{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import isoweek\n", "import requests" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"\n", "data_filename = 'incidence-PAY-7.csv'" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
0202145710708715614260161121FRFrance
12021447868053431201713818FRFrance
22021437816451791114912717FRFrance
32021427944360371284914919FRFrance
42021417402122395803639FRFrance
520214074441245464287410FRFrance
62021397229110563526315FRFrance
720213874325226763837410FRFrance
8202137719647543174315FRFrance
92021367344117305152528FRFrance
102021357256211074017426FRFrance
11202134714293782480204FRFrance
122021337382918305828639FRFrance
132021327410818956321639FRFrance
1420213174793230172857311FRFrance
152021307719041911018911616FRFrance
16202129768004109949110614FRFrance
172021287973402173115033FRFrance
182021277902643161373614721FRFrance
192021267728441081046011616FRFrance
2020212579351654012162141018FRFrance
21202124712034893715131181323FRFrance
2220212379116642011812141018FRFrance
2320212274817275268827410FRFrance
2420212176092345887269513FRFrance
252021207748546011036911715FRFrance
26202119766544370893810713FRFrance
272021187391221105714639FRFrance
2820211774686287864947410FRFrance
2920211674780289166697410FRFrance
.................................
15851991267176081130423912312042FRFrance
15861991257161691070021638281838FRFrance
15871991247161711007122271281739FRFrance
1588199123711947767116223211329FRFrance
1589199122715452995320951271737FRFrance
1590199121714903897520831261636FRFrance
15911991207190531274225364342345FRFrance
15921991197167391124622232291939FRFrance
15931991187213851388228888382551FRFrance
1594199117713462887718047241632FRFrance
15951991167148571006819646261834FRFrance
1596199115713975978118169251832FRFrance
1597199114712265768416846221430FRFrance
159819911379567604113093171123FRFrance
1599199112710864733114397191325FRFrance
16001991117155741118419964271935FRFrance
16011991107166431137221914292038FRFrance
1602199109713741878018702241533FRFrance
1603199108713289881317765231531FRFrance
1604199107712337807716597221529FRFrance
1605199106710877701314741191226FRFrance
1606199105710442654414340181125FRFrance
16071991047791345631126314820FRFrance
16081991037153871048420290271836FRFrance
16091991027162771104621508292038FRFrance
16101991017155651027120859271836FRFrance
16111990527193751329525455342345FRFrance
16121990517190801380724353342543FRFrance
1613199050711079666015498201228FRFrance
16141990497114302610205FRFrance
\n", "

1615 rows × 10 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202145 7 10708 7156 14260 16 11 \n", "1 202144 7 8680 5343 12017 13 8 \n", "2 202143 7 8164 5179 11149 12 7 \n", "3 202142 7 9443 6037 12849 14 9 \n", "4 202141 7 4021 2239 5803 6 3 \n", "5 202140 7 4441 2454 6428 7 4 \n", "6 202139 7 2291 1056 3526 3 1 \n", "7 202138 7 4325 2267 6383 7 4 \n", "8 202137 7 1964 754 3174 3 1 \n", "9 202136 7 3441 1730 5152 5 2 \n", "10 202135 7 2562 1107 4017 4 2 \n", "11 202134 7 1429 378 2480 2 0 \n", "12 202133 7 3829 1830 5828 6 3 \n", "13 202132 7 4108 1895 6321 6 3 \n", "14 202131 7 4793 2301 7285 7 3 \n", "15 202130 7 7190 4191 10189 11 6 \n", "16 202129 7 6800 4109 9491 10 6 \n", "17 202128 7 9734 0 21731 15 0 \n", "18 202127 7 9026 4316 13736 14 7 \n", "19 202126 7 7284 4108 10460 11 6 \n", "20 202125 7 9351 6540 12162 14 10 \n", "21 202124 7 12034 8937 