diff --git a/module2/exo1/Untitled.ipynb b/module2/exo1/Untitled.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..7fec51502cbc3200b3d0ffc6bbba1fe85e197f3d --- /dev/null +++ b/module2/exo1/Untitled.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/module2/exo1/toy_notebook_fr.ipynb b/module2/exo1/toy_notebook_fr.ipynb index 0bbbe371b01e359e381e43239412d77bf53fb1fb..1ef40955f98ec93ffd84d25fb6a99143a23ba1c0 100644 --- a/module2/exo1/toy_notebook_fr.ipynb +++ b/module2/exo1/toy_notebook_fr.ipynb @@ -1,5 +1,149 @@ { - "cells": [], + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## toy_notebook_fr\n", + "\n", + "### March 28,2019\n", + "\n", + " à propos du calcul de $\\pi$\n", + "\n", + " En demandant à la lib maths\n", + "mon ordinateur m'indique que $\\pi$ vaut *approximativement*" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "3.141592653589793\n" + ] + } + ], + "source": [ + "from math import *\n", + "print (pi)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "1.2 En utilisant la méthode des aiguilles de Buffon\n", + "mais calculé avec la méthode des _aiguilles de Buffon_, on obtiendrait comme __approximation__ :\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3.128911138923655" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import numpy as np\n", + "np.random.seed(seed=42)\n", + "N = 10000\n", + "x = np.random.uniform(size=N, low=0, high=1)\n", + "theta = np.random.uniform(size=N, low=0, high=pi/2)\n", + "2/(sum((x+np.sin(theta))>1)/N)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Avec un argument \"fréquentiel\" de surface\n", + "Sinon avec une méthode plus simple à comprendre et ne faisant par intervenir d'appel à la fonction sinus se base sur le fait que si $X\\sim U(0,1)$ et si $Y\\sim U(0,1)$ alors $P[$X^2$+$Y^2$\\leq 1]= $\\pi/4$ (voir [méthode de Monte Carlo sur Wikipedia](https://fr.wikipedia.org/wiki/M%C3%A9thode_de_Monte-Carlo#D%C3%A9termination_de_la_valeur_de_%CF%80)). Le code suivant illustre ce fait :" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "np.random.seed(seed=42)\n", + "N = 1000\n", + "x = np.random.uniform(size=N, low=0, high=1)\n", + "y = np.random.uniform(size=N, low=0, high=1)\n", + "\n", + "accept = (x*x+y*y) <= 1\n", + "reject = np.logical_not(accept)\n", + "\n", + "fig, ax = plt.subplots(1)\n", + "ax.scatter(x[accept], y[accept], c='b', alpha=0.2, edgecolor=None)\n", + "ax.scatter(x[reject], y[reject], c='r', alpha=0.2, edgecolor=None)\n", + "ax.set_aspect('equal')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Il est alors aisé d’obtenir une approximation (pas terrible) de $\\pi$ en comptant combien de fois,\n", + "en moyenne, $X^2 + Y^2$ est inférieur à 1 :\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3.112" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "4*np.mean(accept)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], "metadata": { "kernelspec": { "display_name": "Python 3", @@ -16,10 +160,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.3" + "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 } - diff --git a/module2/exo1/travail pratique COVID19.ipynb b/module2/exo1/travail pratique COVID19.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..d3ff82f703263e11c199fd8c2352c7b2e8b0ed05 --- /dev/null +++ b/module2/exo1/travail pratique COVID19.ipynb @@ -0,0 +1,1898 @@ +{ + "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 +} diff --git a/module2/exo3/Untitled.ipynb b/module2/exo3/Untitled.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..03db7ff270fd867f798367a38163f711a74d44f4 --- /dev/null +++ b/module2/exo3/Untitled.ipynb @@ -0,0 +1,61 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "hideCode": true, + "hidePrompt": true + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import isoweek\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "hideCode": true, + "hidePrompt": true + }, + "outputs": [], + "source": [ + "data = pd.read_csv(\"https://scrippsco2.ucsd.edu/assets/data/atmospheric/stations/in_situ_co2/monthly/monthly_in_situ_co2_mlo.csv\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_code_all_hidden": true, + "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 +} diff --git a/module2/exo3/Untitled1.ipynb b/module2/exo3/Untitled1.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..9b670f6679dbaab66bce968a49dc2bd23c206a3a --- /dev/null +++ b/module2/exo3/Untitled1.ipynb @@ -0,0 +1,1326 @@ +{ + "cells": [ + { + "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\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "y = 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\",index_col=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "Chine=y.loc[['China'],:]" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "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", + "
Province/StateLatLong1/22/201/23/201/24/201/25/201/26/201/27/201/28/20...6/3/206/4/206/5/206/6/206/7/206/8/206/9/206/10/206/11/206/12/20
Country/Region
ChinaAnhui31.8257117.22641915396070106...991991991991991991991991991991
ChinaBeijing40.1824116.414214223641688091...594594594594594594594594595601
ChinaChongqing30.0572107.874069275775110132...579579579579579579579579579579
ChinaFujian26.0789117.9874151018355980...358358358359359359359360361361
ChinaGansu37.8099101.0583022471419...139139139139139139139139139139
ChinaGuangdong23.3417113.424426325378111151207...1598159816011602160216041604160716071608
ChinaGuangxi23.8298108.7881252323364651...254254254254254254254254254254
ChinaGuizhou26.8154106.87481334579...147147147147147147147147147147
ChinaHainan19.1959109.745345819223340...169169169170170170170170170171
ChinaHebei39.5490116.13061128131833...328328328328328328328328328328
ChinaHeilongjiang47.8620127.76150249152133...947947947947947947947947947947
ChinaHenan33.8820113.61405593283128168...1276127612761276127612761276127612761276
ChinaHong Kong22.3000114.20000225888...1093109911021105110611071107110711071108
ChinaHubei30.9756112.2707444444549761105814233554...68135681356813568135681356813568135681356813568135
ChinaHunan27.6104111.708849244369100143...1019101910191019101910191019101910191019
ChinaInner Mongolia44.0935113.9448001771115...235235235235235235237237237237
ChinaJiangsu32.9711119.455015918334770...653653653653653653653653653653
ChinaJiangxi27.6140115.72212718183672109...932932932932932932932932932932
ChinaJilin43.6661126.19230134468...155155155155155155155155155155
ChinaLiaoning41.2956122.608523417212734...149149149149149149149149149149
ChinaMacau22.1667113.55001222567...45454545454545454545
ChinaNingxia37.2692106.165511234711...75757575757575757575
ChinaQinghai35.745295.99560001166...18181818181818181818
ChinaShaanxi35.1917108.870103515223546...309309309311311311311311311311
ChinaShandong36.3427118.1498261527467595...792792792792792792792792792792
ChinaShanghai31.2020121.44919162033405366...673677677677678678678684689690
ChinaShanxi37.5777112.2922111691327...198198198198198198198198198198
ChinaSichuan30.6171102.7103581528446990...577578578578581582582582582583
ChinaTianjin39.3054117.323044810142324...192192192193193193194195195196
ChinaTibet31.692788.09240000000...1111111111
ChinaXinjiang41.112985.240102234510...76767676767676767676
ChinaYunnan24.9740101.487012511162644...185185185185185185185185185185
ChinaZhejiang29.1832120.093410274362104128173...1268126812681268126812681268126812681268
\n", + "

33 rows × 146 columns

\n", + "
" + ], + "text/plain": [ + " Province/State Lat Long 1/22/20 1/23/20 1/24/20 \\\n", + "Country/Region \n", + "China Anhui 31.8257 117.2264 1 9 15 \n", + "China Beijing 40.1824 116.4142 14 22 36 \n", + "China Chongqing 30.0572 107.8740 6 9 27 \n", + "China Fujian 26.0789 117.9874 1 5 10 \n", + "China Gansu 37.8099 101.0583 0 2 2 \n", + "China Guangdong 23.3417 113.4244 26 32 53 \n", + "China Guangxi 23.8298 108.7881 2 5 23 \n", + "China Guizhou 26.8154 106.8748 1 3 3 \n", + "China Hainan 19.1959 109.7453 4 5 8 \n", + "China Hebei 39.5490 116.1306 1 1 2 \n", + "China Heilongjiang 47.8620 127.7615 0 2 4 \n", + "China Henan 33.8820 113.6140 5 5 9 \n", + "China Hong Kong 22.3000 114.2000 0 2 2 \n", + "China Hubei 30.9756 112.2707 444 444 549 \n", + "China Hunan 27.6104 111.7088 4 9 24 \n", + "China Inner Mongolia 44.0935 113.9448 0 0 1 \n", + "China Jiangsu 32.9711 119.4550 1 5 9 \n", + "China Jiangxi 27.6140 115.7221 2 7 18 \n", + "China Jilin 43.6661 126.1923 0 1 3 \n", + "China Liaoning 41.2956 122.6085 2 3 4 \n", + "China Macau 22.1667 113.5500 1 2 2 \n", + "China Ningxia 37.2692 106.1655 1 1 2 \n", + "China Qinghai 35.7452 95.9956 0 0 0 \n", + "China Shaanxi 35.1917 108.8701 0 3 5 \n", + "China Shandong 36.3427 118.1498 2 6 15 \n", + "China Shanghai 31.2020 121.4491 9 16 20 \n", + "China Shanxi 37.5777 112.2922 1 1 1 \n", + "China Sichuan 30.6171 102.7103 5 8 15 \n", + "China Tianjin 39.3054 117.3230 4 4 8 \n", + "China Tibet 31.6927 88.0924 0 0 0 \n", + "China Xinjiang 41.1129 85.2401 0 2 2 \n", + "China Yunnan 24.9740 101.4870 1 2 5 \n", + "China Zhejiang 29.1832 120.0934 10 27 43 \n", + "\n", + " 1/25/20 1/26/20 1/27/20 1/28/20 ... 6/3/20 6/4/20 \\\n", + "Country/Region ... \n", + "China 39 60 70 106 ... 991 991 \n", + "China 41 68 80 91 ... 594 594 \n", + "China 57 75 110 132 ... 579 579 \n", + "China 18 35 59 80 ... 358 358 \n", + "China 4 7 14 19 ... 139 139 \n", + "China 78 111 151 207 ... 1598 1598 \n", + "China 23 36 46 51 ... 254 254 \n", + "China 4 5 7 9 ... 147 147 \n", + "China 19 22 33 40 ... 169 169 \n", + "China 8 13 18 33 ... 328 328 \n", + "China 9 15 21 33 ... 947 947 \n", + "China 32 83 128 168 ... 1276 1276 \n", + "China 5 8 8 8 ... 1093 1099 \n", + "China 761 1058 1423 3554 ... 