diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb index 6b7464b50420df137552dbce21cb3938f846b81e..0932720f2e42960937d74b42ea709e721b80a072 100644 --- a/module3/exo2/exercice.ipynb +++ b/module3/exo2/exercice.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -28,7 +28,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -52,7 +52,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -65,7 +65,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -1030,7 +1030,7 @@ "[1589 rows x 10 columns]" ] }, - "execution_count": 21, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -1049,7 +1049,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -1096,7 +1096,7 @@ "Index: []" ] }, - "execution_count": 22, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -1123,7 +1123,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -1148,130 +1148,2197 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ - "periods = sorted_raw_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": "markdown", - "metadata": {}, - "source": [ - "Les donnees sont propres.On regarde les donnees" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "sorted_raw_data['inc'][-200:].plot()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Etude de l'incidence annuelle" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Etant donné que le pic de l'épidémie se situe en hiver, à cheval entre deux années civiles, nous définissons la période de référence entre deux minima de l'incidence, du 1er septembre de l'année $N$ au 1er septembre de l'année $N+1$.\n", - "Notre tâche est un peu compliquée par le fait que l'année ne comporte pas un nombre entier de semaines. Nous modifions donc un peu nos périodes de référence: à la place du 1er août de chaque année, nous utilisons le premier jour de la semaine qui contient le 1er août.\n", - "Comme l'incidence de syndrome grippal est très faible en été, cette modification ne risque pas de fausser nos conclusions.\n", - "Encore un petit détail: les données commencent an septembre 1991, ce qui rend la première année incomplète. Nous commençons donc l'analyse en 1991." - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "ename": "SyntaxError", - "evalue": "invalid syntax (, line 3)", - "output_type": "error", - "traceback": [ - "\u001b[0;36m File \u001b[0;32m\"\"\u001b[0;36m, line \u001b[0;32m3\u001b[0m\n\u001b[0;31m sorted_raw_data.index[-1].year)]\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n" - ] + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
period
1990-12-03/1990-12-091990497114302610205FRFrance
1990-12-10/1990-12-16199050711079666015498201228FRFrance
1990-12-17/1990-12-231990517190801380724353342543FRFrance
1990-12-24/1990-12-301990527193751329525455342345FRFrance
1990-12-31/1991-01-061991017155651027120859271836FRFrance
1991-01-07/1991-01-131991027162771104621508292038FRFrance
1991-01-14/1991-01-201991037153871048420290271836FRFrance
1991-01-21/1991-01-271991047791345631126314820FRFrance
1991-01-28/1991-02-03199105710442654414340181125FRFrance
1991-02-04/1991-02-10199106710877701314741191226FRFrance
1991-02-11/1991-02-17199107712337807716597221529FRFrance
1991-02-18/1991-02-24199108713289881317765231531FRFrance
1991-02-25/1991-03-03199109713741878018702241533FRFrance
1991-03-04/1991-03-101991107166431137221914292038FRFrance
1991-03-11/1991-03-171991117155741118419964271935FRFrance
1991-03-18/1991-03-24199112710864733114397191325FRFrance
1991-03-25/1991-03-3119911379567604113093171123FRFrance
1991-04-01/1991-04-07199114712265768416846221430FRFrance
1991-04-08/1991-04-14199115713975978118169251832FRFrance
1991-04-15/1991-04-211991167148571006819646261834FRFrance
1991-04-22/1991-04-28199117713462887718047241632FRFrance
1991-04-29/1991-05-051991187213851388228888382551FRFrance
1991-05-06/1991-05-121991197167391124622232291939FRFrance
1991-05-13/1991-05-191991207190531274225364342345FRFrance
1991-05-20/1991-05-26199121714903897520831261636FRFrance
1991-05-27/1991-06-02199122715452995320951271737FRFrance
1991-06-03/1991-06-09199123711947767116223211329FRFrance
1991-06-10/1991-06-161991247161711007122271281739FRFrance
1991-06-17/1991-06-231991257161691070021638281838FRFrance
1991-06-24/1991-06-301991267176081130423912312042FRFrance
.................................
