311FRFrance
2021-08-09/2021-08-152021327410818956321639FRFrance
2021-08-16/2021-08-222021337382918305828639FRFrance
2021-08-23/2021-08-29202134714293782480204FRFrance
2021-08-30/2021-09-052021357256211074017426FRFrance
2021-09-06/2021-09-122021367344117305152528FRFrance
2021-09-13/2021-09-19202137719647543174315FRFrance
2021-09-20/2021-09-2620213874325226763837410FRFrance
2021-09-27/2021-10-032021397229110563526315FRFrance
2021-10-04/2021-10-1020214074441245464287410FRFrance
2021-10-11/2021-10-172021417402122395803639FRFrance
2021-10-18/2021-10-242021427944360371284914919FRFrance
2021-10-25/2021-10-312021437814551641112612717FRFrance
2021-11-01/2021-11-072021447873656361183613818FRFrance
2021-11-08/2021-11-1420214578965646811462141018FRFrance
2021-11-15/2021-11-212021467821657241070812816FRFrance
2021-11-22/2021-11-28202147711419837614462171222FRFrance
2021-11-29/2021-12-05202148711549850314595171222FRFrance
2021-12-06/2021-12-122021497136741036916979211626FRFrance
2021-12-13/2021-12-192021507141281031217944211527FRFrance
2021-12-20/2021-12-26202151713326962917023201426FRFrance
2021-12-27/2022-01-02202152713239961116867201525FRFrance
2022-01-03/2022-01-092022017137931059716989211626FRFrance
2022-01-10/2022-01-162022027849560261096413917FRFrance
2022-01-17/2022-01-232022037139721068017264211626FRFrance
2022-01-24/2022-01-3020220479547672112373141018FRFrance
2022-01-31/2022-02-06202205710851779713905161121FRFrance
2022-02-07/2022-02-1320220679777691612638151119FRFrance
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1628 rows × 10 columns

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"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", + "2021-07-19/2021-07-25 202129 7 6800 4109 9491 10 \n", + "2021-07-26/2021-08-01 202130 7 7190 4191 10189 11 \n", + "2021-08-02/2021-08-08 202131 7 4793 2301 7285 7 \n", + "2021-08-09/2021-08-15 202132 7 4108 1895 6321 6 \n", + "2021-08-16/2021-08-22 202133 7 3829 1830 5828 6 \n", + "2021-08-23/2021-08-29 202134 7 1429 378 2480 2 \n", + "2021-08-30/2021-09-05 202135 7 2562 1107 4017 4 \n", + "2021-09-06/2021-09-12 202136 7 3441 1730 5152 5 \n", + "2021-09-13/2021-09-19 202137 7 1964 754 3174 3 \n", + "2021-09-20/2021-09-26 202138 7 4325 2267 6383 7 \n", + "2021-09-27/2021-10-03 202139 7 2291 1056 3526 3 \n", + "2021-10-04/2021-10-10 202140 7 4441 2454 6428 7 \n", + "2021-10-11/2021-10-17 202141 7 4021 2239 5803 6 \n", + "2021-10-18/2021-10-24 202142 7 9443 6037 12849 14 \n", + "2021-10-25/2021-10-31 202143 7 8145 5164 11126 12 \n", + "2021-11-01/2021-11-07 202144 7 8736 5636 11836 13 \n", + "2021-11-08/2021-11-14 202145 7 8965 6468 11462 14 \n", + "2021-11-15/2021-11-21 202146 7 8216 5724 10708 12 \n", + "2021-11-22/2021-11-28 202147 7 11419 8376 14462 17 \n", + "2021-11-29/2021-12-05 202148 7 11549 8503 14595 17 \n", + "2021-12-06/2021-12-12 202149 7 13674 10369 16979 21 \n", + "2021-12-13/2021-12-19 202150 7 14128 10312 17944 21 \n", + "2021-12-20/2021-12-26 202151 7 13326 9629 17023 20 \n", + "2021-12-27/2022-01-02 202152 7 13239 9611 16867 20 \n", + "2022-01-03/2022-01-09 202201 7 13793 10597 16989 21 \n", + "2022-01-10/2022-01-16 202202 7 8495 6026 10964 13 \n", + "2022-01-17/2022-01-23 202203 7 13972 10680 17264 21 \n", + "2022-01-24/2022-01-30 202204 7 9547 6721 12373 14 \n", + "2022-01-31/2022-02-06 202205 7 10851 7797 13905 16 \n", + "2022-02-07/2022-02-13 202206 7 9777 6916 12638 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", + "2021-07-19/2021-07-25 6 14 FR France \n", + "2021-07-26/2021-08-01 6 16 FR France \n", + "2021-08-02/2021-08-08 3 11 FR France \n", + "2021-08-09/2021-08-15 3 9 FR France \n", + "2021-08-16/2021-08-22 