68135 68135 \n", + "China 43 69 100 143 ... 1019 1019 \n", + "China 7 7 11 15 ... 235 235 \n", + "China 18 33 47 70 ... 653 653 \n", + "China 18 36 72 109 ... 932 932 \n", + "China 4 4 6 8 ... 155 155 \n", + "China 17 21 27 34 ... 149 149 \n", + "China 2 5 6 7 ... 45 45 \n", + "China 3 4 7 11 ... 75 75 \n", + "China 1 1 6 6 ... 18 18 \n", + "China 15 22 35 46 ... 309 309 \n", + "China 27 46 75 95 ... 792 792 \n", + "China 33 40 53 66 ... 673 677 \n", + "China 6 9 13 27 ... 198 198 \n", + "China 28 44 69 90 ... 577 578 \n", + "China 10 14 23 24 ... 192 192 \n", + "China 0 0 0 0 ... 1 1 \n", + "China 3 4 5 10 ... 76 76 \n", + "China 11 16 26 44 ... 185 185 \n", + "China 62 104 128 173 ... 1268 1268 \n", + "\n", + " 6/5/20 6/6/20 6/7/20 6/8/20 6/9/20 6/10/20 6/11/20 \\\n", + "Country/Region \n", + "China 991 991 991 991 991 991 991 \n", + "China 594 594 594 594 594 594 595 \n", + "China 579 579 579 579 579 579 579 \n", + "China 358 359 359 359 359 360 361 \n", + "China 139 139 139 139 139 139 139 \n", + "China 1601 1602 1602 1604 1604 1607 1607 \n", + "China 254 254 254 254 254 254 254 \n", + "China 147 147 147 147 147 147 147 \n", + "China 169 170 170 170 170 170 170 \n", + "China 328 328 328 328 328 328 328 \n", + "China 947 947 947 947 947 947 947 \n", + "China 1276 1276 1276 1276 1276 1276 1276 \n", + "China 1102 1105 1106 1107 1107 1107 1107 \n", + "China 68135 68135 68135 68135 68135 68135 68135 \n", + "China 1019 1019 1019 1019 1019 1019 1019 \n", + "China 235 235 235 235 237 237 237 \n", + "China 653 653 653 653 653 653 653 \n", + "China 932 932 932 932 932 932 932 \n", + "China 155 155 155 155 155 155 155 \n", + "China 149 149 149 149 149 149 149 \n", + "China 45 45 45 45 45 45 45 \n", + "China 75 75 75 75 75 75 75 \n", + "China 18 18 18 18 18 18 18 \n", + "China 309 311 311 311 311 311 311 \n", + "China 792 792 792 792 792 792 792 \n", + "China 677 677 678 678 678 684 689 \n", + "China 198 198 198 198 198 198 198 \n", + "China 578 578 581 582 582 582 582 \n", + "China 192 193 193 193 194 195 195 \n", + "China 1 1 1 1 1 1 1 \n", + "China 76 76 76 76 76 76 76 \n", + "China 185 185 185 185 185 185 185 \n", + "China 1268 1268 1268 1268 1268 1268 1268 \n", + "\n", + " 6/12/20 \n", + "Country/Region \n", + "China 991 \n", + "China 601 \n", + "China 579 \n", + "China 361 \n", + "China 139 \n", + "China 1608 \n", + "China 254 \n", + "China 147 \n", + "China 171 \n", + "China 328 \n", + "China 947 \n", + "China 1276 \n", + "China 1108 \n", + "China 68135 \n", + "China 1019 \n", + "China 237 \n", + "China 653 \n", + "China 932 \n", + "China 155 \n", + "China 149 \n", + "China 45 \n", + "China 75 \n", + "China 18 \n", + "China 311 \n", + "China 792 \n", + "China 690 \n", + "China 198 \n", + "China 583 \n", + "China 196 \n", + "China 1 \n", + "China 76 \n", + "China 185 \n", + "China 1268 \n", + "\n", + "[33 rows x 146 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Chine" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "ename": "SyntaxError", + "evalue": "invalid syntax (, line 1)", + "output_type": "error", + "traceback": [ + "\u001b[0;36m File \u001b[0;32m\"\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m HongKong=Chine.iloc[[12],:]fgdg\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n" + ] + } + ], + "source": [ + "HongKong=Chine.iloc[[12],:]fgdg" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "HongKong.loc['Chine', 'Country/Region'] = 10" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "HongKong" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "H=HongKong.replace(\"China\",\"Hong Kong\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(H.dtypes)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "HongKong.at[0,'Country/Region']= 2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "HongKong=HongKong.drop(columns='Province/State')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "h=H.T" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(h.dtypes)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "HongKong.astype(np.str)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "HongKong.replace['China','H']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = 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\", sep = '\\t', header = None)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "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\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "Belgique=x.loc[['Belgium'],:]\n", + "Chine=x.loc[['China'],:]\n", + "France=x.loc[['France'],:]\n", + "Allemagne=x.loc[['Germany'],:]\n", + "Iran=x.loc[['Iran'],:]\n", + "Italie=x.loc[['Italy'],:]\n", + "Japon=x.loc[['Japan'],:]\n", + "Hollande_et_colonies=x.loc[['Netherlands'],:]\n", + "Portugal=x.loc[['Portugal'],:]\n", + "Espagne=x.loc[['Spain'],:]\n", + "RoyaumeUni_et_colonies=x.loc[['United Kingdom'],:]\n", + "CoréeduSud=x.loc[['Korea, South'],:]\n", + "EtatsUnis=x.loc[['US'],:]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "z=x.reindex(columns = ['Country/Region', 'Province/State'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "z" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "z=x.iloc[[12],:]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "z=z.T" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "z.astype({12: int})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "z" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df=pd.read_csv(\"C:/Users/xavier/Documents/Cours ESPE\")" + ] + }, + { + "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 +} diff --git a/module2/exo3/epidemie coronavirus.ipynb b/module2/exo3/epidemie coronavirus.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..3b16100dfbee4384715ed56d509eea7f9e92675e --- /dev/null +++ b/module2/exo3/epidemie coronavirus.ipynb @@ -0,0 +1,5721 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "source": [ + "# Exercice sur l'épidemiologie du SARS-COV2" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import isoweek\n", + "import numpy as np" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "source": [ + "extraction basique" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "hideCode": false, + "hideOutput": true, + "hidePrompt": false + }, + "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": { + "hideCode": false, + "hidePrompt": false + }, + "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...5/31/206/1/206/2/206/3/206/4/206/5/206/6/206/7/206/8/206/9/20
0NaNAfghanistan33.00000065.000000000000...15205157501650917267180541896919551203422091721459
1NaNAlbania41.15330020.168300000000...1137114311641184119712121232124612631299
2NaNAlgeria28.0339001.659600000000...93949513962697339831993510050101541026510382
3NaNAndorra42.5063001.521800000000...764765844851852852852852852852
4NaNAngola-11.20270017.873900000000...86868686868688919296
5NaNAntigua and Barbuda17.060800-61.796400000000...26262626262626262626
6NaNArgentina-38.416100-63.616700000000...16851174151831919268201972103722020227942362024761
7NaNArmenia40.06910045.038200000000...928294921000910524112211181712364131301332513675
8Australian Capital TerritoryAustralia-35.473500149.012400000000...107107107107107107108108108108
9New South WalesAustralia-33.868800151.209300000034...3098310431043106311031103109311231143117
10Northern TerritoryAustralia-12.463400130.845600000000...29292929292929292929
11QueenslandAustralia-28.016700153.400000000000...1058105910591060106010611061106210621062
12South AustraliaAustralia-34.928500138.600700000000...440440440440440440440440440440
13TasmaniaAustralia-41.454500145.970700000000...228228228228228228228228228228
14VictoriaAustralia-37.813600144.963100000011...1653166316701678168116811685168716871691
15Western AustraliaAustralia-31.950500115.860500000000...589591592592592596599599599599
16NaNAustria47.51620014.550100000000...16731167331675916771168051684316898169021696816979
17NaNAzerbaijan40.14310047.576900000000...5494566259356260652268607239755378768191
18NaNBahamas25.034300-77.396300000000...102102102102102102103103103103
19NaNBahrain26.02750050.550000000000...11398118711231112815132961383514383147631541715731
20NaNBangladesh23.68500090.356300000000...47153495345244555140575636039163026657696850471675
21NaNBarbados13.193900-59.543200000000...92929292929292929292
22NaNBelarus53.70980027.953400000000...42556434034425545116459814686847751486304945350265
23NaNBelgium50.8333004.000000000000...58381585175861558685587675890759072592265934859437
24NaNBenin9.3077002.315800000000...232243244244261261261261288305
25NaNBhutan27.51420090.433600000000...43434747474848595959
26NaNBolivia-16.290200-63.588700000000...9982105311099111638122451272813358136431394914644
27NaNBosnia and Herzegovina43.91590017.679100000000...2510252425352551259426062606260627042728
28NaNBrazil-14.235000-51.925300000000...514849526447555383584016614941645771672846691758707412739503
29NaNBrunei4.535300114.727700000000...141141141141141141141141141141
..................................................................
236NaNTimor-Leste-8.874217125.727539000000...24242424242424242424
237NaNBelize13.193900-59.543200000000...18181818181919191920
238NaNLaos19.856270102.495496000000...19191919191919191919
239NaNLibya26.33510017.228331000000...156168182196209239256256332359
240NaNWest Bank and Gaza31.95220035.233200000000...448449451457464464464472473481
241NaNGuinea-Bissau11.803700-15.180400000000...1256133913391339133913681368136813891389
242NaNMali17.570692-3.996166000000...1265131513511386146114851523153315471586
243NaNSaint Kitts and Nevis17.357822-62.782998000000...15151515151515151515
244Northwest TerritoriesCanada64.825500-124.845700000000...5555555555
245YukonCanada64.282300-135.000000000000...11111111111111111111
