{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Sujet 7 : Autour du SARS-CoV-2" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import re\n", "import math" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Les données de l'incidence du syndrome grippal sont disponibles du site Web du Réseau Sentinelles. Nous les récupérons sous forme d'un fichier en format CSV dont chaque ligne correspond à une semaine de la période demandée. Nous téléchargeons toujours le jeu de données complet." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "data_url=\"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv\"" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Province/StateCountry/RegionLatLong1/22/201/23/201/24/201/25/201/26/201/27/20...8/27/218/28/218/29/218/30/218/31/219/1/219/2/219/3/219/4/219/5/21
0NaNAfghanistan33.93911067.709953000000...152960152960152960153148153220153260153306153375153375153375
1NaNAlbania41.15330020.168300000000...143174144079144847145333146387147369148222149117150101150997
2NaNAlgeria28.0339001.659600000000...194186194671195162195574196080196527196915197308197659198004
3NaNAndorra42.5063001.521800000000...15025150251502515032150331504615052150551505515055
4NaNAngola-11.20270017.873900000000...46929470794716847331475444778148004482614847548656
5NaNAntigua and Barbuda17.060800-61.796400000000...1598163816511713171517191742175017591870
6NaNArgentina-38.416100-63.616700000000...5167733517145851735315178889518562051909485195601519991952024055203802
7NaNArmenia40.06910045.038200000000...240261240953241336241611242135242750243386243981244602245025
8Australian Capital TerritoryAustralia-35.473500149.012400000000...361374386398421433451483498509
9New South WalesAustralia-33.868800151.209300000034...23372245852585727026281112939030807323233379235064
10Northern TerritoryAustralia-12.463400130.845600000000...201202201202202202202202202202
11QueenslandAustralia-27.469800153.025100000000...1977197719791979198019821982198419851991
12South AustraliaAustralia-34.928500138.600700000000...870871871871871871875877879880
13TasmaniaAustralia-42.882100147.327200000000...235235235235235235235235235235
14VictoriaAustralia-37.813600144.963100000011...21835219262199622071221872236122570227592294223188
15Western AustraliaAustralia-31.950500115.860500000000...1084108610861086108610861086108610861086
16NaNAustria47.51620014.550100000000...683219684541685956687076688305690153691663693416695131696905
17NaNAzerbaijan40.14310047.576900000000...409745413986417996421103424891428736432495436257439562442872
18NaNBahamas25.025885-78.035889000000...17940179401794018139181391813918576186941869418694
19NaNBahrain26.02750050.550000000000...272148272246272341272453272540272635272709272807272916273008
20NaNBangladesh23.68500090.356300000000...1486153148958914935371497261150061815036801507116151028315120261514456
21NaNBarbados13.193900-59.543200000000...4789488149314931503250725152518352485349
22NaNBelarus53.70980027.953400000000...476265477901479306480364481532483231485067487017488963490926
23NaNBelgium50.8333004.469936000000...1177909117790911779091182810118466411875061189710119200811920081192008
24NaNBelize17.189900-88.497600000000...16012160121601216220163531649316612167501675016750
25NaNBenin9.3077002.315800000000...13366133661336613366133661593215932169461694616946
26NaNBhutan27.51420090.433600000000...2592259425942595259625962596259625962596
27NaNBolivia-16.290200-63.588700000000...488933489802490056490467490879491340491759491759492509492680
28NaNBosnia and Herzegovina43.91590017.679100000000...212306212306212306213379213853214759215313216124216124216124
29NaNBotswana-22.32850024.684900000000...153793153793153793156927156927156927159317159317159317159317
..................................................................