15131 18 13 \n", "22 202123 7 9116 6420 11812 14 10 \n", "23 202122 7 4817 2752 6882 7 4 \n", "24 202121 7 6092 3458 8726 9 5 \n", "25 202120 7 7485 4601 10369 11 7 \n", "26 202119 7 6654 4370 8938 10 7 \n", "27 202118 7 3912 2110 5714 6 3 \n", "28 202117 7 4686 2878 6494 7 4 \n", "29 202116 7 4780 2891 6669 7 4 \n", "... ... ... ... ... ... ... ... \n", "1585 199126 7 17608 11304 23912 31 20 \n", "1586 199125 7 16169 10700 21638 28 18 \n", "1587 199124 7 16171 10071 22271 28 17 \n", "1588 199123 7 11947 7671 16223 21 13 \n", "1589 199122 7 15452 9953 20951 27 17 \n", "1590 199121 7 14903 8975 20831 26 16 \n", "1591 199120 7 19053 12742 25364 34 23 \n", "1592 199119 7 16739 11246 22232 29 19 \n", "1593 199118 7 21385 13882 28888 38 25 \n", "1594 199117 7 13462 8877 18047 24 16 \n", "1595 199116 7 14857 10068 19646 26 18 \n", "1596 199115 7 13975 9781 18169 25 18 \n", "1597 199114 7 12265 7684 16846 22 14 \n", "1598 199113 7 9567 6041 13093 17 11 \n", "1599 199112 7 10864 7331 14397 19 13 \n", "1600 199111 7 15574 11184 19964 27 19 \n", "1601 199110 7 16643 11372 21914 29 20 \n", "1602 199109 7 13741 8780 18702 24 15 \n", "1603 199108 7 13289 8813 17765 23 15 \n", "1604 199107 7 12337 8077 16597 22 15 \n", "1605 199106 7 10877 7013 14741 19 12 \n", "1606 199105 7 10442 6544 14340 18 11 \n", "1607 199104 7 7913 4563 11263 14 8 \n", "1608 199103 7 15387 10484 20290 27 18 \n", "1609 199102 7 16277 11046 21508 29 20 \n", "1610 199101 7 15565 10271 20859 27 18 \n", "1611 199052 7 19375 13295 25455 34 23 \n", "1612 199051 7 19080 13807 24353 34 25 \n", "1613 199050 7 11079 6660 15498 20 12 \n", "1614 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 21 FR France \n", "1 18 FR France \n", "2 17 FR France \n", "3 19 FR France \n", "4 9 FR France \n", "5 10 FR France \n", "6 5 FR France \n", "7 10 FR France \n", "8 5 FR France \n", "9 8 FR France \n", "10 6 FR France \n", "11 4 FR France \n", "12 9 FR France \n", "13 9 FR France \n", "14 11 FR France \n", "15 16 FR France \n", "16 14 FR France \n", "17 33 FR France \n", "18 21 FR France \n", "19 16 FR France \n", "20 18 FR France \n", "21 23 FR France \n", "22 18 FR France \n", "23 10 FR France \n", "24 13 FR France \n", "25 15 FR France \n", "26 13 FR France \n", "27 9 FR France \n", "28 10 FR France \n", "29 10 FR France \n", "... ... ... ... \n", "1585 42 FR France \n", "1586 38 FR France \n", "1587 39 FR France \n", "1588 29 FR France \n", "1589 37 FR France \n", "1590 36 FR France \n", "1591 45 FR France \n", "1592 39 FR France \n", "1593 51 FR France \n", "1594 32 FR France \n", "1595 34 FR France \n", "1596 32 FR France \n", "1597 30 FR France \n", "1598 23 FR France \n", "1599 25 FR France \n", "1600 35 FR France \n", "1601 38 FR France \n", "1602 33 FR France \n", "1603 31 FR France \n", "1604 29 FR France \n", "1605 26 FR France \n", "1606 25 FR France \n", "1607 20 FR France \n", "1608 36 FR France \n", "1609 38 FR France \n", "1610 36 FR France \n", "1611 45 FR France \n", "1612 43 FR France \n", "1613 28 FR France \n", "1614 5 FR France \n", "\n", "[1615 rows x 10 columns]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# On essaie de lire le fichier csv local si il existe, sinon on le telecharge\n", "# de maniere a avoir une copie locale\n", "\n", "try:\n", " raw_data = pd.read_csv(data_filename, skiprows=1)\n", "except FileNotFoundError:\n", " req = requests.get(data_url)\n", " url_content = req.content\n", " csv_file = open(data_filename, 'wb')\n", " csv_file.write(url_content)\n", " \n", "raw_data = pd.read_csv(data_filename, skiprows=1)\n", "raw_data" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "raw_data[raw_data.isnull().any(axis=1)]\n", "# pas de données manquantes\n", "data = raw_data" ] }, { "cell_type": "code", "execution_count": 13, "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": 14, "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" ] }, { "cell_type": "code", "execution_count": 16, "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": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_nameperiod
0202145710708715614260161121FRFrance2021-11-08/2021-11-14
12021447868053431201713818FRFrance2021-11-01/2021-11-07
22021437816451791114912717FRFrance2021-10-25/2021-10-31
32021427944360371284914919FRFrance2021-10-18/2021-10-24
42021417402122395803639FRFrance2021-10-11/2021-10-17
520214074441245464287410FRFrance2021-10-04/2021-10-10
62021397229110563526315FRFrance2021-09-27/2021-10-03
720213874325226763837410FRFrance2021-09-20/2021-09-26
8202137719647543174315FRFrance2021-09-13/2021-09-19
92021367344117305152528FRFrance2021-09-06/2021-09-12
102021357256211074017426FRFrance2021-08-30/2021-09-05
11202134714293782480204FRFrance2021-08-23/2021-08-29
122021337382918305828639FRFrance2021-08-16/2021-08-22
132021327410818956321639FRFrance2021-08-09/2021-08-15
1420213174793230172857311FRFrance2021-08-02/2021-08-08
152021307719041911018911616FRFrance2021-07-26/2021-08-01
16202129768004109949110614FRFrance2021-07-19/2021-07-25
172021287973402173115033FRFrance2021-07-12/2021-07-18
182021277902643161373614721FRFrance2021-07-05/2021-07-11
192021267728441081046011616FRFrance2021-06-28/2021-07-04
2020212579351654012162141018FRFrance2021-06-21/2021-06-27
21202124712034893715131181323FRFrance2021-06-14/2021-06-20
2220212379116642011812141018FRFrance2021-06-07/2021-06-13
2320212274817275268827410FRFrance2021-05-31/2021-06-06
2420212176092345887269513FRFrance2021-05-24/2021-05-30
252021207748546011036911715FRFrance2021-05-17/2021-05-23
26202119766544370893810713FRFrance2021-05-10/2021-05-16
272021187391221105714639FRFrance2021-05-03/2021-05-09
2820211774686287864947410FRFrance2021-04-26/2021-05-02
2920211674780289166697410FRFrance2021-04-19/2021-04-25
....................................
15851991267176081130423912312042FRFrance1991-06-24/1991-06-30
15861991257161691070021638281838FRFrance1991-06-17/1991-06-23
15871991247161711007122271281739FRFrance1991-06-10/1991-06-16
1588199123711947767116223211329FRFrance1991-06-03/1991-06-09
1589199122715452995320951271737FRFrance1991-05-27/1991-06-02
1590199121714903897520831261636FRFrance1991-05-20/1991-05-26
15911991207190531274225364342345FRFrance1991-05-13/1991-05-19
15921991197167391124622232291939FRFrance1991-05-06/1991-05-12
15931991187213851388228888382551FRFrance1991-04-29/1991-05-05
1594199117713462887718047241632FRFrance1991-04-22/1991-04-28
15951991167148571006819646261834FRFrance1991-04-15/1991-04-21
1596199115713975978118169251832FRFrance1991-04-08/1991-04-14
1597199114712265768416846221430FRFrance1991-04-01/1991-04-07
159819911379567604113093171123FRFrance1991-03-25/1991-03-31
1599199112710864733114397191325FRFrance1991-03-18/1991-03-24
16001991117155741118419964271935FRFrance1991-03-11/1991-03-17
16011991107166431137221914292038FRFrance1991-03-04/1991-03-10
