{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import isoweek" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Les données de l'incidence de la varicelle sont disponibles du 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 1984 et se termine avec une semaine récente." ] }, { "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
0202106713642991417370211527FRFrance
1202105712210898815432181323FRFrance
2202104712026882615226181323FRFrance
32021037891363751145113917FRFrance
42021027779554301016012816FRFrance
5202101710525775013300161220FRFrance
6202053711978840615550181323FRFrance
7202052712012828515739181224FRFrance
8202051710564757413554161121FRFrance
9202050770634744938211715FRFrance
1020204975026314569078511FRFrance
11202048766834312905410614FRFrance
1220204774999296370358511FRFrance
132020467375219635541639FRFrance
142020457369620165376639FRFrance
1520204474391237564077410FRFrance
1620204374376250562477410FRFrance
172020427400019796021639FRFrance
182020417396120995823639FRFrance
19202040720786753481315FRFrance
20202039710492371861213FRFrance
21202038722537823724315FRFrance
22202037715844052763204FRFrance
2320203679191001738102FRFrance
24202035782801694102FRFrance
25202034722723714173306FRFrance
26202033712841772391204FRFrance
27202032726506894611417FRFrance
28202031713031002506204FRFrance
2920203071385752695204FRFrance
.................................
15461991267176081130423912312042FRFrance
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1550199122715452995320951271737FRFrance
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15541991187213851388228888382551FRFrance
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15561991167148571006819646261834FRFrance
1557199115713975978118169251832FRFrance
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1560199112710864733114397191325FRFrance
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15701991027162771104621508292038FRFrance
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15731990517190801380724353342543FRFrance
1574199050711079666015498201228FRFrance
15751990497114302610205FRFrance
\n", "

1576 rows × 10 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202106 7 13642 9914 17370 21 15 \n", "1 202105 7 12210 8988 15432 18 13 \n", "2 202104 7 12026 8826 15226 18 13 \n", "3 202103 7 8913 6375 11451 13 9 \n", "4 202102 7 7795 5430 10160 12 8 \n", "5 202101 7 10525 7750 13300 16 12 \n", "6 202053 7 11978 8406 15550 18 13 \n", "7 202052 7 12012 8285 15739 18 12 \n", "8 202051 7 10564 7574 13554 16 11 \n", "9 202050 7 7063 4744 9382 11 7 \n", "10 202049 7 5026 3145 6907 8 5 \n", "11 202048 7 6683 4312 9054 10 6 \n", "12 202047 7 4999 2963 7035 8 5 \n", "13 202046 7 3752 1963 5541 6 3 \n", "14 202045 7 3696 2016 5376 6 3 \n", "15 202044 7 4391 2375 6407 7 4 \n", "16 202043 7 4376 2505 6247 7 4 \n", "17 202042 7 4000 1979 6021 6 3 \n", "18 202041 7 3961 2099 5823 6 3 \n", "19 202040 7 2078 675 3481 3 1 \n", "20 202039 7 1049 237 1861 2 1 \n", "21 202038 7 2253 782 3724 3 1 \n", "22 202037 7 1584 405 2763 2 0 \n", "23 202036 7 919 100 1738 1 0 \n", "24 202035 7 828 0 1694 1 0 \n", "25 202034 7 2272 371 4173 3 0 \n", "26 202033 7 1284 177 2391 2 0 \n", "27 202032 7 2650 689 4611 4 1 \n", "28 202031 7 1303 100 2506 2 0 \n", "29 202030 7 1385 75 2695 2 0 \n", "... ... ... ... ... ... ... ... \n", "1546 199126 7 17608 11304 23912 31 20 \n", "1547 199125 7 16169 10700 21638 28 18 \n", "1548 199124 7 16171 10071 22271 28 17 \n", "1549 199123 7 11947 7671 16223 21 13 \n", "1550 199122 7 15452 9953 20951 27 17 \n", "1551 199121 7 14903 8975 20831 26 16 \n", "1552 199120 7 19053 12742 25364 34 23 \n", "1553 199119 7 16739 11246 22232 29 19 \n", "1554 199118 7 21385 13882 28888 38 25 \n", "1555 199117 7 13462 8877 18047 24 16 \n", "1556 199116 7 14857 10068 19646 26 18 \n", "1557 199115 7 13975 9781 18169 25 18 \n", "1558 