246NaNKosovo42.60263620.902977000000...1064106410641142114211421142114212631263
247NaNBurma21.91620095.956000000000...224228232233236236240242244246
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...35384040404040404242
253NaNBurundi-3.37310029.918900000000...63636363636383838383
254NaNSierra Leone8.460555-11.779889000000...86186589690991492994696910011025
255Bonaire, Sint Eustatius and SabaNetherlands12.178400-68.238500000000...6777777777
256NaNMalawi-13.25430834.301525000000...284336358369393409409438443455
257Falkland Islands (Malvinas)United Kingdom-51.796300-59.523600000000...13131313131313131313
258Saint Pierre and MiquelonFrance46.885200-56.315900000000...1111111111
259NaNSouth Sudan6.87700031.307000000000...994994994994994994994131716041604
260NaNWestern Sahara24.215500-12.885800000000...9999999999
261NaNSao Tome and Principe0.1863606.613081000000...483484484484485499499513513514
262NaNYemen15.55272748.516388000000...323354399419453469482484496524
263NaNComoros-11.64550043.333300000000...106106132132132132141141141141
264NaNTajikistan38.86103471.276093000000...3930401341004191428943704453452946094690
265NaNLesotho-29.60998828.233608000000...2224444444
\n", + "

266 rows × 144 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", + " 5/31/20 6/1/20 6/2/20 6/3/20 6/4/20 6/5/20 6/6/20 6/7/20 6/8/20 \\\n", + "0 15205 15750 16509 17267 18054 18969 19551 20342 20917 \n", + "1 1137 1143 1164 1184 1197 1212 1232 1246 1263 \n", + "2 9394 9513 9626 9733 9831 9935 10050 10154 10265 \n", + "3 764 765 844 851 852 852 852 852 852 \n", + "4 86 86 86 86 86 86 88 91 92 \n", + "5 26 26 26 26 26 26 26 26 26 \n", + "6 16851 17415 18319 19268 20197 21037 22020 22794 23620 \n", + "7 9282 9492 10009 10524 11221 11817 12364 13130 13325 \n", + "8 107 107 107 107 107 107 108 108 108 \n", + "9 3098 3104 3104 3106 3110 3110 3109 3112 3114 \n", + "10 29 29 29 29 29 29 29 29 29 \n", + "11 1058 1059 1059 1060 1060 1061 1061 1062 1062 \n", + "12 440 440 440 440 440 440 440 440 440 \n", + "13 228 228 228 228 228 228 228 228 228 \n", + "14 1653 1663 1670 1678 1681 1681 1685 1687 1687 \n", + "15 589 591 592 592 592 596 599 599 599 \n", + "16 16731 16733 16759 16771 16805 16843 16898 16902 16968 \n", + "17 5494 5662 5935 6260 6522 6860 7239 7553 7876 \n", + "18 102 102 102 102 102 102 103 103 103 \n", + "19 11398 11871 12311 12815 13296 13835 14383 14763 15417 \n", + "20 47153 49534 52445 55140 57563 60391 63026 65769 68504 \n", + "21 92 92 92 92 92 92 92 92 92 \n", + "22 42556 43403 44255 45116 45981 46868 47751 48630 49453 \n", + "23 58381 58517 58615 58685 58767 58907 59072 59226 59348 \n", + "24 232 243 244 244 261 261 261 261 288 \n", + "25 43 43 47 47 47 48 48 59 59 \n", + "26 9982 10531 10991 11638 12245 12728 13358 13643 13949 \n", + "27 2510 2524 2535 2551 2594 2606 2606 2606 2704 \n", + "28 514849 526447 555383 584016 614941 645771 672846 691758 707412 \n", + "29 141 141 141 141 141 141 141 141 141 \n", + ".. ... ... ... ... ... ... ... ... ... \n", + "236 24 24 24 24 24 24 24 24 24 \n", + "237 18 18 18 18 18 19 19 19 19 \n", + "238 19 19 19 19 19 19 19 19 19 \n", + "239 156 168 182 196 209 239 256 256 332 \n", + "240 448 449 451 457 464 464 464 472 473 \n", + "241 1256 1339 1339 1339 1339 1368 1368 1368 1389 \n", + "242 1265 1315 1351 1386 1461 1485 1523 1533 1547 \n", + "243 15 15 15 15 15 15 15 15 15 \n", + "244 5 5 5 5 5 5 5 5 5 \n", + "245 11 11 11 11 11 11 11 11 11 \n", + "246 1064 1064 1064 1142 1142 1142 1142 1142 1263 \n", + "247 224 228 232 233 236 236 240 242 244 \n", + "248 3 3 3 3 3 3 3 3 3 \n", + "249 8 8 8 8 8 8 8 8 8 \n", + "250 12 12 12 12 12 12 12 12 12 \n", + "251 9 9 9 9 9 9 9 9 9 \n", + "252 35 38 40 40 40 40 40 40 42 \n", + "253 63 63 63 63 63 63 83 83 83 \n", + "254 861 865 896 909 914 929 946 969 1001 \n", + "255 6 7 7 7 7 7 7 7 7 \n", + "256 284 336 358 369 393 409 409 438 443 \n", + "257 13 13 13 13 13 13 13 13 13 \n", + "258 1 1 1 1 1 1 1 1 1 \n", + "259 994 994 994 994 994 994 994 1317 1604 \n", + "260 9 9 9 9 9 9 9 9 9 \n", + "261 483 484 484 484 485 499 499 513 513 \n", + "262 323 354 399 419 453 469 482 484 496 \n", + "263 106 106 132 132 132 132 141 141 141 \n", + "264 3930 4013 4100 4191 4289 4370 4453 4529 4609 \n", + "265 2 2 2 4 4 4 4 4 4 \n", + "\n", + " 6/9/20 \n", + "0 21459 \n", + "1 1299 \n", + "2 10382 \n", + "3 852 \n", + "4 96 \n", + "5 26 \n", + "6 24761 \n", + "7 13675 \n", + "8 108 \n", + "9 3117 \n", + "10 29 \n", + "11 1062 \n", + "12 440 \n", + "13 228 \n", + "14 1691 \n", + "15 599 \n", + "16 16979 \n", + "17 8191 \n", + "18 103 \n", + "19 15731 \n", + "20 71675 \n", + "21 92 \n", + "22 50265 \n", + "23 59437 \n", + "24 305 \n", + "25 59 \n", + "26 14644 \n", + "27 2728 \n", + "28 739503 \n", + "29 141 \n", + ".. ... \n", + "236 24 \n", + "237 20 \n", + "238 19 \n", + "239 359 \n", + "240 481 \n", + "241 1389 \n", + "242 1586 \n", + "243 15 \n", + "244 5 \n", + "245 11 \n", + "246 1263 \n", + "247 246 \n", + "248 3 \n", + "249 8 \n", + "250 12 \n", + "251 9 \n", + "252 42 \n", + "253 83 \n", + "254 1025 \n", + "255 7 \n", + "256 455 \n", + "257 13 \n", + "258 1 \n", + "259 1604 \n", + "260 9 \n", + "261 514 \n", + "262 524 \n", + "263 141 \n", + "264 4690 \n", + "265 4 \n", + "\n", + "[266 rows x 144 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "extraction en indexant la 2e colonne" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "outputs": [], + "source": [ + "y = 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\",index_col=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "hideCode": false, + "hidePrompt": false, + "scrolled": false + }, + "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", + " \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/StateLatLong1/22/201/23/201/24/201/25/201/26/201/27/201/28/20...5/31/206/1/206/2/206/3/206/4/206/5/206/6/206/7/206/8/206/9/20
Country/Region
AfghanistanNaN33.00000065.0000000000000...15205157501650917267180541896919551203422091721459
AlbaniaNaN41.15330020.1683000000000...1137114311641184119712121232124612631299
AlgeriaNaN28.0339001.6596000000000...93949513962697339831993510050101541026510382
AndorraNaN42.5063001.5218000000000...764765844851852852852852852852
AngolaNaN-11.20270017.8739000000000...86868686868688919296
Antigua and BarbudaNaN17.060800-61.7964000000000...26262626262626262626
ArgentinaNaN-38.416100-63.6167000000000...16851174151831919268201972103722020227942362024761
ArmeniaNaN40.06910045.0382000000000...928294921000910524112211181712364131301332513675
AustraliaAustralian Capital Territory-35.473500149.0124000000000...107107107107107107108108108108
AustraliaNew South Wales-33.868800151.2093000000344...3098310431043106311031103109311231143117
AustraliaNorthern Territory-12.463400130.8456000000000...29292929292929292929
AustraliaQueensland-28.016700153.4000000000000...1058105910591060106010611061106210621062
AustraliaSouth Australia-34.928500138.6007000000000...440440440440440440440440440440
AustraliaTasmania-41.454500145.9707000000000...228228228228228228228228228228
AustraliaVictoria-37.813600144.9631000000111...1653166316701678168116811685168716871691
AustraliaWestern Australia-31.950500115.8605000000000...589591592592592596599599599599
AustriaNaN47.51620014.5501000000000...16731167331675916771168051684316898169021696816979
AzerbaijanNaN40.14310047.5769000000000...5494566259356260652268607239755378768191
BahamasNaN25.034300-77.3963000000000...102102102102102102103103103103
BahrainNaN26.02750050.5500000000000...11398118711231112815132961383514383147631541715731
BangladeshNaN23.68500090.3563000000000...47153495345244555140575636039163026657696850471675
BarbadosNaN13.193900-59.5432000000000...92929292929292929292
BelarusNaN53.70980027.9534000000000...42556434034425545116459814686847751486304945350265
BelgiumNaN50.8333004.0000000000000...58381585175861558685587675890759072592265934859437
BeninNaN9.3077002.3158000000000...232243244244261261261261288305
BhutanNaN27.51420090.4336000000000...43434747474848595959
BoliviaNaN-16.290200-63.5887000000000...9982105311099111638122451272813358136431394914644
Bosnia and HerzegovinaNaN43.91590017.6791000000000...2510252425352551259426062606260627042728
BrazilNaN-14.235000-51.9253000000000...514849526447555383584016614941645771672846691758707412739503
BruneiNaN4.535300114.7277000000000...141141141141141141141141141141
..................................................................
Timor-LesteNaN-8.874217125.7275390000000...24242424242424242424
BelizeNaN13.193900-59.5432000000000...18181818181919191920
LaosNaN19.856270102.4954960000000...19191919191919191919
LibyaNaN26.33510017.2283310000000...156168182196209239256256332359
West Bank and GazaNaN31.95220035.2332000000000...448449451457464464464472473481
Guinea-BissauNaN11.803700-15.1804000000000...1256133913391339133913681368136813891389
MaliNaN17.570692-3.9961660000000...1265131513511386146114851523153315471586
Saint Kitts and NevisNaN17.357822-62.7829980000000...15151515151515151515
CanadaNorthwest Territories64.825500-124.8457000000000...5555555555
CanadaYukon64.282300-135.0000000000000...11111111111111111111
KosovoNaN42.60263620.9029770000000...1064106410641142114211421142114212631263
BurmaNaN21.91620095.9560000000000...224228232233236236240242244246
United KingdomAnguilla18.220600-63.0686000000000...3333333333
United KingdomBritish Virgin Islands18.420700-64.6400000000000...8888888888
United KingdomTurks and Caicos Islands21.694000-71.7979000000000...12121212121212121212
MS ZaandamNaN0.0000000.0000000000000...9999999999
BotswanaNaN-22.32850024.6849000000000...35384040404040404242
BurundiNaN-3.37310029.9189000000000...63636363636383838383
