From 6fa1dfd5ba3063b879f80ca531944619006edb1a Mon Sep 17 00:00:00 2001 From: 6ace2fb7013d31885fa16c5877ca5aa1 <6ace2fb7013d31885fa16c5877ca5aa1@app-learninglab.inria.fr> Date: Sun, 5 Dec 2021 07:55:34 +0000 Subject: [PATCH] incidence Varicelle Lm --- module3/exo2/exercice.ipynb | 3387 ++++++++++++++++++++++++++++++++++- 1 file changed, 3384 insertions(+), 3 deletions(-) diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb index 0bbbe37..491b78b 100644 --- a/module3/exo2/exercice.ipynb +++ b/module3/exo2/exercice.ipynb @@ -1,5 +1,3387 @@ { - "cells": [], + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Incidence de la varicelle" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "import isoweek" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "raw_data = pd.read_csv(\"https://www.sentiweb.fr/datasets/incidence-PAY-7.csv\", skiprows = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "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
0202147712654914016168191424FRFrance
12021467831757931084113917FRFrance
220214578965646811462141018FRFrance
32021447873656361183613818FRFrance
42021437814551641112612717FRFrance
52021427944360371284914919FRFrance
62021417402122395803639FRFrance
720214074441245464287410FRFrance
82021397229110563526315FRFrance
920213874325226763837410FRFrance
10202137719647543174315FRFrance
112021367344117305152528FRFrance
122021357256211074017426FRFrance
13202134714293782480204FRFrance
142021337382918305828639FRFrance
152021327410818956321639FRFrance
1620213174793230172857311FRFrance
172021307719041911018911616FRFrance
18202129768004109949110614FRFrance
192021287973402173115033FRFrance
202021277902643161373614721FRFrance
212021267728441081046011616FRFrance
2220212579351654012162141018FRFrance
23202124712034893715131181323FRFrance
2420212379116642011812141018FRFrance
2520212274817275268827410FRFrance
2620212176092345887269513FRFrance
272021207748546011036911715FRFrance
28202119766544370893810713FRFrance
292021187391221105714639FRFrance
.................................
15871991267176081130423912312042FRFrance
15881991257161691070021638281838FRFrance
15891991247161711007122271281739FRFrance
1590199123711947767116223211329FRFrance
1591199122715452995320951271737FRFrance
1592199121714903897520831261636FRFrance
15931991207190531274225364342345FRFrance
15941991197167391124622232291939FRFrance
15951991187213851388228888382551FRFrance
1596199117713462887718047241632FRFrance
15971991167148571006819646261834FRFrance
1598199115713975978118169251832FRFrance
1599199114712265768416846221430FRFrance
160019911379567604113093171123FRFrance
1601199112710864733114397191325FRFrance
16021991117155741118419964271935FRFrance
16031991107166431137221914292038FRFrance
1604199109713741878018702241533FRFrance
1605199108713289881317765231531FRFrance
1606199107712337807716597221529FRFrance
1607199106710877701314741191226FRFrance
1608199105710442654414340181125FRFrance
16091991047791345631126314820FRFrance
16101991037153871048420290271836FRFrance
16111991027162771104621508292038FRFrance
16121991017155651027120859271836FRFrance
16131990527193751329525455342345FRFrance
16141990517190801380724353342543FRFrance
1615199050711079666015498201228FRFrance
16161990497114302610205FRFrance
\n", + "

