{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Travail pratique sur l'épidémiologie du SARS-COV2" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import isoweek" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "x = pd.read_csv(\"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv\")\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Province/StateCountry/RegionLatLong1/22/201/23/201/24/201/25/201/26/201/27/20...5/29/205/30/205/31/206/1/206/2/206/3/206/4/206/5/206/6/206/7/20
0NaNAfghanistan33.00000065.000000000000...13659145251520515750165091726718054189691955120342
1NaNAlbania41.15330020.168300000000...1099112211371143116411841197121212321246
2NaNAlgeria28.0339001.659600000000...913492679394951396269733983199351005010154
3NaNAndorra42.5063001.521800000000...764764764765844851852852852852
4NaNAngola-11.20270017.873900000000...81848686868686868891
5NaNAntigua and Barbuda17.060800-61.796400000000...25252626262626262626
6NaNArgentina-38.416100-63.616700000000...15419162141685117415183191926820197210372202022794
7NaNArmenia40.06910045.038200000000...8676892792829492100091052411221118171236413130
8Australian Capital TerritoryAustralia-35.473500149.012400000000...107107107107107107107107108108
9New South WalesAustralia-33.868800151.209300000034...3092309530983104310431063110311031093112
10Northern TerritoryAustralia-12.463400130.845600000000...29292929292929292929
11QueenslandAustralia-28.016700153.400000000000...1058105810581059105910601060106110611062
12South AustraliaAustralia-34.928500138.600700000000...440440440440440440440440440440
13TasmaniaAustralia-41.454500145.970700000000...228228228228228228228228228228
14VictoriaAustralia-37.813600144.963100000011...1645164916531663167016781681168116851687
15Western AustraliaAustralia-31.950500115.860500000000...585586589591592592592596599599
16NaNAustria47.51620014.550100000000...16655166851673116733167591677116805168431689816902
17NaNAzerbaijan40.14310047.576900000000...4989524654945662593562606522686072397553
18NaNBahamas25.034300-77.396300000000...102102102102102102102102103103
19NaNBahrain26.02750050.550000000000...10449107931139811871123111281513296138351438314763
20NaNBangladesh23.68500090.356300000000...42844446084715349534524455514057563603916302665769
21NaNBarbados13.193900-59.543200000000...92929292929292929292
22NaNBelarus53.70980027.953400000000...40764416584255643403442554511645981468684775148630
23NaNBelgium50.8333004.000000000000...58061581865838158517586155868558767589075907259226
24NaNBenin9.3077002.315800000000...224224232243244244261261261261
25NaNBhutan27.51420090.433600000000...31334343474747484859
26NaNBolivia-16.290200-63.588700000000...87319592998210531109911163812245127281335813643
27NaNBosnia and Herzegovina43.91590017.679100000000...2485249425102524253525512594260626062606
28NaNBrazil-14.235000-51.925300000000...465166498440514849526447555383584016614941645771672846691758
29NaNBrunei4.535300114.727700000000...141141141141141141141141141141
..................................................................