1602199109713741878018702241533FRFrance1991-02-25/1991-03-03
1603199108713289881317765231531FRFrance1991-02-18/1991-02-24
1604199107712337807716597221529FRFrance1991-02-11/1991-02-17
1605199106710877701314741191226FRFrance1991-02-04/1991-02-10
1606199105710442654414340181125FRFrance1991-01-28/1991-02-03
16071991047791345631126314820FRFrance1991-01-21/1991-01-27
16081991037153871048420290271836FRFrance1991-01-14/1991-01-20
16091991027162771104621508292038FRFrance1991-01-07/1991-01-13
16101991017155651027120859271836FRFrance1990-12-31/1991-01-06
16111990527193751329525455342345FRFrance1990-12-24/1990-12-30
16121990517190801380724353342543FRFrance1990-12-17/1990-12-23
1613199050711079666015498201228FRFrance1990-12-10/1990-12-16
16141990497114302610205FRFrance1990-12-03/1990-12-09
\n", "

1615 rows × 11 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202145 7 10708 7156 14260 16 11 \n", "1 202144 7 8680 5343 12017 13 8 \n", "2 202143 7 8164 5179 11149 12 7 \n", "3 202142 7 9443 6037 12849 14 9 \n", "4 202141 7 4021 2239 5803 6 3 \n", "5 202140 7 4441 2454 6428 7 4 \n", "6 202139 7 2291 1056 3526 3 1 \n", "7 202138 7 4325 2267 6383 7 4 \n", "8 202137 7 1964 754 3174 3 1 \n", "9 202136 7 3441 1730 5152 5 2 \n", "10 202135 7 2562 1107 4017 4 2 \n", "11 202134 7 1429 378 2480 2 0 \n", "12 202133 7 3829 1830 5828 6 3 \n", "13 202132 7 4108 1895 6321 6 3 \n", "14 202131 7 4793 2301 7285 7 3 \n", "15 202130 7 7190 4191 10189 11 6 \n", "16 202129 7 6800 4109 9491 10 6 \n", "17 202128 7 9734 0 21731 15 0 \n", "18 202127 7 9026 4316 13736 14 7 \n", "19 202126 7 7284 4108 10460 11 6 \n", "20 202125 7 9351 6540 12162 14 10 \n", "21 202124 7 12034 8937 15131 18 13 \n", "22 202123 7 9116 6420 11812 14 10 \n", "23 202122 7 4817 2752 6882 7 4 \n", "24 202121 7 6092 3458 8726 9 5 \n", "25 202120 7 7485 4601 10369 11 7 \n", "26 202119 7 6654 4370 8938 10 7 \n", "27 202118 7 3912 2110 5714 6 3 \n", "28 202117 7 4686 2878 6494 7 4 \n", "29 202116 7 4780 2891 6669 7 4 \n", "... ... ... ... ... ... ... ... \n", "1585 199126 7 17608 11304 23912 31 20 \n", "1586 199125 7 16169 10700 21638 28 18 \n", "1587 199124 7 16171 10071 22271 28 17 \n", "1588 199123 7 11947 7671 16223 21 13 \n", "1589 199122 7 15452 9953 20951 27 17 \n", "1590 199121 7 14903 8975 20831 26 16 \n", "1591 199120 7 19053 12742 25364 34 23 \n", "1592 199119 7 16739 11246 22232 29 19 \n", "1593 199118 7 21385 13882 28888 38 25 \n", "1594 199117 7 13462 8877 18047 24 16 \n", "1595 199116 7 14857 10068 19646 26 18 \n", "1596 199115 7 13975 9781 18169 25 18 \n", "1597 199114 7 12265 7684 16846 22 14 \n", "1598 199113 7 9567 6041 13093 17 11 \n", "1599 199112 7 10864 7331 14397 19 13 \n", "1600 199111 7 15574 11184 19964 27 19 \n", "1601 199110 7 16643 11372 21914 29 20 \n", "1602 199109 7 13741 8780 18702 24 15 \n", "1603 199108 7 13289 8813 17765 23 15 \n", "1604 199107 7 12337 8077 16597 22 15 \n", "1605 199106 7 10877 7013 14741 19 12 \n", "1606 199105 7 10442 6544 14340 18 11 \n", "1607 199104 7 7913 4563 11263 14 8 \n", "1608 199103 7 15387 10484 20290 27 18 \n", "1609 199102 7 16277 11046 21508 29 20 \n", "1610 199101 7 15565 10271 20859 27 18 \n", "1611 199052 7 19375 13295 25455 34 23 \n", "1612 199051 7 19080 13807 24353 34 25 \n", "1613 199050 7 11079 6660 15498 20 12 \n", "1614 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name period \n", "0 