1617 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202147 7 12654 9140 16168 19 14 \n", + "1 202146 7 8317 5793 10841 13 9 \n", + "2 202145 7 8965 6468 11462 14 10 \n", + "3 202144 7 8736 5636 11836 13 8 \n", + "4 202143 7 8145 5164 11126 12 7 \n", + "5 202142 7 9443 6037 12849 14 9 \n", + "6 202141 7 4021 2239 5803 6 3 \n", + "7 202140 7 4441 2454 6428 7 4 \n", + "8 202139 7 2291 1056 3526 3 1 \n", + "9 202138 7 4325 2267 6383 7 4 \n", + "10 202137 7 1964 754 3174 3 1 \n", + "11 202136 7 3441 1730 5152 5 2 \n", + "12 202135 7 2562 1107 4017 4 2 \n", + "13 202134 7 1429 378 2480 2 0 \n", + "14 202133 7 3829 1830 5828 6 3 \n", + "15 202132 7 4108 1895 6321 6 3 \n", + "16 202131 7 4793 2301 7285 7 3 \n", + "17 202130 7 7190 4191 10189 11 6 \n", + "18 202129 7 6800 4109 9491 10 6 \n", + "19 202128 7 9734 0 21731 15 0 \n", + "20 202127 7 9026 4316 13736 14 7 \n", + "21 202126 7 7284 4108 10460 11 6 \n", + "22 202125 7 9351 6540 12162 14 10 \n", + "23 202124 7 12034 8937 15131 18 13 \n", + "24 202123 7 9116 6420 11812 14 10 \n", + "25 202122 7 4817 2752 6882 7 4 \n", + "26 202121 7 6092 3458 8726 9 5 \n", + "27 202120 7 7485 4601 10369 11 7 \n", + "28 202119 7 6654 4370 8938 10 7 \n", + "29 202118 7 3912 2110 5714 6 3 \n", + "... ... ... ... ... ... ... ... \n", + "1587 199126 7 17608 11304 23912 31 20 \n", + "1588 199125 7 16169 10700 21638 28 18 \n", + "1589 199124 7 16171 10071 22271 28 17 \n", + "1590 199123 7 11947 7671 16223 21 13 \n", + "1591 199122 7 15452 9953 20951 27 17 \n", + "1592 199121 7 14903 8975 20831 26 16 \n", + "1593 199120 7 19053 12742 25364 34 23 \n", + "1594 199119 7 16739 11246 22232 29 19 \n", + "1595 199118 7 21385 13882 28888 38 25 \n", + "1596 199117 7 13462 8877 18047 24 16 \n", + "1597 199116 7 14857 10068 19646 26 18 \n", + "1598 199115 7 13975 9781 18169 25 18 \n", + "1599 199114 7 12265 7684 16846 22 14 \n", + "1600 199113 7 9567 6041 13093 17 11 \n", + "1601 199112 7 10864 7331 14397 19 13 \n", + "1602 199111 7 15574 11184 19964 27 19 \n", + "1603 199110 7 16643 11372 21914 29 20 \n", + "1604 199109 7 13741 8780 18702 24 15 \n", + "1605 199108 7 13289 8813 17765 23 15 \n", + "1606 199107 7 12337 8077 16597 22 15 \n", + "1607 199106 7 10877 7013 14741 19 12 \n", + "1608 199105 7 10442 6544 14340 18 11 \n", + "1609 199104 7 7913 4563 11263 14 8 \n", + "1610 199103 7 15387 10484 20290 27 18 \n", + "1611 199102 7 16277 11046 21508 29 20 \n", + "1612 199101 7 15565 10271 20859 27 18 \n", + "1613 199052 7 19375 13295 25455 34 23 \n", + "1614 199051 7 19080 13807 24353 34 25 \n", + "1615 199050 7 11079 6660 15498 20 12 \n", + "1616 199049 7 1143 0 2610 2 0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 24 FR France \n", + "1 17 FR France \n", + "2 18 FR France \n", + "3 18 FR France \n", + "4 17 FR France \n", + "5 19 FR France \n", + "6 9 FR France \n", + "7 10 FR France \n", + "8 5 FR France \n", + "9 10 FR France \n", + "10 5 FR France \n", + "11 8 FR France \n", + "12 6 FR France \n", + "13 4 FR France \n", + "14 9 FR France \n", + "15 9 FR France \n", + "16 11 FR France \n", + "17 16 FR France \n", + "18 14 FR France \n", + "19 33 FR France \n", + "20 21 FR France \n", + "21 16 FR France \n", + "22 18 FR France \n", + "23 23 FR France \n", + "24 18 FR France \n", + "25 10 FR France \n", + "26 13 FR France \n", + "27 15 FR France \n", + "28 13 FR France \n", + "29 9 FR France \n", + "... ... ... ... \n", + "1587 42 FR France \n", + "1588 38 FR France \n", + "1589 39 FR France \n", + "1590 29 FR France \n", + "1591 37 FR France \n", + "1592 36 FR France \n", + "1593 45 FR France \n", + "1594 39 FR France \n", + "1595 51 FR France \n", + "1596 32 FR France \n", + "1597 34 FR France \n", + "1598 32 FR France \n", + "1599 30 FR France \n", + "1600 23 FR France \n", + "1601 25 FR France \n", + "1602 35 FR France \n", + "1603 38 FR France \n", + "1604 33 FR France \n", + "1605 31 FR France \n", + "1606 29 FR France \n", + "1607 26 FR France \n", + "1608 25 FR France \n", + "1609 20 FR France \n", + "1610 36 FR France \n", + "1611 38 FR France \n", + "1612 36 FR France \n", + "1613 45 FR France \n", + "1614 43 FR France \n", + "1615 28 FR France \n", + "1616 5 FR France \n", + "\n", + "[1617 rows x 10 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "raw_data" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "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": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "raw_data[raw_data.isnull().any(axis=1)]" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "data=raw_data" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "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": 12, + "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", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \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_nameperiod
0202147712654914016168191424FRFrance2021-11-22/2021-11-28
12021467831757931084113917FRFrance2021-11-15/2021-11-21
220214578965646811462141018FRFrance2021-11-08/2021-11-14
32021447873656361183613818FRFrance2021-11-01/2021-11-07
42021437814551641112612717FRFrance2021-10-25/2021-10-31
52021427944360371284914919FRFrance2021-10-18/2021-10-24
62021417402122395803639FRFrance2021-10-11/2021-10-17
720214074441245464287410FRFrance2021-10-04/2021-10-10
82021397229110563526315FRFrance2021-09-27/2021-10-03
920213874325226763837410FRFrance2021-09-20/2021-09-26
10202137719647543174315FRFrance2021-09-13/2021-09-19
112021367344117305152528FRFrance2021-09-06/2021-09-12
122021357256211074017426FRFrance2021-08-30/2021-09-05
13202134714293782480204FRFrance2021-08-23/2021-08-29
142021337382918305828639FRFrance2021-08-16/2021-08-22
152021327410818956321639FRFrance2021-08-09/2021-08-15
1620213174793230172857311FRFrance2021-08-02/2021-08-08
172021307719041911018911616FRFrance2021-07-26/2021-08-01
18202129768004109949110614FRFrance2021-07-19/2021-07-25
192021287973402173115033FRFrance2021-07-12/2021-07-18
202021277902643161373614721FRFrance2021-07-05/2021-07-11
212021267728441081046011616FRFrance2021-06-28/2021-07-04
2220212579351654012162141018FRFrance2021-06-21/2021-06-27
23202124712034893715131181323FRFrance2021-06-14/2021-06-20
2420212379116642011812141018FRFrance2021-06-07/2021-06-13
2520212274817275268827410FRFrance2021-05-31/2021-06-06
2620212176092345887269513FRFrance2021-05-24/2021-05-30
272021207748546011036911715FRFrance2021-05-17/2021-05-23
28202119766544370893810713FRFrance2021-05-10/2021-05-16
292021187391221105714639FRFrance2021-05-03/2021-05-09
....................................
15871991267176081130423912312042FRFrance1991-06-24/1991-06-30
15881991257161691070021638281838FRFrance1991-06-17/1991-06-23
15891991247161711007122271281739FRFrance1991-06-10/1991-06-16
1590199123711947767116223211329FRFrance1991-06-03/1991-06-09
1591199122715452995320951271737FRFrance1991-05-27/1991-06-02
1592199121714903897520831261636FRFrance1991-05-20/1991-05-26
15931991207190531274225364342345FRFrance1991-05-13/1991-05-19
15941991197167391124622232291939FRFrance1991-05-06/1991-05-12
15951991187213851388228888382551FRFrance1991-04-29/1991-05-05
1596199117713462887718047241632FRFrance1991-04-22/1991-04-28
15971991167148571006819646261834FRFrance1991-04-15/1991-04-21
1598199115713975978118169251832FRFrance1991-04-08/1991-04-14