236NaNTimor-Leste-8.874217125.727539000000...24242424242424242424
237NaNBelize13.193900-59.543200000000...18181818181818191919
238NaNLaos19.856270102.495496000000...19191919191919191919
239NaNLibya26.33510017.228331000000...118130156168182196209239256256
240NaNWest Bank and Gaza31.95220035.233200000000...446447448449451457464464464472
241NaNGuinea-Bissau11.803700-15.180400000000...1256125612561339133913391339136813681368
242NaNMali17.570692-3.996166000000...1226125012651315135113861461148515231533
243NaNSaint Kitts and Nevis17.357822-62.782998000000...15151515151515151515
244Northwest TerritoriesCanada64.825500-124.845700000000...5555555555
245YukonCanada64.282300-135.000000000000...11111111111111111111
246NaNKosovo42.60263620.902977000000...1048106410641064106411421142114211421142
247NaNBurma21.91620095.956000000000...207224224228232233236236240242
248AnguillaUnited Kingdom18.220600-63.068600000000...3333333333
249British Virgin IslandsUnited Kingdom18.420700-64.640000000000...8888888888
250Turks and Caicos IslandsUnited Kingdom21.694000-71.797900000000...12121212121212121212
251NaNMS Zaandam0.0000000.000000000000...9999999999
252NaNBotswana-22.32850024.684900000000...35353538404040404040
253NaNBurundi-3.37310029.918900000000...42636363636363638383
254NaNSierra Leone8.460555-11.779889000000...829852861865896909914929946969
255Bonaire, Sint Eustatius and SabaNetherlands12.178400-68.238500000000...6667777777
256NaNMalawi-13.25430834.301525000000...273279284336358369393409409438
257Falkland Islands (Malvinas)United Kingdom-51.796300-59.523600000000...13131313131313131313
258Saint Pierre and MiquelonFrance46.885200-56.315900000000...1111111111
259NaNSouth Sudan6.87700031.307000000000...9949949949949949949949949941317
260NaNWestern Sahara24.215500-12.885800000000...9999999999
261NaNSao Tome and Principe0.1863606.613081000000...463479483484484484485499499513
262NaNYemen15.55272748.516388000000...283310323354399419453469482484
263NaNComoros-11.64550043.333300000000...87106106106132132132132141141
264NaNTajikistan38.86103471.276093000000...3686380739304013410041914289437044534529
265NaNLesotho-29.60998828.233608000000...2222244444
\n", "

266 rows × 142 columns

\n", "
" ], "text/plain": [ " Province/State Country/Region Lat \\\n", "0 NaN Afghanistan 33.000000 \n", "1 NaN Albania 41.153300 \n", "2 NaN Algeria 28.033900 \n", "3 NaN Andorra 42.506300 \n", "4 NaN Angola -11.202700 \n", "5 NaN Antigua and Barbuda 17.060800 \n", "6 NaN Argentina -38.416100 \n", "7 NaN Armenia 40.069100 \n", "8 Australian Capital Territory Australia -35.473500 \n", "9 New South Wales Australia -33.868800 \n", "10 Northern Territory Australia -12.463400 \n", "11 Queensland Australia -28.016700 \n", "12 South Australia Australia -34.928500 \n", "13 Tasmania Australia -41.454500 \n", "14 Victoria Australia -37.813600 \n", "15 Western Australia Australia -31.950500 \n", "16 NaN Austria 47.516200 \n", "17 NaN Azerbaijan 40.143100 \n", "18 NaN Bahamas 25.034300 \n", "19 NaN Bahrain 26.027500 \n", "20 NaN Bangladesh 23.685000 \n", "21 NaN Barbados 13.193900 \n", "22 NaN Belarus 53.709800 \n", "23 NaN Belgium 50.833300 \n", "24 NaN Benin 9.307700 \n", "25 NaN Bhutan 27.514200 \n", "26 NaN Bolivia -16.290200 \n", "27 NaN Bosnia and Herzegovina 43.915900 \n", "28 NaN Brazil -14.235000 \n", "29 NaN Brunei 4.535300 \n", ".. ... ... ... \n", "236 