Sierra LeoneNaN8.460555-11.7798890000000...86186589690991492994696910011025
NetherlandsBonaire, Sint Eustatius and Saba12.178400-68.2385000000000...6777777777
MalawiNaN-13.25430834.3015250000000...284336358369393409409438443455
United KingdomFalkland Islands (Malvinas)-51.796300-59.5236000000000...13131313131313131313
FranceSaint Pierre and Miquelon46.885200-56.3159000000000...1111111111
South SudanNaN6.87700031.3070000000000...994994994994994994994131716041604
Western SaharaNaN24.215500-12.8858000000000...9999999999
Sao Tome and PrincipeNaN0.1863606.6130810000000...483484484484485499499513513514
YemenNaN15.55272748.5163880000000...323354399419453469482484496524
ComorosNaN-11.64550043.3333000000000...106106132132132132141141141141
TajikistanNaN38.86103471.2760930000000...3930401341004191428943704453452946094690
LesothoNaN-29.60998828.2336080000000...2224444444
\n", + "

266 rows × 143 columns

\n", + "
" + ], + "text/plain": [ + " Province/State Lat \\\n", + "Country/Region \n", + "Afghanistan NaN 33.000000 \n", + "Albania NaN 41.153300 \n", + "Algeria NaN 28.033900 \n", + "Andorra NaN 42.506300 \n", + "Angola NaN -11.202700 \n", + "Antigua and Barbuda NaN 17.060800 \n", + "Argentina NaN -38.416100 \n", + "Armenia NaN 40.069100 \n", + "Australia Australian Capital Territory -35.473500 \n", + "Australia New South Wales -33.868800 \n", + "Australia Northern Territory -12.463400 \n", + "Australia Queensland -28.016700 \n", + "Australia South Australia -34.928500 \n", + "Australia Tasmania -41.454500 \n", + "Australia Victoria -37.813600 \n", + "Australia Western Australia -31.950500 \n", + "Austria NaN 47.516200 \n", + "Azerbaijan NaN 40.143100 \n", + "Bahamas NaN 25.034300 \n", + "Bahrain NaN 26.027500 \n", + "Bangladesh NaN 23.685000 \n", + "Barbados NaN 13.193900 \n", + "Belarus NaN 53.709800 \n", + "Belgium NaN 50.833300 \n", + "Benin NaN 9.307700 \n", + "Bhutan NaN 27.514200 \n", + "Bolivia NaN -16.290200 \n", + "Bosnia and Herzegovina NaN 43.915900 \n", + "Brazil NaN -14.235000 \n", + "Brunei NaN 4.535300 \n", + "... ... ... \n", + "Timor-Leste NaN -8.874217 \n", + "Belize NaN 13.193900 \n", + "Laos NaN 19.856270 \n", + "Libya NaN 26.335100 \n", + "West Bank and Gaza NaN 31.952200 \n", + "Guinea-Bissau NaN 11.803700 \n", + "Mali NaN 17.570692 \n", + "Saint Kitts and Nevis NaN 17.357822 \n", + "Canada Northwest Territories 64.825500 \n", + "Canada Yukon 64.282300 \n", + "Kosovo NaN 42.602636 \n", + "Burma NaN 21.916200 \n", + "United Kingdom Anguilla 18.220600 \n", + "United Kingdom British Virgin Islands 18.420700 \n", + "United Kingdom Turks and Caicos Islands 21.694000 \n", + "MS Zaandam NaN 0.000000 \n", + "Botswana NaN -22.328500 \n", + "Burundi NaN -3.373100 \n", + "Sierra Leone NaN 8.460555 \n", + "Netherlands Bonaire, Sint Eustatius and Saba 12.178400 \n", + "Malawi NaN -13.254308 \n", + "United Kingdom Falkland Islands (Malvinas) -51.796300 \n", + "France Saint Pierre and Miquelon 46.885200 \n", + "South Sudan NaN 6.877000 \n", + "Western Sahara NaN 24.215500 \n", + "Sao Tome and Principe NaN 0.186360 \n", + "Yemen NaN 15.552727 \n", + "Comoros NaN -11.645500 \n", + "Tajikistan NaN 38.861034 \n", + "Lesotho NaN -29.609988 \n", + "\n", + " Long 1/22/20 1/23/20 1/24/20 1/25/20 \\\n", + "Country/Region \n", + "Afghanistan 65.000000 0 0 0 0 \n", + "Albania 20.168300 0 0 0 0 \n", + "Algeria 1.659600 0 0 0 0 \n", + "Andorra 1.521800 0 0 0 0 \n", + "Angola 17.873900 0 0 0 0 \n", + "Antigua and Barbuda -61.796400 0 0 0 0 \n", + "Argentina -63.616700 0 0 0 0 \n", + "Armenia 45.038200 0 0 0 0 \n", + "Australia 149.012400 0 0 0 0 \n", + "Australia 151.209300 0 0 0 0 \n", + "Australia 130.845600 0 0 0 0 \n", + "Australia 153.400000 0 0 0 0 \n", + "Australia 138.600700 0 0 0 0 \n", + "Australia 145.970700 0 0 0 0 \n", + "Australia 144.963100 0 0 0 0 \n", + "Australia 115.860500 0 0 0 0 \n", + "Austria 14.550100 0 0 0 0 \n", + "Azerbaijan 47.576900 0 0 0 0 \n", + "Bahamas -77.396300 0 0 0 0 \n", + "Bahrain 50.550000 0 0 0 0 \n", + "Bangladesh 90.356300 0 0 0 0 \n", + "Barbados -59.543200 0 0 0 0 \n", + "Belarus 27.953400 0 0 0 0 \n", + "Belgium 4.000000 0 0 0 0 \n", + "Benin 2.315800 0 0 0 0 \n", + "Bhutan 90.433600 0 0 0 0 \n", + "Bolivia -63.588700 0 0 0 0 \n", + "Bosnia and Herzegovina 17.679100 0 0 0 0 \n", + "Brazil -51.925300 0 0 0 0 \n", + "Brunei 114.727700 0 0 0 0 \n", + "... ... ... ... ... ... \n", + "Timor-Leste 125.727539 0 0 0 0 \n", + "Belize -59.543200 0 0 0 0 \n", + "Laos 102.495496 0 0 0 0 \n", + "Libya 17.228331 0 0 0 0 \n", + "West Bank and Gaza 35.233200 0 0 0 0 \n", + "Guinea-Bissau -15.180400 0 0 0 0 \n", + "Mali -3.996166 0 0 0 0 \n", + "Saint Kitts and Nevis -62.782998 0 0 0 0 \n", + "Canada -124.845700 0 0 0 0 \n", + "Canada -135.000000 0 0 0 0 \n", + "Kosovo 20.902977 0 0 0 0 \n", + "Burma 95.956000 0 0 0 0 \n", + "United Kingdom -63.068600 0 0 0 0 \n", + "United Kingdom -64.640000 0 0 0 0 \n", + "United Kingdom -71.797900 0 0 0 0 \n", + "MS Zaandam 0.000000 0 0 0 0 \n", + "Botswana 24.684900 0 0 0 0 \n", + "Burundi 29.918900 0 0 0 0 \n", + "Sierra Leone -11.779889 0 0 0 0 \n", + "Netherlands -68.238500 0 0 0 0 \n", + "Malawi 34.301525 0 0 0 0 \n", + "United Kingdom -59.523600 0 0 0 0 \n", + "France -56.315900 0 0 0 0 \n", + "South Sudan 31.307000 0 0 0 0 \n", + "Western Sahara -12.885800 0 0 0 0 \n", + "Sao Tome and Principe 6.613081 0 0 0 0 \n", + "Yemen 48.516388 0 0 0 0 \n", + "Comoros 43.333300 0 0 0 0 \n", + "Tajikistan 71.276093 0 0 0 0 \n", + "Lesotho 28.233608 0 0 0 0 \n", + "\n", + " 1/26/20 1/27/20 1/28/20 ... 5/31/20 6/1/20 \\\n", + "Country/Region ... \n", + "Afghanistan 0 0 0 ... 15205 15750 \n", + "Albania 0 0 0 ... 1137 1143 \n", + "Algeria 0 0 0 ... 9394 9513 \n", + "Andorra 0 0 0 ... 764 765 \n", + "Angola 0 0 0 ... 86 86 \n", + "Antigua and Barbuda 0 0 0 ... 26 26 \n", + "Argentina 0 0 0 ... 16851 17415 \n", + "Armenia 0 0 0 ... 9282 9492 \n", + "Australia 0 0 0 ... 107 107 \n", + "Australia 3 4 4 ... 3098 3104 \n", + "Australia 0 0 0 ... 29 29 \n", + "Australia 0 0 0 ... 1058 1059 \n", + "Australia 0 0 0 ... 440 440 \n", + "Australia 0 0 0 ... 228 228 \n", + "Australia 1 1 1 ... 1653 1663 \n", + "Australia 0 0 0 ... 589 591 \n", + "Austria 0 0 0 ... 16731 16733 \n", + "Azerbaijan 0 0 0 ... 5494 5662 \n", + "Bahamas 0 0 0 ... 102 102 \n", + "Bahrain 0 0 0 ... 11398 11871 \n", + "Bangladesh 0 0 0 ... 47153 49534 \n", + "Barbados 0 0 0 ... 92 92 \n", + "Belarus 0 0 0 ... 42556 43403 \n", + "Belgium 0 0 0 ... 58381 58517 \n", + "Benin 0 0 0 ... 232 243 \n", + "Bhutan 0 0 0 ... 43 43 \n", + "Bolivia 0 0 0 ... 9982 10531 \n", + "Bosnia and Herzegovina 0 0 0 ... 2510 2524 \n", + "Brazil 0 0 0 ... 514849 526447 \n", + "Brunei 0 0 0 ... 141 141 \n", + "... ... ... ... ... ... ... \n", + "Timor-Leste 0 0 0 ... 24 24 \n", + "Belize 0 0 0 ... 18 18 \n", + "Laos 0 0 0 ... 19 19 \n", + "Libya 0 0 0 ... 156 168 \n", + "West Bank and Gaza 0 0 0 ... 448 449 \n", + "Guinea-Bissau 0 0 0 ... 1256 1339 \n", + "Mali 0 0 0 ... 1265 1315 \n", + "Saint Kitts and Nevis 0 0 0 ... 15 15 \n", + "Canada 0 0 0 ... 5 5 \n", + "Canada 0 0 0 ... 11 11 \n", + "Kosovo 0 0 0 ... 1064 1064 \n", + "Burma 0 0 0 ... 224 228 \n", + "United Kingdom 0 0 0 ... 3 3 \n", + "United Kingdom 0 0 0 ... 8 8 \n", + "United Kingdom 0 0 0 ... 12 12 \n", + "MS Zaandam 0 0 0 ... 9 9 \n", + "Botswana 0 0 0 ... 35 38 \n", + "Burundi 0 0 0 ... 63 63 \n", + "Sierra Leone 0 0 0 ... 861 865 \n", + "Netherlands 0 0 0 ... 6 7 \n", + "Malawi 0 0 0 ... 284 336 \n", + "United Kingdom 0 0 0 ... 13 13 \n", + "France 0 0 0 ... 1 1 \n", + "South Sudan 0 0 0 ... 994 994 \n", + "Western Sahara 0 0 0 ... 9 9 \n", + "Sao Tome and Principe 0 0 0 ... 483 484 \n", + "Yemen 0 0 0 ... 323 354 \n", + "Comoros 0 0 0 ... 106 106 \n", + "Tajikistan 0 0 0 ... 3930 4013 \n", + "Lesotho 0 0 0 ... 2 2 \n", + "\n", + " 6/2/20 6/3/20 6/4/20 6/5/20 6/6/20 6/7/20 \\\n", + "Country/Region \n", + "Afghanistan 16509 17267 18054 18969 19551 20342 \n", + "Albania 1164 1184 1197 1212 1232 1246 \n", + "Algeria 9626 9733 9831 9935 10050 10154 \n", + "Andorra 844 851 852 852 852 852 \n", + "Angola 86 86 86 86 88 91 \n", + "Antigua and Barbuda 26 26 26 26 26 26 \n", + "Argentina 18319 19268 20197 21037 22020 22794 \n", + "Armenia 10009 10524 11221 11817 12364 13130 \n", + "Australia 107 107 107 107 108 108 \n", + "Australia 3104 3106 3110 3110 3109 3112 \n", + "Australia 29 29 29 29 29 29 \n", + "Australia 1059 1060 1060 1061 1061 1062 \n", + "Australia 440 440 440 440 440 440 \n", + "Australia 228 228 228 228 228 228 \n", + "Australia 1670 1678 1681 1681 1685 1687 \n", + "Australia 592 592 592 596 599 599 \n", + "Austria 16759 16771 16805 16843 16898 16902 \n", + "Azerbaijan 5935 6260 6522 6860 7239 7553 \n", + "Bahamas 102 102 102 102 103 103 \n", + "Bahrain 12311 12815 13296 13835 14383 14763 \n", + "Bangladesh 52445 55140 57563 60391 63026 65769 \n", + "Barbados 92 92 92 92 92 92 \n", + "Belarus 44255 45116 45981 46868 47751 48630 \n", + "Belgium 58615 58685 58767 58907 59072 59226 \n", + "Benin 244 244 261 261 261 261 \n", + "Bhutan 47 47 47 48 48 59 \n", + "Bolivia 10991 11638 12245 12728 13358 13643 \n", + "Bosnia and Herzegovina 2535 2551 2594 2606 2606 2606 \n", + "Brazil 555383 584016 614941 645771 672846 691758 \n", + "Brunei 141 141 141 141 141 141 \n", + "... ... ... ... ... ... ... \n", + "Timor-Leste 24 24 24 24 24 24 \n", + "Belize 18 18 18 19 19 19 \n", + "Laos 19 19 19 19 19 19 \n", + "Libya 182 196 209 239 256 256 \n", + "West Bank and Gaza 451 457 464 464 464 472 \n", + "Guinea-Bissau 1339 1339 1339 1368 1368 1368 \n", + "Mali 1351 1386 1461 1485 1523 1533 \n", + "Saint Kitts and Nevis 15 15 15 15 15 