{ "cells": [ { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import isoweek" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": [ "data_url = \"https://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
02023487820251151128912717FRFrance
1202347765864308886410713FRFrance
220234675223296874788511FRFrance
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10202338716632743052315FRFrance
11202337711222232021213FRFrance
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132023357961961826102FRFrance
142023347116892327204FRFrance
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162023327799611201487212222FRFrance
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20202328767004043935710614FRFrance
21202327772534599990711715FRFrance
2220232679192622312161141018FRFrance
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2520232371256361341899219929FRFrance
26202322712184812516243181224FRFrance
27202321711349759815100171123FRFrance
282023207900046151338514721FRFrance
292023197934460911259714919FRFrance
.................................
16921991267176081130423912312042FRFrance
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1695199123711947767116223211329FRFrance
1696199122715452995320951271737FRFrance
1697199121714903897520831261636FRFrance
16981991207190531274225364342345FRFrance
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17001991187213851388228888382551FRFrance
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17211990497114302610205FRFrance
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1722 rows × 10 columns

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" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202348 7 8202 5115 11289 12 7 \n", "1 202347 7 6586 4308 8864 10 7 \n", "2 202346 7 5223 2968 7478 8 5 \n", "3 202345 7 5007 2675 7339 8 4 \n", "4 202344 7 3688 1664 5712 6 3 \n", "5 202343 7 3891 1675 6107 6 3 \n", "6 202342 7 3968 1212 6724 6 2 \n", "7 202341 7 3356 1764 4948 5 3 \n", "8 202340 7 2845 1410 4280 4 2 \n", "9 202339 7 1739 629 2849 3 1 \n", "10 202338 7 1663 274 3052 3 1 \n", "11 202337 7 1122 223 2021 2 1 \n", "12 202336 7 726 10 1442 1 0 \n", "13 202335 7 961 96 1826 1 0 \n", "14 202334 7 1168 9 2327 2 0 \n", "15 202333 7 3308 1184 5432 5 2 \n", "16 202332 7 7996 1120 14872 12 2 \n", "17 202331 7 3318 1398 5238 5 2 \n", "18 202330 7 5821 3269 8373 9 5 \n", "19 202329 7 13558 8297 18819 20 12 \n", "20 202328 7 6700 4043 9357 10 6 \n", "21 202327 7 7253 4599 9907 11 7 \n", "22 202326 7 9192 6223 12161 14 10 \n", "23 202325 7 11498 8257 14739 17 12 \n", "24 202324 7 11115 7968 14262 17 12 \n", "25 202323 7 12563 6134 18992 19 9 \n", "26 202322 7 12184 8125 16243 18 12 \n", "27 202321 7 11349 7598 15100 17 11 \n", "28 202320 7 9000 4615 13385 14 7 \n", "29 202319 7 9344 6091 12597 14 9 \n", "... ... ... ... ... ... ... ... \n", "1692 199126 7 17608 11304 23912 31 20 \n", "1693 199125 7 16169 10700 21638 28 18 \n", "1694 199124 7 16171 10071 22271 28 17 \n", "1695 199123 7 11947 7671 16223 21 13 \n", "1696 199122 7 15452 9953 20951 27 17 \n", "1697 199121 7 14903 8975 20831 26 16 \n", "1698 199120 7 19053 12742 25364 34 23 \n", "1699 199119 7 16739 11246 22232 29 19 \n", "1700 199118 7 21385 13882 28888 38 25 \n", "1701 199117 7 13462 8877 18047 24 16 \n", "1702 199116 7 14857 10068 19646 26 18 \n", "1703 199115 7 13975 9781 18169 25 18 \n", "1704 199114 7 12265 7684 16846 22 