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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
0202104711410818414636171222FRFrance
12021037879962691132913917FRFrance
22021027779554301016012816FRFrance
3202101710525775013300161220FRFrance
4202053711978840615550181323FRFrance
5202052712012828515739181224FRFrance
6202051710564757413554161121FRFrance
7202050770634744938211715FRFrance
820204975026314569078511FRFrance
9202048766834312905410614FRFrance
1020204774999296370358511FRFrance
112020467375219635541639FRFrance
122020457369620165376639FRFrance
1320204474391237564077410FRFrance
1420204374376250562477410FRFrance
152020427400019796021639FRFrance
162020417396120995823639FRFrance
17202040720786753481315FRFrance
18202039710492371861213FRFrance
19202038722537823724315FRFrance
20202037715844052763204FRFrance
2120203679191001738102FRFrance
22202035782801694102FRFrance
23202034722723714173306FRFrance
24202033712841772391204FRFrance
25202032726506894611417FRFrance
26202031713031002506204FRFrance
2720203071385752695204FRFrance
282020297841101672102FRFrance
29202028772801515102FRFrance
.................................
15441991267176081130423912312042FRFrance
15451991257161691070021638281838FRFrance
15461991247161711007122271281739FRFrance
1547199123711947767116223211329FRFrance
1548199122715452995320951271737FRFrance
1549199121714903897520831261636FRFrance
15501991207190531274225364342345FRFrance
15511991197167391124622232291939FRFrance
15521991187213851388228888382551FRFrance
1553199117713462887718047241632FRFrance
15541991167148571006819646261834FRFrance
1555199115713975978118169251832FRFrance
1556199114712265768416846221430FRFrance
155719911379567604113093171123FRFrance
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15591991117155741118419964271935FRFrance
15601991107166431137221914292038FRFrance
1561199109713741878018702241533FRFrance
1562199108713289881317765231531FRFrance
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1564199106710877701314741191226FRFrance
1565199105710442654414340181125FRFrance
15661991047791345631126314820FRFrance
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15681991027162771104621508292038FRFrance
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15701990527193751329525455342345FRFrance
15711990517190801380724353342543FRFrance
1572199050711079666015498201228FRFrance
15731990497114302610205FRFrance
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1574 rows × 10 columns

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" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202104 7 11410 8184 14636 17 12 \n", "1 202103 7 8799 6269 11329 13 9 \n", "2 202102 7 7795 5430 10160 12 8 \n", "3 202101 7 10525 7750 13300 16 12 \n", "4 202053 7 11978 8406 15550 18 13 \n", "5 202052 7 12012 8285 15739 18 12 \n", "6 202051 7 10564 7574 13554 16 11 \n", "7 202050 7 7063 4744 9382 11 7 \n", "8 202049 7 5026 3145 6907 8 5 \n", "9 202048 7 6683 4312 9054 10 6 \n", "10 202047 7 4999 2963 7035 8 5 \n", "11 202046 7 3752 1963 5541 6 3 \n", "12 202045 7 3696 2016 5376 6 3 \n", "13 202044 7 4391 2375 6407 7 4 \n", "14 202043 7 4376 2505 6247 7 4 \n", "15 202042 7 4000 1979 6021 6 3 \n", "16 202041 7 3961 2099 5823 6 3 \n", "17 202040 7 2078 675 3481 3 1 \n", "18 202039 7 1049 237 1861 2 1 \n", "19 202038 7 2253 782 3724 3 1 \n", "20 202037 7 1584 405 2763 2 0 \n", "21 202036 7 919 100 1738 1 0 \n", "22 202035 7 828 0 1694 1 0 \n", "23 202034 7 2272 371 4173 3 0 \n", "24 202033 7 1284 177 2391 2 0 \n", "25 202032 7 2650 689 4611 4 1 \n", "26 202031 7 1303 100 2506 2 0 \n", "27 202030 7 1385 75 2695 2 0 \n", "28 202029 7 841 10 1672 1 0 \n", "29 202028 7 728 0 1515 1 0 \n", "... ... ... ... ... ... ... ... \n", "1544 199126 7 17608 11304 23912 31 20 \n", "1545 199125 7 16169 10700 21638 28 18 \n", "1546 199124 