249NaNTimor-Leste-8.874217125.727539000000...15960162361640216515166821694117183173791746817618
250NaNTogo8.6195000.824800000000...20698206982118121261212612156121785219802223422562
251NaNTrinidad and Tobago10.691800-61.222500000000...43999442964448144606448474495745061453004548745714
252NaNTunisia33.8869179.537499000000...654798658322660587662752664034666168668051670027672236674047
253NaNTurkey38.96370035.243300000000...6311607632951963468516366408638830164122476412247641224764122476412247
254NaNUS40.000000-100.000000112255...38707343387604143879888939057426391981313939615639549299398502563990642639944987
255NaNUganda1.37333332.290275000000...119327119544119732119825119915120075120208120377120466120581
256NaNUkraine48.37940031.165600000000...2376571237915923815532382769238456423870522389923239300223956162397758
257NaNUnited Arab Emirates23.42407653.847818000000...714396715394716381717374718370719355720330721308722292723263
258AnguillaUnited Kingdom18.220600-63.068600000000...194194201217217217256256279279
259BermudaUnited Kingdom32.307800-64.750500000000...2844284428442844292329232923304830483048
260British Virgin IslandsUnited Kingdom18.420700-64.640000000000...2568256825682568256825682568264026402640
261Cayman IslandsUnited Kingdom19.313300-81.254600000000...669669669680680688689690690690
262Channel IslandsUnited Kingdom49.372300-2.364400000000...10486104861048610486106081064910689107381073810738
263Falkland Islands (Malvinas)United Kingdom-51.796300-59.523600000000...66666666666767676767
264GibraltarUnited Kingdom36.140800-5.353600000000...5323533253385342535453675371537653865388
265Isle of ManUnited Kingdom54.236100-4.548100000000...6554658766296653667666946741677968096832
266MontserratUnited Kingdom16.742498-62.187366000000...26262629292929293131
267Saint Helena, Ascension and Tristan da CunhaUnited Kingdom-7.946700-14.355900000000...4444444444
268Turks and Caicos IslandsUnited Kingdom21.694000-71.797900000000...2637265026502650265026532674267426922697
269NaNUnited Kingdom55.378100-3.436000000000...6666399669848667314236757650678958168250746862904690496969416116978126
270NaNUruguay-32.522800-55.765800000000...384531384622384692384778384934385078385264385423385557385660
271NaNUzbekistan41.37749164.585262000000...153204154033154844155639156394157136157872158561159209159871
272NaNVanuatu-15.376700166.959200000000...4444444444
273NaNVenezuela6.423800-66.589700000000...329736332172333125334343334343335233337359337359338300339255
274NaNVietnam14.058324108.277199022222...410366422469435265449489462096473530486727501649511170524307
275NaNWest Bank and Gaza31.95220035.233200000000...334472335709337405339816342282344957347730350224351809353732
276NaNYemen15.55272748.516388000000...7711775177847829786979007951801880568108
277NaNZambia-13.13389727.849332000000...205704205893206051206145206327206522206705206884207028207114
278NaNZimbabwe-19.01543829.154857000000...124236124367124437124581124773124960125118125331125425125550
\n", "

279 rows × 597 columns

\n", "
