diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb index c3d122771360424bca738dcce3b95fbe6de5cac4..2ce944001d0f5d134898505c2cf3501e80de6b3c 100644 --- a/module3/exo2/exercice.ipynb +++ b/module3/exo2/exercice.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -23,18 +23,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Les données de l'incidence du syndrome grippal sont disponibles du site Web du [Réseau Sentinelles](http://www.sentiweb.fr/). 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, qui commence en 1984 et se termine avec une semaine récente." + "Les données de l'incidence de la varicelle sont disponibles du site Web du [Réseau Sentinelles](http://www.sentiweb.fr/). 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, qui commence en 1991 et se termine avec une semaine récente." ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 2, + "metadata": {}, "outputs": [], "source": [ - "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" + "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"" ] }, { @@ -61,9 +59,976 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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.................................
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1532 rows × 10 columns

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" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202015 7 1928 661 3195 3 1 \n", + "1 202014 7 3879 2227 5531 6 3 \n", + "2 202013 7 7326 5236 9416 11 8 \n", + "3 202012 7 8123 5790 10456 12 8 \n", + "4 202011 7 10198 7568 12828 15 11 \n", + "5 202010 7 9011 6691 11331 14 10 \n", + "6 202009 7 13631 10544 16718 21 16 \n", + "7 202008 7 10424 7708 13140 16 12 \n", + "8 202007 7 8959 6574 11344 14 10 \n", + "9 202006 7 9264 6925 11603 14 10 \n", + "10 202005 7 8505 6314 10696 13 10 \n", + "11 202004 7 7991 5831 10151 12 9 \n", + "12 202003 7 5968 4100 7836 9 6 \n", + "13 202002 7 6534 4530 8538 10 7 \n", + "14 202001 7 9835 7019 12651 15 11 \n", + "15 201952 7 7941 5246 10636 12 8 \n", + "16 201951 7 5823 3675 7971 9 6 \n", + "17 201950 7 6424 4276 8572 10 7 \n", + "18 201949 7 6621 4540 8702 10 7 \n", + "19 201948 7 5542 3383 7701 8 5 \n", + "20 201947 7 7536 5058 10014 11 7 \n", + "21 201946 7 2638 1316 3960 4 2 \n", + "22 201945 7 4492 2615 6369 7 4 \n", + "23 201944 7 5728 3627 7829 9 6 \n", + "24 201943 7 4834 2751 6917 7 4 \n", + "25 201942 7 6279 3989 8569 10 7 \n", + "26 201941 7 4130 2030 6230 6 3 \n", + "27 201940 7 4211 2218 6204 6 3 \n", + "28 201939 7 3137 1310 4964 5 2 \n", + "29 201938 7 3078 1416 4740 5 2 \n", + "... ... ... ... ... ... ... ... \n", + "1502 199126 7 17608 11304 23912 31 20 \n", + "1503 199125 7 16169 10700 21638 28 18 \n", + "1504 199124 7 16171 10071 22271 28 17 \n", + "1505 199123 7 11947 7671 16223 21 13 \n", + "1506 199122 7 15452 9953 20951 27 17 \n", + "1507 199121 7 14903 8975 20831 26 16 \n", + "1508 199120 7 19053 12742 25364 34 23 \n", + "1509 199119 7 16739 11246 22232 29 19 \n", + "1510 199118 7 21385 13882 28888 38 25 \n", + "1511 199117 7 13462 8877 18047 24 16 \n", + "1512 199116 7 14857 10068 19646 26 18 \n", + "1513 199115 7 13975 9781 18169 25 18 \n", + "1514 199114 7 12265 7684 16846 22 14 \n", + "1515 199113 7 9567 6041 13093 17 11 \n", + "1516 199112 7 10864 7331 14397 19 13 \n", + "1517 199111 7 15574 11184 19964 27 19 \n", + "1518 199110 7 16643 11372 21914 29 20 \n", + "1519 199109 7 13741 8780 18702 24 15 \n", + "1520 199108 7 13289 8813 17765 23 15 \n", + "1521 199107 7 12337 8077 16597 22 15 \n", + "1522 199106 7 10877 7013 14741 19 12 \n", + "1523 199105 7 10442 6544 14340 18 11 \n", + "1524 199104 7 7913 4563 11263 14 8 \n", + "1525 