199114 7 12265 7684 16846 22 14 \n", "1559 199113 7 9567 6041 13093 17 11 \n", "1560 199112 7 10864 7331 14397 19 13 \n", "1561 199111 7 15574 11184 19964 27 19 \n", "1562 199110 7 16643 11372 21914 29 20 \n", "1563 199109 7 13741 8780 18702 24 15 \n", "1564 199108 7 13289 8813 17765 23 15 \n", "1565 199107 7 12337 8077 16597 22 15 \n", "1566 199106 7 10877 7013 14741 19 12 \n", "1567 199105 7 10442 6544 14340 18 11 \n", "1568 199104 7 7913 4563 11263 14 8 \n", "1569 199103 7 15387 10484 20290 27 18 \n", "1570 199102 7 16277 11046 21508 29 20 \n", "1571 199101 7 15565 10271 20859 27 18 \n", "1572 199052 7 19375 13295 25455 34 23 \n", "1573 199051 7 19080 13807 24353 34 25 \n", "1574 199050 7 11079 6660 15498 20 12 \n", "1575 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 27 FR France \n", "1 23 FR France \n", "2 23 FR France \n", "3 17 FR France \n", "4 16 FR France \n", "5 20 FR France \n", "6 23 FR France \n", "7 24 FR France \n", "8 21 FR France \n", "9 15 FR France \n", "10 11 FR France \n", "11 14 FR France \n", "12 11 FR France \n", "13 9 FR France \n", "14 9 FR France \n", "15 10 FR France \n", "16 10 FR France \n", "17 9 FR France \n", "18 9 FR France \n", "19 5 FR France \n", "20 3 FR France \n", "21 5 FR France \n", "22 4 FR France \n", "23 2 FR France \n", "24 2 FR France \n", "25 6 FR France \n", "26 4 FR France \n", "27 7 FR France \n", "28 4 FR France \n", "29 4 FR France \n", "... ... ... ... \n", "1546 42 FR France \n", "1547 38 FR France \n", "1548 39 FR France \n", "1549 29 FR France \n", "1550 37 FR France \n", "1551 36 FR France \n", "1552 45 FR France \n", "1553 39 FR France \n", "1554 51 FR France \n", "1555 32 FR France \n", "1556 34 FR France \n", "1557 32 FR France \n", "1558 30 FR France \n", "1559 23 FR France \n", "1560 25 FR France \n", "1561 35 FR France \n", "1562 38 FR France \n", "1563 33 FR France \n", "1564 31 FR France \n", "1565 29 FR France \n", "1566 26 FR France \n", "1567 25 FR France \n", "1568 20 FR France \n", "1569 36 FR France \n", "1570 38 FR France \n", "1571 36 FR France \n", "1572 45 FR France \n", "1573 43 FR France \n", "1574 28 FR France \n", "1575 5 FR France \n", "\n", "[1576 rows x 10 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_up
count1576.0000001576.01576.0000001576.0000001576.0000001576.0000001576.0000001576.000000
mean200578.8585037.012567.8908637918.39847717254.60406120.66180213.01840128.367386
std872.1123550.06659.3935115180.0470638424.45603011.0336508.57661913.974450
min199049.0000007.0161.0000000.000000597.0000000.0000000.0000001.000000
25%199825.7500007.07228.5000003541.75000010709.50000012.0000006.00000017.000000
50%200601.5000007.012526.5000007826.50000017241.50000021.00000013.00000029.000000
75%201330.2500007.017142.25000011622.00000022757.50000028.00000019.00000038.000000
max202106.0000007.036298.00000025490.00000054240.00000061.00000044.00000090.000000
\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up \\\n", "count 1576.000000 1576.0 1576.000000 1576.000000 1576.000000 \n", "mean 200578.858503 7.0 12567.890863 7918.398477 17254.604061 \n", "std 872.112355 0.0 6659.393511 5180.047063 8424.456030 \n", "min 199049.000000 7.0 161.000000 0.000000 597.000000 \n", "25% 199825.750000 7.0 7228.500000 3541.750000 10709.500000 \n", "50% 200601.500000 7.0 12526.500000 7826.500000 17241.500000 \n", "75% 201330.250000 7.0 17142.250000 11622.000000 22757.500000 \n", "max 202106.000000 7.0 36298.000000 25490.000000 54240.000000 \n", "\n", " inc100 inc100_low inc100_up \n", "count 1576.000000 1576.000000 1576.000000 \n", "mean 20.661802 13.018401 28.367386 \n", "std 11.033650 8.576619 13.974450 \n", "min 0.000000 0.000000 1.000000 \n", "25% 12.000000 6.000000 17.000000 \n", "50% 21.000000 13.000000 29.000000 \n", "75% 28.000000 19.000000 38.000000 \n", "max 61.000000 44.000000 90.000000 " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data.describe()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "scrolled": true }, "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": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "data = raw_data.copy()" ] }, { "cell_type": "code", "execution_count": 7, "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": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_nameperiod
