{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Analyse de l'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": 9, "metadata": {}, "outputs": [], "source": [ "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
02020427299312834703528FRFrance
12020417397421065842639FRFrance
2202040720786753481315FRFrance
3202039710492371861213FRFrance
4202038722537823724315FRFrance
5202037715844052763204FRFrance
620203679191001738102FRFrance
7202035782801694102FRFrance
8202034722723714173306FRFrance
9202033712841772391204FRFrance
10202032726506894611417FRFrance
11202031713031002506204FRFrance
1220203071385752695204FRFrance
132020297841101672102FRFrance
14202028772801515102FRFrance
1520202779861491823102FRFrance
16202026769401454102FRFrance
1720202572280597001FRFrance
1820202473880959102FRFrance
19202023755811115102FRFrance
2020202272770633001FRFrance
212020217602361168102FRFrance
222020207824201628102FRFrance
2320201973100753001FRFrance
242020187849981600102FRFrance
2520201772720658001FRFrance
262020167758781438102FRFrance
27202015719186753161315FRFrance
282020147387922275531639FRFrance
29202013773265236941611814FRFrance
.................................
15291991267176081130423912312042FRFrance
15301991257161691070021638281838FRFrance
15311991247161711007122271281739FRFrance
1532199123711947767116223211329FRFrance
1533199122715452995320951271737FRFrance
1534199121714903897520831261636FRFrance
15351991207190531274225364342345FRFrance
15361991197167391124622232291939FRFrance
15371991187213851388228888382551FRFrance
1538199117713462887718047241632FRFrance
15391991167148571006819646261834FRFrance
1540199115713975978118169251832FRFrance
1541199114712265768416846221430FRFrance
154219911379567604113093171123FRFrance
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15451991107166431137221914292038FRFrance
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1550199105710442654414340181125FRFrance
15511991047791345631126314820FRFrance
15521991037153871048420290271836FRFrance
15531991027162771104621508292038FRFrance
15541991017155651027120859271836FRFrance
15551990527193751329525455342345FRFrance
15561990517190801380724353342543FRFrance
1557199050711079666015498201228FRFrance
15581990497114302610205FRFrance
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1559 rows × 10 columns

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" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202042 7 2993 1283 4703 5 2 \n", "1 202041 7 3974 2106 5842 6 3 \n", "2 202040 7 2078 675 3481 3 1 \n", "3 202039 7 1049 237 1861 2 1 \n", "4 202038 7 2253 782 3724 3 1 \n", "5 202037 7 1584 405 2763 2 0 \n", "6 202036 7 919 100 1738 1 0 \n", "7 202035 7 828 0 1694 1 0 \n", "8 202034 7 2272 371 4173 3 0 \n", "9 202033 7 1284 177 2391 2 0 \n", "10 202032 7 2650 689 4611 4 1 \n", "11 202031 7 1303 100 2506 2 0 \n", "12 202030 7 1385 75 2695 2 0 \n", "13 202029 7 841 10 1672 1 0 \n", "14 202028 7 728 0 1515 1 0 \n", "15 202027 7 986 149 1823 1 0 \n", "16 202026 7 694 0 1454 1 0 \n", "17 202025 7 228 0 597 0 0 \n", "18 202024 7 388 0 959 1 0 \n", "19 202023 7 558 1 1115 1 0 \n", "20 202022 7 277 0 633 0 0 \n", "21 202021 7 602 36 1168 1 0 \n", "22 202020 7 824 20 1628 1 0 \n", "23 202019 7 310 0 753 0 0 \n", "24 202018 7 849 98 1600 1 0 \n", "25 202017 7 272 0 658 0 0 \n", "26 202016 7 758 78 1438 1 0 \n", "27 202015 7 1918 675 3161 3 1 \n", "28 202014 7 3879 2227 5531 6 3 \n", "29 202013 7 7326 5236 9416 11 8 \n", "... ... ... ... ... ... ... ... \n", "1529 199126 7 17608 11304 23912 31 20 \n", "1530 199125 7 16169 10700 21638 28 18 \n", "1531 199124 7 16171 10071 22271 28 17 \n", "1532 199123 7 11947 7671 16223 21 13 \n", "1533 199122 7 15452 