199103 7 15387 10484 20290 27 18 \n", + "1526 199102 7 16277 11046 21508 29 20 \n", + "1527 199101 7 15565 10271 20859 27 18 \n", + "1528 199052 7 19375 13295 25455 34 23 \n", + "1529 199051 7 19080 13807 24353 34 25 \n", + "1530 199050 7 11079 6660 15498 20 12 \n", + "1531 199049 7 1143 0 2610 2 0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 5 FR France \n", + "1 9 FR France \n", + "2 14 FR France \n", + "3 16 FR France \n", + "4 19 FR France \n", + "5 18 FR France \n", + "6 26 FR France \n", + "7 20 FR France \n", + "8 18 FR France \n", + "9 18 FR France \n", + "10 16 FR France \n", + "11 15 FR France \n", + "12 12 FR France \n", + "13 13 FR France \n", + "14 19 FR France \n", + "15 16 FR France \n", + "16 12 FR France \n", + "17 13 FR France \n", + "18 13 FR France \n", + "19 11 FR France \n", + "20 15 FR France \n", + "21 6 FR France \n", + "22 10 FR France \n", + "23 12 FR France \n", + "24 10 FR France \n", + "25 13 FR France \n", + "26 9 FR France \n", + "27 9 FR France \n", + "28 8 FR France \n", + "29 8 FR France \n", + "... ... ... ... \n", + "1502 42 FR France \n", + "1503 38 FR France \n", + "1504 39 FR France \n", + "1505 29 FR France \n", + "1506 37 FR France \n", + "1507 36 FR France \n", + "1508 45 FR France \n", + "1509 39 FR France \n", + "1510 51 FR France \n", + "1511 32 FR France \n", + "1512 34 FR France \n", + "1513 32 FR France \n", + "1514 30 FR France \n", + "1515 23 FR France \n", + "1516 25 FR France \n", + "1517 35 FR France \n", + "1518 38 FR France \n", + "1519 33 FR France \n", + "1520 31 FR France \n", + "1521 29 FR France \n", + "1522 26 FR France \n", + "1523 25 FR France \n", + "1524 20 FR France \n", + "1525 36 FR France \n", + "1526 38 FR France \n", + "1527 36 FR France \n", + "1528 45 FR France \n", + "1529 43 FR France \n", + "1530 28 FR France \n", + "1531 5 FR France \n", + "\n", + "[1532 rows x 10 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data" @@ -73,32 +1038,1041 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Y a-t-il des points manquants dans ce jeux de données ? Oui, la semaine 19 de l'année 1989 n'a pas de valeurs associées." + "Y a-t-il des points manquants dans ce jeux de données ? Non." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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" + ], + "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": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Nous éliminons ce point, ce qui n'a pas d'impact fort sur notre analyse qui est assez simple." - ] - }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
0202015719286613195315FRFrance
12020147387922275531639FRFrance
2202013773265236941611814FRFrance
32020127812357901045612816FRFrance
4202011710198756812828151119FRFrance
520201079011669111331141018FRFrance
62020097136311054416718211626FRFrance
7202008710424770813140161220FRFrance
820200778959657411344141018FRFrance
920200679264692511603141018FRFrance
1020200578505631410696131016FRFrance
112020047799158311015112915FRFrance
1220200375968410078369612FRFrance
13202002765344530853810713FRFrance
1420200179835701912651151119FRFrance
152019527794152461063612816FRFrance
1620195175823367579719612FRFrance
17201950764244276857210713FRFrance
18201949766214540870210713FRFrance
1920194875542338377018511FRFrance
202019477753650581001411715FRFrance
212019467263813163960426FRFrance
2220194574492261563697410FRFrance
2320194475728362778299612FRFrance
2420194374834275169177410FRFrance
25201942762793989856910713FRFrance
262019417413020306230639FRFrance
272019407421122186204639FRFrance
282019397313713104964528FRFrance
292019387307814164740528FRFrance
.................................