14 \n", "1705 199113 7 9567 6041 13093 17 11 \n", "1706 199112 7 10864 7331 14397 19 13 \n", "1707 199111 7 15574 11184 19964 27 19 \n", "1708 199110 7 16643 11372 21914 29 20 \n", "1709 199109 7 13741 8780 18702 24 15 \n", "1710 199108 7 13289 8813 17765 23 15 \n", "1711 199107 7 12337 8077 16597 22 15 \n", "1712 199106 7 10877 7013 14741 19 12 \n", "1713 199105 7 10442 6544 14340 18 11 \n", "1714 199104 7 7913 4563 11263 14 8 \n", "1715 199103 7 15387 10484 20290 27 18 \n", "1716 199102 7 16277 11046 21508 29 20 \n", "1717 199101 7 15565 10271 20859 27 18 \n", "1718 199052 7 19375 13295 25455 34 23 \n", "1719 199051 7 19080 13807 24353 34 25 \n", "1720 199050 7 11079 6660 15498 20 12 \n", "1721 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 17 FR France \n", "1 13 FR France \n", "2 11 FR France \n", "3 12 FR France \n", "4 9 FR France \n", "5 9 FR France \n", "6 10 FR France \n", "7 7 FR France \n", "8 6 FR France \n", "9 5 FR France \n", "10 5 FR France \n", "11 3 FR France \n", "12 2 FR France \n", "13 2 FR France \n", "14 4 FR France \n", "15 8 FR France \n", "16 22 FR France \n", "17 8 FR France \n", "18 13 FR France \n", "19 28 FR France \n", "20 14 FR France \n", "21 15 FR France \n", "22 18 FR France \n", "23 22 FR France \n", "24 22 FR France \n", "25 29 FR France \n", "26 24 FR France \n", "27 23 FR France \n", "28 21 FR France \n", "29 19 FR France \n", "... ... ... ... \n", "1692 42 FR France \n", "1693 38 FR France \n", "1694 39 FR France \n", "1695 29 FR France \n", "1696 37 FR France \n", "1697 36 FR France \n", "1698 45 FR France \n", "1699 39 FR France \n", "1700 51 FR France \n", "1701 32 FR France \n", "1702 34 FR France \n", "1703 32 FR France \n", "1704 30 FR France \n", "1705 23 FR France \n", "1706 25 FR France \n", "1707 35 FR France \n", "1708 38 FR France \n", "1709 33 FR France \n", "1710 31 FR France \n", "1711 29 FR France \n", "1712 26 FR France \n", "1713 25 FR France \n", "1714 20 FR France \n", "1715 36 FR France \n", "1716 38 FR France \n", "1717 36 FR France \n", "1718 45 FR France \n", "1719 43 FR France \n", "1720 28 FR France \n", "1721 5 FR France \n", "\n", "[1722 rows x 10 columns]" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = pd.read_csv(data_url, encoding = 'iso-8859-1', skiprows=1)\n", "raw_data" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
02023487820251151128912717FRFrance
1202347765864308886410713FRFrance
220234675223296874788511FRFrance
320234575007267573398412FRFrance
42023447368816645712639FRFrance
52023437389116756107639FRFrance
620234273968121267246210FRFrance
72023417335617644948537FRFrance
82023407284514104280426FRFrance
9202339717396292849315FRFrance
10202338716632743052315FRFrance
11202337711222232021213FRFrance
122023367726101442102FRFrance
132023357961961826102FRFrance
142023347116892327204FRFrance
152023337330811845432528FRFrance
162023327799611201487212222FRFrance
172023317331813985238528FRFrance
1820233075821326983739513FRFrance
19202329713558829718819201228FRFrance
20202328767004043935710614FRFrance
21202327772534599990711715FRFrance
2220232679192622312161141018FRFrance
23202325711498825714739171222FRFrance
24202324711115796814262171222FRFrance
2520232371256361341899219929FRFrance
26202322712184812516243181224FRFrance
27202321711349759815100171123FRFrance
282023207900046151338514721FRFrance
292023197934460911259714919FRFrance
.................................
