diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb index 0bbbe371b01e359e381e43239412d77bf53fb1fb..dac62863a792a0b26538beba7863cfc383c2d02d 100644 --- a/module3/exo2/exercice.ipynb +++ b/module3/exo2/exercice.ipynb @@ -1,5 +1,1380 @@ { - "cells": [], + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Analyse de l'incidence de la varicelle" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "import isoweek" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Les données de l'incidence de la varicelle 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, qui commence en 1991 et se termine avec une semaine récente." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "La première ligne du fichier CSV est un commentaire, que nous ignorons en précisant `skiprows=1`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nous remplacons le téléchargement des données à chaque lancement du notebook par l'utilisation d'un fichier local (si celui-ci est présent). Cela permet de toujours travailler sur les mêmes donnéeset ainsi d'éviter d'éventuels problèmes dans le futur. Aves des fichiers de données plus lourds nous gagnons aussi le temps de téléchargement." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fichier présent localement\n" + ] + }, + { + "data": { + "text/html": [ + "
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199111 7 15574 11184 19964 27 \n", + "1534 1534 199110 7 16643 11372 21914 29 \n", + "1535 1535 199109 7 13741 8780 18702 24 \n", + "1536 1536 199108 7 13289 8813 17765 23 \n", + "1537 1537 199107 7 12337 8077 16597 22 \n", + "1538 1538 199106 7 10877 7013 14741 19 \n", + "1539 1539 199105 7 10442 6544 14340 18 \n", + "1540 1540 199104 7 7913 4563 11263 14 \n", + "1541 1541 199103 7 15387 10484 20290 27 \n", + "1542 1542 199102 7 16277 11046 21508 29 \n", + "1543 1543 199101 7 15565 10271 20859 27 \n", + "1544 1544 199052 7 19375 13295 25455 34 \n", + "1545 1545 199051 7 19080 13807 24353 34 \n", + "1546 1546 199050 7 11079 6660 15498 20 \n", + "1547 1547 199049 7 1143 0 2610 2 \n", + "\n", + " inc100_low inc100_up geo_insee geo_name \n", + "0 0 4 FR France \n", + "1 0 4 FR France \n", + "2 0 2 FR France \n", + "3 0 2 FR France \n", + "4 0 2 FR France \n", + "5 0 2 FR France \n", + "6 0 1 FR France \n", + "7 0 2 FR France \n", + "8 0 2 FR France \n", + "9 0 1 FR France \n", + "10 0 2 FR France \n", + "11 0 2 FR France \n", + "12 0 1 FR France \n", + "13 0 2 FR France \n", + "14 0 1 FR France \n", + "15 0 2 FR France \n", + "16 1 5 FR France \n", + "17 3 9 FR France \n", + "18 8 14 FR France \n", + "19 8 16 FR France \n", + "20 11 19 FR France \n", + "21 10 18 FR France \n", + "22 16 26 FR France \n", + "23 12 20 FR France \n", + "24 10 18 FR France \n", + "25 10 18 FR France \n", + "26 10 16 FR France \n", + "27 