7 16171 10071 22271 28 17 \n", "1547 199123 7 11947 7671 16223 21 13 \n", "1548 199122 7 15452 9953 20951 27 17 \n", "1549 199121 7 14903 8975 20831 26 16 \n", "1550 199120 7 19053 12742 25364 34 23 \n", "1551 199119 7 16739 11246 22232 29 19 \n", "1552 199118 7 21385 13882 28888 38 25 \n", "1553 199117 7 13462 8877 18047 24 16 \n", "1554 199116 7 14857 10068 19646 26 18 \n", "1555 199115 7 13975 9781 18169 25 18 \n", "1556 199114 7 12265 7684 16846 22 14 \n", "1557 199113 7 9567 6041 13093 17 11 \n", "1558 199112 7 10864 7331 14397 19 13 \n", "1559 199111 7 15574 11184 19964 27 19 \n", "1560 199110 7 16643 11372 21914 29 20 \n", "1561 199109 7 13741 8780 18702 24 15 \n", "1562 199108 7 13289 8813 17765 23 15 \n", "1563 199107 7 12337 8077 16597 22 15 \n", "1564 199106 7 10877 7013 14741 19 12 \n", "1565 199105 7 10442 6544 14340 18 11 \n", "1566 199104 7 7913 4563 11263 14 8 \n", "1567 199103 7 15387 10484 20290 27 18 \n", "1568 199102 7 16277 11046 21508 29 20 \n", "1569 199101 7 15565 10271 20859 27 18 \n", "1570 199052 7 19375 13295 25455 34 23 \n", "1571 199051 7 19080 13807 24353 34 25 \n", "1572 199050 7 11079 6660 15498 20 12 \n", "1573 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 22 FR France \n", "1 17 FR France \n", "2 16 FR France \n", "3 20 FR France \n", "4 23 FR France \n", "5 24 FR France \n", "6 21 FR France \n", "7 15 FR France \n", "8 11 FR France \n", "9 14 FR France \n", "10 11 FR France \n", "11 9 FR France \n", "12 9 FR France \n", "13 10 FR France \n", "14 10 FR France \n", "15 9 FR France \n", "16 9 FR France \n", "17 5 FR France \n", "18 3 FR France \n", "19 5 FR France \n", "20 4 FR France \n", "21 2 FR France \n", "22 2 FR France \n", "23 6 FR France \n", "24 4 FR France \n", "25 7 FR France \n", "26 4 FR France \n", "27 4 FR France \n", "28 2 FR France \n", "29 2 FR France \n", "... ... ... ... \n", "1544 42 FR France \n", "1545 38 FR France \n", "1546 39 FR France \n", "1547 29 FR France \n", "1548 37 FR France \n", "1549 36 FR France \n", "1550 45 FR France \n", "1551 39 FR France \n", "1552 51 FR France \n", "1553 32 FR France \n", "1554 34 FR France \n", "1555 32 FR France \n", "1556 30 FR France \n", "1557 23 FR France \n", "1558 25 FR France \n", "1559 35 FR France \n", "1560 38 FR France \n", "1561 33 FR France \n", "1562 31 FR France \n", "1563 29 FR France \n", "1564 26 FR France \n", "1565 25 FR France \n", "1566 20 FR France \n", "1567 36 FR France \n", "1568 38 FR France \n", "1569 36 FR France \n", "1570 45 FR France \n", "1571 43 FR France \n", "1572 28 FR France \n", "1573 5 FR France \n", "\n", "[1574 rows x 10 columns]" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data" ] }, { "cell_type": "code", "execution_count": 25, "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
0202104711410818414636171222FRFrance
12021037879962691132913917FRFrance
22021027779554301016012816FRFrance
3202101710525775013300161220FRFrance
4202053711978840615550181323FRFrance
5202052712012828515739181224FRFrance
6202051710564757413554161121FRFrance
7202050770634744938211715FRFrance
820204975026314569078511FRFrance
9202048766834312905410614FRFrance
1020204774999296370358511FRFrance
112020467375219635541639FRFrance
122020457369620165376639FRFrance
1320204474391237564077410FRFrance
1420204374376250562477410FRFrance
152020427400019796021639FRFrance
162020417396120995823639FRFrance
17202040720786753481315FRFrance
18202039710492371861213FRFrance
19202038722537823724315FRFrance
20202037715844052763204FRFrance
2120203679191001738102FRFrance
22202035782801694102FRFrance
23202034722723714173306FRFrance
24202033712841772391204FRFrance
25202032726506894611417FRFrance
26202031713031002506204FRFrance
2720203071385752695204FRFrance
282020297841101672102FRFrance
29202028772801515102FRFrance
.................................