15021991267176081130423912312042FRFrance
15031991257161691070021638281838FRFrance
15041991247161711007122271281739FRFrance
1505199123711947767116223211329FRFrance
1506199122715452995320951271737FRFrance
1507199121714903897520831261636FRFrance
15081991207190531274225364342345FRFrance
15091991197167391124622232291939FRFrance
15101991187213851388228888382551FRFrance
1511199117713462887718047241632FRFrance
15121991167148571006819646261834FRFrance
1513199115713975978118169251832FRFrance
1514199114712265768416846221430FRFrance
151519911379567604113093171123FRFrance
1516199112710864733114397191325FRFrance
15171991117155741118419964271935FRFrance
15181991107166431137221914292038FRFrance
1519199109713741878018702241533FRFrance
1520199108713289881317765231531FRFrance
1521199107712337807716597221529FRFrance
1522199106710877701314741191226FRFrance
1523199105710442654414340181125FRFrance
15241991047791345631126314820FRFrance
15251991037153871048420290271836FRFrance
15261991027162771104621508292038FRFrance
15271991017155651027120859271836FRFrance
15281990527193751329525455342345FRFrance
15291990517190801380724353342543FRFrance
1530199050711079666015498201228FRFrance
15311990497114302610205FRFrance
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1532 rows × 10 columns

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" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202015 7 1928 661 3195 3 1 \n", + "1 202014 7 3879 2227 5531 6 3 \n", + "2 202013 7 7326 5236 9416 11 8 \n", + "3 202012 7 8123 5790 10456 12 8 \n", + "4 202011 7 10198 7568 12828 15 11 \n", + "5 202010 7 9011 6691 11331 14 10 \n", + "6 202009 7 13631 10544 16718 21 16 \n", + "7 202008 7 10424 7708 13140 16 12 \n", + "8 202007 7 8959 6574 11344 14 10 \n", + "9 202006 7 9264 6925 11603 14 10 \n", + "10 202005 7 8505 6314 10696 13 10 \n", + "11 202004 7 7991 5831 10151 12 9 \n", + "12 202003 7 5968 4100 7836 9 6 \n", + "13 202002 7 6534 4530 8538 10 7 \n", + "14 202001 7 9835 7019 12651 15 11 \n", + "15 201952 7 7941 5246 10636 12 8 \n", + "16 201951 7 5823 3675 7971 9 6 \n", + "17 201950 7 6424 4276 8572 10 7 \n", + "18 201949 7 6621 4540 8702 10 7 \n", + "19 201948 7 5542 3383 7701 8 5 \n", + "20 201947 7 7536 5058 10014 11 7 \n", + "21 201946 7 2638 1316 3960 4 2 \n", + "22 201945 7 4492 2615 6369 7 4 \n", + "23 201944 7 5728 3627 7829 9 6 \n", + "24 201943 7 4834 2751 6917 7 4 \n", + "25 201942 7 6279 3989 8569 10 7 \n", + "26 201941 7 4130 2030 6230 6 3 \n", + "27 201940 7 4211 2218 6204 6 3 \n", + "28 201939 7 3137 1310 4964 5 2 \n", + "29 201938 7 3078 1416 4740 5 2 \n", + "... ... ... ... ... ... ... ... \n", + "1502 199126 7 17608 11304 23912 31 20 \n", + "1503 199125 7 16169 10700 21638 28 18 \n", + "1504 199124 7 16171 10071 22271 28 17 \n", + "1505 199123 7 11947 7671 16223 21 13 \n", + "1506 199122 7 15452 9953 20951 27 17 \n", + "1507 199121 7 14903 8975 20831 26 16 \n", + "1508 199120 7 19053 12742 25364 34 23 \n", + "1509 199119 7 16739 11246 22232 29 19 \n", + "1510 199118 7 21385 13882 28888 38 25 \n", + "1511 199117 7 13462 8877 18047 24 16 \n", + "1512 199116 7 14857 10068 19646 26 18 \n", + "1513 199115 7 13975 9781 18169 25 18 \n", + "1514 199114 7 12265 7684 16846 22 14 \n", + "1515 199113 7 9567 6041 13093 17 11 \n", + "1516 199112 7 10864 7331 14397 19 13 \n", + "1517 199111 7 15574 11184 19964 27 19 \n", + "1518 199110 7 16643 11372 21914 29 20 \n", + "1519 199109 7 13741 8780 18702 24 15 \n", + "1520 199108 7 13289 8813 17765 23 15 \n", + "1521 199107 7 12337 8077 16597 22 15 \n", + "1522 199106 7 10877 7013 