9953 20951 27 17 \n", "1534 199121 7 14903 8975 20831 26 16 \n", "1535 199120 7 19053 12742 25364 34 23 \n", "1536 199119 7 16739 11246 22232 29 19 \n", "1537 199118 7 21385 13882 28888 38 25 \n", "1538 199117 7 13462 8877 18047 24 16 \n", "1539 199116 7 14857 10068 19646 26 18 \n", "1540 199115 7 13975 9781 18169 25 18 \n", "1541 199114 7 12265 7684 16846 22 14 \n", "1542 199113 7 9567 6041 13093 17 11 \n", "1543 199112 7 10864 7331 14397 19 13 \n", "1544 199111 7 15574 11184 19964 27 19 \n", "1545 199110 7 16643 11372 21914 29 20 \n", "1546 199109 7 13741 8780 18702 24 15 \n", "1547 199108 7 13289 8813 17765 23 15 \n", "1548 199107 7 12337 8077 16597 22 15 \n", "1549 199106 7 10877 7013 14741 19 12 \n", "1550 199105 7 10442 6544 14340 18 11 \n", "1551 199104 7 7913 4563 11263 14 8 \n", "1552 199103 7 15387 10484 20290 27 18 \n", "1553 199102 7 16277 11046 21508 29 20 \n", "1554 199101 7 15565 10271 20859 27 18 \n", "1555 199052 7 19375 13295 25455 34 23 \n", "1556 199051 7 19080 13807 24353 34 25 \n", "1557 199050 7 11079 6660 15498 20 12 \n", "1558 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 8 FR France \n", "1 9 FR France \n", "2 5 FR France \n", "3 3 FR France \n", "4 5 FR France \n", "5 4 FR France \n", "6 2 FR France \n", "7 2 FR France \n", "8 6 FR France \n", "9 4 FR France \n", "10 7 FR France \n", "11 4 FR France \n", "12 4 FR France \n", "13 2 FR France \n", "14 2 FR France \n", "15 2 FR France \n", "16 2 FR France \n", "17 1 FR France \n", "18 2 FR France \n", "19 2 FR France \n", "20 1 FR France \n", "21 2 FR France \n", "22 2 FR France \n", "23 1 FR France \n", "24 2 FR France \n", "25 1 FR France \n", "26 2 FR France \n", "27 5 FR France \n", "28 9 FR France \n", "29 14 FR France \n", "... ... ... ... \n", "1529 42 FR France \n", "1530 38 FR France \n", "1531 39 FR France \n", "1532 29 FR France \n", "1533 37 FR France \n", "1534 36 FR France \n", "1535 45 FR France \n", "1536 39 FR France \n", "1537 51 FR France \n", "1538 32 FR France \n", "1539 34 FR France \n", "1540 32 FR France \n", "1541 30 FR France \n", "1542 23 FR France \n", "1543 25 FR France \n", "1544 35 FR France \n", "1545 38 FR France \n", "1546 33 FR France \n", "1547 31 FR France \n", "1548 29 FR France \n", "1549 26 FR France \n", "1550 25 FR France \n", "1551 20 FR France \n", "1552 36 FR France \n", "1553 38 FR France \n", "1554 36 FR France \n", "1555 45 FR France \n", "1556 43 FR France \n", "1557 28 FR France \n", "1558 5 FR France \n", "\n", "[1559 rows x 10 columns]" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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" ], "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": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
02020427299312834703528FRFrance
12020417397421065842639FRFrance
2202040720786753481315FRFrance
3202039710492371861213FRFrance
4202038722537823724315FRFrance
5202037715844052763204FRFrance
620203679191001738102FRFrance
7202035782801694102FRFrance
8202034722723714173306FRFrance
9202033712841772391204FRFrance
10202032726506894611417FRFrance
11202031713031002506204FRFrance
1220203071385752695204FRFrance
132020297841101672102FRFrance
14202028772801515102FRFrance
1520202779861491823102FRFrance
16202026769401454102FRFrance
1720202572280597001FRFrance
1820202473880959102FRFrance
19202023755811115102FRFrance
2020202272770633001FRFrance
212020217602361168102FRFrance
222020207824201628102FRFrance
2320201973100753001FRFrance
242020187849981600102FRFrance
2520201772720658001FRFrance
262020167758781438102FRFrance
27202015719186753161315FRFrance
282020147387922275531639FRFrance
29202013773265236941611814FRFrance
.................................