9 15 FR France \n", + "28 6 12 FR France \n", + "29 7 13 FR France \n", + "... ... ... ... ... \n", + "1518 20 42 FR France \n", + "1519 18 38 FR France \n", + "1520 17 39 FR France \n", + "1521 13 29 FR France \n", + "1522 17 37 FR France \n", + "1523 16 36 FR France \n", + "1524 23 45 FR France \n", + "1525 19 39 FR France \n", + "1526 25 51 FR France \n", + "1527 16 32 FR France \n", + "1528 18 34 FR France \n", + "1529 18 32 FR France \n", + "1530 14 30 FR France \n", + "1531 11 23 FR France \n", + "1532 13 25 FR France \n", + "1533 19 35 FR France \n", + "1534 20 38 FR France \n", + "1535 15 33 FR France \n", + "1536 15 31 FR France \n", + "1537 15 29 FR France \n", + "1538 12 26 FR France \n", + "1539 11 25 FR France \n", + "1540 8 20 FR France \n", + "1541 18 36 FR France \n", + "1542 20 38 FR France \n", + "1543 18 36 FR France \n", + "1544 23 45 FR France \n", + "1545 25 43 FR France \n", + "1546 12 28 FR France \n", + "1547 0 5 FR France \n", + "\n", + "[1548 rows x 11 columns]" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import os\n", + "fichiers_disponibles = os.listdir(os.getcwd())\n", + "if \"incidence-PAY-7.csv\" not in fichiers_disponibles:\n", + " raw_data = pd.read_csv(data_url, skiprows=1)\n", + " raw_data.to_csv(\"incidence-PAY-7.csv\")\n", + "else:\n", + " print(\"Fichier présent localement\")\n", + " raw_data = pd.read_csv(\"incidence-PAY-7.csv\")\n", + "raw_data" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "raw_data[raw_data.isnull().any(axis=1)]\n", + "data = raw_data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Il n'y a pas de données manquantes. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nos données utilisent une convention inhabituelle: le numéro de semaine est collé à l'année, donnant l'impression qu'il s'agit de nombre entier. C'est comme ça que Pandas les interprète.\n", + "\n", + "Un deuxième problème est que Pandas ne comprend pas les numéros de semaine. Il faut lui fournir les dates de début et de fin de semaine. Nous utilisons pour cela la bibliothèque isoweek.\n", + "\n", + "Comme la conversion des semaines est devenu assez complexe, nous écrivons une petite fonction Python pour cela. Ensuite, nous l'appliquons à tous les points de nos donnés. Les résultats vont dans une nouvelle colonne 'period'." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "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": "markdown", + "metadata": {}, + "source": [ + "Il restent deux petites modifications à faire.\n", + "\n", + "Premièrement, nous définissons les périodes d'observation comme nouvel index de notre jeux de données. Ceci en fait une suite chronologique, ce qui sera pratique par la suite.\n", + "\n", + "Deuxièmement, nous trions les points par période, dans le sens chronologique." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_data = data.set_index('period').sort_index()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nous vérifions la cohérence des données. Entre la fin d'une période et le début de la période qui suit, la différence temporelle doit être zéro, ou au moins très faible. Nous laissons une \"marge d'erreur\" d'une seconde." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "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('1s'):\n", + " print(p1, p2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Pas de problème sur ce jeu de données" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 25, + "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": "markdown", + "metadata": {}, + "source": [ + "Un zoom sur les dernières années montre mieux la situation. Les pics sont au printemps et les creux à la fin de l'été." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sorted_data['inc'][-200:].plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Etude de l'incidence annuelle" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Etant donné que le pic ce situe vers septembre, nous définissons la période de référence entre deux minima de l'incidence, du 1er septembre de l'année 𝑁 au 1er septembre de l'année 𝑁+1 .\n", + "\n", + "Notre tâche est un peu compliquée par le fait que l'année ne comporte pas un nombre entier de semaines. Nous modifions donc un peu nos périodes de référence: à la place du 1er août de chaque année, nous utilisons le premier jour de la semaine qui contient le 1er septembre.\n", + "\n", + "Comme l'incidence de la varicelle est très faible en été, cette modification ne risque pas de fausser nos conclusions.\n", + "\n", + "Nous commençons donc l'analyse en 1991. Car 1990 n'est pas complète." + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "first_september_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", + " for y in range(1991,\n", + " sorted_data.index[-1].year)]" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "scrolled": true + }, + "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", + " assert abs(len(one_year)-52) < 2\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": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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pcjOrd04mw8ALLJpZvfPU4CHkp8nNbKRwy2QIeelrMxspnEyGkJ8mN7ORwslkiA106WsP1ptZLSoqmUj6qKSNkn4laY+kz0i6R9Lbkl5L2xdyx98pqVXSXkmLcvG5kl5P362RpBQfI+mZFG+RND1XZpmkfWlbVr6qD49Hbp7H6qWXM2vyOFYvvbzbUti98WC9mdWiopZTkbQOeDkivi/pI8A5wNeB9yLi2z2OnQWsBxqBycCLwJ9ExElJ24GvAf8EPAesiYgtkr4C/OuI+FtJTcB1EfGXkiYAO4F5QACvAHMj4uiZrrVWl1PpOVhf4MF6MxsOQ76ciqRxwGeBRwEi4g8R8bs+iiwBno6Izoh4E2gFGiVdBIyLiG2RZbDHgaW5MuvS/kZgQWq1LAKaI6IjJZBmYPGAa1kDPFhvZrWsmG6uPwbagR9KelXS9yWdm767XdIvJf1A0vgUmwK8lSt/MMWmpP2e8W5lIqILeBe4oI9z1R0P1ptZLSsmmTQAnwYejogrgN8DdwAPA58A5gCHge+k49XLOaKP+GDLfEDSCkk7Je1sb2/voyrVze+pNrNaVcxDiweBgxHRkn7eCNwREUcKB0j6HvA/c8dfnCs/FTiU4lN7iefLHJTUAJwPdKT453qU+VnPC4yItcBayMZMiqhTydqOneD29a/y4I1XlK314PdUm1mt6rdlEhHvAG9JuiyFFgBvpDGQguuAXWl/M9CUZmjNAGYC2yPiMHBc0pVpPOQW4NlcmcJMreuBl9K4yvPAQknjUzfawhSrOM+6MiuOp7uPDMUup/JV4EdpJte/AF8G1kiaQ9bttB+4FSAidkvaALwBdAErI+JkOs9twGPA2cCWtEE2uP+EpFayFklTOleHpPuAHem4eyOiY3BVLQ8vkWI2MPk/vFZf96lKX44NEb9pcYDajp1g9XN7eGH3O5x4/xRjR49i0eyPc9cXP+nBcrMcT3evLX7T4jDzrCuz4ni6+8jiVYMHoTDr6sbGaTy1/QDt7gs2+xD/4TWyOJkMgmddWbkMxazAauI/vEYOj5mYVdDdm17nR9sPcFPjNA9OW0WVOmbilolZBXhWoNUbD8CblVkxz1V4cNrqjZOJWZkV80CrB6et3riby6xMBtp15cHpD6v3CQn1zAPwZmXiB1pL5wkJleMBeLMq4a6rwfOEhNrnMROzMvJrBAbHExJqn1smVtVqrQ/dD7QOjlt1tc8tExt2A1mS3Ev9jxxu1dU2D8DbsCtmkNUrzpoNr1IH4J1MbNgMJEF4ZpTZ8PIS9FYzBjLI6j50s9riAXgbNgNNEH6oz6x2OJnYsBpIgvDMKLPa4TETMzPzmImZmVWek4mZWQ8DeRbKMk4mZmY9+GHZgSsqmUj6qKSNkn4laY+kz0iaIKlZ0r70OT53/J2SWiXtlbQoF58r6fX03RpJSvExkp5J8RZJ03NllqV/Y5+kZeWruplZd5fdvYXpd/yEJ1sOEJEtODn9jp9w2d1bKn1pVa/Ylsl3gZ9GxL8C/hTYA9wBbI2ImcDW9DOSZgFNwGxgMfCQpLPSeR4GVgAz07Y4xZcDRyPiUuAB4P50rgnAKmA+0AisyictM7Ny8oKTg9dvMpE0Dvgs8ChARPwhIn4HLAHWpcPWAUvT/hLg6YjojIg3gVagUdJFwLiI2BbZFLLHe5QpnGsjsCC1WhYBzRHRERFHgWZOJyAzs7Lyw7KDV0zL5I+BduCHkl6V9H1J5wIXRsRhgPQ5KR0/BXgrV/5gik1J+z3j3cpERBfwLnBBH+fqRtIKSTsl7Wxvby+iSmZmvfOCk4NTzEOLDcCnga9GRIuk75K6tM5AvcSij/hgy5wORKwF1kL2nEkf12Zm1ic/LDs4xbRMDgIHI6Il/byRLLkcSV1XpM+23PEX58pPBQ6l+NRe4t3KSGoAzgc6+jiXmZlVkX6TSUS8A7wl6bIUWgC8AWwGCrOrlgHPpv3NQFOaoTWDbKB9e+oKOy7pyjQeckuPMoVzXQ+8lMZVngcWShqfBt4XppiZmVWRYtfm+irwI0kfAf4F+DJZItogaTlwALgBICJ2S9pAlnC6gJURcTKd5zbgMeBsYEvaIBvcf0JSK1mLpCmdq0PSfcCOdNy9EdExyLqamdkQ8dpcZmbmtbnMzKzynEzMzOpApdcTczIxM6sDlV5PzC/HMjOrYZfdvYXOrlMf/PxkywGebDnAmIZR7F19zbBdh1smZmY1rFrWE3MyMTOrYdWynpi7uczMalxhPbEbG6fx1PYDtFdgEN7PmZiZmZ8zMTOzynMyMTOzkjmZmJlZyZxMzMysZE4mZmZWMieTGlfp9XjMzMDJpOZVej0eMzPwQ4s1q1rW4zEzA7dMala1rMdjZgZOJjWrWtbjMTMDd3PVtGpYj8fMDLw2l5mZ4bW5zMysChSVTCTtl/S6pNck7UyxeyS9nWKvSfpC7vg7JbVK2itpUS4+N52nVdIaSUrxMZKeSfEWSdNzZZZJ2pe2ZeWquJnZcKvn58IG0jK5OiLm9GgGPZBicyLiOQBJs4AmYDawGHhI0lnp+IeBFcDMtC1O8eXA0Yi4FHgAuD+dawKwCpgPNAKrJI0fRD3NzCqunp8LG4oB+CXA0xHRCbwpqRVolLQfGBcR2wAkPQ4sBbakMvek8huBB1OrZRHQHBEdqUwzWQJaPwTXbWY2JEbCc2HFtkwCeEHSK5JW5OK3S/qlpB/kWgxTgLdyxxxMsSlpv2e8W5mI6ALeBS7o41xmZjVjJDwXVmwyuSoiPg1cA6yU9FmyLqtPAHOAw8B30rHqpXz0ER9smQ9IWiFpp6Sd7e3tfVbEzGy4jYTnwopKJhFxKH22AZuAxog4EhEnI+IU8D2yMQ3IWg8X54pPBQ6l+NRe4t3KSGoAzgc6+jhXz+tbGxHzImLexIkTi6mSmdmwKjwXtukrV3HT/Etof6+z3zK1NGDfbzKRdK6k8wr7wEJgl6SLcoddB+xK+5uBpjRDawbZQPv2iDgMHJd0ZRoPuQV4NlemMFPreuClyB6AeR5YKGl86kZbmGJmZjXlkZvnsXrp5cyaPI7VSy/nkZv7f6SjlgbsixmAvxDYlGbxNgBPRcRPJT0haQ5Zt9N+4FaAiNgtaQPwBtAFrIyIk+lctwGPAWeTDbxvSfFHgSfSYH0H2WwwIqJD0n3AjnTcvYXBeDOzelWLA/Z+At7MrMq0HTvB6uf28MLudzjx/inGjh7Fotkf564vfnLIxln8BLyZWZ2pxQF7L/