14741 19 12 \n", + "1523 199105 7 10442 6544 14340 18 11 \n", + "1524 199104 7 7913 4563 11263 14 8 \n", + "1525 199103 7 15387 10484 20290 27 18 \n", + "1526 199102 7 16277 11046 21508 29 20 \n", + "1527 199101 7 15565 10271 20859 27 18 \n", + "1528 199052 7 19375 13295 25455 34 23 \n", + "1529 199051 7 19080 13807 24353 34 25 \n", + "1530 199050 7 11079 6660 15498 20 12 \n", + "1531 199049 7 1143 0 2610 2 0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 5 FR France \n", + "1 9 FR France \n", + "2 14 FR France \n", + "3 16 FR France \n", + "4 19 FR France \n", + "5 18 FR France \n", + "6 26 FR France \n", + "7 20 FR France \n", + "8 18 FR France \n", + "9 18 FR France \n", + "10 16 FR France \n", + "11 15 FR France \n", + "12 12 FR France \n", + "13 13 FR France \n", + "14 19 FR France \n", + "15 16 FR France \n", + "16 12 FR France \n", + "17 13 FR France \n", + "18 13 FR France \n", + "19 11 FR France \n", + "20 15 FR France \n", + "21 6 FR France \n", + "22 10 FR France \n", + "23 12 FR France \n", + "24 10 FR France \n", + "25 13 FR France \n", + "26 9 FR France \n", + "27 9 FR France \n", + "28 8 FR France \n", + "29 8 FR France \n", + "... ... ... ... \n", + "1502 42 FR France \n", + "1503 38 FR France \n", + "1504 39 FR France \n", + "1505 29 FR France \n", + "1506 37 FR France \n", + "1507 36 FR France \n", + "1508 45 FR France \n", + "1509 39 FR France \n", + "1510 51 FR France \n", + "1511 32 FR France \n", + "1512 34 FR France \n", + "1513 32 FR France \n", + "1514 30 FR France \n", + "1515 23 FR France \n", + "1516 25 FR France \n", + "1517 35 FR France \n", + "1518 38 FR France \n", + "1519 33 FR France \n", + "1520 31 FR France \n", + "1521 29 FR France \n", + "1522 26 FR France \n", + "1523 25 FR France \n", + "1524 20 FR France \n", + "1525 36 FR France \n", + "1526 38 FR France \n", + "1527 36 FR France \n", + "1528 45 FR France \n", + "1529 43 FR France \n", + "1530 28 FR France \n", + "1531 5 FR France \n", + "\n", + "[1532 rows x 10 columns]" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "data = raw_data.dropna().copy()\n", + "data = raw_data\n", "data" ] }, @@ -122,7 +2096,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -152,10 +2126,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 7, + "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" @@ -171,15 +2143,12 @@ "d'une seconde.\n", "\n", "Ceci s'avère tout à fait juste sauf pour deux périodes consécutives\n", - "entre lesquelles il manque une semaine.\n", - "\n", - "Nous reconnaissons ces dates: c'est la semaine sans observations\n", - "que nous avions supprimées !" + "entre lesquelles il manque une semaine." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -199,25 +2168,64 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "sorted_data['inc'].plot()" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Un zoom sur les dernières années montre mieux la situation des pics en hiver. Le creux des incidences se trouve en été." - ] - }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "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()" ] @@ -233,33 +2241,26 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Etant donné que le pic de l'épidémie se situe en hiver, à cheval\n", - "entre deux années civiles, nous définissons la période de référence\n", - "entre deux minima de l'incidence, du 1er août de l'année $N$ au\n", - "1er août de l'année $N+1$.\n", + "Nous définissons la période de référence entre deux minima de l'incidence, du 1er septembre de l'année $N$ au\n", + "1er août de l'année $N+1$. Pour être sûr de trouver les mêmes réponses que nous, vous devez choisir le 1er septembre comme début de chaque période annuelle.