0202106713642991417370211527FRFrance2021-02-08/2021-02-14
1202105712210898815432181323FRFrance2021-02-01/2021-02-07
2202104712026882615226181323FRFrance2021-01-25/2021-01-31
32021037891363751145113917FRFrance2021-01-18/2021-01-24
42021027779554301016012816FRFrance2021-01-11/2021-01-17
5202101710525775013300161220FRFrance2021-01-04/2021-01-10
6202053711978840615550181323FRFrance2020-12-28/2021-01-03
7202052712012828515739181224FRFrance2020-12-21/2020-12-27
8202051710564757413554161121FRFrance2020-12-14/2020-12-20
9202050770634744938211715FRFrance2020-12-07/2020-12-13
1020204975026314569078511FRFrance2020-11-30/2020-12-06
11202048766834312905410614FRFrance2020-11-23/2020-11-29
1220204774999296370358511FRFrance2020-11-16/2020-11-22
132020467375219635541639FRFrance2020-11-09/2020-11-15
142020457369620165376639FRFrance2020-11-02/2020-11-08
1520204474391237564077410FRFrance2020-10-26/2020-11-01
1620204374376250562477410FRFrance2020-10-19/2020-10-25
172020427400019796021639FRFrance2020-10-12/2020-10-18
182020417396120995823639FRFrance2020-10-05/2020-10-11
19202040720786753481315FRFrance2020-09-28/2020-10-04
20202039710492371861213FRFrance2020-09-21/2020-09-27
21202038722537823724315FRFrance2020-09-14/2020-09-20
22202037715844052763204FRFrance2020-09-07/2020-09-13
2320203679191001738102FRFrance2020-08-31/2020-09-06
24202035782801694102FRFrance2020-08-24/2020-08-30
25202034722723714173306FRFrance2020-08-17/2020-08-23
26202033712841772391204FRFrance2020-08-10/2020-08-16
27202032726506894611417FRFrance2020-08-03/2020-08-09
28202031713031002506204FRFrance2020-07-27/2020-08-02
2920203071385752695204FRFrance2020-07-20/2020-07-26
....................................
15461991267176081130423912312042FRFrance1991-06-24/1991-06-30
15471991257161691070021638281838FRFrance1991-06-17/1991-06-23
15481991247161711007122271281739FRFrance1991-06-10/1991-06-16
1549199123711947767116223211329FRFrance1991-06-03/1991-06-09
1550199122715452995320951271737FRFrance1991-05-27/1991-06-02
1551199121714903897520831261636FRFrance1991-05-20/1991-05-26
15521991207190531274225364342345FRFrance1991-05-13/1991-05-19
15531991197167391124622232291939FRFrance1991-05-06/1991-05-12
15541991187213851388228888382551FRFrance1991-04-29/1991-05-05
1555199117713462887718047241632FRFrance1991-04-22/1991-04-28
15561991167148571006819646261834FRFrance1991-04-15/1991-04-21
1557199115713975978118169251832FRFrance1991-04-08/1991-04-14
1558199114712265768416846221430FRFrance1991-04-01/1991-04-07
155919911379567604113093171123FRFrance1991-03-25/1991-03-31
1560199112710864733114397191325FRFrance1991-03-18/1991-03-24
15611991117155741118419964271935FRFrance1991-03-11/1991-03-17
15621991107166431137221914292038FRFrance1991-03-04/1991-03-10
1563199109713741878018702241533FRFrance1991-02-25/1991-03-03
1564199108713289881317765231531FRFrance1991-02-18/1991-02-24
1565199107712337807716597221529FRFrance1991-02-11/1991-02-17
1566199106710877701314741191226FRFrance1991-02-04/1991-02-10
1567199105710442654414340181125FRFrance1991-01-28/1991-02-03
15681991047791345631126314820FRFrance1991-01-21/1991-01-27
15691991037153871048420290271836FRFrance1991-01-14/1991-01-20
15701991027162771104621508292038FRFrance1991-01-07/1991-01-13
15711991017155651027120859271836FRFrance1990-12-31/1991-01-06
15721990527193751329525455342345FRFrance1990-12-24/1990-12-30
15731990517190801380724353342543FRFrance1990-12-17/1990-12-23
1574199050711079666015498201228FRFrance1990-12-10/1990-12-16