" ], "text/plain": [ " Province/State Country/Region \\\n", "0 NaN Afghanistan \n", "1 NaN Albania \n", "2 NaN Algeria \n", "3 NaN Andorra \n", "4 NaN Angola \n", "5 NaN Antigua and Barbuda \n", "6 NaN Argentina \n", "7 NaN Armenia \n", "8 Australian Capital Territory Australia \n", "9 New South Wales Australia \n", "10 Northern Territory Australia \n", "11 Queensland Australia \n", "12 South Australia Australia \n", "13 Tasmania Australia \n", "14 Victoria Australia \n", "15 Western Australia Australia \n", "16 NaN Austria \n", "17 NaN Azerbaijan \n", "18 NaN Bahamas \n", "19 NaN Bahrain \n", "20 NaN Bangladesh \n", "21 NaN Barbados \n", "22 NaN Belarus \n", "23 NaN Belgium \n", "24 NaN Belize \n", "25 NaN Benin \n", "26 NaN Bhutan \n", "27 NaN Bolivia \n", "28 NaN Bosnia and Herzegovina \n", "29 NaN Botswana \n", ".. ... ... \n", "249 NaN Timor-Leste \n", "250 NaN Togo \n", "251 NaN Trinidad and Tobago \n", "252 NaN Tunisia \n", "253 NaN Turkey \n", "254 NaN US \n", "255 NaN Uganda \n", "256 NaN Ukraine \n", "257 NaN United Arab Emirates \n", "258 Anguilla United Kingdom \n", "259 Bermuda United Kingdom \n", "260 British Virgin Islands United Kingdom \n", "261 Cayman Islands United Kingdom \n", "262 Channel Islands United Kingdom \n", "263 Falkland Islands (Malvinas) United Kingdom \n", "264 Gibraltar United Kingdom \n", "265 Isle of Man United Kingdom \n", "266 Montserrat United Kingdom \n", "267 Saint Helena, Ascension and Tristan da Cunha United Kingdom \n", "268 Turks and Caicos Islands United Kingdom \n", "269 NaN United Kingdom \n", "270 NaN Uruguay \n", "271 NaN Uzbekistan \n", "272 NaN Vanuatu \n", "273 NaN Venezuela \n", "274 NaN Vietnam \n", "275 NaN West Bank and Gaza \n", "276 NaN Yemen \n", "277 NaN Zambia \n", "278 NaN Zimbabwe \n", "\n", " Lat Long 1/22/20 1/23/20 1/24/20 1/25/20 1/26/20 \\\n", "0 33.939110 67.709953 0 0 0 0 0 \n", "1 41.153300 20.168300 0 0 0 0 0 \n", "2 28.033900 1.659600 0 0 0 0 0 \n", "3 42.506300 1.521800 0 0 0 0 0 \n", "4 -11.202700 17.873900 0 0 0 0 0 \n", "5 17.060800 -61.796400 0 0 0 0 0 \n", "6 -38.416100 -63.616700 0 0 0 0 0 \n", "7 40.069100 45.038200 0 0 0 0 0 \n", "8 -35.473500 149.012400 0 0 0 0 0 \n", "9 -33.868800 151.209300 0 0 0 0 3 \n", "10 -12.463400 130.845600 0 0 0 0 0 \n", "11 -27.469800 153.025100 0 0 0 0 0 \n", "12 -34.928500 138.600700 0 0 0 0 0 \n", "13 -42.882100 147.327200 0 0 0 0 0 \n", "14 -37.813600 144.963100 0 0 0 0 1 \n", "15 -31.950500 115.860500 0 0 0 0 0 \n", "16 47.516200 14.550100 0 0 0 0 0 \n", "17 40.143100 47.576900 0 0 0 0 0 \n", "18 25.025885 -78.035889 0 0 0 0 0 \n", "19 26.027500 50.550000 0 0 0 0 0 \n", "20 23.685000 90.356300 0 0 0 0 0 \n", "21 13.193900 -59.543200 0 0 0 0 0 \n", "22 53.709800 27.953400 0 0 0 0 0 \n", "23 50.833300 4.469936 0 0 0 0 0 \n", "24 17.189900 -88.497600 0 0 0 0 0 \n", "25 9.307700 2.315800 0 0 0 0 0 \n", "26 27.514200 90.433600 0 0 0 0 0 \n", "27 -16.290200 -63.588700 0 0 0 0 0 \n", "28 43.915900 17.679100 0 0 0 0 0 \n", "29 -22.328500 24.684900 0 0 0 0 0 \n", ".. ... ... ... ... ... ... ... \n", "249 -8.874217 125.727539 0 0 0 0 0 \n", "250 8.619500 0.824800 0 0 0 0 0 \n", "251 10.691800 -61.222500 0 0 0 0 0 \n", "252 33.886917 9.537499 0 