2020-10-19/2020-10-2520204374376250562477410FRFrance
2020-10-26/2020-11-0120204474391237564077410FRFrance
2020-11-02/2020-11-082020457369620165376639FRFrance
2020-11-09/2020-11-152020467375219635541639FRFrance
2020-11-16/2020-11-2220204774999296370358511FRFrance
2020-11-23/2020-11-29202048766834312905410614FRFrance
2020-11-30/2020-12-0620204975026314569078511FRFrance
2020-12-07/2020-12-13202050770634744938211715FRFrance
2020-12-14/2020-12-20202051710564757413554161121FRFrance
2020-12-21/2020-12-27202052712012828515739181224FRFrance
2020-12-28/2021-01-03202053711978840615550181323FRFrance
2021-01-04/2021-01-10202101710525775013300161220FRFrance
2021-01-11/2021-01-172021027779554301016012816FRFrance
2021-01-18/2021-01-242021037891363751145113917FRFrance
2021-01-25/2021-01-31202104712026882615226181323FRFrance
2021-02-01/2021-02-07202105712210898815432181323FRFrance
2021-02-08/2021-02-14202106713401981016992201525FRFrance
2021-02-15/2021-02-212021077135611031516807211626FRFrance
2021-02-22/2021-02-28202108711281836114201171321FRFrance
2021-03-01/2021-03-07202109710988793814038171222FRFrance
2021-03-08/2021-03-1420211079056645211660141018FRFrance
2021-03-15/2021-03-2120211179386667812094141018FRFrance
2021-03-22/2021-03-28202112711520841514625171222FRFrance
2021-03-29/2021-04-0420211379714628913139151020FRFrance
2021-04-05/2021-04-11202114711197799414400171222FRFrance
2021-04-12/2021-04-18202115711215762714803171222FRFrance
2021-04-19/2021-04-2520211674780289166697410FRFrance
2021-04-26/2021-05-0220211774686287864947410FRFrance
2021-05-03/2021-05-092021187393220935771639FRFrance
2021-05-10/2021-05-162021197806049411117912717FRFrance
\n", + "

1589 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 \\\n", + "period \n", + "1990-12-03/1990-12-09 199049 7 1143 0 2610 2 \n", + "1990-12-10/1990-12-16 199050 7 11079 6660 15498 20 \n", + "1990-12-17/1990-12-23 199051 7 19080 13807 24353 34 \n", + "1990-12-24/1990-12-30 199052 7 19375 13295 25455 34 \n", + "1990-12-31/1991-01-06 199101 7 15565 10271 20859 27 \n", + "1991-01-07/1991-01-13 199102 7 16277 11046 21508 29 \n", + "1991-01-14/1991-01-20 199103 7 15387 10484 20290 27 \n", + "1991-01-21/1991-01-27 199104 7 7913 4563 11263 14 \n", + "1991-01-28/1991-02-03 199105 7 10442 6544 14340 18 \n", + "1991-02-04/1991-02-10 199106 7 10877 7013 14741 19 \n", + "1991-02-11/1991-02-17 199107 7 12337 8077 16597 22 \n", + "1991-02-18/1991-02-24 199108 7 13289 8813 17765 23 \n", + "1991-02-25/1991-03-03 199109 7 13741 8780 18702 24 \n", + "1991-03-04/1991-03-10 199110 7 16643 11372 21914 29 \n", + "1991-03-11/1991-03-17 199111 7 15574 11184 19964 27 \n", + "1991-03-18/1991-03-24 199112 7 10864 7331 14397 19 \n", + "1991-03-25/1991-03-31 199113 7 9567 6041 13093 17 \n", + "1991-04-01/1991-04-07 199114 7 12265 7684 16846 22 \n", + "1991-04-08/1991-04-14 199115 7 13975 9781 18169 25 \n", + "1991-04-15/1991-04-21 199116 7 14857 10068 19646 26 \n", + "1991-04-22/1991-04-28 199117 7 13462 8877 18047 24 \n", + "1991-04-29/1991-05-05 199118 7 21385 13882 28888 38 \n", + "1991-05-06/1991-05-12 199119 7 16739 11246 22232 29 \n", + "1991-05-13/1991-05-19 199120 7 19053 12742 25364 34 \n", + "1991-05-20/1991-05-26 199121 7 14903 8975 20831 26 \n", + "1991-05-27/1991-06-02 199122 7 15452 9953 20951 27 \n", + "1991-06-03/1991-06-09 199123 7 11947 7671 16223 21 \n", + "1991-06-10/1991-06-16 199124 7 16171 10071 22271 28 \n", + "1991-06-17/1991-06-23 