3 9 FR France \n", + "2021-08-23/2021-08-29 0 4 FR France \n", + "2021-08-30/2021-09-05 2 6 FR France \n", + "2021-09-06/2021-09-12 2 8 FR France \n", + "2021-09-13/2021-09-19 1 5 FR France \n", + "2021-09-20/2021-09-26 4 10 FR France \n", + "2021-09-27/2021-10-03 1 5 FR France \n", + "2021-10-04/2021-10-10 4 10 FR France \n", + "2021-10-11/2021-10-17 3 9 FR France \n", + "2021-10-18/2021-10-24 9 19 FR France \n", + "2021-10-25/2021-10-31 7 17 FR France \n", + "2021-11-01/2021-11-07 8 18 FR France \n", + "2021-11-08/2021-11-14 10 18 FR France \n", + "2021-11-15/2021-11-21 8 16 FR France \n", + "2021-11-22/2021-11-28 12 22 FR France \n", + "2021-11-29/2021-12-05 12 22 FR France \n", + "2021-12-06/2021-12-12 16 26 FR France \n", + "2021-12-13/2021-12-19 15 27 FR France \n", + "2021-12-20/2021-12-26 14 26 FR France \n", + "2021-12-27/2022-01-02 15 25 FR France \n", + "2022-01-03/2022-01-09 16 26 FR France \n", + "2022-01-10/2022-01-16 9 17 FR France \n", + "2022-01-17/2022-01-23 16 26 FR France \n", + "2022-01-24/2022-01-30 10 18 FR France \n", + "2022-01-31/2022-02-06 11 21 FR France \n", + "2022-02-07/2022-02-13 11 19 FR France \n", + "\n", + "[1628 rows x 10 columns]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + " sorted_data = data.set_index('period').sort_index()\n", + "sorted_data" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "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": 9, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "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": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[Period('1991-08-26/1991-09-01', 'W-SUN'),\n", + " Period('1992-08-31/1992-09-06', 'W-SUN'),\n", + " Period('1993-08-30/1993-09-05', 'W-SUN'),\n", + " Period('1994-08-29/1994-09-04', 'W-SUN'),\n", + " Period('1995-08-28/1995-09-03', 'W-SUN'),\n", + " Period('1996-08-26/1996-09-01', 'W-SUN'),\n", + " Period('1997-09-01/1997-09-07', 'W-SUN'),\n", + " Period('1998-08-31/1998-09-06', 'W-SUN'),\n", + " Period('1999-08-30/1999-09-05', 'W-SUN'),\n", + " Period('2000-08-28/2000-09-03', 'W-SUN'),\n", + " Period('2001-08-27/2001-09-02', 'W-SUN'),\n", + " Period('2002-08-26/2002-09-01', 'W-SUN'),\n", + " Period('2003-09-01/2003-09-07', 'W-SUN'),\n", + " Period('2004-08-30/2004-09-05', 'W-SUN'),\n", + " Period('2005-08-29/2005-09-04', 'W-SUN'),\n", + " Period('2006-08-28/2006-09-03', 'W-SUN'),\n", + " Period('2007-08-27/2007-09-02', 'W-SUN'),\n", + " Period('2008-09-01/2008-09-07', 'W-SUN'),\n", + " Period('2009-08-31/2009-09-06', 'W-SUN'),\n", + " Period('2010-08-30/2010-09-05', 'W-SUN'),\n", + " Period('2011-08-29/2011-09-04', 'W-SUN'),\n", + " Period('2012-08-27/2012-09-02', 'W-SUN'),\n", + " Period('2013-08-26/2013-09-01', 'W-SUN'),\n", + " Period('2014-09-01/2014-09-07', 'W-SUN'),\n", + " Period('2015-08-31/2015-09-06', 'W-SUN'),\n", + " Period('2016-08-29/2016-09-04', 'W-SUN'),\n", + " Period('2017-08-28/2017-09-03', 'W-SUN'),\n", + " Period('2018-08-27/2018-09-02', 'W-SUN'),\n", + " Period('2019-08-26/2019-09-01', 'W-SUN'),\n", + " Period('2020-08-31/2020-09-06', 'W-SUN'),\n", + " Period('2021-08-30/2021-09-05', 'W-SUN')]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "first_sept_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W') for y in range(1991,sorted_data.index[-1].year)]\n", + "first_sept_week" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + " year = []\n", + "yearly_incidence = []\n", + "for week1, week2 in zip(first_sept_week[:-1],first_sept_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": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
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