16921991267176081130423912312042FRFrance
16931991257161691070021638281838FRFrance
16941991247161711007122271281739FRFrance
1695199123711947767116223211329FRFrance
1696199122715452995320951271737FRFrance
1697199121714903897520831261636FRFrance
16981991207190531274225364342345FRFrance
16991991197167391124622232291939FRFrance
17001991187213851388228888382551FRFrance
1701199117713462887718047241632FRFrance
17021991167148571006819646261834FRFrance
1703199115713975978118169251832FRFrance
1704199114712265768416846221430FRFrance
170519911379567604113093171123FRFrance
1706199112710864733114397191325FRFrance
17071991117155741118419964271935FRFrance
17081991107166431137221914292038FRFrance
1709199109713741878018702241533FRFrance
1710199108713289881317765231531FRFrance
1711199107712337807716597221529FRFrance
1712199106710877701314741191226FRFrance
1713199105710442654414340181125FRFrance
17141991047791345631126314820FRFrance
17151991037153871048420290271836FRFrance
17161991027162771104621508292038FRFrance
17171991017155651027120859271836FRFrance
17181990527193751329525455342345FRFrance
17191990517190801380724353342543FRFrance
1720199050711079666015498201228FRFrance
17211990497114302610205FRFrance
\n", "

1722 rows × 10 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202348 7 8202 5115 11289 12 7 \n", "1 202347 7 6586 4308 8864 10 7 \n", "2 202346 7 5223 2968 7478 8 5 \n", "3 202345 7 5007 2675 7339 8 4 \n", "4 202344 7 3688 1664 5712 6 3 \n", "5 202343 7 3891 1675 6107 6 3 \n", "6 202342 7 3968 1212 6724 6 2 \n", "7 202341 7 3356 1764 4948 5 3 \n", "8 202340 7 2845 1410 4280 4 2 \n", "9 202339 7 1739 629 2849 3 1 \n", "10 202338 7 1663 274 3052 3 1 \n", "11 202337 7 1122 223 2021 2 1 \n", "12 202336 7 726 10 1442 1 0 \n", "13 202335 7 961 96 1826 1 0 \n", "14 202334 7 1168 9 2327 2 0 \n", "15 202333 7 3308 1184 5432 5 2 \n", "16 202332 7 7996 1120 14872 12 2 \n", "17 202331 7 3318 1398 5238 5 2 \n", "18 202330 7 5821 3269 8373 9 5 \n", "19 202329 7 13558 8297 18819 20 12 \n", "20 202328 7 6700 4043 9357 10 6 \n", "21 202327 7 7253 4599 9907 11 7 \n", "22 202326 7 9192 6223 12161 14 10 \n", "23 202325 7 11498 8257 14739 17 12 \n", "24 202324 7 11115 7968 14262 17 12 \n", "25 202323 7 12563 6134 18992 19 9 \n", "26 202322 7 12184 8125 16243 18 12 \n", "27 202321 7 11349 7598 15100 17 11 \n", "28 202320 7 9000 4615 13385 14 7 \n", "29 202319 7 9344 6091 12597 14 9 \n", "... ... ... ... ... ... ... ... \n", "1692 199126 7 17608 11304 23912 31 20 \n", "1693 199125 7 16169 10700 21638 28 18 \n", "1694 199124 7 16171 10071 22271 28 17 \n", "1695 199123 7 11947 7671 16223 21 13 \n", "1696 199122 7 15452 9953 20951 27 17 \n", "1697 199121 7 14903 8975 20831 26 16 \n", "1698 199120 7 19053 12742 25364 34 23 \n", "1699 199119 7 16739 11246 22232 29 19 \n", "1700 199118 7 21385 13882 28888 38 25 \n", "1701 199117 7 13462 8877 18047 24 16 \n", "1702 199116 7 14857 10068 19646 26 18 \n", "1703 199115 7 13975 9781 18169 25 18 \n", "1704 199114 7 12265 7684 16846 22 14 \n", "1705 199113 7 9567 6041 13093 17 11 \n", "1706 199112 7 10864 7331 14397 19 13 \n", "1707 199111 7 15574 11184 19964 27 19 \n", "1708 199110 7 16643 11372 21914 29 20 \n", "1709 199109 7 13741 8780 18702 24 15 \n", "1710 199108 7 13289 8813 17765 23 15 \n", "1711 199107 7 12337 8077 16597 22 15 \n", "1712 199106 7 10877 7013 14741 19 12 \n", "1713 199105 7 10442 6544 14340 18 11 \n", "1714 199104 7 7913 4563 11263 14 8 \n", "1715 199103 7 15387 10484 20290 27 18 \n", "1716 199102 7 16277 11046 21508 29 20 \n", "1717 199101 7 15565 10271 20859 27 18 \n", "1718 199052 7 19375 13295 25455 34 23 \n", "1719 199051 7 19080 13807 24353 34 25 \n", "1720 199050 7 11079 6660 15498 20 12 \n", "1721 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 17 FR France \n", "1 13 FR France \n", "2 11 FR France \n", "3 12 FR France \n", "4 9 FR France \n", "5 9 FR France \n", "6 10 FR France \n", "7 