diff --git a/module3/exo1/Untitled.ipynb b/module3/exo1/Untitled.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..7fec51502cbc3200b3d0ffc6bbba1fe85e197f3d --- /dev/null +++ b/module3/exo1/Untitled.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb index 0bbbe371b01e359e381e43239412d77bf53fb1fb..5de6e599d48218994d038b46bab9ee311795f3b0 100644 --- a/module3/exo2/exercice.ipynb +++ b/module3/exo2/exercice.ipynb @@ -1,5 +1,2256 @@ { - "cells": [], + "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" + ] + }, + { + "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": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020214579178662511731141018FRFrance
12021447876256531187113818FRFrance
22021437814551641112612717FRFrance
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 9178 6625 11731 14 10 \n", + "1 202144 7 8762 5653 11871 13 8 \n", + "2 202143 7 8145 5164 11126 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 18 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": 3, + "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": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
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": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "raw_data[raw_data.isnull().any(axis=1)]" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020214579178662511731141018FRFrance
12021447876256531187113818FRFrance
22021437814551641112612717FRFrance
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 9178 6625 11731 14 10 \n", + "1 202144 7 8762 5653 11871 13 8 \n", + "2 202143 7 8145 5164 11126 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 18 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": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = raw_data.dropna().copy()\n", + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "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": 7, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_data = data.set_index('period').sort_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "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": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sorted_data['inc'].plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "first_august_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", + " for y in range(1992,\n", + " sorted_data.index[-1].year)]" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "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": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "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": 18, + "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", + "2009 842373\n", + "dtype: int64" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "yearly_incidence.sort_values()" + ] + }, + { + "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "yearly_incidence.hist(xrot=20)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], "metadata": { "kernelspec": { "display_name": "Python 3", @@ -16,10 +2267,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.3" + "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 } -