15 \n", + "Canada 5 5 5 5 5 5 \n", + "Canada 11 11 11 11 11 11 \n", + "Kosovo 1064 1142 1142 1142 1142 1142 \n", + "Burma 232 233 236 236 240 242 \n", + "United Kingdom 3 3 3 3 3 3 \n", + "United Kingdom 8 8 8 8 8 8 \n", + "United Kingdom 12 12 12 12 12 12 \n", + "MS Zaandam 9 9 9 9 9 9 \n", + "Botswana 40 40 40 40 40 40 \n", + "Burundi 63 63 63 63 83 83 \n", + "Sierra Leone 896 909 914 929 946 969 \n", + "Netherlands 7 7 7 7 7 7 \n", + "Malawi 358 369 393 409 409 438 \n", + "United Kingdom 13 13 13 13 13 13 \n", + "France 1 1 1 1 1 1 \n", + "South Sudan 994 994 994 994 994 1317 \n", + "Western Sahara 9 9 9 9 9 9 \n", + "Sao Tome and Principe 484 484 485 499 499 513 \n", + "Yemen 399 419 453 469 482 484 \n", + "Comoros 132 132 132 132 141 141 \n", + "Tajikistan 4100 4191 4289 4370 4453 4529 \n", + "Lesotho 2 4 4 4 4 4 \n", + "\n", + " 6/8/20 6/9/20 \n", + "Country/Region \n", + "Afghanistan 20917 21459 \n", + "Albania 1263 1299 \n", + "Algeria 10265 10382 \n", + "Andorra 852 852 \n", + "Angola 92 96 \n", + "Antigua and Barbuda 26 26 \n", + "Argentina 23620 24761 \n", + "Armenia 13325 13675 \n", + "Australia 108 108 \n", + "Australia 3114 3117 \n", + "Australia 29 29 \n", + "Australia 1062 1062 \n", + "Australia 440 440 \n", + "Australia 228 228 \n", + "Australia 1687 1691 \n", + "Australia 599 599 \n", + "Austria 16968 16979 \n", + "Azerbaijan 7876 8191 \n", + "Bahamas 103 103 \n", + "Bahrain 15417 15731 \n", + "Bangladesh 68504 71675 \n", + "Barbados 92 92 \n", + "Belarus 49453 50265 \n", + "Belgium 59348 59437 \n", + "Benin 288 305 \n", + "Bhutan 59 59 \n", + "Bolivia 13949 14644 \n", + "Bosnia and Herzegovina 2704 2728 \n", + "Brazil 707412 739503 \n", + "Brunei 141 141 \n", + "... ... ... \n", + "Timor-Leste 24 24 \n", + "Belize 19 20 \n", + "Laos 19 19 \n", + "Libya 332 359 \n", + "West Bank and Gaza 473 481 \n", + "Guinea-Bissau 1389 1389 \n", + "Mali 1547 1586 \n", + "Saint Kitts and Nevis 15 15 \n", + "Canada 5 5 \n", + "Canada 11 11 \n", + "Kosovo 1263 1263 \n", + "Burma 244 246 \n", + "United Kingdom 3 3 \n", + "United Kingdom 8 8 \n", + "United Kingdom 12 12 \n", + "MS Zaandam 9 9 \n", + "Botswana 42 42 \n", + "Burundi 83 83 \n", + "Sierra Leone 1001 1025 \n", + "Netherlands 7 7 \n", + "Malawi 443 455 \n", + "United Kingdom 13 13 \n", + "France 1 1 \n", + "South Sudan 1604 1604 \n", + "Western Sahara 9 9 \n", + "Sao Tome and Principe 513 514 \n", + "Yemen 496 524 \n", + "Comoros 141 141 \n", + "Tajikistan 4609 4690 \n", + "Lesotho 4 4 \n", + "\n", + "[266 rows x 143 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y.plot" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 Afghanistan\n", + "1 Albania\n", + "2 Algeria\n", + "3 Andorra\n", + "4 Angola\n", + "5 Antigua and Barbuda\n", + "6 Argentina\n", + "7 Armenia\n", + "8 Australia\n", + "9 Australia\n", + "10 Australia\n", + "11 Australia\n", + "12 Australia\n", + "13 Australia\n", + "14 Australia\n", + "15 Australia\n", + "16 Austria\n", + "17 Azerbaijan\n", + "18 Bahamas\n", + "19 Bahrain\n", + "20 Bangladesh\n", + "21 Barbados\n", + "22 Belarus\n", + "23 Belgium\n", + "24 Benin\n", + "25 Bhutan\n", + "26 Bolivia\n", + "27 Bosnia and Herzegovina\n", + "28 Brazil\n", + "29 Brunei\n", + " ... \n", + "236 Timor-Leste\n", + "237 Belize\n", + "238 Laos\n", + "239 Libya\n", + "240 West Bank and Gaza\n", + "241 Guinea-Bissau\n", + "242 Mali\n", + "243 Saint Kitts and Nevis\n", + "244 Canada\n", + "245 Canada\n", + "246 Kosovo\n", + "247 Burma\n", + "248 United Kingdom\n", + "249 United Kingdom\n", + "250 United Kingdom\n", + "251 MS Zaandam\n", + "252 Botswana\n", + "253 Burundi\n", + "254 Sierra Leone\n", + "255 Netherlands\n", + "256 Malawi\n", + "257 United Kingdom\n", + "258 France\n", + "259 South Sudan\n", + "260 Western Sahara\n", + "261 Sao Tome and Principe\n", + "262 Yemen\n", + "263 Comoros\n", + "264 Tajikistan\n", + "265 Lesotho\n", + "Name: Country/Region, Length: 266, dtype: object" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x['Country/Region']" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 Afghanistan\n", + "1 Albania\n", + "2 Algeria\n", + "3 Andorra\n", + "4 Angola\n", + "5 Antigua and Barbuda\n", + "6 Argentina\n", + "7 Armenia\n", + "8 Australia\n", + "9 Australia\n", + "10 Australia\n", + "11 Australia\n", + "12 Australia\n", + "13 Australia\n", + "14 Australia\n", + "15 Australia\n", + "16 Austria\n", + "17 Azerbaijan\n", + "18 Bahamas\n", + "19 Bahrain\n", + "20 Bangladesh\n", + "21 Barbados\n", + "22 Belarus\n", + "23 Belgium\n", + "24 Benin\n", + "25 Bhutan\n", + "26 Bolivia\n", + "27 Bosnia and Herzegovina\n", + "28 Brazil\n", + "29 Brunei\n", + " ... \n", + "236 Timor-Leste\n", + "237 Belize\n", + "238 Laos\n", + "239 Libya\n", + "240 West Bank and Gaza\n", + "241 Guinea-Bissau\n", + "242 Mali\n", + "243 Saint Kitts and Nevis\n", + "244 Canada\n", + "245 Canada\n", + "246 Kosovo\n", + "247 Burma\n", + "248 United Kingdom\n", + "249 United Kingdom\n", + "250 United Kingdom\n", + "251 MS Zaandam\n", + "252 Botswana\n", + "253 Burundi\n", + "254 Sierra Leone\n", + "255 Netherlands\n", + "256 Malawi\n", + "257 United Kingdom\n", + "258 France\n", + "259 South Sudan\n", + "260 Western Sahara\n", + "261 Sao Tome and Principe\n", + "262 Yemen\n", + "263 Comoros\n", + "264 Tajikistan\n", + "265 Lesotho\n", + "Name: Country/Region, Length: 266, dtype: object" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m=x['Country/Region']\n", + "m" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(x.Lat)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "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", + "
Country/RegionLat
0Afghanistan33.000000
1Albania41.153300
2Algeria28.033900
3Andorra42.506300
4Angola-11.202700
5Antigua and Barbuda17.060800
6Argentina-38.416100
7Armenia40.069100
8Australia-35.473500
9Australia-33.868800
10Australia-12.463400
11Australia-28.016700
12Australia-34.928500
13Australia-41.454500
14Australia-37.813600
15Australia-31.950500
16Austria47.516200
17Azerbaijan40.143100
18Bahamas25.034300
19Bahrain26.027500
20Bangladesh23.685000
21Barbados13.193900
22Belarus53.709800
23Belgium50.833300
24Benin9.307700
25Bhutan27.514200
26Bolivia-16.290200
27Bosnia and Herzegovina43.915900
28Brazil-14.235000
29Brunei4.535300
.........
236Timor-Leste-8.874217
237Belize13.193900
238Laos19.856270
239Libya26.335100
240West Bank and Gaza31.952200
241Guinea-Bissau11.803700
242Mali17.570692
243Saint Kitts and Nevis17.357822
244Canada64.825500
245Canada64.282300
246Kosovo42.602636
247Burma21.916200
248United Kingdom18.220600
249United Kingdom18.420700
250United Kingdom21.694000
251MS Zaandam0.000000
252Botswana-22.328500
253Burundi-3.373100
254Sierra Leone8.460555
255Netherlands12.178400
256Malawi-13.254308
257United Kingdom-51.796300
258France46.885200
259South Sudan6.877000
260Western Sahara24.215500
261Sao Tome and Principe0.186360
262Yemen15.552727
263Comoros-11.645500
264Tajikistan38.861034
265Lesotho-29.609988
\n", + "

266 rows × 2 columns

\n", + "
" + ], + "text/plain": [ + " Country/Region Lat\n", + "0 Afghanistan 33.000000\n", + "1 Albania 41.153300\n", + "2 Algeria 28.033900\n", + "3 Andorra 42.506300\n", + "4 Angola -11.202700\n", + "5 Antigua and Barbuda 17.060800\n", + "6 Argentina -38.416100\n", + "7 Armenia 40.069100\n", + "8 Australia -35.473500\n", + "9 Australia -33.868800\n", + "10 Australia -12.463400\n", + "11 Australia -28.016700\n", + "12 Australia -34.928500\n", + "13 Australia -41.454500\n", + "14 Australia -37.813600\n", + "15 Australia -31.950500\n", + "16 Austria 47.516200\n", + "17 Azerbaijan 40.143100\n", + "18 Bahamas 25.034300\n", + "19 Bahrain 26.027500\n", + "20 Bangladesh 23.685000\n", + "21 Barbados 13.193900\n", + "22 Belarus 53.709800\n", + "23 Belgium 50.833300\n", + "24 Benin 9.307700\n", + "25 Bhutan 27.514200\n", + "26 Bolivia -16.290200\n", + "27 Bosnia and Herzegovina 43.915900\n", + "28 Brazil -14.235000\n", + "29 Brunei 4.535300\n", + ".. ... ...\n", + "236 Timor-Leste -8.874217\n", + "237 Belize 13.193900\n", + "238 Laos 19.856270\n", + "239 Libya 26.335100\n", + "240 West Bank and Gaza 31.952200\n", + "241 Guinea-Bissau 11.803700\n", + "242 Mali 17.570692\n", + "243 Saint Kitts and Nevis 17.357822\n", + "244 Canada 64.825500\n", + "245 Canada 64.282300\n", + "246 Kosovo 42.602636\n", + "247 Burma 21.916200\n", + "248 United Kingdom 18.220600\n", + "249 United Kingdom 18.420700\n", + "250 United Kingdom 21.694000\n", + "251 MS Zaandam 0.000000\n", + "252 Botswana -22.328500\n", + "253 Burundi -3.373100\n", + "254 Sierra Leone 8.460555\n", + "255 Netherlands 12.178400\n", + "256 Malawi -13.254308\n", + "257 United Kingdom -51.796300\n", + "258 France 46.885200\n", + "259 South Sudan 6.877000\n", + "260 Western Sahara 24.215500\n", + "261 Sao Tome and Principe 0.186360\n", + "262 Yemen 15.552727\n", + "263 Comoros -11.645500\n", + "264 Tajikistan 38.861034\n", + "265 Lesotho -29.609988\n", + "\n", + "[266 rows x 2 columns]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x.loc[:,['Country/Region', 'Lat']]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "x.loc[[1,2],:]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "y.loc[['Belgium','China'],:]" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "Belgique=y.loc[['Belgium'],:]\n", + "Chine=y.loc[['China'],:]\n", + "France=y.loc[['France'],:]\n", + "Allemagne=y.loc[['Germany'],:]\n", + "Iran=y.loc[['Iran'],:]\n", + "Italie=y.loc[['Italy'],:]\n", + "Japon=y.loc[['Japan'],:]\n", + "Hollande_et_colonies=y.loc[['Netherlands'],:]\n", + "Portugal=y.loc[['Portugal'],:]\n", + "Espagne=y.loc[['Spain'],:]\n", + "RoyaumeUni_et_colonies=y.loc[['United Kingdom'],:]\n", + "CoréeduSud=y.loc[['Korea, South'],:]\n", + "EtatsUnis=y.loc[['US'],:]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "attention nous n'avons pas encore séparé hong kong et les colonies" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "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", + "