15291991267176081130423912312042FRFrance
15301991257161691070021638281838FRFrance
15311991247161711007122271281739FRFrance
1532199123711947767116223211329FRFrance
1533199122715452995320951271737FRFrance
1534199121714903897520831261636FRFrance
15351991207190531274225364342345FRFrance
15361991197167391124622232291939FRFrance
15371991187213851388228888382551FRFrance
1538199117713462887718047241632FRFrance
15391991167148571006819646261834FRFrance
1540199115713975978118169251832FRFrance
1541199114712265768416846221430FRFrance
154219911379567604113093171123FRFrance
1543199112710864733114397191325FRFrance
15441991117155741118419964271935FRFrance
15451991107166431137221914292038FRFrance
1546199109713741878018702241533FRFrance
1547199108713289881317765231531FRFrance
1548199107712337807716597221529FRFrance
1549199106710877701314741191226FRFrance
1550199105710442654414340181125FRFrance
15511991047791345631126314820FRFrance
15521991037153871048420290271836FRFrance
15531991027162771104621508292038FRFrance
15541991017155651027120859271836FRFrance
15551990527193751329525455342345FRFrance
15561990517190801380724353342543FRFrance
1557199050711079666015498201228FRFrance
15581990497114302610205FRFrance
\n", "

1559 rows × 10 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202042 7 2993 1283 4703 5 2 \n", "1 202041 7 3974 2106 5842 6 3 \n", "2 202040 7 2078 675 3481 3 1 \n", "3 202039 7 1049 237 1861 2 1 \n", "4 202038 7 2253 782 3724 3 1 \n", "5 202037 7 1584 405 2763 2 0 \n", "6 202036 7 919 100 1738 1 0 \n", "7 202035 7 828 0 1694 1 0 \n", "8 202034 7 2272 371 4173 3 0 \n", "9 202033 7 1284 177 2391 2 0 \n", "10 202032 7 2650 689 4611 4 1 \n", "11 202031 7 1303 100 2506 2 0 \n", "12 202030 7 1385 75 2695 2 0 \n", "13 202029 7 841 10 1672 1 0 \n", "14 202028 7 728 0 1515 1 0 \n", "15 202027 7 986 149 1823 1 0 \n", "16 202026 7 694 0 1454 1 0 \n", "17 202025 7 228 0 597 0 0 \n", "18 202024 7 388 0 959 1 0 \n", "19 202023 7 558 1 1115 1 0 \n", "20 202022 7 277 0 633 0 0 \n", "21 202021 7 602 36 1168 1 0 \n", "22 202020 7 824 20 1628 1 0 \n", "23 202019 7 310 0 753 0 0 \n", "24 202018 7 849 98 1600 1 0 \n", "25 202017 7 272 0 658 0 0 \n", "26 202016 7 758 78 1438 1 0 \n", "27 202015 7 1918 675 3161 3 1 \n", "28 202014 7 3879 2227 5531 6 3 \n", "29 202013 7 7326 5236 9416 11 8 \n", "... ... ... ... ... ... ... ... \n", "1529 199126 7 17608 11304 23912 31 20 \n", "1530 199125 7 16169 10700 21638 28 18 \n", "1531 199124 7 16171 10071 22271 28 17 \n", "1532 199123 7 11947 7671 16223 21 13 \n", "1533 199122 7 15452 9953 20951 27 17 \n", "1534 199121 7 14903 8975 20831 26 16 \n", "1535 199120 7 19053 12742 25364 34 23 \n", "1536 199119 7 16739 11246 22232 29 19 \n", "1537 199118 7 21385 13882 28888 38 25 \n", "1538 199117 7 13462 8877 18047 24 16 \n", "1539 199116 7 14857 10068 19646 26 18 \n", "1540 199115 7 13975 9781 18169 25 18 \n", "1541 199114 7 12265 7684 16846 22 14 \n", "1542 199113 7 9567 6041 13093 17 11 \n", "1543 199112 7 10864 7331 14397 19 13 \n", "1544 199111 7 15574 11184 19964 27 19 \n", "1545 199110 7 16643 11372 21914 29 20 \n", "1546 199109 7 13741 8780 18702 24 15 \n", "1547 199108 7 13289 8813 17765 23 15 \n", "1548 199107 7 12337 8077 16597 22 15 \n", "1549 199106 7 10877 7013 14741 19 12 \n", "1550 199105 7 10442 6544 14340 18 11 \n", "1551 199104 7 7913 4563 11263 14 8 \n", "1552 199103 7 15387 10484 