1599199114712265768416846221430FRFrance1991-04-01/1991-04-07
160019911379567604113093171123FRFrance1991-03-25/1991-03-31
1601199112710864733114397191325FRFrance1991-03-18/1991-03-24
16021991117155741118419964271935FRFrance1991-03-11/1991-03-17
16031991107166431137221914292038FRFrance1991-03-04/1991-03-10
1604199109713741878018702241533FRFrance1991-02-25/1991-03-03
1605199108713289881317765231531FRFrance1991-02-18/1991-02-24
1606199107712337807716597221529FRFrance1991-02-11/1991-02-17
1607199106710877701314741191226FRFrance1991-02-04/1991-02-10
1608199105710442654414340181125FRFrance1991-01-28/1991-02-03
16091991047791345631126314820FRFrance1991-01-21/1991-01-27
16101991037153871048420290271836FRFrance1991-01-14/1991-01-20
16111991027162771104621508292038FRFrance1991-01-07/1991-01-13
16121991017155651027120859271836FRFrance1990-12-31/1991-01-06
16131990527193751329525455342345FRFrance1990-12-24/1990-12-30
16141990517190801380724353342543FRFrance1990-12-17/1990-12-23
1615199050711079666015498201228FRFrance1990-12-10/1990-12-16
16161990497114302610205FRFrance1990-12-03/1990-12-09
\n", + "

1617 rows × 11 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202147 7 12654 9140 16168 19 14 \n", + "1 202146 7 8317 5793 10841 13 9 \n", + "2 202145 7 8965 6468 11462 14 10 \n", + "3 202144 7 8736 5636 11836 13 8 \n", + "4 202143 7 8145 5164 11126 12 7 \n", + "5 202142 7 9443 6037 12849 14 9 \n", + "6 202141 7 4021 2239 5803 6 3 \n", + "7 202140 7 4441 2454 6428 7 4 \n", + "8 202139 7 2291 1056 3526 3 1 \n", + "9 202138 7 4325 2267 6383 7 4 \n", + "10 202137 7 1964 754 3174 3 1 \n", + "11 202136 7 3441 1730 5152 5 2 \n", + "12 202135 7 2562 1107 4017 4 2 \n", + "13 202134 7 1429 378 2480 2 0 \n", + "14 202133 7 3829 1830 5828 6 3 \n", + "15 202132 7 4108 1895 6321 6 3 \n", + "16 202131 7 4793 2301 7285 7 3 \n", + "17 202130 7 7190 4191 10189 11 6 \n", + "18 202129 7 6800 4109 9491 10 6 \n", + "19 202128 7 9734 0 21731 15 0 \n", + "20 202127 7 9026 4316 13736 14 7 \n", + "21 202126 7 7284 4108 10460 11 6 \n", + "22 202125 7 9351 6540 12162 14 10 \n", + "23 202124 7 12034 8937 15131 18 13 \n", + "24 202123 7 9116 6420 11812 14 10 \n", + "25 202122 7 4817 2752 6882 7 4 \n", + "26 202121 7 6092 3458 8726 9 5 \n", + "27 202120 7 7485 4601 10369 11 7 \n", + "28 202119 7 6654 4370 8938 10 7 \n", + "29 202118 7 3912 2110 5714 6 3 \n", + "... ... ... ... ... ... ... ... \n", + "1587 199126 7 17608 11304 23912 31 20 \n", + "1588 199125 7 16169 10700 21638 28 18 \n", + "1589 199124 7 16171 10071 22271 28 17 \n", + "1590 199123 7 11947 7671 16223 21 13 \n", + "1591 199122 7 15452 9953 20951 27 17 \n", + "1592 199121 7 14903 8975 20831 26 16 \n", + "1593 199120 7 19053 12742 25364 34 23 \n", + "1594 199119 7 16739 11246 22232 29 19 \n", + "1595 199118 7 21385 13882 28888 38 25 \n", + "1596 199117 7 13462 8877 18047 24 16 \n", + "1597 199116 7 14857 10068 19646 26 18 \n", + "1598 199115 7 13975 9781 18169 25 18 \n", + "1599 199114 7 12265 7684 16846 22 14 \n", + "1600 199113 7 9567 6041 13093 17 11 \n", + "1601 199112 7 10864 7331 14397 19 13 \n", + "1602 199111 7 15574 11184 19964 27 19 \n", + "1603 199110 7 16643 11372 21914 29 20 \n", + "1604 199109 7 13741 8780 18702 24 15 \n", + "1605 199108 7 13289 8813 17765 23 15 \n", + "1606 199107 7 12337 8077 16597 22 15 \n", + "1607 199106 7 10877 7013 14741 19 12 \n", + "1608 199105 7 10442 6544 14340 18 11 \n", + "1609 199104 7 7913 4563 11263 14 8 \n", + "1610 199103 7 15387 10484 20290 27 18 \n", + "1611 199102 7 