15441991267176081130423912312042FRFrance
15451991257161691070021638281838FRFrance
15461991247161711007122271281739FRFrance
1547199123711947767116223211329FRFrance
1548199122715452995320951271737FRFrance
1549199121714903897520831261636FRFrance
15501991207190531274225364342345FRFrance
15511991197167391124622232291939FRFrance
15521991187213851388228888382551FRFrance
1553199117713462887718047241632FRFrance
15541991167148571006819646261834FRFrance
1555199115713975978118169251832FRFrance
1556199114712265768416846221430FRFrance
155719911379567604113093171123FRFrance
1558199112710864733114397191325FRFrance
15591991117155741118419964271935FRFrance
15601991107166431137221914292038FRFrance
1561199109713741878018702241533FRFrance
1562199108713289881317765231531FRFrance
1563199107712337807716597221529FRFrance
1564199106710877701314741191226FRFrance
1565199105710442654414340181125FRFrance
15661991047791345631126314820FRFrance
15671991037153871048420290271836FRFrance
15681991027162771104621508292038FRFrance
15691991017155651027120859271836FRFrance
15701990527193751329525455342345FRFrance
15711990517190801380724353342543FRFrance
1572199050711079666015498201228FRFrance
15731990497114302610205FRFrance
\n", "

1574 rows × 10 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202104 7 11410 8184 14636 17 12 \n", "1 202103 7 8799 6269 11329 13 9 \n", "2 202102 7 7795 5430 10160 12 8 \n", "3 202101 7 10525 7750 13300 16 12 \n", "4 202053 7 11978 8406 15550 18 13 \n", "5 202052 7 12012 8285 15739 18 12 \n", "6 202051 7 10564 7574 13554 16 11 \n", "7 202050 7 7063 4744 9382 11 7 \n", "8 202049 7 5026 3145 6907 8 5 \n", "9 202048 7 6683 4312 9054 10 6 \n", "10 202047 7 4999 2963 7035 8 5 \n", "11 202046 7 3752 1963 5541 6 3 \n", "12 202045 7 3696 2016 5376 6 3 \n", "13 202044 7 4391 2375 6407 7 4 \n", "14 202043 7 4376 2505 6247 7 4 \n", "15 202042 7 4000 1979 6021 6 3 \n", "16 202041 7 3961 2099 5823 6 3 \n", "17 202040 7 2078 675 3481 3 1 \n", "18 202039 7 1049 237 1861 2 1 \n", "19 202038 7 2253 782 3724 3 1 \n", "20 202037 7 1584 405 2763 2 0 \n", "21 202036 7 919 100 1738 1 0 \n", "22 202035 7 828 0 1694 1 0 \n", "23 202034 7 2272 371 4173 3 0 \n", "24 202033 7 1284 177 2391 2 0 \n", "25 202032 7 2650 689 4611 4 1 \n", "26 202031 7 1303 100 2506 2 0 \n", "27 202030 7 1385 75 2695 2 0 \n", "28 202029 7 841 10 1672 1 0 \n", "29 202028 7 728 0 1515 1 0 \n", "... ... ... ... ... ... ... ... \n", "1544 199126 7 17608 11304 23912 31 20 \n", "1545 199125 7 16169 10700 21638 28 18 \n", "1546 199124 7 16171 10071 22271 28 17 \n", "1547 199123 7 11947 7671 16223 21 13 \n", "1548 199122 7 15452 9953 20951 27 17 \n", "1549 199121 7 14903 8975 20831 26 16 \n", "1550 199120 7 19053 12742 25364 34 23 \n", "1551 199119 7 16739 11246 22232 29 19 \n", "1552 199118 7 21385 13882 28888 38 25 \n", "1553 199117 7 13462 8877 18047 24 16 \n", "1554 199116 7 14857 10068 19646 26 18 \n", "1555 199115 7 13975 9781 18169 25 18 \n", "1556 199114 7 12265 7684 16846 22 14 \n", "1557 199113 7 9567 6041 13093 17 11 \n", "1558 199112 7 10864 7331 14397 19 13 \n", "1559 199111 7 15574 11184 19964 27 19 \n", "1560 199110 7 16643 11372 21914 29 20 \n", "1561 199109 7 13741 8780 18702 24 15 \n", "1562 199108 7 13289 8813 17765 23 15 \n", "1563 199107 7 12337 8077 16597 