RoZlaFam0hV3dzmZmZu7nMzKzynEzMzKxkTiZmZlYyJxMzMyuZk4mZmZXMycTMzErmZGJmZiVzMjEzs5I5mZiZWcmcTKxu1NK7H8zqjZOJ1Y1aeveDWb3xQo9W82rx3Q9m9cYtE6t5L3/zaq6dM5mxo7P/nceOHsWSOZN5+VtXV/jKzEYOJxOrebX47gezeuNuLqsLtfbuB7N64/eZmJmZ32diZmaV52RiZmYlKyqZSNov6XVJr0namWITJDVL2pc+x+eOv1NSq6S9khbl4nPTeVolrZGkFB8j6ZkUb5E0PVdmWfo39klaVq6Km5lZ+QykZXJ1RMzJ9andAWyNiJnA1vQzkmYBTcBsYDHwkKSzUpmHgRXAzLQtTvHlwNGIuBR4ALg/nWsCsAqYDzQCq/JJy8zMqkMp3VxLgHVpfx2wNBd/OiI6I+JNoBVolHQRMC4itkU26v94jzKFc20EFqRWyyKgOSI6IuIo0MzpBGRmZlWi2GQSwAuSXpG0IsUujIjDAOlzUopPAd7KlT2YYlPSfs94tzIR0QW8C1zQx7nMzKyKFPucyVURcUjSJKBZ0q/6OFa9xKKP+GDLnP4HswRXSHLvSdrbx/XVgo8Bv630RQyxeq9jvdcP6r+OI61+l5RysqKSSUQcSp9tkjaRjV8ckXRRRBxOXVht6fCDwMW54lOBQyk+tZd4vsxBSQ3A+UBHin+uR5mf9XJ9a4G1xdSlFkjaWcp871pQ73Ws9/pB/dfR9RuYfru5JJ0r6bzCPrAQ2AVsBgqzq5YBz6b9zUBTmqE1g2ygfXvqCjsu6co0HnJLjzKFc10PvJTGVZ4HFkoanwbeF6aYmZlVkWJaJhcCm9Is3gbgqYj4qaQdwAZJy4EDwA0AEbFb0gbgDaALWBkRJ9O5bgMeA84GtqQN4FHgCUmtZC2SpnSuDkn3ATvScfdGREcJ9TUzsyFQd8up1ANJK1LXXd2q9zrWe/2g/uvo+g3wfE4mZmZWKi+nYmZmJXMyGSaSfiCpTdKuXOxPJW1LS8z8D0njUvwjkn6Y4r+Q9LlcmZ+lZWpeS9ukXv65YSfpYkn/S9IeSbslfS3Fy7bsTiWVuX51cQ8lXZCOf0/Sgz3OVfP3sJ/6Vd09HET9Pq/s2cHX0+e/z51r4PcvIrwNwwZ8Fvg0sCsX2wH8u7T/N8B9aX8l8MO0Pwl4BRiVfv4ZMK/S9emlfhcBn0775wH/DMwC/gG4I8XvAO5P+7OAXwBjgBnAr4Gz0nfbgc+QPWe0BbimzupXL/fwXODfAH8LPNjjXPVwD/uqX9Xdw0HU7wpgctq/HHi7lPvnlskwiYh/JJuplncZ8I9pvxn4i7Q/i2y9MyKiDfgdUNXz3SPicET8PO0fB/aQrVZQzmV3KqZc9Rveqx6YgdYxIn4fEf8b6PYmsnq5h2eqX7UaRP1ejfQMIbAbGKvskY5B3T8nk8raBVyb9m/g9MOevwCWSGpQ9qzOXLo/CPrD1LT+T9XQfdCTslWfrwBaKO+yO1WhxPoV1MM9PJN6uYf9qdp7OIj6/QXwakR0Msj752RSWX8DrJT0Clmz9A8p/gOyG7gT+C/A/yV7Zgfgpoj4FPBv03bzsF5xPyT9EfDfga9HxLG+Du0lVvQSOpVShvpB/dzDM56il1gt3sO+VO09HGj9JM0mW6n91kKol8P6vX9OJhUUEb+KiIURMRdYT9avTkR0RcQ3IlvyfwnwUWBf+u7t9HkceIoq6jqRNJrsf+IfRcSPU/hIajYXuj9KWXanospUv3q6h2dSL/fwjKr1Hg60fpKmApuAWyLi1yk8qPvnZFJBhRkgkkYBdwP/Nf18jrKla5D0eaArIt5I3V4fS/HRwH8g6yqruNTMfxTYExH/OfdVOZfdqZhy1a/O7mGv6ugenuk8VXkPB1o/SR8FfgLcGRH/p3DwoO9fpWYejLSNrOVxGHifLPMvB75GNuPin4G/5/RDpNOBvWQDaC8Cl6T4uWQzu35JNmD2XdIMoUpvZLNeIl3ba2n7AtmrBLaStay2AhNyZe4ia43tJTdbhGyywa703YOF/y71UL86vIf7ySaWvJf+v55VZ/fwQ/Wr1ns40PqR/QH7+9yxrwGTBnv//AS8mZmVzN1cZmZWMicTMzMrmZOJmZmVzMnEzMxK5mRiZmYlczIxM7OSOZmYmVnJnEzMzKxk/x+qftJYVEr3+gAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "yearly_incidence.plot(style='*')" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "incidence max en 2009\n", + "incidence min en 2002\n" + ] + } + ], + "source": [ + "print(\"incidence max en \", yearly_incidence.idxmax())\n", + "print(\"incidence min en \", yearly_incidence.idxmin())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], "metadata": { "kernelspec": { "display_name": "Python 3", @@ -16,10 +1391,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.3" + "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 } -