16277 11046 21508 29 20 \n", + "1612 199101 7 15565 10271 20859 27 18 \n", + "1613 199052 7 19375 13295 25455 34 23 \n", + "1614 199051 7 19080 13807 24353 34 25 \n", + "1615 199050 7 11079 6660 15498 20 12 \n", + "1616 199049 7 1143 0 2610 2 0 \n", + "\n", + " inc100_up geo_insee geo_name period \n", + "0 24 FR France 2021-11-22/2021-11-28 \n", + "1 17 FR France 2021-11-15/2021-11-21 \n", + "2 18 FR France 2021-11-08/2021-11-14 \n", + "3 18 FR France 2021-11-01/2021-11-07 \n", + "4 17 FR France 2021-10-25/2021-10-31 \n", + "5 19 FR France 2021-10-18/2021-10-24 \n", + "6 9 FR France 2021-10-11/2021-10-17 \n", + "7 10 FR France 2021-10-04/2021-10-10 \n", + "8 5 FR France 2021-09-27/2021-10-03 \n", + "9 10 FR France 2021-09-20/2021-09-26 \n", + "10 5 FR France 2021-09-13/2021-09-19 \n", + "11 8 FR France 2021-09-06/2021-09-12 \n", + "12 6 FR France 2021-08-30/2021-09-05 \n", + "13 4 FR France 2021-08-23/2021-08-29 \n", + "14 9 FR France 2021-08-16/2021-08-22 \n", + "15 9 FR France 2021-08-09/2021-08-15 \n", + "16 11 FR France 2021-08-02/2021-08-08 \n", + "17 16 FR France 2021-07-26/2021-08-01 \n", + "18 14 FR France 2021-07-19/2021-07-25 \n", + "19 33 FR France 2021-07-12/2021-07-18 \n", + "20 21 FR France 2021-07-05/2021-07-11 \n", + "21 16 FR France 2021-06-28/2021-07-04 \n", + "22 18 FR France 2021-06-21/2021-06-27 \n", + "23 23 FR France 2021-06-14/2021-06-20 \n", + "24 18 FR France 2021-06-07/2021-06-13 \n", + "25 10 FR France 2021-05-31/2021-06-06 \n", + "26 13 FR France 2021-05-24/2021-05-30 \n", + "27 15 FR France 2021-05-17/2021-05-23 \n", + "28 13 FR France 2021-05-10/2021-05-16 \n", + "29 9 FR France 2021-05-03/2021-05-09 \n", + "... ... ... ... ... \n", + "1587 42 FR France 1991-06-24/1991-06-30 \n", + "1588 38 FR France 1991-06-17/1991-06-23 \n", + "1589 39 FR France 1991-06-10/1991-06-16 \n", + "1590 29 FR France 1991-06-03/1991-06-09 \n", + "1591 37 FR France 1991-05-27/1991-06-02 \n", + "1592 36 FR France 1991-05-20/1991-05-26 \n", + "1593 45 FR France 1991-05-13/1991-05-19 \n", + "1594 39 FR France 1991-05-06/1991-05-12 \n", + "1595 51 FR France 1991-04-29/1991-05-05 \n", + "1596 32 FR France 1991-04-22/1991-04-28 \n", + "1597 34 FR France 1991-04-15/1991-04-21 \n", + "1598 32 FR France 1991-04-08/1991-04-14 \n", + "1599 30 FR France 1991-04-01/1991-04-07 \n", + "1600 23 FR France 1991-03-25/1991-03-31 \n", + "1601 25 FR France 1991-03-18/1991-03-24 \n", + "1602 35 FR France 1991-03-11/1991-03-17 \n", + "1603 38 FR France 1991-03-04/1991-03-10 \n", + "1604 33 FR France 1991-02-25/1991-03-03 \n", + "1605 31 FR France 1991-02-18/1991-02-24 \n", + "1606 29 FR France 1991-02-11/1991-02-17 \n", + "1607 26 FR France 1991-02-04/1991-02-10 \n", + "1608 25 FR France 1991-01-28/1991-02-03 \n", + "1609 20 FR France 1991-01-21/1991-01-27 \n", + "1610 36 FR France 1991-01-14/1991-01-20 \n", + "1611 38 FR France 1991-01-07/1991-01-13 \n", + "1612 36 FR France 1990-12-31/1991-01-06 \n", + "1613 45 FR France 1990-12-24/1990-12-30 \n", + "1614 43 FR France 1990-12-17/1990-12-23 \n", + "1615 28 FR France 1990-12-10/1990-12-16 \n", + "1616 5 FR France 1990-12-03/1990-12-09 \n", + "\n", + "[1617 rows x 11 columns]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_data = data.set_index('period').sort_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "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", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
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
.................................
