diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb index 0bbbe371b01e359e381e43239412d77bf53fb1fb..00ccbdbe9919a22bbca3be541c767c4bc4a62c58 100644 --- a/module3/exo2/exercice.ipynb +++ b/module3/exo2/exercice.ipynb @@ -1,5 +1,2224 @@ { - "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": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020204975164288074488511FRFrance
1202048767474331916310614FRFrance
220204774999296370358511FRFrance
32020467375219635541639FRFrance
42020457369620165376639FRFrance
520204474391237564077410FRFrance
620204374376250562477410FRFrance
72020427400019796021639FRFrance
82020417396120995823639FRFrance
9202040720786753481315FRFrance
10202039710492371861213FRFrance
11202038722537823724315FRFrance
12202037715844052763204FRFrance
1320203679191001738102FRFrance
14202035782801694102FRFrance
15202034722723714173306FRFrance
16202033712841772391204FRFrance
17202032726506894611417FRFrance
18202031713031002506204FRFrance
1920203071385752695204FRFrance
202020297841101672102FRFrance
21202028772801515102FRFrance
2220202779861491823102FRFrance
23202026769401454102FRFrance
2420202572280597001FRFrance
2520202473880959102FRFrance
26202023755811115102FRFrance
2720202272770633001FRFrance
282020217602361168102FRFrance
292020207824201628102FRFrance
.................................
15361991267176081130423912312042FRFrance
15371991257161691070021638281838FRFrance
15381991247161711007122271281739FRFrance
1539199123711947767116223211329FRFrance
1540199122715452995320951271737FRFrance
1541199121714903897520831261636FRFrance
15421991207190531274225364342345FRFrance
15431991197167391124622232291939FRFrance
15441991187213851388228888382551FRFrance
1545199117713462887718047241632FRFrance
15461991167148571006819646261834FRFrance
1547199115713975978118169251832FRFrance
1548199114712265768416846221430FRFrance
154919911379567604113093171123FRFrance
1550199112710864733114397191325FRFrance
15511991117155741118419964271935FRFrance
15521991107166431137221914292038FRFrance
1553199109713741878018702241533FRFrance
1554199108713289881317765231531FRFrance
1555199107712337807716597221529FRFrance
1556199106710877701314741191226FRFrance
1557199105710442654414340181125FRFrance
15581991047791345631126314820FRFrance
15591991037153871048420290271836FRFrance
15601991027162771104621508292038FRFrance
15611991017155651027120859271836FRFrance
15621990527193751329525455342345FRFrance
15631990517190801380724353342543FRFrance
1564199050711079666015498201228FRFrance
15651990497114302610205FRFrance
\n", + "

1566 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202049 7 5164 2880 7448 8 5 \n", + "1 202048 7 6747 4331 9163 10 6 \n", + "2 202047 7 4999 2963 7035 8 5 \n", + "3 202046 7 3752 1963 5541 6 3 \n", + "4 202045 7 3696 2016 5376 6 3 \n", + "5 202044 7 4391 2375 6407 7 4 \n", + "6 202043 7 4376 2505 6247 7 4 \n", + "7 202042 7 4000 1979 6021 6 3 \n", + "8 202041 7 3961 2099 5823 6 3 \n", + "9 202040 7 2078 675 3481 3 1 \n", + "10 202039 7 1049 237 1861 2 1 \n", + "11 202038 7 2253 782 3724 3 1 \n", + "12 202037 7 1584 405 2763 2 0 \n", + "13 202036 7 919 100 1738 1 0 \n", + "14 202035 7 828 0 1694 1 0 \n", + "15 202034 7 2272 371 4173 3 0 \n", + "16 202033 7 1284 177 2391 2 0 \n", + "17 202032 7 2650 689 4611 4 1 \n", + "18 202031 7 1303 100 2506 2 0 \n", + "19 202030 7 1385 75 2695 2 0 \n", + "20 202029 7 841 10 1672 1 0 \n", + "21 202028 7 728 0 1515 1 0 \n", + "22 202027 7 986 149 1823 1 0 \n", + "23 202026 7 694 0 1454 1 0 \n", + "24 202025 7 228 0 597 0 0 \n", + "25 202024 7 388 0 959 1 0 \n", + "26 202023 7 558 1 1115 1 0 \n", + "27 202022 7 277 0 633 0 0 \n", + "28 202021 7 602 36 1168 1 0 \n", + "29 