199125 7 16169 10700 21638 28 \n", + "1991-06-24/1991-06-30 199126 7 17608 11304 23912 31 \n", + "... ... ... ... ... ... ... \n", + "2020-10-19/2020-10-25 202043 7 4376 2505 6247 7 \n", + "2020-10-26/2020-11-01 202044 7 4391 2375 6407 7 \n", + "2020-11-02/2020-11-08 202045 7 3696 2016 5376 6 \n", + "2020-11-09/2020-11-15 202046 7 3752 1963 5541 6 \n", + "2020-11-16/2020-11-22 202047 7 4999 2963 7035 8 \n", + "2020-11-23/2020-11-29 202048 7 6683 4312 9054 10 \n", + "2020-11-30/2020-12-06 202049 7 5026 3145 6907 8 \n", + "2020-12-07/2020-12-13 202050 7 7063 4744 9382 11 \n", + "2020-12-14/2020-12-20 202051 7 10564 7574 13554 16 \n", + "2020-12-21/2020-12-27 202052 7 12012 8285 15739 18 \n", + "2020-12-28/2021-01-03 202053 7 11978 8406 15550 18 \n", + "2021-01-04/2021-01-10 202101 7 10525 7750 13300 16 \n", + "2021-01-11/2021-01-17 202102 7 7795 5430 10160 12 \n", + "2021-01-18/2021-01-24 202103 7 8913 6375 11451 13 \n", + "2021-01-25/2021-01-31 202104 7 12026 8826 15226 18 \n", + "2021-02-01/2021-02-07 202105 7 12210 8988 15432 18 \n", + "2021-02-08/2021-02-14 202106 7 13401 9810 16992 20 \n", + "2021-02-15/2021-02-21 202107 7 13561 10315 16807 21 \n", + "2021-02-22/2021-02-28 202108 7 11281 8361 14201 17 \n", + "2021-03-01/2021-03-07 202109 7 10988 7938 14038 17 \n", + "2021-03-08/2021-03-14 202110 7 9056 6452 11660 14 \n", + "2021-03-15/2021-03-21 202111 7 9386 6678 12094 14 \n", + "2021-03-22/2021-03-28 202112 7 11520 8415 14625 17 \n", + "2021-03-29/2021-04-04 202113 7 9714 6289 13139 15 \n", + "2021-04-05/2021-04-11 202114 7 11197 7994 14400 17 \n", + "2021-04-12/2021-04-18 202115 7 11215 7627 14803 17 \n", + "2021-04-19/2021-04-25 202116 7 4780 2891 6669 7 \n", + "2021-04-26/2021-05-02 202117 7 4686 2878 6494 7 \n", + "2021-05-03/2021-05-09 202118 7 3932 2093 5771 6 \n", + "2021-05-10/2021-05-16 202119 7 8060 4941 11179 12 \n", + "\n", + " inc100_low inc100_up geo_insee geo_name \n", + "period \n", + "1990-12-03/1990-12-09 0 5 FR France \n", + "1990-12-10/1990-12-16 12 28 FR France \n", + "1990-12-17/1990-12-23 25 43 FR France \n", + "1990-12-24/1990-12-30 23 45 FR France \n", + "1990-12-31/1991-01-06 18 36 FR France \n", + "1991-01-07/1991-01-13 20 38 FR France \n", + "1991-01-14/1991-01-20 18 36 FR France \n", + "1991-01-21/1991-01-27 8 20 FR France \n", + "1991-01-28/1991-02-03 11 25 FR France \n", + "1991-02-04/1991-02-10 12 26 FR France \n", + "1991-02-11/1991-02-17 15 29 FR France \n", + "1991-02-18/1991-02-24 15 31 FR France \n", + "1991-02-25/1991-03-03 15 33 FR France \n", + "1991-03-04/1991-03-10 20 38 FR France \n", + "1991-03-11/1991-03-17 19 35 FR France \n", + "1991-03-18/1991-03-24 13 25 FR France \n", + "1991-03-25/1991-03-31 11 23 FR France \n", + "1991-04-01/1991-04-07 14 30 FR France \n", + "1991-04-08/1991-04-14 18 32 FR France \n", + "1991-04-15/1991-04-21 18 34 FR France \n", + "1991-04-22/1991-04-28 16 32 FR France \n", + "1991-04-29/1991-05-05 25 51 FR France \n", + "1991-05-06/1991-05-12 19 39 FR France \n", + "1991-05-13/1991-05-19 23 45 FR France \n", + "1991-05-20/1991-05-26 16 36 FR France \n", + "1991-05-27/1991-06-02 17 37 FR France \n", + "1991-06-03/1991-06-09 13 29 FR France \n", + "1991-06-10/1991-06-16 17 39 FR France \n", + "1991-06-17/1991-06-23 18 38 FR France \n", + "1991-06-24/1991-06-30 20 42 FR France \n", + "... ... ... ... ... \n", + "2020-10-19/2020-10-25 4 10 FR France \n", + "2020-10-26/2020-11-01 4 10 FR France \n", + "2020-11-02/2020-11-08 3 9 FR France \n", + "2020-11-09/2020-11-15 3 9 FR France \n", + "2020-11-16/2020-11-22 5 11 FR France \n", + "2020-11-23/2020-11-29 6 14 FR France \n", + "2020-11-30/2020-12-06 5 11 FR France \n", + "2020-12-07/2020-12-13 7 15 FR France \n", + "2020-12-14/2020-12-20 11 21 FR France \n", + "2020-12-21/2020-12-27 12 24 FR France \n", + "2020-12-28/2021-01-03 13 23 FR France \n", + "2021-01-04/2021-01-10 12 20 FR France \n", + "2021-01-11/2021-01-17 8 16 FR France \n", + "2021-01-18/2021-01-24 9 17 FR France \n", + "2021-01-25/2021-01-31 13 23 FR France \n", + "2021-02-01/2021-02-07 13 23 FR France \n", + "2021-02-08/2021-02-14 15 25 FR France \n", + "2021-02-15/2021-02-21 16 26 FR France \n", + "2021-02-22/2021-02-28 13 21 FR France \n", + "2021-03-01/2021-03-07 12 22 FR France \n", + "2021-03-08/2021-03-14 10 18 FR France \n", + "2021-03-15/2021-03-21 10 18 FR France \n", + "2021-03-22/2021-03-28 12 22 FR France \n", + "2021-03-29/2021-04-04 10 20 FR France \n", + "2021-04-05/2021-04-11 12 22 FR France \n", + "2021-04-12/2021-04-18 12 22 FR France \n", + "2021-04-19/2021-04-25 4 10 FR France \n", + "2021-04-26/2021-05-02 4 10 FR France \n", + "2021-05-03/2021-05-09 3 9 FR France \n", + "2021-05-10/2021-05-16 7 17 FR France \n", + "\n", + "[1589 rows x 10 columns]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted_raw_data" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "periods = sorted_raw_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": "markdown", + "metadata": {}, + "source": [ + "Les donnees sont propres.On regarde les donnees" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "period\n", + "1990-12-03/1990-12-09 1143\n", + "1990-12-10/1990-12-16 11079\n", + "1990-12-17/1990-12-23 19080\n", + "1990-12-24/1990-12-30 19375\n", + "1990-12-31/1991-01-06 15565\n", + "1991-01-07/1991-01-13 16277\n", + "1991-01-14/1991-01-20 15387\n", + "1991-01-21/1991-01-27 7913\n", + "1991-01-28/1991-02-03 10442\n", + "1991-02-04/1991-02-10 10877\n", + "1991-02-11/1991-02-17 12337\n", + "1991-02-18/1991-02-24 13289\n", + "1991-02-25/1991-03-03 13741\n", + "1991-03-04/1991-03-10 16643\n", + "1991-03-11/1991-03-17 15574\n", + "1991-03-18/1991-03-24 10864\n", + "1991-03-25/1991-03-31 9567\n", + "1991-04-01/1991-04-07 12265\n", + "1991-04-08/1991-04-14 13975\n", + "1991-04-15/1991-04-21 14857\n", + "1991-04-22/1991-04-28 13462\n", + "1991-04-29/1991-05-05 21385\n", + "1991-05-06/1991-05-12 16739\n", + "1991-05-13/1991-05-19 19053\n", + "1991-05-20/1991-05-26 14903\n", + "1991-05-27/1991-06-02 15452\n", + "1991-06-03/1991-06-09 11947\n", + "1991-06-10/1991-06-16 16171\n", + "1991-06-17/1991-06-23 16169\n", + "1991-06-24/1991-06-30 17608\n", + " ... \n", + "2020-10-19/2020-10-25 4376\n", + "2020-10-26/2020-11-01 4391\n", + "2020-11-02/2020-11-08 3696\n", + "2020-11-09/2020-11-15 3752\n", + "2020-11-16/2020-11-22 4999\n", + "2020-11-23/2020-11-29 6683\n", + "2020-11-30/2020-12-06 5026\n", + "2020-12-07/2020-12-13 7063\n", + "2020-12-14/2020-12-20 10564\n", + "2020-12-21/2020-12-27 12012\n", + "2020-12-28/2021-01-03 11978\n", + "2021-01-04/2021-01-10 10525\n", + "2021-01-11/2021-01-17 7795\n", + "2021-01-18/2021-01-24 8913\n", + "2021-01-25/2021-01-31 12026\n", + "2021-02-01/2021-02-07 12210\n", + "2021-02-08/2021-02-14 13401\n", + "2021-02-15/2021-02-21 13561\n", + "2021-02-22/2021-02-28 11281\n", + "2021-03-01/2021-03-07 10988\n", + "2021-03-08/2021-03-14 