NaN Timor-Leste -8.874217 \n", "237 NaN Belize 13.193900 \n", "238 NaN Laos 19.856270 \n", "239 NaN Libya 26.335100 \n", "240 NaN West Bank and Gaza 31.952200 \n", "241 NaN Guinea-Bissau 11.803700 \n", "242 NaN Mali 17.570692 \n", "243 NaN Saint Kitts and Nevis 17.357822 \n", "244 Northwest Territories Canada 64.825500 \n", "245 Yukon Canada 64.282300 \n", "246 NaN Kosovo 42.602636 \n", "247 NaN Burma 21.916200 \n", "248 Anguilla United Kingdom 18.220600 \n", "249 British Virgin Islands United Kingdom 18.420700 \n", "250 Turks and Caicos Islands United Kingdom 21.694000 \n", "251 NaN MS Zaandam 0.000000 \n", "252 NaN Botswana -22.328500 \n", "253 NaN Burundi -3.373100 \n", "254 NaN Sierra Leone 8.460555 \n", "255 Bonaire, Sint Eustatius and Saba Netherlands 12.178400 \n", "256 NaN Malawi -13.254308 \n", "257 Falkland Islands (Malvinas) United Kingdom -51.796300 \n", "258 Saint Pierre and Miquelon France 46.885200 \n", "259 NaN South Sudan 6.877000 \n", "260 NaN Western Sahara 24.215500 \n", "261 NaN Sao Tome and Principe 0.186360 \n", "262 NaN Yemen 15.552727 \n", "263 NaN Comoros -11.645500 \n", "264 NaN Tajikistan 38.861034 \n", "265 NaN Lesotho -29.609988 \n", "\n", " Long 1/22/20 1/23/20 1/24/20 1/25/20 1/26/20 1/27/20 ... \\\n", "0 65.000000 0 0 0 0 0 0 ... \n", "1 20.168300 0 0 0 0 0 0 ... \n", "2 1.659600 0 0 0 0 0 0 ... \n", "3 1.521800 0 0 0 0 0 0 ... \n", "4 17.873900 0 0 0 0 0 0 ... \n", "5 -61.796400 0 0 0 0 0 0 ... \n", "6 -63.616700 0 0 0 0 0 0 ... \n", "7 45.038200 0 0 0 0 0 0 ... \n", "8 149.012400 0 0 0 0 0 0 ... \n", "9 151.209300 0 0 0 0 3 4 ... \n", "10 130.845600 0 0 0 0 0 0 ... \n", "11 153.400000 0 0 0 0 0 0 ... \n", "12 138.600700 0 0 0 0 0 0 ... \n", "13 145.970700 0 0 0 0 0 0 ... \n", "14 144.963100 0 0 0 0 1 1 ... \n", "15 115.860500 0 0 0 0 0 0 ... \n", "16 14.550100 0 0 0 0 0 0 ... \n", "17 47.576900 0 0 0 0 0 0 ... \n", "18 -77.396300 0 0 0 0 0 0 ... \n", "19 50.550000 0 0 0 0 0 0 ... \n", "20 90.356300 0 0 0 0 0 0 ... \n", "21 -59.543200 0 0 0 0 0 0 ... \n", "22 27.953400 0 0 0 0 0 0 ... \n", "23 4.000000 0 0 0 0 0 0 ... \n", "24 2.315800 0 0 0 0 0 0 ... \n", "25 90.433600 0 0 0 0 0 0 ... \n", "26 -63.588700 0 0 0 0 0 0 ... \n", "27 17.679100 0 0 0 0 0 0 ... \n", "28 -51.925300 0 0 0 0 0 0 ... \n", "29 114.727700 0 0 0 0 0 0 ... \n", ".. ... ... ... ... ... ... ... ... \n", "236 125.727539 0 0 0 0 0 0 ... \n", "237 -59.543200 0 0 0 0 0 0 ... \n", "238 102.495496 0 0 0 0 0 0 ... \n", "239 17.228331 0 0 0 0 0 0 ... \n", "240 35.233200 0 0 0 0 0 0 ... \n", "241 -15.180400 0 0 0 0 0 0 ... \n", "242 -3.996166 0 0 0 0 0 0 ... \n", "243 -62.782998 0 0 0 0 0 0 ... \n", "244 -124.845700 0 0 0 0 0 0 ... \n", "245 -135.000000 0 0 0 0 0 0 ... \n", "246 20.902977 0 0 0 0 0 0 ... \n", "247 95.956000 0 0 0 0 0 0 ... \n", "248 -63.068600 0 0 0 0 0 0 ... \n", "249 -64.640000 0 0 0 0 0 0 ... \n", "250 -71.797900 0 0 0 0 0 0 ... \n", "251 0.000000 0 0 0 0 0 0 ... \n", "252 24.684900 0 0 0 0 0 0 ... \n", "253 29.918900 0 0 0 0 0 0 ... \n", "254 -11.779889 0 0 0 0 0 0 ... \n", "255 -68.238500 0 0 0 0 0 0 ... \n", "256 34.301525 0 0 0 0 0 0 ... \n", "257 -59.523600 0 0 0 0 0 0 ... \n", "258 -56.315900 0 0 0 0 0 0 ... \n", "259 31.307000 0 0 0 0 0 0 ... \n", "260 -12.885800 0 0 0 0 0 0 ... \n", "261 6.613081 0 0 0 0 0 0 ... \n", "262 48.516388 0 0 0 0 0 0 ... \n", "263 43.333300 0 0 