2021-05-03/2021-05-092021187391221105714639FRFrance
2021-05-10/2021-05-16202119766544370893810713FRFrance
2021-05-17/2021-05-232021207748546011036911715FRFrance
2021-05-24/2021-05-3020212176092345887269513FRFrance
2021-05-31/2021-06-0620212274817275268827410FRFrance
2021-06-07/2021-06-1320212379116642011812141018FRFrance
2021-06-14/2021-06-20202124712034893715131181323FRFrance
2021-06-21/2021-06-2720212579351654012162141018FRFrance
2021-06-28/2021-07-042021267728441081046011616FRFrance
2021-07-05/2021-07-112021277902643161373614721FRFrance
2021-07-12/2021-07-182021287973402173115033FRFrance
2021-07-19/2021-07-25202129768004109949110614FRFrance
2021-07-26/2021-08-012021307719041911018911616FRFrance
2021-08-02/2021-08-0820213174793230172857311FRFrance
2021-08-09/2021-08-152021327410818956321639FRFrance
2021-08-16/2021-08-222021337382918305828639FRFrance
2021-08-23/2021-08-29202134714293782480204FRFrance
2021-08-30/2021-09-052021357256211074017426FRFrance
2021-09-06/2021-09-122021367344117305152528FRFrance
2021-09-13/2021-09-19202137719647543174315FRFrance
2021-09-20/2021-09-2620213874325226763837410FRFrance
2021-09-27/2021-10-032021397229110563526315FRFrance
2021-10-04/2021-10-1020214074441245464287410FRFrance
2021-10-11/2021-10-172021417402122395803639FRFrance
2021-10-18/2021-10-242021427944360371284914919FRFrance
2021-10-25/2021-10-312021437814551641112612717FRFrance
2021-11-01/2021-11-072021447873656361183613818FRFrance
2021-11-08/2021-11-1420214578965646811462141018FRFrance
2021-11-15/2021-11-212021467831757931084113917FRFrance
2021-11-22/2021-11-28202147712654914016168191424FRFrance
\n", + "

1617 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", + "2021-05-03/2021-05-09 202118 7 3912 2110 5714 6 \n", + "2021-05-10/2021-05-16 202119 7 6654 4370 8938 10 \n", + "2021-05-17/2021-05-23 202120 7 7485 4601 10369 11 \n", + "2021-05-24/2021-05-30 202121 7 6092 3458 8726 9 \n", + "2021-05-31/2021-06-06 202122 7 4817 2752 6882 7 \n", + "2021-06-07/2021-06-13 202123 7 9116 6420 11812 14 \n", + "2021-06-14/2021-06-20 202124 7 12034 8937 15131 18 \n", + "2021-06-21/2021-06-27 202125 7 9351 6540 12162 14 \n", + "2021-06-28/2021-07-04 202126 7 7284 4108 10460 11 \n", + "2021-07-05/2021-07-11 202127 7 9026 4316 13736 14 \n", + "2021-07-12/2021-07-18 202128 7 9734 0 21731 15 \n", + "2021-07-19/2021-07-25 202129 7 6800 4109 9491 10 \n", + "2021-07-26/2021-08-01 202130 7 7190 4191 10189 11 \n", + "2021-08-02/2021-08-08 202131 7 4793 2301 7285 7 \n", + "2021-08-09/2021-08-15 202132 7 4108 1895 6321 6 \n", + "2021-08-16/2021-08-22 202133 7 3829 1830 5828 6 \n", + "2021-08-23/2021-08-29 202134 7 1429 378 2480 2 \n", + "2021-08-30/2021-09-05 202135 7 2562 1107 4017 4 \n", + "2021-09-06/2021-09-12 202136 7 3441 1730 5152 5 \n", + "2021-09-13/2021-09-19 202137 7 1964 754 3174 3 \n", + "2021-09-20/2021-09-26 202138 7 4325 2267 6383 7 \n", + "2021-09-27/2021-10-03 202139 7 2291 1056 3526 3 \n", + "2021-10-04/2021-10-10 202140 7 4441 2454 6428 7 \n", + "2021-10-11/2021-10-17 202141 7 4021 2239 5803 6 \n", + "2021-10-18/2021-10-24 202142 7 9443 6037 12849 14 \n", + "2021-10-25/2021-10-31 202143 7 8145 5164 11126 12 \n", + "2021-11-01/2021-11-07 202144 7 8736 5636 11836 13 \n", + "2021-11-08/2021-11-14 202145 7 8965 6468 11462 14 \n", + "2021-11-15/2021-11-21 202146 7 8317 5793 10841 13 \n", + "2021-11-22/2021-11-28 202147 7 12654 9140 16168 19 \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", + "2021-05-03/2021-05-09 3 9 FR France \n", + "2021-05-10/2021-05-16 7 13 FR