15751990497114302610205FRFrance1990-12-03/1990-12-09
\n", "

1576 rows × 11 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202106 7 13642 9914 17370 21 15 \n", "1 202105 7 12210 8988 15432 18 13 \n", "2 202104 7 12026 8826 15226 18 13 \n", "3 202103 7 8913 6375 11451 13 9 \n", "4 202102 7 7795 5430 10160 12 8 \n", "5 202101 7 10525 7750 13300 16 12 \n", "6 202053 7 11978 8406 15550 18 13 \n", "7 202052 7 12012 8285 15739 18 12 \n", "8 202051 7 10564 7574 13554 16 11 \n", "9 202050 7 7063 4744 9382 11 7 \n", "10 202049 7 5026 3145 6907 8 5 \n", "11 202048 7 6683 4312 9054 10 6 \n", "12 202047 7 4999 2963 7035 8 5 \n", "13 202046 7 3752 1963 5541 6 3 \n", "14 202045 7 3696 2016 5376 6 3 \n", "15 202044 7 4391 2375 6407 7 4 \n", "16 202043 7 4376 2505 6247 7 4 \n", "17 202042 7 4000 1979 6021 6 3 \n", "18 202041 7 3961 2099 5823 6 3 \n", "19 202040 7 2078 675 3481 3 1 \n", "20 202039 7 1049 237 1861 2 1 \n", "21 202038 7 2253 782 3724 3 1 \n", "22 202037 7 1584 405 2763 2 0 \n", "23 202036 7 919 100 1738 1 0 \n", "24 202035 7 828 0 1694 1 0 \n", "25 202034 7 2272 371 4173 3 0 \n", "26 202033 7 1284 177 2391 2 0 \n", "27 202032 7 2650 689 4611 4 1 \n", "28 202031 7 1303 100 2506 2 0 \n", "29 202030 7 1385 75 2695 2 0 \n", "... ... ... ... ... ... ... ... \n", "1546 199126 7 17608 11304 23912 31 20 \n", "1547 199125 7 16169 10700 21638 28 18 \n", "1548 199124 7 16171 10071 22271 28 17 \n", "1549 199123 7 11947 7671 16223 21 13 \n", "1550 199122 7 15452 9953 20951 27 17 \n", "1551 199121 7 14903 8975 20831 26 16 \n", "1552 199120 7 19053 12742 25364 34 23 \n", "1553 199119 7 16739 11246 22232 29 19 \n", "1554 199118 7 21385 13882 28888 38 25 \n", "1555 199117 7 13462 8877 18047 24 16 \n", "1556 199116 7 14857 10068 19646 26 18 \n", "1557 199115 7 13975 9781 18169 25 18 \n", "1558 199114 7 12265 7684 16846 22 14 \n", "1559 199113 7 9567 6041 13093 17 11 \n", "1560 199112 7 10864 7331 14397 19 13 \n", "1561 199111 7 15574 11184 19964 27 19 \n", "1562 199110 7 16643 11372 21914 29 20 \n", "1563 199109 7 13741 8780 18702 24 15 \n", "1564 199108 7 13289 8813 17765 23 15 \n", "1565 199107 7 12337 8077 16597 22 15 \n", "1566 199106 7 10877 7013 14741 19 12 \n", "1567 199105 7 10442 6544 14340 18 11 \n", "1568 199104 7 7913 4563 11263 14 8 \n", "1569 199103 7 15387 10484 20290 27 18 \n", "1570 199102 7 16277 11046 21508 29 20 \n", "1571 199101 7 15565 10271 20859 27 18 \n", "1572 199052 7 19375 13295 25455 34 23 \n", "1573 199051 7 19080 13807 24353 34 25 \n", "1574 199050 7 11079 6660 15498 20 12 \n", "1575 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name period \n", "0 27 FR France 2021-02-08/2021-02-14 \n", "1 23 FR France 2021-02-01/2021-02-07 \n", "2 23 FR France 2021-01-25/2021-01-31 \n", "3 17 FR France 2021-01-18/2021-01-24 \n", "4 16 FR France 2021-01-11/2021-01-17 \n", "5 20 FR France 2021-01-04/2021-01-10 \n", "6 23 FR France 2020-12-28/2021-01-03 \n", "7 24 FR France 2020-12-21/2020-12-27 \n", "8 21 FR France 2020-12-14/2020-12-20 \n", "9 15 FR France 2020-12-07/2020-12-13 \n", "10 11 FR France 2020-11-30/2020-12-06 \n", "11 14 FR France 2020-11-23/2020-11-29 \n", "12 11 FR France 2020-11-16/2020-11-22 \n", "13 9 FR France 2020-11-09/2020-11-15 \n", "14 9 FR France 2020-11-02/2020-11-08 \n", "15 10 FR France 2020-10-26/2020-11-01 \n", "16 10 FR France 2020-10-19/2020-10-25 \n", "17 9 FR France 2020-10-12/2020-10-18 \n", "18 9 FR France 2020-10-05/2020-10-11 \n", "19 5 FR France 2020-09-28/2020-10-04 \n", "20 3 FR France 2020-09-21/2020-09-27 \n", "21 5 FR France 2020-09-14/2020-09-20 \n", "22 4 FR France 2020-09-07/2020-09-13 \n", "23 2 FR France 2020-08-31/2020-09-06 \n", "24 2 FR France 2020-08-24/2020-08-30 \n", "25 6 FR France 2020-08-17/2020-08-23 \n", "26 4 FR France 2020-08-10/2020-08-16 \n", "27 7 FR France 2020-08-03/2020-08-09 \n", "28 4 FR France 