0 0 0 0 \n", "253 38.963700 35.243300 0 0 0 0 0 \n", "254 40.000000 -100.000000 1 1 2 2 5 \n", "255 1.373333 32.290275 0 0 0 0 0 \n", "256 48.379400 31.165600 0 0 0 0 0 \n", "257 23.424076 53.847818 0 0 0 0 0 \n", "258 18.220600 -63.068600 0 0 0 0 0 \n", "259 32.307800 -64.750500 0 0 0 0 0 \n", "260 18.420700 -64.640000 0 0 0 0 0 \n", "261 19.313300 -81.254600 0 0 0 0 0 \n", "262 49.372300 -2.364400 0 0 0 0 0 \n", "263 -51.796300 -59.523600 0 0 0 0 0 \n", "264 36.140800 -5.353600 0 0 0 0 0 \n", "265 54.236100 -4.548100 0 0 0 0 0 \n", "266 16.742498 -62.187366 0 0 0 0 0 \n", "267 -7.946700 -14.355900 0 0 0 0 0 \n", "268 21.694000 -71.797900 0 0 0 0 0 \n", "269 55.378100 -3.436000 0 0 0 0 0 \n", "270 -32.522800 -55.765800 0 0 0 0 0 \n", "271 41.377491 64.585262 0 0 0 0 0 \n", "272 -15.376700 166.959200 0 0 0 0 0 \n", "273 6.423800 -66.589700 0 0 0 0 0 \n", "274 14.058324 108.277199 0 2 2 2 2 \n", "275 31.952200 35.233200 0 0 0 0 0 \n", "276 15.552727 48.516388 0 0 0 0 0 \n", "277 -13.133897 27.849332 0 0 0 0 0 \n", "278 -19.015438 29.154857 0 0 0 0 0 \n", "\n", " 1/27/20 ... 8/27/21 8/28/21 8/29/21 8/30/21 8/31/21 \\\n", "0 0 ... 152960 152960 152960 153148 153220 \n", "1 0 ... 143174 144079 144847 145333 146387 \n", "2 0 ... 194186 194671 195162 195574 196080 \n", "3 0 ... 15025 15025 15025 15032 15033 \n", "4 0 ... 46929 47079 47168 47331 47544 \n", "5 0 ... 1598 1638 1651 1713 1715 \n", "6 0 ... 5167733 5171458 5173531 5178889 5185620 \n", "7 0 ... 240261 240953 241336 241611 242135 \n", "8 0 ... 361 374 386 398 421 \n", "9 4 ... 23372 24585 25857 27026 28111 \n", "10 0 ... 201 202 201 202 202 \n", "11 0 ... 1977 1977 1979 1979 1980 \n", "12 0 ... 870 871 871 871 871 \n", "13 0 ... 235 235 235 235 235 \n", "14 1 ... 21835 21926 21996 22071 22187 \n", "15 0 ... 1084 1086 1086 1086 1086 \n", "16 0 ... 683219 684541 685956 687076 688305 \n", "17 0 ... 409745 413986 417996 421103 424891 \n", "18 0 ... 17940 17940 17940 18139 18139 \n", "19 0 ... 272148 272246 272341 272453 272540 \n", "20 0 ... 1486153 1489589 1493537 1497261 1500618 \n", "21 0 ... 4789 4881 4931 4931 5032 \n", "22 0 ... 476265 477901 479306 480364 481532 \n", "23 0 ... 1177909 1177909 1177909 1182810 1184664 \n", "24 0 ... 16012 16012 16012 16220 16353 \n", "25 0 ... 13366 13366 13366 13366 13366 \n", "26 0 ... 2592 2594 2594 2595 2596 \n", "27 0 ... 488933 489802 490056 490467 490879 \n", "28 0 ... 212306 212306 212306 213379 213853 \n", "29 0 ... 153793 153793 153793 156927 156927 \n", ".. ... ... ... ... ... ... ... \n", "249 0 ... 15960 16236 16402 16515 16682 \n", "250 0 ... 20698 20698 21181 21261 21261 \n", "251 0 ... 43999 44296 44481 44606 44847 \n", "252 0 ... 654798 658322 660587 662752 664034 \n", "253 0 ... 6311607 6329519 6346851 6366408 6388301 \n", "254 5 ... 38707343 38760414 38798889 39057426 39198131 \n", "255 0 ... 119327 119544 119732 119825 119915 \n", "256 0 ... 2376571 2379159 2381553 2382769 2384564 \n", "257 0 ... 714396 715394 716381 717374 718370 \n", "258 0 ... 194 194 201 217 217 \n", "259 0 ... 2844 2844 2844 2844 2923 \n", "260 0 ... 2568 2568 2568 2568 2568 \n", "261 0 ... 