France \n", + "2021-05-17/2021-05-23 7 15 FR France \n", + "2021-05-24/2021-05-30 5 13 FR France \n", + "2021-05-31/2021-06-06 4 10 FR France \n", + "2021-06-07/2021-06-13 10 18 FR France \n", + "2021-06-14/2021-06-20 13 23 FR France \n", + "2021-06-21/2021-06-27 10 18 FR France \n", + "2021-06-28/2021-07-04 6 16 FR France \n", + "2021-07-05/2021-07-11 7 21 FR France \n", + "2021-07-12/2021-07-18 0 33 FR France \n", + "2021-07-19/2021-07-25 6 14 FR France \n", + "2021-07-26/2021-08-01 6 16 FR France \n", + "2021-08-02/2021-08-08 3 11 FR France \n", + "2021-08-09/2021-08-15 3 9 FR France \n", + "2021-08-16/2021-08-22 3 9 FR France \n", + "2021-08-23/2021-08-29 0 4 FR France \n", + "2021-08-30/2021-09-05 2 6 FR France \n", + "2021-09-06/2021-09-12 2 8 FR France \n", + "2021-09-13/2021-09-19 1 5 FR France \n", + "2021-09-20/2021-09-26 4 10 FR France \n", + "2021-09-27/2021-10-03 1 5 FR France \n", + "2021-10-04/2021-10-10 4 10 FR France \n", + "2021-10-11/2021-10-17 3 9 FR France \n", + "2021-10-18/2021-10-24 9 19 FR France \n", + "2021-10-25/2021-10-31 7 17 FR France \n", + "2021-11-01/2021-11-07 8 18 FR France \n", + "2021-11-08/2021-11-14 10 18 FR France \n", + "2021-11-15/2021-11-21 9 17 FR France \n", + "2021-11-22/2021-11-28 14 24 FR France \n", + "\n", + "[1617 rows x 10 columns]" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted_data" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "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('1d'):\n", + " print(p1, p2)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "PeriodIndex(['1990-12-03/1990-12-09', '1990-12-10/1990-12-16',\n", + " '1990-12-17/1990-12-23', '1990-12-24/1990-12-30',\n", + " '1990-12-31/1991-01-06', '1991-01-07/1991-01-13',\n", + " '1991-01-14/1991-01-20', '1991-01-21/1991-01-27',\n", + " '1991-01-28/1991-02-03', '1991-02-04/1991-02-10',\n", + " ...\n", + " '2021-09-20/2021-09-26', '2021-09-27/2021-10-03',\n", + " '2021-10-04/2021-10-10', '2021-10-11/2021-10-17',\n", + " '2021-10-18/2021-10-24', '2021-10-25/2021-10-31',\n", + " '2021-11-01/2021-11-07', '2021-11-08/2021-11-14',\n", + " '2021-11-15/2021-11-21', '2021-11-22/2021-11-28'],\n", + " dtype='period[W-SUN]', name='period', length=1617, freq='W-SUN')" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "periods" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "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": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "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'][-200:].plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "first_september_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", + " for y in range(1990,\n", + " sorted_data.index[-1].year)]" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "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", + " 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": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 31, + "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": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "2020 221186\n", + "2002 516689\n", + "2018 542312\n", + "2017 551041\n", + "1991 553090\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": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "yearly_incidence.sort_values()" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 33, + "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 +3398,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.3" + "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 } - -- 2.18.1