2020-07-27/2020-08-02 \n", "29 4 FR France 2020-07-20/2020-07-26 \n", "... ... ... ... ... \n", "1546 42 FR France 1991-06-24/1991-06-30 \n", "1547 38 FR France 1991-06-17/1991-06-23 \n", "1548 39 FR France 1991-06-10/1991-06-16 \n", "1549 29 FR France 1991-06-03/1991-06-09 \n", "1550 37 FR France 1991-05-27/1991-06-02 \n", "1551 36 FR France 1991-05-20/1991-05-26 \n", "1552 45 FR France 1991-05-13/1991-05-19 \n", "1553 39 FR France 1991-05-06/1991-05-12 \n", "1554 51 FR France 1991-04-29/1991-05-05 \n", "1555 32 FR France 1991-04-22/1991-04-28 \n", "1556 34 FR France 1991-04-15/1991-04-21 \n", "1557 32 FR France 1991-04-08/1991-04-14 \n", "1558 30 FR France 1991-04-01/1991-04-07 \n", "1559 23 FR France 1991-03-25/1991-03-31 \n", "1560 25 FR France 1991-03-18/1991-03-24 \n", "1561 35 FR France 1991-03-11/1991-03-17 \n", "1562 38 FR France 1991-03-04/1991-03-10 \n", "1563 33 FR France 1991-02-25/1991-03-03 \n", "1564 31 FR France 1991-02-18/1991-02-24 \n", "1565 29 FR France 1991-02-11/1991-02-17 \n", "1566 26 FR France 1991-02-04/1991-02-10 \n", "1567 25 FR France 1991-01-28/1991-02-03 \n", "1568 20 FR France 1991-01-21/1991-01-27 \n", "1569 36 FR France 1991-01-14/1991-01-20 \n", "1570 38 FR France 1991-01-07/1991-01-13 \n", "1571 36 FR France 1990-12-31/1991-01-06 \n", "1572 45 FR France 1990-12-24/1990-12-30 \n", "1573 43 FR France 1990-12-17/1990-12-23 \n", "1574 28 FR France 1990-12-10/1990-12-16 \n", "1575 5 FR France 1990-12-03/1990-12-09 \n", "\n", "[1576 rows x 11 columns]" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" ] }, { "cell_type": "code", "execution_count": 10, "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
.................................
2020-07-20/2020-07-2620203071385752695204FRFrance
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
2021-01-04/2021-01-10202101710525775013300161220FRFrance
2021-01-11/2021-01-172021027779554301016012816FRFrance
2021-01-18/2021-01-242021037891363751145113917FRFrance
2021-01-25/2021-01-31202104712026882615226181323FRFrance
2021-02-01/2021-02-07202105712210898815432181323FRFrance
2021-02-08/2021-02-14202106713642991417370211527FRFrance
\n", "

1576 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", "2020-07-20/2020-07-26 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 10525 7750 13300 16 \n", "2021-01-11/2021-01-17 202102 7 7795 5430 10160 12 \n", "2021-01-18/2021-01-24 202103 7 8913 6375 11451 13 \n", "2021-01-25/2021-01-31 202104 7 12026 8826 15226 18 \n", "2021-02-01/2021-02-07 202105 7 12210 8988 15432 18 \n", "2021-02-08/2021-02-14 202106 7 13642 9914 17370 21 \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", "2020-07-20/2020-07-26 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", "2021-01-25/2021-01-31 13 23 FR France \n", "2021-02-01/2021-02-07 13 23 FR France \n", "2021-02-08/2021-02-14 15 27 FR France \n", "\n", "[1576 rows x 10 columns]" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sorted_data" ] }, { "cell_type": "code", "execution_count": 11, "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": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sorted_data['inc'][-120:].plot()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "first_september_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_september_week[:-1],\n", " first_september_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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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "yearly_incidence.plot(style='*')" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2020 221186\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", "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": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.sort_values()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "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 }