669 669 669 680 680 \n", "262 0 ... 10486 10486 10486 10486 10608 \n", "263 0 ... 66 66 66 66 66 \n", "264 0 ... 5323 5332 5338 5342 5354 \n", "265 0 ... 6554 6587 6629 6653 6676 \n", "266 0 ... 26 26 26 29 29 \n", "267 0 ... 4 4 4 4 4 \n", "268 0 ... 2637 2650 2650 2650 2650 \n", "269 0 ... 6666399 6698486 6731423 6757650 6789581 \n", "270 0 ... 384531 384622 384692 384778 384934 \n", "271 0 ... 153204 154033 154844 155639 156394 \n", "272 0 ... 4 4 4 4 4 \n", "273 0 ... 329736 332172 333125 334343 334343 \n", "274 2 ... 410366 422469 435265 449489 462096 \n", "275 0 ... 334472 335709 337405 339816 342282 \n", "276 0 ... 7711 7751 7784 7829 7869 \n", "277 0 ... 205704 205893 206051 206145 206327 \n", "278 0 ... 124236 124367 124437 124581 124773 \n", "\n", " 9/1/21 9/2/21 9/3/21 9/4/21 9/5/21 \n", "0 153260 153306 153375 153375 153375 \n", "1 147369 148222 149117 150101 150997 \n", "2 196527 196915 197308 197659 198004 \n", "3 15046 15052 15055 15055 15055 \n", "4 47781 48004 48261 48475 48656 \n", "5 1719 1742 1750 1759 1870 \n", "6 5190948 5195601 5199919 5202405 5203802 \n", "7 242750 243386 243981 244602 245025 \n", "8 433 451 483 498 509 \n", "9 29390 30807 32323 33792 35064 \n", "10 202 202 202 202 202 \n", "11 1982 1982 1984 1985 1991 \n", "12 871 875 877 879 880 \n", "13 235 235 235 235 235 \n", "14 22361 22570 22759 22942 23188 \n", "15 1086 1086 1086 1086 1086 \n", "16 690153 691663 693416 695131 696905 \n", "17 428736 432495 436257 439562 442872 \n", "18 18139 18576 18694 18694 18694 \n", "19 272635 272709 272807 272916 273008 \n", "20 1503680 1507116 1510283 1512026 1514456 \n", "21 5072 5152 5183 5248 5349 \n", "22 483231 485067 487017 488963 490926 \n", "23 1187506 1189710 1192008 1192008 1192008 \n", "24 16493 16612 16750 16750 16750 \n", "25 15932 15932 16946 16946 16946 \n", "26 2596 2596 2596 2596 2596 \n", "27 491340 491759 491759 492509 492680 \n", "28 214759 215313 216124 216124 216124 \n", "29 156927 159317 159317 159317 159317 \n", ".. ... ... ... ... ... \n", "249 16941 17183 17379 17468 17618 \n", "250 21561 21785 21980 22234 22562 \n", "251 44957 45061 45300 45487 45714 \n", "252 666168 668051 670027 672236 674047 \n", "253 6412247 6412247 6412247 6412247 6412247 \n", "254 39396156 39549299 39850256 39906426 39944987 \n", "255 120075 120208 120377 120466 120581 \n", "256 2387052 2389923 2393002 2395616 2397758 \n", "257 719355 720330 721308 722292 723263 \n", "258 217 256 256 279 279 \n", "259 2923 2923 3048 3048 3048 \n", "260 2568 2568 2640 2640 2640 \n", "261 688 689 690 690 690 \n", "262 10649 10689 10738 10738 10738 \n", "263 67 67 67 67 67 \n", "264 5367 5371 5376 5386 5388 \n", "265 6694 6741 6779 6809 6832 \n", "266 29 29 29 31 31 \n", "267 4 4 4 4 4 \n", "268 2653 2674 2674 2692 2697 \n", "269 6825074 6862904 6904969 6941611 6978126 \n", "270 385078 385264 385423 385557 385660 \n", "271 157136 157872 158561 159209 159871 \n", "272 4 4 4 4 4 \n", "273 335233 337359 337359 338300 339255 \n", "274 473530 486727 501649 511170 524307 \n", "275 344957 347730 350224 351809 353732 \n", "276 7900 7951 8018 8056 