7 FR France \n", "8 6 FR France \n", "9 5 FR France \n", "10 5 FR France \n", "11 3 FR France \n", "12 2 FR France \n", "13 2 FR France \n", "14 4 FR France \n", "15 8 FR France \n", "16 22 FR France \n", "17 8 FR France \n", "18 13 FR France \n", "19 28 FR France \n", "20 14 FR France \n", "21 15 FR France \n", "22 18 FR France \n", "23 22 FR France \n", "24 22 FR France \n", "25 29 FR France \n", "26 24 FR France \n", "27 23 FR France \n", "28 21 FR France \n", "29 19 FR France \n", "... ... ... ... \n", "1692 42 FR France \n", "1693 38 FR France \n", "1694 39 FR France \n", "1695 29 FR France \n", "1696 37 FR France \n", "1697 36 FR France \n", "1698 45 FR France \n", "1699 39 FR France \n", "1700 51 FR France \n", "1701 32 FR France \n", "1702 34 FR France \n", "1703 32 FR France \n", "1704 30 FR France \n", "1705 23 FR France \n", "1706 25 FR France \n", "1707 35 FR France \n", "1708 38 FR France \n", "1709 33 FR France \n", "1710 31 FR France \n", "1711 29 FR France \n", "1712 26 FR France \n", "1713 25 FR France \n", "1714 20 FR France \n", "1715 36 FR France \n", "1716 38 FR France \n", "1717 36 FR France \n", "1718 45 FR France \n", "1719 43 FR France \n", "1720 28 FR France \n", "1721 5 FR France \n", "\n", "[1722 rows x 10 columns]" ] }, "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = raw_data.dropna().copy()\n", "data" ] }, { "cell_type": "code", "execution_count": 49, "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": 50, "metadata": {}, "outputs": [], "source": [ " sorted_data = data.set_index('period').sort_index()" ] }, { "cell_type": "code", "execution_count": 51, "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": 52, "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
.................................
2023-05-08/2023-05-142023197934460911259714919FRFrance
2023-05-15/2023-05-212023207900046151338514721FRFrance
2023-05-22/2023-05-28202321711349759815100171123FRFrance
2023-05-29/2023-06-04202322712184812516243181224FRFrance
2023-06-05/2023-06-1120232371256361341899219929FRFrance
2023-06-12/2023-06-18202324711115796814262171222FRFrance
2023-06-19/2023-06-25202325711498825714739171222FRFrance
2023-06-26/2023-07-0220232679192622312161141018FRFrance
2023-07-03/2023-07-09202327772534599990711715FRFrance
2023-07-10/2023-07-16202328767004043935710614FRFrance
2023-07-17/2023-07-23202329713558829718819201228FRFrance
2023-07-24/2023-07-3020233075821326983739513FRFrance
2023-07-31/2023-08-062023317331813985238528FRFrance
2023-08-07/2023-08-132023327799611201487212222FRFrance
2023-08-14/2023-08-202023337330811845432528FRFrance
2023-08-21/2023-08-272023347116892327204FRFrance
2023-08-28/2023-09-032023357961961826102FRFrance
2023-09-04/2023-09-102023367726101442102FRFrance
2023-09-11/2023-09-17202337711222232021213FRFrance
2023-09-18/2023-09-24202338716632743052315FRFrance
2023-09-25/2023-10-01202339717396292849315FRFrance
2023-10-02/2023-10-082023407284514104280426FRFrance
2023-10-09/2023-10-152023417335617644948537FRFrance
2023-10-16/2023-10-2220234273968121267246210FRFrance
2023-10-23/2023-10-292023437389116756107639FRFrance
2023-10-30/2023-11-052023447368816645712639FRFrance
2023-11-06/2023-11-1220234575007267573398412FRFrance
2023-11-13/2023-11-1920234675223296874788511FRFrance
2023-11-20/2023-11-26202347765864308886410713FRFrance
2023-11-27/2023-12-032023487820251151128912717FRFrance
\n", "