22 15 \n", "1564 199106 7 10877 7013 14741 19 12 \n", "1565 199105 7 10442 6544 14340 18 11 \n", "1566 199104 7 7913 4563 11263 14 8 \n", "1567 199103 7 15387 10484 20290 27 18 \n", "1568 199102 7 16277 11046 21508 29 20 \n", "1569 199101 7 15565 10271 20859 27 18 \n", "1570 199052 7 19375 13295 25455 34 23 \n", "1571 199051 7 19080 13807 24353 34 25 \n", "1572 199050 7 11079 6660 15498 20 12 \n", "1573 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 22 FR France \n", "1 17 FR France \n", "2 16 FR France \n", "3 20 FR France \n", "4 23 FR France \n", "5 24 FR France \n", "6 21 FR France \n", "7 15 FR France \n", "8 11 FR France \n", "9 14 FR France \n", "10 11 FR France \n", "11 9 FR France \n", "12 9 FR France \n", "13 10 FR France \n", "14 10 FR France \n", "15 9 FR France \n", "16 9 FR France \n", "17 5 FR France \n", "18 3 FR France \n", "19 5 FR France \n", "20 4 FR France \n", "21 2 FR France \n", "22 2 FR France \n", "23 6 FR France \n", "24 4 FR France \n", "25 7 FR France \n", "26 4 FR France \n", "27 4 FR France \n", "28 2 FR France \n", "29 2 FR France \n", "... ... ... ... \n", "1544 42 FR France \n", "1545 38 FR France \n", "1546 39 FR France \n", "1547 29 FR France \n", "1548 37 FR France \n", "1549 36 FR France \n", "1550 45 FR France \n", "1551 39 FR France \n", "1552 51 FR France \n", "1553 32 FR France \n", "1554 34 FR France \n", "1555 32 FR France \n", "1556 30 FR France \n", "1557 23 FR France \n", "1558 25 FR France \n", "1559 35 FR France \n", "1560 38 FR France \n", "1561 33 FR France \n", "1562 31 FR France \n", "1563 29 FR France \n", "1564 26 FR France \n", "1565 25 FR France \n", "1566 20 FR France \n", "1567 36 FR France \n", "1568 38 FR France \n", "1569 36 FR France \n", "1570 45 FR France \n", "1571 43 FR France \n", "1572 28 FR France \n", "1573 5 FR France \n", "\n", "[1574 rows x 10 columns]" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = raw_data.dropna().copy()\n", "data" ] }, { "cell_type": "code", "execution_count": 27, "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": 28, "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" ] }, { "cell_type": "code", "execution_count": 29, "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": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 30, "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": [ "sorted_data['inc'].plot()" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "first_september_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", " for y in range(1985,\n", " sorted_data.index[-1].year)]" ] }, { "cell_type": "code", "execution_count": 34, "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)-51) < 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": 36, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 36, "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": 37, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1986 0\n", "1987 0\n", "1988 0\n", "1989 0\n", "1990 0\n", "2020 221186\n", "2002 516689\n", "2018 542312\n", "2017 551041\n", "1991 553090\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": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.sort_values()" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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