9056\n", + "2021-03-15/2021-03-21 9386\n", + "2021-03-22/2021-03-28 11520\n", + "2021-03-29/2021-04-04 9714\n", + "2021-04-05/2021-04-11 11197\n", + "2021-04-12/2021-04-18 11215\n", + "2021-04-19/2021-04-25 4780\n", + "2021-04-26/2021-05-02 4686\n", + "2021-05-03/2021-05-09 3932\n", + "2021-05-10/2021-05-16 8060\n", + "Freq: W-SUN, Name: inc, Length: 1589, dtype: int64" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted_raw_data['inc']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_raw_data['inc'].plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "on fait un zoom" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_raw_data['inc'][-200:].plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Etude de l'incidence annuelle" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Etant donné que le pic de l'épidémie se situe en hiver, à cheval entre deux années civiles, nous définissons la période de référence entre deux minima de l'incidence, du 1er septembre de l'année $N$ au 1er septembre de l'année $N+1$.\n", + "Notre tâche est un peu compliquée par le fait que l'année ne comporte pas un nombre entier de semaines. Nous modifions donc un peu nos périodes de référence: à la place du 1er septembre de chaque année, nous utilisons le premier jour de la semaine qui contient le 1er septembre.\n", + "Comme l'incidence de syndrome de varicelle est très faible en été, cette modification ne risque pas de fausser nos conclusions.\n", + "Encore un petit détail: les données commencent en decembre 1990, ce qui rend la première année incomplète. Nous commençons donc l'analyse en 1992." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
period
1990-12-03/1990-12-091990497114302610205FRFrance
1990-12-10/1990-12-16199050711079666015498201228FRFrance
1990-12-17/1990-12-231990517190801380724353342543FRFrance
1990-12-24/1990-12-301990527193751329525455342345FRFrance
1990-12-31/1991-01-061991017155651027120859271836FRFrance
1991-01-07/1991-01-131991027162771104621508292038FRFrance
1991-01-14/1991-01-201991037153871048420290271836FRFrance
1991-01-21/1991-01-271991047791345631126314820FRFrance
1991-01-28/1991-02-03199105710442654414340181125FRFrance
1991-02-04/1991-02-10199106710877701314741191226FRFrance
1991-02-11/1991-02-17199107712337807716597221529FRFrance
1991-02-18/1991-02-24199108713289881317765231531FRFrance
1991-02-25/1991-03-03199109713741878018702241533FRFrance
1991-03-04/1991-03-101991107166431137221914292038FRFrance
1991-03-11/1991-03-171991117155741118419964271935FRFrance
1991-03-18/1991-03-24199112710864733114397191325FRFrance
1991-03-25/1991-03-3119911379567604113093171123FRFrance
1991-04-01/1991-04-07199114712265768416846221430FRFrance
1991-04-08/1991-04-14199115713975978118169251832FRFrance
1991-04-15/1991-04-211991167148571006819646261834FRFrance
1991-04-22/1991-04-28199117713462887718047241632FRFrance
1991-04-29/1991-05-051991187213851388228888382551FRFrance
1991-05-06/1991-05-121991197167391124622232291939FRFrance
1991-05-13/1991-05-191991207190531274225364342345FRFrance
1991-05-20/1991-05-26199121714903897520831261636FRFrance
1991-05-27/1991-06-02199122715452995320951271737FRFrance
1991-06-03/1991-06-09199123711947767116223211329FRFrance
1991-06-10/1991-06-161991247161711007122271281739FRFrance
1991-06-17/1991-06-231991257161691070021638281838FRFrance
1991-06-24/1991-06-301991267176081130423912312042FRFrance
.................................