202020 7 824 20 1628 1 0 \n", + "... ... ... ... ... ... ... ... \n", + "1536 199126 7 17608 11304 23912 31 20 \n", + "1537 199125 7 16169 10700 21638 28 18 \n", + "1538 199124 7 16171 10071 22271 28 17 \n", + "1539 199123 7 11947 7671 16223 21 13 \n", + "1540 199122 7 15452 9953 20951 27 17 \n", + "1541 199121 7 14903 8975 20831 26 16 \n", + "1542 199120 7 19053 12742 25364 34 23 \n", + "1543 199119 7 16739 11246 22232 29 19 \n", + "1544 199118 7 21385 13882 28888 38 25 \n", + "1545 199117 7 13462 8877 18047 24 16 \n", + "1546 199116 7 14857 10068 19646 26 18 \n", + "1547 199115 7 13975 9781 18169 25 18 \n", + "1548 199114 7 12265 7684 16846 22 14 \n", + "1549 199113 7 9567 6041 13093 17 11 \n", + "1550 199112 7 10864 7331 14397 19 13 \n", + "1551 199111 7 15574 11184 19964 27 19 \n", + "1552 199110 7 16643 11372 21914 29 20 \n", + "1553 199109 7 13741 8780 18702 24 15 \n", + "1554 199108 7 13289 8813 17765 23 15 \n", + "1555 199107 7 12337 8077 16597 22 15 \n", + "1556 199106 7 10877 7013 14741 19 12 \n", + "1557 199105 7 10442 6544 14340 18 11 \n", + "1558 199104 7 7913 4563 11263 14 8 \n", + "1559 199103 7 15387 10484 20290 27 18 \n", + "1560 199102 7 16277 11046 21508 29 20 \n", + "1561 199101 7 15565 10271 20859 27 18 \n", + "1562 199052 7 19375 13295 25455 34 23 \n", + "1563 199051 7 19080 13807 24353 34 25 \n", + "1564 199050 7 11079 6660 15498 20 12 \n", + "1565 199049 7 1143 0 2610 2 0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 11 FR France \n", + "1 14 FR France \n", + "2 11 FR France \n", + "3 9 FR France \n", + "4 9 FR France \n", + "5 10 FR France \n", + "6 10 FR France \n", + "7 9 FR France \n", + "8 9 FR France \n", + "9 5 FR France \n", + "10 3 FR France \n", + "11 5 FR France \n", + "12 4 FR France \n", + "13 2 FR France \n", + "14 2 FR France \n", + "15 6 FR France \n", + "16 4 FR France \n", + "17 7 FR France \n", + "18 4 FR France \n", + "19 4 FR France \n", + "20 2 FR France \n", + "21 2 FR France \n", + "22 2 FR France \n", + "23 2 FR France \n", + "24 1 FR France \n", + "25 2 FR France \n", + "26 2 FR France \n", + "27 1 FR France \n", + "28 2 FR France \n", + "29 2 FR France \n", + "... ... ... ... \n", + "1536 42 FR France \n", + "1537 38 FR France \n", + "1538 39 FR France \n", + "1539 29 FR France \n", + "1540 37 FR France \n", + "1541 36 FR France \n", + "1542 45 FR France \n", + "1543 39 FR France \n", + "1544 51 FR France \n", + "1545 32 FR France \n", + "1546 34 FR France \n", + "1547 32 FR France \n", + "1548 30 FR France \n", + "1549 23 FR France \n", + "1550 25 FR France \n", + "1551 35 FR France \n", + "1552 38 FR France \n", + "1553 33 FR France \n", + "1554 31 FR France \n", + "1555 29 FR France \n", + "1556 26 FR France \n", + "1557 25 FR France \n", + "1558 20 FR France \n", + "1559 36 FR France \n", + "1560 38 FR France \n", + "1561 36 FR France \n", + "1562 45 FR France \n", + "1563 43 FR France \n", + "1564 28 FR France \n", + "1565 5 FR France \n", + "\n", + "[1566 rows x 10 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = raw_data.dropna().copy()\n", + "data" + ] + }, + { + "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": [], + "source": [ + "sorted_data = data.set_index('period').sort_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "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": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "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": 19, + "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": 20, + "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": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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