Province/StateLatLong1/22/201/23/201/24/201/25/201/26/201/27/201/28/20...5/31/206/1/206/2/206/3/206/4/206/5/206/6/206/7/206/8/206/9/20
Country/Region
BelgiumNaN50.83334.00000000...58381585175861558685587675890759072592265934859437
\n", + "

1 rows × 143 columns

\n", + "
" + ], + "text/plain": [ + " Province/State Lat Long 1/22/20 1/23/20 1/24/20 \\\n", + "Country/Region \n", + "Belgium NaN 50.8333 4.0 0 0 0 \n", + "\n", + " 1/25/20 1/26/20 1/27/20 1/28/20 ... 5/31/20 6/1/20 \\\n", + "Country/Region ... \n", + "Belgium 0 0 0 0 ... 58381 58517 \n", + "\n", + " 6/2/20 6/3/20 6/4/20 6/5/20 6/6/20 6/7/20 6/8/20 6/9/20 \n", + "Country/Region \n", + "Belgium 58615 58685 58767 58907 59072 59226 59348 59437 \n", + "\n", + "[1 rows x 143 columns]" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + " Belgique[Belgique.isnull().any(axis=1)]" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "France_metropolitaine=France[France.isnull().any(axis=1)]\n", + "RoyaumeUnis=RoyaumeUni_et_colonies[RoyaumeUni_et_colonies.isnull().any(axis=1)]\n", + "Hollande=Hollande_et_colonies[Hollande_et_colonies.isnull().any(axis=1)]" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "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", + "
Province/StateLatLong1/22/201/23/201/24/201/25/201/26/201/27/201/28/20...5/31/206/1/206/2/206/3/206/4/206/5/206/6/206/7/206/8/206/9/20
Country/Region
United KingdomNaN55.3781-3.4360000000...274762276332277985279856281661283311284868286194287399289140
\n", + "

1 rows × 143 columns

\n", + "
" + ], + "text/plain": [ + " Province/State Lat Long 1/22/20 1/23/20 1/24/20 \\\n", + "Country/Region \n", + "United Kingdom NaN 55.3781 -3.436 0 0 0 \n", + "\n", + " 1/25/20 1/26/20 1/27/20 1/28/20 ... 5/31/20 6/1/20 \\\n", + "Country/Region ... \n", + "United Kingdom 0 0 0 0 ... 274762 276332 \n", + "\n", + " 6/2/20 6/3/20 6/4/20 6/5/20 6/6/20 6/7/20 6/8/20 6/9/20 \n", + "Country/Region \n", + "United Kingdom 277985 279856 281661 283311 284868 286194 287399 289140 \n", + "\n", + "[1 rows x 143 columns]" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "RoyaumeUnis" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "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", + "
Province/StateLatLong1/22/201/23/201/24/201/25/201/26/201/27/201/28/20...5/31/206/1/206/2/206/3/206/4/206/5/206/6/206/7/206/8/206/9/20
Country/Region
ChinaAnhui31.8257117.22641915396070106...991991991991991991991991991991
ChinaBeijing40.1824116.414214223641688091...593593593594594594594594594594
ChinaChongqing30.0572107.874069275775110132...579579579579579579579579579579
ChinaFujian26.0789117.9874151018355980...358358358358358358359359359359
ChinaGansu37.8099101.0583022471419...139139139139139139139139139139
ChinaGuangdong23.3417113.424426325378111151207...1595159615971598159816011602160216041604
ChinaGuangxi23.8298108.7881252323364651...254254254254254254254254254254
ChinaGuizhou26.8154106.87481334579...147147147147147147147147147147
ChinaHainan19.1959109.745345819223340...169169169169169169170170170170
ChinaHebei39.5490116.13061128131833...328328328328328328328328328328
ChinaHeilongjiang47.8620127.76150249152133...945945945947947947947947947947
ChinaHenan33.8820113.61405593283128168...1276127612761276127612761276127612761276
ChinaHong Kong22.3000114.20000225888...1084108710931093109911021105110611071107
ChinaHubei30.9756112.2707444444549761105814233554...68135681356813568135681356813568135681356813568135
ChinaHunan27.6104111.708849244369100143...1019101910191019101910191019101910191019
ChinaInner Mongolia44.0935113.9448001771115...235235235235235235235235235237
ChinaJiangsu32.9711119.455015918334770...653653653653653653653653653653
ChinaJiangxi27.6140115.72212718183672109...937937937932932932932932932932
ChinaJilin43.6661126.19230134468...155155155155155155155155155155
ChinaLiaoning41.2956122.608523417212734...149149149149149149149149149149
ChinaMacau22.1667113.55001222567...45454545454545454545
ChinaNingxia37.2692106.165511234711...75757575757575757575
ChinaQinghai35.745295.99560001166...18181818181818181818
ChinaShaanxi35.1917108.870103515223546...308309309309309309311311311311
ChinaShandong36.3427118.1498261527467595...792792792792792792792792792792
ChinaShanghai31.2020121.44919162033405366...672673673673677677677678678678
ChinaShanxi37.5777112.2922111691327...198198198198198198198198198198
ChinaSichuan30.6171102.7103581528446990...575577577577578578578581582582
ChinaTianjin39.3054117.323044810142324...192192192192192192193193193194
ChinaTibet31.692788.09240000000...1111111111
ChinaXinjiang41.112985.240102234510...76767676767676767676
ChinaYunnan24.9740101.487012511162644...185185185185185185185185185185
ChinaZhejiang29.1832120.093410274362104128173...1268126812681268126812681268126812681268
\n", + "

33 rows × 143 columns

\n", + "
" + ], + "text/plain": [ + " Province/State Lat Long 1/22/20 1/23/20 1/24/20 \\\n", + "Country/Region \n", + "China Anhui 31.8257 117.2264 1 9 15 \n", + "China Beijing 40.1824 116.4142 14 22 36 \n", + "China Chongqing 30.0572 107.8740 6 9 27 \n", + "China Fujian 26.0789 117.9874 1 5 10 \n", + "China Gansu 37.8099 101.0583 0 2 2 \n", + "China Guangdong 23.3417 113.4244 26 32 53 \n", + "China Guangxi 23.8298 108.7881 2 5 23 \n", + "China Guizhou 26.8154 106.8748 1 3 3 \n", + "China Hainan 19.1959 109.7453 4 5 8 \n", + "China Hebei 39.5490 116.1306 1 1 2 \n", + "China Heilongjiang 47.8620 127.7615 0 2 4 \n", + "China Henan 33.8820 113.6140 5 5 9 \n", + "China Hong Kong 22.3000 114.2000 0 2 2 \n", + "China Hubei 30.9756 112.2707 444 444 549 \n", + "China Hunan 27.6104 111.7088 4 9 24 \n", + "China Inner Mongolia 44.0935 113.9448 0 0 1 \n", + "China Jiangsu 32.9711 119.4550 1 5 9 \n", + "China Jiangxi 27.6140 115.7221 2 7 18 \n", + "China Jilin 43.6661 126.1923 0 1 3 \n", + "China Liaoning 41.2956 122.6085 2 3 4 \n", + "China Macau 22.1667 113.5500 1 2 2 \n", + "China Ningxia 37.2692 106.1655 1 1 2 \n", + "China Qinghai 35.7452 95.9956 0 0 0 \n", + "China Shaanxi 35.1917 108.8701 0 3 5 \n", + "China Shandong 36.3427 118.1498 2 6 15 \n", + "China Shanghai 31.2020 121.4491 9 16 20 \n", + "China Shanxi 37.5777 112.2922 1 1 1 \n", + "China Sichuan 30.6171 102.7103 5 8 15 \n", + "China Tianjin 39.3054 117.3230 4 4 8 \n", + "China Tibet 31.6927 88.0924 0 0 0 \n", + "China Xinjiang 41.1129 85.2401 0 2 2 \n", + "China Yunnan 24.9740 101.4870 1 2 5 \n", + "China Zhejiang 29.1832 120.0934 10 27 43 \n", + "\n", + " 1/25/20 1/26/20 1/27/20 1/28/20 ... 5/31/20 6/1/20 \\\n", + "Country/Region ... \n", + "China 39 60 70 106 ... 991 991 \n", + "China 41 68 80 91 ... 593 593 \n", + "China 57 75 110 132 ... 579 579 \n", + "China 18 35 59 80 ... 358 358 \n", + "China 4 7 14 19 ... 139 139 \n", + "China 78 111 151 207 ... 1595 1596 \n", + "China 23 36 46 51 ... 254 254 \n", + "China 4 5 7 9 ... 147 147 \n", + "China 19 22 33 40 ... 169 169 \n", + "China 8 13 18 33 ... 328 328 \n", + "China 9 15 21 33 ... 945 945 \n", + "China 32 83 128 168 ... 1276 1276 \n", + "China 5 8 8 8 ... 1084 1087 \n", + "China 761 1058 1423 3554 ... 68135 68135 \n", + "China 43 69 100 143 ... 1019 1019 \n", + "China 7 7 11 15 ... 235 235 \n", + "China 18 33 47 70 ... 653 653 \n", + "China 18 36 72 109 ... 937 937 \n", + "China 4 4 6 8 ... 155 155 \n", + "China 17 21 27 34 ... 149 149 \n", + "China 2 5 6 7 ... 45 45 \n", + "China 3 4 7 11 ... 75 75 \n", + "China 1 1 6 6 ... 18 18 \n", + "China 15 22 35 46 ... 308 309 \n", + "China 27 46 75 95 ... 792 792 \n", + "China 33 40 53 66 ... 672 673 \n", + "China 6 9 13 27 ... 198 198 \n", + "China 28 44 69 90 ... 575 577 \n", + "China 10 14 23 24 ... 192 192 \n", + "China 0 0 0 0 ... 1 1 \n", + "China 3 4 5 10 ... 76 76 \n", + "China 11 16 26 44 ... 185 185 \n", + "China 62 104 128 173 ... 1268 1268 \n", + "\n", + " 6/2/20 6/3/20 6/4/20 6/5/20 6/6/20 6/7/20 6/8/20 6/9/20 \n", + "Country/Region \n", + "China 991 991 991 991 991 991 991 991 \n", + "China 593 594 594 594 594 594 594 594 \n", + "China 579 579 579 579 579 579 579 579 \n", + "China 358 358 358 358 359 359 359 359 \n", + "China 139 139 139 139 139 139 139 139 \n", + "China 1597 1598 1598 1601 1602 1602 1604 1604 \n", + "China 254 254 254 254 254 254 254 254 \n", + "China 147 147 147 147 147 147 147 147 \n", + "China 169 169 169 169 170 170 170 170 \n", + "China 328 328 328 328 328 328 328 328 \n", + "China 945 947 947 947 947 947 947 947 \n", + "China 1276 1276 1276 1276 1276 1276 1276 1276 \n", + "China 1093 1093 1099 1102 1105 1106 1107 1107 \n", + "China 68135 68135 68135 68135 68135 68135 68135 68135 \n", + "China 1019 1019 1019 1019 1019 1019 1019 1019 \n", + "China 235 235 235 235 235 235 235 237 \n", + "China 653 653 653 653 653 653 653 653 \n", + "China 937 932 932 932 932 932 932 932 \n", + "China 155 155 155 155 155 155 155 155 \n", + "China 149 149 149 149 149 149 149 149 \n", + "China 45 45 45 45 45 45 45 45 \n", + "China 75 75 75 75 75 75 75 75 \n", + "China 18 18 18 18 18 18 18 18 \n", + "China 309 309 309 309 311 311 311 311 \n", + "China 792 792 792 792 792 792 792 792 \n", + "China 673 673 677 677 677 678 678 678 \n", + "China 198 198 198 198 198 198 198 198 \n", + "China 577 577 578 578 578 581 582 582 \n", + "China 192 192 192 192 193 193 193 194 \n", + "China 1 1 1 1 1 1 1 1 \n", + "China 76 76 76 76 76 76 76 76 \n", + "China 185 185 185 185 185 185 185 185 \n", + "China 1268 1268 1268 1268 