1722 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", "2023-05-08/2023-05-14 202319 7 9344 6091 12597 14 \n", "2023-05-15/2023-05-21 202320 7 9000 4615 13385 14 \n", "2023-05-22/2023-05-28 202321 7 11349 7598 15100 17 \n", "2023-05-29/2023-06-04 202322 7 12184 8125 16243 18 \n", "2023-06-05/2023-06-11 202323 7 12563 6134 18992 19 \n", "2023-06-12/2023-06-18 202324 7 11115 7968 14262 17 \n", "2023-06-19/2023-06-25 202325 7 11498 8257 14739 17 \n", "2023-06-26/2023-07-02 202326 7 9192 6223 12161 14 \n", "2023-07-03/2023-07-09 202327 7 7253 4599 9907 11 \n", "2023-07-10/2023-07-16 202328 7 6700 4043 9357 10 \n", "2023-07-17/2023-07-23 202329 7 13558 8297 18819 20 \n", "2023-07-24/2023-07-30 202330 7 5821 3269 8373 9 \n", "2023-07-31/2023-08-06 202331 7 3318 1398 5238 5 \n", "2023-08-07/2023-08-13 202332 7 7996 1120 14872 12 \n", "2023-08-14/2023-08-20 202333 7 3308 1184 5432 5 \n", "2023-08-21/2023-08-27 202334 7 1168 9 2327 2 \n", "2023-08-28/2023-09-03 202335 7 961 96 1826 1 \n", "2023-09-04/2023-09-10 202336 7 726 10 1442 1 \n", "2023-09-11/2023-09-17 202337 7 1122 223 2021 2 \n", "2023-09-18/2023-09-24 202338 7 1663 274 3052 3 \n", "2023-09-25/2023-10-01 202339 7 1739 629 2849 3 \n", "2023-10-02/2023-10-08 202340 7 2845 1410 4280 4 \n", "2023-10-09/2023-10-15 202341 7 3356 1764 4948 5 \n", "2023-10-16/2023-10-22 202342 7 3968 1212 6724 6 \n", "2023-10-23/2023-10-29 202343 7 3891 1675 6107 6 \n", "2023-10-30/2023-11-05 202344 7 3688 1664 5712 6 \n", "2023-11-06/2023-11-12 202345 7 5007 2675 7339 8 \n", "2023-11-13/2023-11-19 202346 7 5223 2968 7478 8 \n", "2023-11-20/2023-11-26 202347 7 6586 4308 8864 10 \n", "2023-11-27/2023-12-03 202348 7 8202 5115 11289 12 \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", "2023-05-08/2023-05-14 9 19 FR France \n", "2023-05-15/2023-05-21 7 21 FR France \n", "2023-05-22/2023-05-28 11 23 FR France \n", "2023-05-29/2023-06-04 12 24 FR France \n", "2023-06-05/2023-06-11 9 29 FR France \n", "2023-06-12/2023-06-18 12 22 FR France \n", "2023-06-19/2023-06-25 12 22 FR France \n", "2023-06-26/2023-07-02 10 18 FR France \n", "2023-07-03/2023-07-09 7 15 FR France \n", "2023-07-10/2023-07-16 6 14 FR France \n", "2023-07-17/2023-07-23 12 28 FR France \n", "2023-07-24/2023-07-30 5 13 FR France \n", "2023-07-31/2023-08-06 2 8 FR France \n", "2023-08-07/2023-08-13 2 22 FR France \n", "2023-08-14/2023-08-20 2 8 FR France \n", "2023-08-21/2023-08-27 0 4 FR France \n", "2023-08-28/2023-09-03 0 2 FR France \n", "2023-09-04/2023-09-10 0 2 FR France \n", "2023-09-11/2023-09-17 1 3 FR France \n", "2023-09-18/2023-09-24 1 5 FR France \n", "2023-09-25/2023-10-01 1 5 FR France \n", "2023-10-02/2023-10-08 2 6 FR France \n", "2023-10-09/2023-10-15 3 7 FR France \n", "2023-10-16/2023-10-22 2 10 FR France \n", "2023-10-23/2023-10-29 3 9 FR France \n", "2023-10-30/2023-11-05 3 9 FR France \n", "2023-11-06/2023-11-12 4 12 FR France \n", "2023-11-13/2023-11-19 5 11 FR France \n", "2023-11-20/2023-11-26 7 13 FR France \n", "2023-11-27/2023-12-03 7 17 FR France \n", "\n", "[1722 rows x 10 columns]" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sorted_data" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 53, "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": [ "pd.to_numeric(sorted_data['inc']).plot()" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 54, "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": [ "pd.to_numeric(sorted_data['inc'][-200:]).plot()" ] }, { "cell_type": "code", "execution_count": 59, "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": 60, "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 = pd.to_numeric(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": 61, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 61, "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": 62, "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": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.sort_values()" ] }, { "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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mePMY+sj0ADgNOL1j+Z9Z/I99ZHrQdc+GXcAyP8S7gReB/2Hxf8kPsHjc6mHgmeb6zI71P8ziu9lP07xz3YxPAnua+/6MN79EdUrzA3mWxXe+L+jY5pea8WeB93eMX9Cs+2yz7ckDfPw/yeKvcP8KPN5crh6xHvwI8FjTgz3A7zbjI9ODJf2Y4s1AH5keNHM90VyeBD48aj3o9uI3RSWpiPVyDF2StAIDXZKKMNAlqQgDXZKKMNAlqQgDXZKKMNAlqQgDXZKK+D+/pikGg4qXaQAAAABJRU5ErkJggg==\n", 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