8108 \n", "277 206522 206705 206884 207028 207114 \n", "278 124960 125118 125331 125425 125550 \n", "\n", "[279 rows x 597 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = pd.read_csv(data_url, skiprows=0)\n", "raw_data" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "Belgium = raw_data[raw_data['Country/Region'].str.match('Belgium')]\n", "Germany = raw_data[raw_data['Country/Region'].str.match('Germany')]\n", "Iran = raw_data[raw_data['Country/Region'].str.match('Iran')]\n", "Italy = raw_data[raw_data['Country/Region'].str.match('Italy')]\n", "Japan = raw_data[raw_data['Country/Region'].str.match('Japan')]\n", "Korea = raw_data[raw_data['Country/Region'].str.match('Korea, South')]\n", "Portugal = raw_data[raw_data['Country/Region'].str.match('Portugal')]\n", "Spain = raw_data[raw_data['Country/Region'].str.match('Spain')]\n", "US = raw_data[raw_data['Country/Region'].str.match('US')]\n", "\n", "temp = raw_data[raw_data['Country/Region'].str.match('China')]\n", "China = temp.drop(index=temp[temp['Province/State'].str.match('Hong Kong')].index[0])\n", "\n", "temp = raw_data[raw_data['Country/Region'].str.match('France')]\n", "France = temp[temp.isnull().any(axis=1)]\n", "\n", "temp = raw_data[raw_data['Country/Region'].str.match('United Kingdom')]\n", "UK = temp[temp.isnull().any(axis=1)]\n", "\n", "temp = raw_data[raw_data['Country/Region'].str.match('Netherlands')]\n", "Netherlands = temp[temp.isnull().any(axis=1)]" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "def conv_date(ind):\n", " d=[]\n", " for i in ind[4:]:\n", " a = re.split('/',i)\n", " d.append(a[1]+'-'+a[0]+'-20'+a[2])\n", " return d\n", "\n", "date = conv_date(US.transpose().index)\n", "def log(df):\n", " val = []\n", " for i in df['cumul']:\n", " if i!=0:\n", " val.append(math.log(i))\n", " else:\n", " val.append(0)\n", " df['cumul_log']=val\n", " return df\n", "\n", "def arrangement(df,rename,calc_log):\n", " df=df.transpose()\n", " df=df.drop(index='Country/Region')\n", " df=df.drop(index='Province/State')\n", " df=df.drop(index='Long')\n", " df=df.drop(index='Lat')\n", " df['date']=date\n", " df1 = df.set_index('date')\n", " if rename:\n", " df1 = df1.rename(columns={list(df1)[0]:\"cumul\"})\n", " if calc_log:\n", " log(df1)\n", " return df1" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "Belgium = arrangement(Belgium,True,True)\n", "Germany = arrangement(Germany,True,True)\n", "Iran = arrangement(Iran,True,True)\n", "Italy = arrangement(Italy,True,True)\n", "Japan = arrangement(Japan,True,True)\n", "Korea = arrangement(Korea,True,True)\n", "Portugal = arrangement(Portugal,True,True)\n", "Spain = arrangement(Spain,True,True)\n", "US = arrangement(US,True,True)\n", "China = arrangement(China,False,False)\n", "China['cumul']=China.sum(axis=1)\n", "China = log(China)\n", "France = arrangement(France,True,True)\n", "UK =arrangement(UK,True,True)\n", "Netherlands = arrangement(Netherlands,True,True)\n", "liste = [Belgium,Germany,Iran,Italy,Japan,Korea,Portugal,Spain,US,China,France,UK,Netherlands]" ] }, { "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": 2 }