1268 1268 1268 1268 \n", + "\n", + "[33 rows x 143 columns]" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Chine" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "ename": "SyntaxError", + "evalue": "invalid syntax (, line 1)", + "output_type": "error", + "traceback": [ + "\u001b[0;36m File \u001b[0;32m\"\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m HongKong=Chine[Chine.is'Hong Kong'().any(axis=1)]\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n" + ] + } + ], + "source": [ + "HongKong=Chine[Chine.is'Hong Kong'().any(axis=1)]" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'plot' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\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[0mplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mFrance\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mNameError\u001b[0m: name 'plot' is not defined" + ] + } + ], + "source": [ + "plot.France" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_code_all_hidden": false, + "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 +} diff --git a/module2/exo3/exercice_fr.ipynb b/module2/exo3/exercice_fr.ipynb deleted file mode 100644 index 0bbbe371b01e359e381e43239412d77bf53fb1fb..0000000000000000000000000000000000000000 --- a/module2/exo3/exercice_fr.ipynb +++ /dev/null @@ -1,25 +0,0 @@ -{ - "cells": [], - "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": "3.6.3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} - diff --git a/module2/exo3/monthly_in_situ_co2_mlo.csv b/module2/exo3/monthly_in_situ_co2_mlo.csv new file mode 100644 index 0000000000000000000000000000000000000000..d966dba4240c93de6a4dbb53433e0c0ecfe57d5b --- /dev/null +++ b/module2/exo3/monthly_in_situ_co2_mlo.csv @@ -0,0 +1,813 @@ +"-------------------------------------------------------------------------------------------" +" Atmospheric CO2 concentrations (ppm) derived from in situ air measurements " +" at Mauna Loa, Observatory, Hawaii: Latitude 19.5°N Longitude 155.6°W Elevation 3397m " +" " +" Source: R. F. Keeling, S. J. Walker, S. C. Piper and A. F. Bollenbacher " +" Scripps CO2 Program ( http://scrippsco2.ucsd.edu ) " +" Scripps Institution of Oceanography (SIO) " +" University of California " +" La Jolla, California USA 92093-0244 " +" " +" Status of data and correspondence: " +" " +" These data are subject to revision based on recalibration of standard gases. Questions " +" about the data should be directed to Dr. Ralph Keeling (rkeeling@ucsd.edu), Stephen Walker" +" (sjwalker@ucsd.edu) and Stephen Piper (scpiper@ucsd.edu), Scripps CO2 Program. " +" " +" Baseline data in this file through 03-Jun-2020 from archive dated 03-Jun-2020 08:07:43 " +" " +"-------------------------------------------------------------------------------------------" +" " +" Please cite as: " +" " +" C. D. Keeling, S. C. Piper, R. B. Bacastow, M. Wahlen, T. P. Whorf, M. Heimann, and " +" H. A. Meijer, Exchanges of atmospheric CO2 and 13CO2 with the terrestrial biosphere and " +" oceans from 1978 to 2000. I. Global aspects, SIO Reference Series, No. 01-06, Scripps " +" Institution of Oceanography, San Diego, 88 pages, 2001. " +" " +" If it is necessary to cite a peer-reviewed article, please cite as: " +" " +" C. D. Keeling, S. C. Piper, R. B. Bacastow, M. Wahlen, T. P. Whorf, M. Heimann, and " +" H. A. Meijer, Atmospheric CO2 and 13CO2 exchange with the terrestrial biosphere and " +" oceans from 1978 to 2000: observations and carbon cycle implications, pages 83-113, " +" in "A History of Atmospheric CO2 and its effects on Plants, Animals, and Ecosystems", " +" editors, Ehleringer, J.R., T. E. Cerling, M. D. Dearing, Springer Verlag, " +" New York, 2005. " +" " +"-------------------------------------------------------------------------------------------" +" " +" The data file below contains 10 columns. Columns 1-4 give the dates in several redundant " +" formats. Column 5 below gives monthly Mauna Loa CO2 concentrations in micro-mol CO2 per " +" mole (ppm), reported on the 2008A SIO manometric mole fraction scale. This is the " +" standard version of the data most often sought. The monthly values have been adjusted " +" to 24:00 hours on the 15th of each month. Column 6 gives the same data after a seasonal " +" adjustment to remove the quasi-regular seasonal cycle. The adjustment involves " +" subtracting from the data a 4-harmonic fit with a linear gain factor. Column 7 is a " +" smoothed version of the data generated from a stiff cubic spline function plus 4-harmonic " +" functions with linear gain. Column 8 is the same smoothed version with the seasonal " +" cycle removed. Column 9 is identical to Column 5 except that the missing values from " +" Column 5 have been filled with values from Column 7. Column 10 is identical to Column 6 " +" except missing values have been filled with values from Column 8. Missing values are " +" denoted by -99.99 " +" " +" CO2 concentrations are measured on the '08A' calibration scale " +" " + Yr, Mn, Date, Date, CO2,seasonally, fit, seasonally, CO2, seasonally + , , , , , adjusted, ,adjusted fit, filled,adjusted filled + , , Excel, , [ppm], [ppm] , [ppm], [ppm], [ppm], [ppm] +1958, 01, 21200, 1958.0411, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +1958, 02, 21231, 1958.1260, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +1958, 03, 21259, 1958.2027, 315.70, 314.44, 316.18, 314.90, 315.70, 314.44 +1958, 04, 21290, 1958.2877, 317.45, 315.16, 317.29, 314.98, 317.45, 315.16 +1958, 05, 21320, 1958.3699, 317.51, 314.71, 317.86, 315.06, 317.51, 314.71 +1958, 06, 21351, 1958.4548, -99.99, -99.99, 317.24, 315.14, 317.24, 315.14 +1958, 07, 21381, 1958.5370, 315.86, 315.19, 315.86, 315.21, 315.86, 315.19 +1958, 08, 21412, 1958.6219, 314.93, 316.19, 313.99, 315.28, 314.93, 316.19 +1958, 09, 21443, 1958.7068, 313.21, 316.08, 312.45, 315.35, 313.21, 316.08 +1958, 10, 21473, 1958.7890, -99.99, -99.99, 312.43, 315.40, 312.43, 315.40 +1958, 11, 21504, 1958.8740, 313.33, 315.20, 313.61, 315.46, 313.33, 315.20 +1958, 12, 21534, 1958.9562, 314.67, 315.43, 314.76, 315.51, 314.67, 315.43 +1959, 01, 21565, 1959.0411, 315.58, 315.54, 315.62, 315.57, 315.58, 315.54 +1959, 02, 21596, 1959.1260, 316.49, 315.86, 316.26, 315.63, 316.49, 315.86 +1959, 03, 21624, 1959.2027, 316.65, 315.38, 316.97, 315.69, 316.65, 315.38 +1959, 04, 21655, 1959.2877, 317.72, 315.42, 318.08, 315.76, 317.72, 315.42 +1959, 05, 21685, 1959.3699, 318.29, 315.49, 318.65, 315.84, 318.29, 315.49 +1959, 06, 21716, 1959.4548, 318.15, 316.03, 318.04, 315.93, 318.15, 316.03 +1959, 07, 21746, 1959.5370, 316.54, 315.86, 316.67, 316.02, 316.54, 315.86 +1959, 08, 21777, 1959.6219, 314.80, 316.06, 314.82, 316.12, 314.80, 316.06 +1959, 09, 21808, 1959.7068, 313.84, 316.73, 313.31, 316.21, 313.84, 316.73 +1959, 10, 21838, 1959.7890, 313.33, 316.33, 313.32, 316.30, 313.33, 316.33 +1959, 11, 21869, 1959.8740, 314.81, 316.68, 314.54, 316.39, 314.81, 316.68 +1959, 12, 21899, 1959.9562, 315.58, 316.35, 315.72, 316.47, 315.58, 316.35 +1960, 01, 21930, 1960.0410, 316.43, 316.39, 316.61, 316.55, 316.43, 316.39 +1960, 02, 21961, 1960.1257, 316.98, 316.35, 317.27, 316.64, 316.98, 316.35 +1960, 03, 21990, 1960.2049, 317.58, 316.28, 318.02, 316.71, 317.58, 316.28 +1960, 04, 22021, 1960.2896, 319.03, 316.70, 319.14, 316.79, 319.03, 316.70 +1960, 05, 22051, 1960.3716, 320.04, 317.22, 319.68, 316.86, 320.04, 317.22 +1960, 06, 22082, 1960.4563, 319.58, 317.48, 319.01, 316.92, 319.58, 317.48 +1960, 07, 22112, 1960.5383, 318.18, 317.52, 317.60, 316.97, 318.18, 317.52 +1960, 08, 22143, 1960.6230, 315.90, 317.20, 315.68, 317.01, 315.90, 317.20 +1960, 09, 22174, 1960.7077, 314.17, 317.08, 314.12, 317.04, 314.17, 317.08 +1960, 10, 22204, 1960.7896, 313.83, 316.83, 314.08, 317.07, 313.83, 316.83 +1960, 11, 22235, 1960.8743, 315.00, 316.88, 315.25, 317.10, 315.00, 316.88 +1960, 12, 22265, 1960.9563, 316.19, 316.96, 316.39, 317.15, 316.19, 316.96 +1961, 01, 22296, 1961.0411, 316.90, 316.85, 317.25, 317.20, 316.90, 316.85 +1961, 02, 22327, 1961.1260, 317.70, 317.07, 317.90, 317.26, 317.70, 317.07 +1961, 03, 22355, 1961.2027, 318.54, 317.26, 318.62, 317.33, 318.54, 317.26 +1961, 04, 22386, 1961.2877, 319.48, 317.16, 319.75, 317.41, 319.48, 317.16 +1961, 05, 22416, 1961.3699, 320.58, 317.76, 320.32, 317.50, 320.58, 317.76 +1961, 06, 22447, 1961.4548, 319.77, 317.63, 319.71, 317.59, 319.77, 317.63 +1961, 07, 22477, 1961.5370, 318.57, 317.88, 318.33, 317.67, 318.57, 317.88 +1961, 08, 22508, 1961.6219, 316.79, 318.06, 316.45, 317.76, 316.79, 318.06 +1961, 09, 22539, 1961.7068, 314.99, 317.90, 314.92, 317.84, 314.99, 317.90 +1961, 10, 22569, 1961.7890, 315.31, 318.32, 314.92, 317.92, 315.31, 318.32 +1961, 11, 22600, 1961.8740, 316.10, 317.99, 316.12, 317.99, 316.10, 317.99 +1961, 12, 22630, 1961.9562, 317.01, 317.78, 317.30, 318.05, 317.01, 317.78 +1962, 01, 22661, 1962.0411, 317.94, 317.90, 318.18, 318.12, 317.94, 317.90 +1962, 02, 22692, 1962.1260, 318.55, 317.92, 318.83, 318.19, 318.55, 317.92 +1962, 03, 22720, 1962.2027, 319.68, 318.40, 319.55, 318.25, 319.68, 318.40 +1962, 04, 22751, 1962.2877, 320.57, 318.24, 320.66, 318.32, 320.57, 318.24 +1962, 05, 22781, 1962.3699, 321.02, 318.18, 321.22, 318.38, 321.02, 318.18 +1962, 06, 22812, 1962.4548, 320.62, 318.47, 320.57, 318.45, 320.62, 318.47 +1962, 07, 22842, 1962.5370, 319.61, 318.93, 319.16, 318.50, 319.61, 318.93 +1962, 08, 22873, 1962.6219, 317.40, 318.68, 317.24, 318.55, 317.40, 318.68 +1962, 09, 22904, 1962.7068, 316.25, 319.17, 315.66, 318.60, 316.25, 319.17 +1962, 10, 22934, 1962.7890, 315.42, 318.44, 315.62, 318.64, 315.42, 318.44 +1962, 11, 22965, 1962.8740, 316.69, 318.58, 