2020-10-19/2020-10-2520204374376250562477410FRFrance
2020-10-26/2020-11-0120204474391237564077410FRFrance
2020-11-02/2020-11-082020457369620165376639FRFrance
2020-11-09/2020-11-152020467375219635541639FRFrance
2020-11-16/2020-11-2220204774999296370358511FRFrance
2020-11-23/2020-11-29202048766834312905410614FRFrance
2020-11-30/2020-12-0620204975026314569078511FRFrance
2020-12-07/2020-12-13202050770634744938211715FRFrance
2020-12-14/2020-12-20202051710564757413554161121FRFrance
2020-12-21/2020-12-27202052712012828515739181224FRFrance
2020-12-28/2021-01-03202053711978840615550181323FRFrance
2021-01-04/2021-01-10202101710525775013300161220FRFrance
2021-01-11/2021-01-172021027779554301016012816FRFrance
2021-01-18/2021-01-242021037891363751145113917FRFrance
2021-01-25/2021-01-31202104712026882615226181323FRFrance
2021-02-01/2021-02-07202105712210898815432181323FRFrance
2021-02-08/2021-02-14202106713401981016992201525FRFrance
2021-02-15/2021-02-212021077135611031516807211626FRFrance
2021-02-22/2021-02-28202108711281836114201171321FRFrance
2021-03-01/2021-03-07202109710988793814038171222FRFrance
2021-03-08/2021-03-1420211079056645211660141018FRFrance
2021-03-15/2021-03-2120211179386667812094141018FRFrance
2021-03-22/2021-03-28202112711520841514625171222FRFrance
2021-03-29/2021-04-0420211379714628913139151020FRFrance
2021-04-05/2021-04-11202114711197799414400171222FRFrance
2021-04-12/2021-04-18202115711215762714803171222FRFrance
2021-04-19/2021-04-2520211674780289166697410FRFrance
2021-04-26/2021-05-0220211774686287864947410FRFrance
2021-05-03/2021-05-092021187393220935771639FRFrance
2021-05-10/2021-05-162021197806049411117912717FRFrance
\n", + "

1589 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 \\\n", + "period \n", + "1990-12-03/1990-12-09 199049 7 1143 0 2610 2 \n", + "1990-12-10/1990-12-16 199050 7 11079 6660 15498 20 \n", + "1990-12-17/1990-12-23 199051 7 19080 13807 24353 34 \n", + "1990-12-24/1990-12-30 199052 7 19375 13295 25455 34 \n", + "1990-12-31/1991-01-06 199101 7 15565 10271 20859 27 \n", + "1991-01-07/1991-01-13 199102 7 16277 11046 21508 29 \n", + "1991-01-14/1991-01-20 199103 7 15387 10484 20290 27 \n", + "1991-01-21/1991-01-27 199104 7 7913 4563 11263 14 \n", + "1991-01-28/1991-02-03 199105 7 10442 6544 14340 18 \n", + "1991-02-04/1991-02-10 199106 7 10877 7013 14741 19 \n", + "1991-02-11/1991-02-17 199107 7 12337 8077 16597 22 \n", + "1991-02-18/1991-02-24 199108 7 13289 8813 17765 23 \n", + "1991-02-25/1991-03-03 199109 7 13741 8780 18702 24 \n", + "1991-03-04/1991-03-10 199110 7 16643 11372 21914 29 \n", + "1991-03-11/1991-03-17 199111 7 15574 11184 19964 27 \n", + "1991-03-18/1991-03-24 199112 7 10864 7331 14397 19 \n", + "1991-03-25/1991-03-31 199113 7 9567 6041 13093 17 \n", + "1991-04-01/1991-04-07 199114 7 12265 7684 16846 22 \n", + "1991-04-08/1991-04-14 199115 7 13975 9781 18169 25 \n", + "1991-04-15/1991-04-21 199116 7 14857 10068 19646 26 \n", + "1991-04-22/1991-04-28 199117 7 13462 8877 18047 24 \n", + "1991-04-29/1991-05-05 199118 7 21385 13882 28888 38 \n", + "1991-05-06/1991-05-12 199119 7 16739 11246 22232 29 \n", + "1991-05-13/1991-05-19 199120 7 19053 12742 25364 34 \n", + "1991-05-20/1991-05-26 199121 7 14903 8975 20831 26 \n", + "1991-05-27/1991-06-02 199122 7 15452 9953 20951 27 \n", + "1991-06-03/1991-06-09 199123 7 11947 7671 16223 21 \n", + "1991-06-10/1991-06-16 199124 7 16171 10071 22271 28 \n", + "1991-06-17/1991-06-23 199125 7 16169 10700 21638 28 \n", + "1991-06-24/1991-06-30 199126 7 17608 11304 23912 31 \n", + "... ... ... ... ... ... ... \n", + "2020-10-19/2020-10-25 202043 7 4376 2505 6247 7 \n", + "2020-10-26/2020-11-01 202044 7 4391 2375 6407 7 \n", + "2020-11-02/2020-11-08 202045 7 3696 2016 5376 6 \n", + "2020-11-09/2020-11-15 202046 7 3752 1963 5541 6 \n", + "2020-11-16/2020-11-22 202047 7 4999 2963 7035 8 \n", + "2020-11-23/2020-11-29 202048 7 6683 4312 9054 10 \n", + "2020-11-30/2020-12-06 202049 7 5026 3145 6907 8 \n", + "2020-12-07/2020-12-13 202050 7 7063 4744 9382 11 \n", + "2020-12-14/2020-12-20 202051 7 10564 7574 13554 16 \n", + "2020-12-21/2020-12-27 202052 7 12012 8285 15739 18 \n", + "2020-12-28/2021-01-03 202053 7 11978 8406 15550 18 \n", + "2021-01-04/2021-01-10 202101 7 10525 7750 13300 16 \n", + "2021-01-11/2021-01-17 202102 7 7795 5430 10160 12 \n", + "2021-01-18/2021-01-24 202103 7 8913 6375 11451 13 \n", + "2021-01-25/2021-01-31 202104 7 12026 8826 15226 18 \n", + "2021-02-01/2021-02-07 202105 7 12210 8988 15432 18 \n", + "2021-02-08/2021-02-14 202106 7 13401 9810 16992 20 \n", + "2021-02-15/2021-02-21 202107 7 13561 10315 16807 21 \n", + "2021-02-22/2021-02-28 202108 7 11281 8361 14201 17 \n", + "2021-03-01/2021-03-07 202109 7 10988 7938 14038 17 \n", + "2021-03-08/2021-03-14 202110 7 9056 6452 11660 14 \n", + "2021-03-15/2021-03-21 202111 7 9386 6678 12094 14 \n", + "2021-03-22/2021-03-28 202112 7 11520 8415 14625 17 \n", + "2021-03-29/2021-04-04 202113 7 9714 6289 13139 15 \n", + "2021-04-05/2021-04-11 202114 7 11197 7994 14400 17 \n", + "2021-04-12/2021-04-18 202115 7 11215 7627 14803 17 \n", + "2021-04-19/2021-04-25 202116 7 4780 2891 6669 7 \n", + "2021-04-26/2021-05-02 202117 7 4686 2878 6494 7 \n", + "2021-05-03/2021-05-09 202118 7 3932 2093 5771 6 \n", + "2021-05-10/2021-05-16 202119 7 8060 4941 11179 12 \n", + "\n", + " inc100_low inc100_up geo_insee geo_name \n", + "period \n", + "1990-12-03/1990-12-09 0 5 FR France \n", + "1990-12-10/1990-12-16 12 28 FR France \n", + "1990-12-17/1990-12-23 25 43 FR France \n", + "1990-12-24/1990-12-30 23 45 FR France \n", + "1990-12-31/1991-01-06 18 36 FR France \n", + "1991-01-07/1991-01-13 20 38 FR France \n", + "1991-01-14/1991-01-20 18 36 FR France \n", + "1991-01-21/1991-01-27 8 20 FR France \n", + "1991-01-28/1991-02-03 11 25 FR France \n", + "1991-02-04/1991-02-10 12 26 FR France \n", + "1991-02-11/1991-02-17 15 29 FR France \n", + "1991-02-18/1991-02-24 15 31 FR France \n", + "1991-02-25/1991-03-03 15 33 FR France \n", + "1991-03-04/1991-03-10 20 38 FR France \n", + "1991-03-11/1991-03-17 19 35 FR France \n", + "1991-03-18/1991-03-24 13 25 FR France \n", + "1991-03-25/1991-03-31 11 23 FR France \n", + "1991-04-01/1991-04-07 14 30 FR France \n", + "1991-04-08/1991-04-14 18 32 FR France \n", + "1991-04-15/1991-04-21 18 34 FR France \n", + "1991-04-22/1991-04-28 16 32 FR France \n", + "1991-04-29/1991-05-05 25 51 FR France \n", + "1991-05-06/1991-05-12 19 39 FR France \n", + "1991-05-13/1991-05-19 23 45 FR France \n", + "1991-05-20/1991-05-26 16 36 FR France \n", + "1991-05-27/1991-06-02 17 37 FR France \n", + "1991-06-03/1991-06-09 13 29 FR France \n", + "1991-06-10/1991-06-16 17 39 FR France \n", + "1991-06-17/1991-06-23 18 38 FR France \n", + "1991-06-24/1991-06-30 20 42 FR France \n", + "... ... ... ... ... \n", + "2020-10-19/2020-10-25 4 10 