21 FR France 2021-11-08/2021-11-14 \n", "1 18 FR France 2021-11-01/2021-11-07 \n", "2 17 FR France 2021-10-25/2021-10-31 \n", "3 19 FR France 2021-10-18/2021-10-24 \n", "4 9 FR France 2021-10-11/2021-10-17 \n", "5 10 FR France 2021-10-04/2021-10-10 \n", "6 5 FR France 2021-09-27/2021-10-03 \n", "7 10 FR France 2021-09-20/2021-09-26 \n", "8 5 FR France 2021-09-13/2021-09-19 \n", "9 8 FR France 2021-09-06/2021-09-12 \n", "10 6 FR France 2021-08-30/2021-09-05 \n", "11 4 FR France 2021-08-23/2021-08-29 \n", "12 9 FR France 2021-08-16/2021-08-22 \n", "13 9 FR France 2021-08-09/2021-08-15 \n", "14 11 FR France 2021-08-02/2021-08-08 \n", "15 16 FR France 2021-07-26/2021-08-01 \n", "16 14 FR France 2021-07-19/2021-07-25 \n", "17 33 FR France 2021-07-12/2021-07-18 \n", "18 21 FR France 2021-07-05/2021-07-11 \n", "19 16 FR France 2021-06-28/2021-07-04 \n", "20 18 FR France 2021-06-21/2021-06-27 \n", "21 23 FR France 2021-06-14/2021-06-20 \n", "22 18 FR France 2021-06-07/2021-06-13 \n", "23 10 FR France 2021-05-31/2021-06-06 \n", "24 13 FR France 2021-05-24/2021-05-30 \n", "25 15 FR France 2021-05-17/2021-05-23 \n", "26 13 FR France 2021-05-10/2021-05-16 \n", "27 9 FR France 2021-05-03/2021-05-09 \n", "28 10 FR France 2021-04-26/2021-05-02 \n", "29 10 FR France 2021-04-19/2021-04-25 \n", "... ... ... ... ... \n", "1585 42 FR France 1991-06-24/1991-06-30 \n", "1586 38 FR France 1991-06-17/1991-06-23 \n", "1587 39 FR France 1991-06-10/1991-06-16 \n", "1588 29 FR France 1991-06-03/1991-06-09 \n", "1589 37 FR France 1991-05-27/1991-06-02 \n", "1590 36 FR France 1991-05-20/1991-05-26 \n", "1591 45 FR France 1991-05-13/1991-05-19 \n", "1592 39 FR France 1991-05-06/1991-05-12 \n", "1593 51 FR France 1991-04-29/1991-05-05 \n", "1594 32 FR France 1991-04-22/1991-04-28 \n", "1595 34 FR France 1991-04-15/1991-04-21 \n", "1596 32 FR France 1991-04-08/1991-04-14 \n", "1597 30 FR France 1991-04-01/1991-04-07 \n", "1598 23 FR France 1991-03-25/1991-03-31 \n", "1599 25 FR France 1991-03-18/1991-03-24 \n", "1600 35 FR France 1991-03-11/1991-03-17 \n", "1601 38 FR France 1991-03-04/1991-03-10 \n", "1602 33 FR France 1991-02-25/1991-03-03 \n", "1603 31 FR France 1991-02-18/1991-02-24 \n", "1604 29 FR France 1991-02-11/1991-02-17 \n", "1605 26 FR France 1991-02-04/1991-02-10 \n", "1606 25 FR France 1991-01-28/1991-02-03 \n", "1607 20 FR France 1991-01-21/1991-01-27 \n", "1608 36 FR France 1991-01-14/1991-01-20 \n", "1609 38 FR France 1991-01-07/1991-01-13 \n", "1610 36 FR France 1990-12-31/1991-01-06 \n", "1611 45 FR France 1990-12-24/1990-12-30 \n", "1612 43 FR France 1990-12-17/1990-12-23 \n", "1613 28 FR France 1990-12-10/1990-12-16 \n", "1614 5 FR France 1990-12-03/1990-12-09 \n", "\n", "[1615 rows x 11 columns]" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "first_sep_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": 27, "metadata": {}, "outputs": [], "source": [ "year = []\n", "yearly_incidence = []\n", "for week1, week2 in zip(first_sep_week[:-1],\n", " first_sep_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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ " yearly_incidence.plot(style='*')" ] }, { "cell_type": "code", "execution_count": 30, "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": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.sort_values()" ] } ], "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 }