0 0 0 0 ... \n", "264 71.276093 0 0 0 0 0 0 ... \n", "265 28.233608 0 0 0 0 0 0 ... \n", "\n", " 5/29/20 5/30/20 5/31/20 6/1/20 6/2/20 6/3/20 6/4/20 6/5/20 \\\n", "0 13659 14525 15205 15750 16509 17267 18054 18969 \n", "1 1099 1122 1137 1143 1164 1184 1197 1212 \n", "2 9134 9267 9394 9513 9626 9733 9831 9935 \n", "3 764 764 764 765 844 851 852 852 \n", "4 81 84 86 86 86 86 86 86 \n", "5 25 25 26 26 26 26 26 26 \n", "6 15419 16214 16851 17415 18319 19268 20197 21037 \n", "7 8676 8927 9282 9492 10009 10524 11221 11817 \n", "8 107 107 107 107 107 107 107 107 \n", "9 3092 3095 3098 3104 3104 3106 3110 3110 \n", "10 29 29 29 29 29 29 29 29 \n", "11 1058 1058 1058 1059 1059 1060 1060 1061 \n", "12 440 440 440 440 440 440 440 440 \n", "13 228 228 228 228 228 228 228 228 \n", "14 1645 1649 1653 1663 1670 1678 1681 1681 \n", "15 585 586 589 591 592 592 592 596 \n", "16 16655 16685 16731 16733 16759 16771 16805 16843 \n", "17 4989 5246 5494 5662 5935 6260 6522 6860 \n", "18 102 102 102 102 102 102 102 102 \n", "19 10449 10793 11398 11871 12311 12815 13296 13835 \n", "20 42844 44608 47153 49534 52445 55140 57563 60391 \n", "21 92 92 92 92 92 92 92 92 \n", "22 40764 41658 42556 43403 44255 45116 45981 46868 \n", "23 58061 58186 58381 58517 58615 58685 58767 58907 \n", "24 224 224 232 243 244 244 261 261 \n", "25 31 33 43 43 47 47 47 48 \n", "26 8731 9592 9982 10531 10991 11638 12245 12728 \n", "27 2485 2494 2510 2524 2535 2551 2594 2606 \n", "28 465166 498440 514849 526447 555383 584016 614941 645771 \n", "29 141 141 141 141 141 141 141 141 \n", ".. ... ... ... ... ... ... ... ... \n", "236 24 24 24 24 24 24 24 24 \n", "237 18 18 18 18 18 18 18 19 \n", "238 19 19 19 19 19 19 19 19 \n", "239 118 130 156 168 182 196 209 239 \n", "240 446 447 448 449 451 457 464 464 \n", "241 1256 1256 1256 1339 1339 1339 1339 1368 \n", "242 1226 1250 1265 1315 1351 1386 1461 1485 \n", "243 15 15 15 15 15 15 15 15 \n", "244 5 5 5 5 5 5 5 5 \n", "245 11 11 11 11 11 11 11 11 \n", "246 1048 1064 1064 1064 1064 1142 1142 1142 \n", "247 207 224 224 228 232 233 236 236 \n", "248 3 3 3 3 3 3 3 3 \n", "249 8 8 8 8 8 8 8 8 \n", "250 12 12 12 12 12 12 12 12 \n", "251 9 9 9 9 9 9 9 9 \n", "252 35 35 35 38 40 40 40 40 \n", "253 42 63 63 63 63 63 63 63 \n", "254 829 852 861 865 896 909 914 929 \n", "255 6 6 6 7 7 7 7 7 \n", "256 273 279 284 336 358 369 393 409 \n", "257 13 13 13 13 13 13 13 13 \n", "258 1 1 1 1 1 1 1 1 \n", "259 994 994 994 994 994 994 994 994 \n", "260 9 9 9 9 9 9 9 9 \n", "261 463 479 483 484 484 484 485 499 \n", "262 283 310 323 354 399 419 453 469 \n", "263 87 106 106 106 132 132 132 132 \n", "264 3686 3807 3930 4013 4100 4191 4289 4370 \n", "265 2 2 2 2 2 4 4 4 \n", "\n", " 6/6/20 6/7/20 \n", "0 19551 20342 \n", "1 1232 1246 \n", "2 10050 10154 \n", "3 852 852 \n", "4 88 91 \n", "5 26 26 \n", "6 22020 22794 \n", "7 12364 13130 \n", "8 108 108 \n", "9 3109 3112 \n", "10 29 29 \n", "11 1061 1062 \n", "12 440 440 \n", "13 228 228 \n", "14 1685 1687 \n", "15 599 599 \n", "16 16898 16902 \n", "17 7239 7553 \n", "18 103 103 \n", "19 14383 14763 \n", "20 63026 65769 \n", "21 92 92 \n", "22 47751 48630 \n", "23 59072 59226 \n", "24 261 261 \n", "25 48 59 \n", "26 13358 13643 \n", "27 2606 2606 \n", "28 672846 691758 \n", "29 141 141 \n", ".. ... ... \n", "236 24 24 \n", "237 19 19 \n", "238 19 19 \n", "239 256 256 \n", "240 464 