FR France \n", + "2020-10-26/2020-11-01 4 10 FR France \n", + "2020-11-02/2020-11-08 3 9 FR France \n", + "2020-11-09/2020-11-15 3 9 FR France \n", + "2020-11-16/2020-11-22 5 11 FR France \n", + "2020-11-23/2020-11-29 6 14 FR France \n", + "2020-11-30/2020-12-06 5 11 FR France \n", + "2020-12-07/2020-12-13 7 15 FR France \n", + "2020-12-14/2020-12-20 11 21 FR France \n", + "2020-12-21/2020-12-27 12 24 FR France \n", + "2020-12-28/2021-01-03 13 23 FR France \n", + "2021-01-04/2021-01-10 12 20 FR France \n", + "2021-01-11/2021-01-17 8 16 FR France \n", + "2021-01-18/2021-01-24 9 17 FR France \n", + "2021-01-25/2021-01-31 13 23 FR France \n", + "2021-02-01/2021-02-07 13 23 FR France \n", + "2021-02-08/2021-02-14 15 25 FR France \n", + "2021-02-15/2021-02-21 16 26 FR France \n", + "2021-02-22/2021-02-28 13 21 FR France \n", + "2021-03-01/2021-03-07 12 22 FR France \n", + "2021-03-08/2021-03-14 10 18 FR France \n", + "2021-03-15/2021-03-21 10 18 FR France \n", + "2021-03-22/2021-03-28 12 22 FR France \n", + "2021-03-29/2021-04-04 10 20 FR France \n", + "2021-04-05/2021-04-11 12 22 FR France \n", + "2021-04-12/2021-04-18 12 22 FR France \n", + "2021-04-19/2021-04-25 4 10 FR France \n", + "2021-04-26/2021-05-02 4 10 FR France \n", + "2021-05-03/2021-05-09 3 9 FR France \n", + "2021-05-10/2021-05-16 7 17 FR France \n", + "\n", + "[1589 rows x 10 columns]" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted_raw_data" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "first_septembre_week =[pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", + " for y in range(1991,\n", + " sorted_raw_data.index[-1].year)]" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[Period('1991-08-26/1991-09-01', 'W-SUN'),\n", + " Period('1992-08-31/1992-09-06', 'W-SUN'),\n", + " Period('1993-08-30/1993-09-05', 'W-SUN'),\n", + " Period('1994-08-29/1994-09-04', 'W-SUN'),\n", + " Period('1995-08-28/1995-09-03', 'W-SUN'),\n", + " Period('1996-08-26/1996-09-01', 'W-SUN'),\n", + " Period('1997-09-01/1997-09-07', 'W-SUN'),\n", + " Period('1998-08-31/1998-09-06', 'W-SUN'),\n", + " Period('1999-08-30/1999-09-05', 'W-SUN'),\n", + " Period('2000-08-28/2000-09-03', 'W-SUN'),\n", + " Period('2001-08-27/2001-09-02', 'W-SUN'),\n", + " Period('2002-08-26/2002-09-01', 'W-SUN'),\n", + " Period('2003-09-01/2003-09-07', 'W-SUN'),\n", + " Period('2004-08-30/2004-09-05', 'W-SUN'),\n", + " Period('2005-08-29/2005-09-04', 'W-SUN'),\n", + " Period('2006-08-28/2006-09-03', 'W-SUN'),\n", + " Period('2007-08-27/2007-09-02', 'W-SUN'),\n", + " Period('2008-09-01/2008-09-07', 'W-SUN'),\n", + " Period('2009-08-31/2009-09-06', 'W-SUN'),\n", + " Period('2010-08-30/2010-09-05', 'W-SUN'),\n", + " Period('2011-08-29/2011-09-04', 'W-SUN'),\n", + " Period('2012-08-27/2012-09-02', 'W-SUN'),\n", + " Period('2013-08-26/2013-09-01', 'W-SUN'),\n", + " Period('2014-09-01/2014-09-07', 'W-SUN'),\n", + " Period('2015-08-31/2015-09-06', 'W-SUN'),\n", + " Period('2016-08-29/2016-09-04', 'W-SUN'),\n", + " Period('2017-08-28/2017-09-03', 'W-SUN'),\n", + " Period('2018-08-27/2018-09-02', 'W-SUN'),\n", + " Period('2019-08-26/2019-09-01', 'W-SUN'),\n", + " Period('2020-08-31/2020-09-06', 'W-SUN')]" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "first_septembre_week = [pd.Period(pd.Timestamp(y, (9, 1), 'W')\n", - " for y in range(1991,\n", - " sorted_raw_data.index[-1].year)]" + "first_septembre_week" ] }, {