20290 27 18 \n", "1553 199102 7 16277 11046 21508 29 20 \n", "1554 199101 7 15565 10271 20859 27 18 \n", "1555 199052 7 19375 13295 25455 34 23 \n", "1556 199051 7 19080 13807 24353 34 25 \n", "1557 199050 7 11079 6660 15498 20 12 \n", "1558 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 8 FR France \n", "1 9 FR France \n", "2 5 FR France \n", "3 3 FR France \n", "4 5 FR France \n", "5 4 FR France \n", "6 2 FR France \n", "7 2 FR France \n", "8 6 FR France \n", "9 4 FR France \n", "10 7 FR France \n", "11 4 FR France \n", "12 4 FR France \n", "13 2 FR France \n", "14 2 FR France \n", "15 2 FR France \n", "16 2 FR France \n", "17 1 FR France \n", "18 2 FR France \n", "19 2 FR France \n", "20 1 FR France \n", "21 2 FR France \n", "22 2 FR France \n", "23 1 FR France \n", "24 2 FR France \n", "25 1 FR France \n", "26 2 FR France \n", "27 5 FR France \n", "28 9 FR France \n", "29 14 FR France \n", "... ... ... ... \n", "1529 42 FR France \n", "1530 38 FR France \n", "1531 39 FR France \n", "1532 29 FR France \n", "1533 37 FR France \n", "1534 36 FR France \n", "1535 45 FR France \n", "1536 39 FR France \n", "1537 51 FR France \n", "1538 32 FR France \n", "1539 34 FR France \n", "1540 32 FR France \n", "1541 30 FR France \n", "1542 23 FR France \n", "1543 25 FR France \n", "1544 35 FR France \n", "1545 38 FR France \n", "1546 33 FR France \n", "1547 31 FR France \n", "1548 29 FR France \n", "1549 26 FR France \n", "1550 25 FR France \n", "1551 20 FR France \n", "1552 36 FR France \n", "1553 38 FR France \n", "1554 36 FR France \n", "1555 45 FR France \n", "1556 43 FR France \n", "1557 28 FR France \n", "1558 5 FR France \n", "\n", "[1559 rows x 10 columns]" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = raw_data.dropna().copy()\n", "data" ] }, { "cell_type": "code", "execution_count": 16, "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": 17, "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" ] }, { "cell_type": "code", "execution_count": 18, "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": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 19, "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": "markdown", "metadata": {}, "source": [ "# Etude de l'incidence annuelle" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", " for y in range(1985,\n", " sorted_data.index[-1].year)]" ] }, { "cell_type": "code", "execution_count": 28, "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": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 29, "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": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1986 0\n", "1987 0\n", "1988 0\n", "1989 0\n", "1990 0\n", "2002 502271\n", "1991 507329\n", "2018 543281\n", "1996 553859\n", "2017 557449\n", "2019 584926\n", "2000 605096\n", "2015 613286\n", "2012 620315\n", "2011 645042\n", "1995 648598\n", "2001 650660\n", "1993 653058\n", "2005 654308\n", "2006 657482\n", "1998 660316\n", "2014 673458\n", "1997 679308\n", "1994 682920\n", "2007 701566\n", "2013 708874\n", "2004 736266\n", "2008 745701\n", "2003 770211\n", "2016 780645\n", "1999 784963\n", "1992 821558\n", "2009 822819\n", "2010 848236\n", "dtype: int64" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.sort_values()" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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