472 \n", "241 1368 1368 \n", "242 1523 1533 \n", "243 15 15 \n", "244 5 5 \n", "245 11 11 \n", "246 1142 1142 \n", "247 240 242 \n", "248 3 3 \n", "249 8 8 \n", "250 12 12 \n", "251 9 9 \n", "252 40 40 \n", "253 83 83 \n", "254 946 969 \n", "255 7 7 \n", "256 409 438 \n", "257 13 13 \n", "258 1 1 \n", "259 994 1317 \n", "260 9 9 \n", "261 499 513 \n", "262 482 484 \n", "263 141 141 \n", "264 4453 4529 \n", "265 4 4 \n", "\n", "[266 rows x 142 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "x" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "tableau indicatif\n", "le format des dates est actuellement en mois/jourdumois/année" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "en dessous on a une proposition pour faire une curvefit voir s'il faut pas faire autre chose\n", "trouver une code pour faire les mois voulu avec string ou autre" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "ename": "KeyError", "evalue": "'time (day)'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 2524\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2525\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2526\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", "\u001b[0;31mKeyError\u001b[0m: 'time (day)'", "\nDuring handling of the above exception, another exception occurred:\n", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'time (day)'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'case (unit)'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2137\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2138\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2139\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2140\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2141\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2144\u001b[0m \u001b[0;31m# get column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2145\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2146\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2147\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2148\u001b[0m \u001b[0;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m 1840\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1841\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1842\u001b[0;31m \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1843\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_box_item_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1844\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/internals.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, item, fastpath)\u001b[0m\n\u001b[1;32m 3841\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3842\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3843\u001b[0;31m \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3844\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3845\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 2525\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2526\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2527\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2528\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2529\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", "\u001b[0;31mKeyError\u001b[0m: 'time (day)'" ] } ], "source": [ "plt.plot(x['time (day)'],x['case (unit)'])\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 4 }