diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb index 0bbbe371b01e359e381e43239412d77bf53fb1fb..7f134afda2de45e49a2cf20fe87f59078958b5db 100644 --- a/module3/exo2/exercice.ipynb +++ b/module3/exo2/exercice.ipynb @@ -1,5 +1,1194 @@ { - "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": [ + "raw_data = pd.read_csv(\"https://www.sentiweb.fr/datasets/all/inc-7-PAY.csv\",skiprows=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
0202537794801992103FRFrance
1202536716083342882204FRFrance
2202535713271622492204FRFrance
320253471438482828204FRFrance
4202533735796926466519FRFrance
52025327238404809408FRFrance
6202531757030130829020FRFrance
72025307710235901061411616FRFrance
8202529763853384938610614FRFrance
920252875584312380458412FRFrance
1020252775667285084848412FRFrance
1120252675872328584599513FRFrance
1220252575953369882089612FRFrance
1320252474580255866027410FRFrance
1420252374911266371597410FRFrance
15202522768373940973410614FRFrance
1620252174693265367337410FRFrance
172025207308315354631537FRFrance
1820251975084199781718313FRFrance
1920251875003271872887410FRFrance
2020251776246342490689513FRFrance
2120251676151319391099513FRFrance
2220251575557326278528511FRFrance
2320251474984285871107410FRFrance
2420251375964360883209513FRFrance
252025127385519955715639FRFrance
2620251175878274790099414FRFrance
272025107292114214421426FRFrance
282025097338114685294528FRFrance
292025087283512864384426FRFrance
.................................
17851991267176081130423912312042FRFrance
17861991257161691070021638281838FRFrance
17871991247161711007122271281739FRFrance
1788199123711947767116223211329FRFrance
1789199122715452995320951271737FRFrance
1790199121714903897520831261636FRFrance
17911991207190531274225364342345FRFrance
17921991197167391124622232291939FRFrance
17931991187213851388228888382551FRFrance
1794199117713462887718047241632FRFrance
17951991167148571006819646261834FRFrance
1796199115713975978118169251832FRFrance
1797199114712265768416846221430FRFrance
179819911379567604113093171123FRFrance
1799199112710864733114397191325FRFrance
18001991117155741118419964271935FRFrance
18011991107166431137221914292038FRFrance
1802199109713741878018702241533FRFrance
1803199108713289881317765231531FRFrance
1804199107712337807716597221529FRFrance
1805199106710877701314741191226FRFrance
1806199105710442654414340181125FRFrance
18071991047791345631126314820FRFrance
18081991037153871048420290271836FRFrance
18091991027162771104621508292038FRFrance
18101991017155651027120859271836FRFrance
18111990527193751329525455342345FRFrance
18121990517190801380724353342543FRFrance
1813199050711079666015498201228FRFrance
18141990497114302610205FRFrance
\n", + "

1815 rows × 10 columns

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" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202537 7 948 0 1992 1 0 \n", + "1 202536 7 1608 334 2882 2 0 \n", + "2 202535 7 1327 162 2492 2 0 \n", + "3 202534 7 1438 48 2828 2 0 \n", + "4 202533 7 3579 692 6466 5 1 \n", + "5 202532 7 2384 0 4809 4 0 \n", + "6 202531 7 5703 0 13082 9 0 \n", + "7 202530 7 7102 3590 10614 11 6 \n", + "8 202529 7 6385 3384 9386 10 6 \n", + "9 202528 7 5584 3123 8045 8 4 \n", + "10 202527 7 5667 2850 8484 8 4 \n", + "11 202526 7 5872 3285 8459 9 5 \n", + "12 202525 7 5953 3698 8208 9 6 \n", + "13 202524 7 4580 2558 6602 7 4 \n", + "14 202523 7 4911 2663 7159 7 4 \n", + "15 202522 7 6837 3940 9734 10 6 \n", + "16 202521 7 4693 2653 6733 7 4 \n", + "17 202520 7 3083 1535 4631 5 3 \n", + "18 202519 7 5084 1997 8171 8 3 \n", + "19 202518 7 5003 2718 7288 7 4 \n", + "20 202517 7 6246 3424 9068 9 5 \n", + "21 202516 7 6151 3193 9109 9 5 \n", + "22 202515 7 5557 3262 7852 8 5 \n", + "23 202514 7 4984 2858 7110 7 4 \n", + "24 202513 7 5964 3608 8320 9 5 \n", + "25 202512 7 3855 1995 5715 6 3 \n", + "26 202511 7 5878 2747 9009 9 4 \n", + "27 202510 7 2921 1421 4421 4 2 \n", + "28 202509 7 3381 1468 5294 5 2 \n", + "29 202508 7 2835 1286 4384 4 2 \n", + "... ... ... ... ... ... ... ... \n", + "1785 199126 7 17608 11304 23912 31 20 \n", + "1786 199125 7 16169 10700 21638 28 18 \n", + "1787 199124 7 16171 10071 22271 28 17 \n", + "1788 199123 7 11947 7671 16223 21 13 \n", + "1789 199122 7 15452 9953 20951 27 17 \n", + "1790 199121 7 14903 8975 20831 26 16 \n", + "1791 199120 7 19053 12742 25364 34 23 \n", + "1792 199119 7 16739 11246 22232 29 19 \n", + "1793 199118 7 21385 13882 28888 38 25 \n", + "1794 199117 7 13462 8877 18047 24 16 \n", + "1795 199116 7 14857 10068 19646 26 18 \n", + "1796 199115 7 13975 9781 18169 25 18 \n", + "1797 199114 7 12265 7684 16846 22 14 \n", + "1798 199113 7 9567 6041 13093 17 11 \n", + "1799 199112 7 10864 7331 14397 19 13 \n", + "1800 199111 7 15574 11184 19964 27 19 \n", + "1801 199110 7 16643 11372 21914 29 20 \n", + "1802 199109 7 13741 8780 18702 24 15 \n", + "1803 199108 7 13289 8813 17765 23 15 \n", + "1804 199107 7 12337 8077 16597 22 15 \n", + "1805 199106 7 10877 7013 14741 19 12 \n", + "1806 199105 7 10442 6544 14340 18 11 \n", + "1807 199104 7 7913 4563 11263 14 8 \n", + "1808 199103 7 15387 10484 20290 27 18 \n", + "1809 199102 7 16277 11046 21508 29 20 \n", + "1810 199101 7 15565 10271 20859 27 18 \n", + "1811 199052 7 19375 13295 25455 34 23 \n", + "1812 199051 7 19080 13807 24353 34 25 \n", + "1813 199050 7 11079 6660 15498 20 12 \n", + "1814 199049 7 1143 0 2610 2 0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 3 FR France \n", + "1 4 FR France \n", + "2 4 FR France \n", + "3 4 FR France \n", + "4 9 FR France \n", + "5 8 FR France \n", + "6 20 FR France \n", + "7 16 FR France \n", + "8 14 FR France \n", + "9 12 FR France \n", + "10 12 FR France \n", + "11 13 FR France \n", + "12 12 FR France \n", + "13 10 FR France \n", + "14 10 FR France \n", + "15 14 FR France \n", + "16 10 FR France \n", + "17 7 FR France \n", + "18 13 FR France \n", + "19 10 FR France \n", + "20 13 FR France \n", + "21 13 FR France \n", + "22 11 FR France \n", + "23 10 FR France \n", + "24 13 FR France \n", + "25 9 FR France \n", + "26 14 FR France \n", + "27 6 FR France \n", + "28 8 FR France \n", + "29 6 FR France \n", + "... ... ... ... \n", + "1785 42 FR France \n", + "1786 38 FR France \n", + "1787 39 FR France \n", + "1788 29 FR France \n", + "1789 37 FR France \n", + "1790 36 FR France \n", + "1791 45 FR France \n", + "1792 39 FR France \n", + "1793 51 FR France \n", + "1794 32 FR France \n", + "1795 34 FR France \n", + "1796 32 FR France \n", + "1797 30 FR France \n", + "1798 23 FR France \n", + "1799 25 FR France \n", + "1800 35 FR France \n", + "1801 38 FR France \n", + "1802 33 FR France \n", + "1803 31 FR France \n", + "1804 29 FR France \n", + "1805 26 FR France \n", + "1806 25 FR France \n", + "1807 20 FR France \n", + "1808 36 FR France \n", + "1809 38 FR France \n", + "1810 36 FR France \n", + "1811 45 FR France \n", + "1812 43 FR France \n", + "1813 28 FR France \n", + "1814 5 FR France \n", + "\n", + "[1815 rows x 10 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = raw_data.dropna().copy()\n", + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "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": 6, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_data = data.set_index('period').sort_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "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": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "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": 21, + "metadata": {}, + "outputs": [], + "source": [ + "first_august_week = [pd.Period(pd.Timestamp(y, 10, 1), 'W')\n", + " for y in range(1991,\n", + " sorted_data.index[-1].year)]" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "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": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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