\n", "\n", "Notre tâche est un peu compliquée par le fait que l'année ne comporte\n", "pas un nombre entier de semaines. Nous modifions donc un peu nos périodes\n", - "de référence: à la place du 1er août de chaque année, nous utilisons le\n", - "premier jour de la semaine qui contient le 1er août.\n", - "\n", - "Comme l'incidence de syndrome grippal est très faible en été, cette\n", - "modification ne risque pas de fausser nos conclusions.\n", + "de référence: à la place du 1er septembre de chaque année, nous utilisons le\n", + "premier jour de la semaine qui contient le 1er septembre.\n", "\n", - "Encore un petit détail: les données commencent an octobre 1984, ce qui\n", - "rend la première année incomplète. Nous commençons donc l'analyse en 1985." + "Encore un petit détail: les données commencent en décembre 1990, ce qui\n", + "rend la première année incomplète. Nous commençons donc l'analyse en 1991." ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 18, + "metadata": {}, "outputs": [], "source": [ - "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", - " for y in range(1985,\n", + "first_sept_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", + " for y in range(1991,\n", " sorted_data.index[-1].year)]" ] }, @@ -267,21 +2268,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "En partant de cette liste des semaines qui contiennent un 1er août, nous obtenons nos intervalles d'environ un an comme les périodes entre deux semaines adjacentes dans cette liste. Nous calculons les sommes des incidences hebdomadaires pour toutes ces périodes.\n", + "En partant de cette liste des semaines qui contiennent un 1er septembre, nous obtenons nos intervalles d'environ un an comme les périodes entre deux semaines adjacentes dans cette liste. Nous calculons les sommes des incidences hebdomadaires pour toutes ces périodes.\n", "\n", "Nous vérifions également que ces périodes contiennent entre 51 et 52 semaines, pour nous protéger contre des éventuelles erreurs dans notre code." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "year = []\n", "yearly_incidence = []\n", - "for week1, week2 in zip(first_august_week[:-1],\n", - " first_august_week[1:]):\n", + "for week1, week2 in zip(first_sept_week[:-1],\n", + " first_sept_week[1:]):\n", " one_year = sorted_data['inc'][week1:week2-1]\n", " assert abs(len(one_year)-52) < 2\n", " yearly_incidence.append(one_year.sum())\n", @@ -298,9 +2299,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + }, + { + 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "yearly_incidence.plot(style='*')" ] @@ -309,31 +2333,85 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Une liste triée permet de plus facilement répérer les valeurs les plus élevées (à la fin)." + "Une liste triée permet de plus facilement répérer les valeurs les plus élevées." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2002 516689\n", + "2018 542312\n", + "2017 551041\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": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "yearly_incidence.sort_values()" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Enfin, un histogramme montre bien que les épidémies fortes, qui touchent environ 10% de la population\n", - " française, sont assez rares: il y en eu trois au cours des 35 dernières années." - ] - }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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