316.80, 318.68, 316.69, 318.58 +1962, 12, 22995, 1962.9562, 317.70, 318.47, 317.96, 318.72, 317.70, 318.47 +1963, 01, 23026, 1963.0411, 318.74, 318.70, 318.81, 318.76, 318.74, 318.70 +1963, 02, 23057, 1963.1260, 319.07, 318.43, 319.45, 318.81, 319.07, 318.43 +1963, 03, 23085, 1963.2027, 319.86, 318.57, 320.15, 318.85, 319.86, 318.57 +1963, 04, 23116, 1963.2877, 321.38, 319.05, 321.26, 318.91, 321.38, 319.05 +1963, 05, 23146, 1963.3699, 322.25, 319.40, 321.80, 318.96, 322.25, 319.40 +1963, 06, 23177, 1963.4548, 321.48, 319.33, 321.14, 319.01, 321.48, 319.33 +1963, 07, 23207, 1963.5370, 319.74, 319.06, 319.71, 319.05, 319.74, 319.06 +1963, 08, 23238, 1963.6219, 317.77, 319.05, 317.78, 319.10, 317.77, 319.05 +1963, 09, 23269, 1963.7068, 316.21, 319.14, 316.19, 319.14, 316.21, 319.14 +1963, 10, 23299, 1963.7890, 315.99, 319.02, 316.16, 319.18, 315.99, 319.02 +1963, 11, 23330, 1963.8740, 317.07, 318.97, 317.34, 319.22, 317.07, 318.97 +1963, 12, 23360, 1963.9562, 318.35, 319.13, 318.51, 319.27, 318.35, 319.13 +1964, 01, 23391, 1964.0410, 319.57, 319.53, 319.37, 319.31, 319.57, 319.53 +1964, 02, 23422, 1964.1257, -99.99, -99.99, 320.00, 319.36, 320.00, 319.36 +1964, 03, 23451, 1964.2049, -99.99, -99.99, 320.73, 319.40, 320.73, 319.40 +1964, 04, 23482, 1964.2896, -99.99, -99.99, 321.83, 319.45, 321.83, 319.45 +1964, 05, 23512, 1964.3716, 322.26, 319.40, 322.34, 319.49, 322.26, 319.40 +1964, 06, 23543, 1964.4563, 321.89, 319.75, 321.64, 319.52, 321.89, 319.75 +1964, 07, 23573, 1964.5383, 320.44, 319.78, 320.18, 319.55, 320.44, 319.78 +1964, 08, 23604, 1964.6230, 318.69, 320.01, 318.23, 319.58, 318.69, 320.01 +1964, 09, 23635, 1964.7077, 316.70, 319.66, 316.63, 319.60, 316.70, 319.66 +1964, 10, 23665, 1964.7896, 316.87, 319.91, 316.59, 319.62, 316.87, 319.91 +1964, 11, 23696, 1964.8743, 317.68, 319.58, 317.75, 319.63, 317.68, 319.58 +1964, 12, 23726, 1964.9563, 318.71, 319.49, 318.89, 319.65, 318.71, 319.49 +1965, 01, 23757, 1965.0411, 319.44, 319.40, 319.73, 319.68, 319.44, 319.40 +1965, 02, 23788, 1965.1260, 320.44, 319.81, 320.37, 319.72, 320.44, 319.81 +1965, 03, 23816, 1965.2027, 320.89, 319.59, 321.08, 319.77, 320.89, 319.59 +1965, 04, 23847, 1965.2877, 322.14, 319.78, 322.20, 319.83, 322.14, 319.78 +1965, 05, 23877, 1965.3699, 322.17, 319.30, 322.77, 319.90, 322.17, 319.30 +1965, 06, 23908, 1965.4548, 321.87, 319.70, 322.15, 320.00, 321.87, 319.70 +1965, 07, 23938, 1965.5370, 321.21, 320.52, 320.76, 320.10, 321.21, 320.52 +1965, 08, 23969, 1965.6219, 318.87, 320.16, 318.88, 320.21, 318.87, 320.16 +1965, 09, 24000, 1965.7068, 317.81, 320.77, 317.35, 320.32, 317.81, 320.77 +1965, 10, 24030, 1965.7890, 317.30, 320.36, 317.39, 320.43, 317.30, 320.36 +1965, 11, 24061, 1965.8740, 318.87, 320.78, 318.65, 320.55, 318.87, 320.78 +1965, 12, 24091, 1965.9562, 319.42, 320.20, 319.89, 320.66, 319.42, 320.20 +1966, 01, 24122, 1966.0411, 320.62, 320.58, 320.84, 320.78, 320.62, 320.58 +1966, 02, 24153, 1966.1260, 321.60, 320.95, 321.55, 320.90, 321.60, 320.95 +1966, 03, 24181, 1966.2027, 322.39, 321.09, 322.32, 321.01, 322.39, 321.09 +1966, 04, 24212, 1966.2877, 323.70, 321.34, 323.50, 321.12, 323.70, 321.34 +1966, 05, 24242, 1966.3699, 324.08, 321.20, 324.10, 321.22, 324.08, 321.20 +1966, 06, 24273, 1966.4548, 323.75, 321.57, 323.47, 321.32, 323.75, 321.57 +1966, 07, 24303, 1966.5370, 322.38, 321.69, 322.06, 321.40, 322.38, 321.69 +1966, 08, 24334, 1966.6219, 320.36, 321.66, 320.15, 321.48, 320.36, 321.66 +1966, 09, 24365, 1966.7068, 318.64, 321.60, 318.57, 321.55, 318.64, 321.60 +1966, 10, 24395, 1966.7890, 318.10, 321.17, 318.56, 321.62, 318.10, 321.17 +1966, 11, 24426, 1966.8740, 319.78, 321.70, 319.78, 321.68, 319.78, 321.70 +1966, 12, 24456, 1966.9562, 321.03, 321.81, 320.97, 321.74, 321.03, 321.81 +1967, 01, 24487, 1967.0411, 322.33, 322.29, 321.85, 321.80, 322.33, 322.29 +1967, 02, 24518, 1967.1260, 322.50, 321.85, 322.51, 321.85, 322.50, 321.85 +1967, 03, 24546, 1967.2027, 323.04, 321.73, 323.22, 321.90, 323.04, 321.73 +1967, 04, 24577, 1967.2877, 324.42, 322.05, 324.34, 321.96, 324.42, 322.05 +1967, 05, 24607, 1967.3699, 325.00, 322.11, 324.90, 322.01, 325.00, 322.11 +1967, 06, 24638, 1967.4548, 324.09, 321.91, 324.24, 322.07, 324.09, 321.91 +1967, 07, 24668, 1967.5370, 322.54, 321.85, 322.80, 322.13, 322.54, 321.85 +1967, 08, 24699, 1967.6219, 320.92, 322.22, 320.87, 322.20, 320.92, 322.22 +1967, 09, 24730, 1967.7068, 319.25, 322.23, 319.28, 322.27, 319.25, 322.23 +1967, 10, 24760, 1967.7890, 319.39, 322.47, 319.28, 322.34, 319.39, 322.47 +1967, 11, 24791, 1967.8740, 320.73, 322.65, 320.51, 322.42, 320.73, 322.65 +1967, 12, 24821, 1967.9562, 321.96, 322.74, 321.72, 322.49, 321.96, 322.74 +1968, 01, 24852, 1968.0410, 322.57, 322.53, 322.62, 322.57, 322.57, 322.53 +1968, 02, 24883, 1968.1257, 323.15, 322.50, 323.30, 322.65, 323.15, 322.50 +1968, 03, 24912, 1968.2049, 323.89, 322.55, 324.08, 322.73, 323.89, 322.55 +1968, 04, 24943, 1968.2896, 325.02, 322.62, 325.24, 322.82, 325.02, 322.62 +1968, 05, 24973, 1968.3716, 325.57, 322.68, 325.81, 322.92, 325.57, 322.68 +1968, 06, 25004, 1968.4563, 325.36, 323.19, 325.18, 323.03, 325.36, 323.19 +1968, 07, 25034, 1968.5383, 324.14, 323.47, 323.78, 323.13, 324.14, 323.47 +1968, 08, 25065, 1968.6230, 322.11, 323.44, 321.88, 323.25, 322.11, 323.44 +1968, 09, 25096, 1968.7077, 320.33, 323.32, 320.36, 323.37, 320.33, 323.32 +1968, 10, 25126, 1968.7896, 320.25, 323.33, 320.41, 323.48, 320.25, 323.33 +1968, 11, 25157, 1968.8743, 321.32, 323.25, 321.71, 323.61, 321.32, 323.25 +1968, 12, 25187, 1968.9563, 322.89, 323.68, 322.97, 323.74, 322.89, 323.68 +1969, 01, 25218, 1969.0411, 324.00, 323.96, 323.94, 323.88, 324.00, 323.96 +1969, 02, 25249, 1969.1260, 324.41, 323.77, 324.68, 324.03, 324.41, 323.77 +1969, 03, 25277, 1969.2027, 325.63, 324.32, 325.49, 324.16, 325.63, 324.32 +1969, 04, 25308, 1969.2877, 326.66, 324.28, 326.70, 324.30, 326.66, 324.28 +1969, 05, 25338, 1969.3699, 327.38, 324.48, 327.34, 324.44, 327.38, 324.48 +1969, 06, 25369, 1969.4548, 326.71, 324.51, 326.75, 324.57, 326.71, 324.51 +1969, 07, 25399, 1969.5370, 325.88, 325.18, 325.36, 324.69, 325.88, 325.18 +1969, 08, 25430, 1969.6219, 323.66, 324.97, 323.46, 324.80, 323.66, 324.97 +1969, 09, 25461, 1969.7068, 322.38, 325.37, 321.89, 324.90, 322.38, 325.37 +1969, 10, 25491, 1969.7890, 321.78, 324.88, 321.90, 324.99, 321.78, 324.88 +1969, 11, 25522, 1969.8740, 322.85, 324.79, 323.16, 325.07, 322.85, 324.79 +1969, 12, 25552, 1969.9562, 324.12, 324.91, 324.38, 325.15, 324.12, 324.91 +1970, 01, 25583, 1970.0411, 325.06, 325.02, 325.29, 325.24, 325.06, 325.02 +1970, 02, 25614, 1970.1260, 325.98, 325.33, 325.98, 325.32, 325.98, 325.33 +1970, 03, 25642, 1970.2027, 326.93, 325.61, 326.73, 325.39, 326.93, 325.61 +1970, 04, 25673, 1970.2877, 328.13, 325.74, 327.88, 325.47, 328.13, 325.74 +1970, 05, 25703, 1970.3699, 328.08, 325.16, 328.47, 325.55, 328.08, 325.16 +1970, 06, 25734, 1970.4548, 327.67, 325.46, 327.81, 325.63, 327.67, 325.46 +1970, 07, 25764, 1970.5370, 326.34, 325.64, 326.37, 325.70, 326.34, 325.64 +1970, 08, 25795, 1970.6219, 324.69, 326.00, 324.42, 325.77, 324.69, 326.00 +1970, 09, 25826, 1970.7068, 323.10, 326.10, 322.81, 325.83, 323.10, 326.10 +1970, 10, 25856, 1970.7890, 323.06, 326.18, 322.78, 325.88, 323.06, 326.18 +1970, 11, 25887, 1970.8740, 324.01, 325.95, 324.00, 325.93, 324.01, 325.95 +1970, 12, 25917, 1970.9562, 325.13, 325.93, 325.19, 325.97, 325.13, 325.93 +1971, 01, 25948, 1971.0411, 326.17, 326.13, 326.06, 326.00, 326.17, 326.13 +1971, 02, 25979, 1971.1260, 326.68, 326.03, 326.71, 326.04, 326.68, 326.03 +1971, 03, 26007, 1971.2027, 327.17, 325.85, 327.42, 326.08, 327.17, 325.85 +1971, 04, 26038, 1971.2877, 327.79, 325.38, 328.55, 326.13, 327.79, 325.38 +1971, 05, 26068, 1971.3699, 328.93, 326.00, 329.12, 326.19, 328.93, 326.00 +1971, 06, 26099, 1971.4548, 328.57, 326.36, 328.45, 326.26, 328.57, 326.36 +1971, 07, 26129, 1971.5370, 327.36, 326.65, 327.00, 326.33, 327.36, 326.65 +1971, 08, 26160, 1971.6219, 325.43, 326.75, 325.05, 326.40, 325.43, 326.75 +1971, 09, 26191, 1971.7068, 323.36, 326.37, 323.44, 326.47, 323.36, 326.37 +1971, 10, 26221, 1971.7890, 323.56, 326.68, 323.43, 326.54, 323.56, 326.68 +1971, 11, 26252, 1971.8740, 324.80, 326.75, 324.69, 326.62, 324.80, 326.75 +1971, 12, 26282, 1971.9562, 326.01, 326.81, 325.91, 326.69, 326.01, 326.81 +1972, 01, 26313, 1972.0410, 326.77, 326.73, 326.83, 326.78, 326.77, 326.73 +1972, 02, 26344, 1972.1257, 327.63, 326.98, 327.54, 326.87, 327.63, 326.98 +1972, 03, 26373, 1972.2049, 327.75, 326.40, 328.34, 326.97, 327.75, 326.40 +1972, 04, 26404, 1972.2896, 329.72, 327.29, 329.54, 327.09, 329.72, 327.29 +1972, 05, 26434, 1972.3716, 330.07, 327.13, 330.16, 327.22, 330.07, 327.13 +1972, 06, 26465, 1972.4563, 329.09, 326.89, 329.55, 327.37, 329.09, 326.89 +1972, 07, 26495, 1972.5383, 328.04, 327.36, 328.18, 327.53, 328.04, 327.36 +1972, 08, 26526, 1972.6230, 326.32, 327.67, 326.33, 327.71, 326.32, 327.67 +1972, 09, 26557, 1972.7077, 324.84, 327.87, 324.86, 327.91, 324.84, 327.87 +1972, 10, 26587, 1972.7896, 325.20, 328.33, 324.99, 328.10, 325.20, 328.33 +1972, 11, 26618, 1972.8743, 326.50, 328.45, 326.37, 328.30, 326.50, 328.45 +1972, 12, 26648, 1972.9563, 327.55, 328.35, 327.72, 328.50, 327.55, 328.35 +1973, 01, 26679, 1973.0411, 328.55, 328.50, 328.77, 328.71, 328.55, 328.50 +1973, 02, 26710, 1973.1260, 329.56, 328.90, 329.59, 328.92, 329.56, 328.90 +1973, 03, 26738, 1973.2027, 330.30, 328.97, 330.45, 329.10, 330.30, 328.97 +1973, 04, 26769, 1973.2877, 331.50, 329.08, 331.73, 329.30, 331.50, 329.08 +1973, 05, 26799, 1973.3699, 332.48, 329.53, 332.42, 329.47, 332.48, 329.53 +1973, 06, 26830, 1973.4548, 332.07, 329.84, 331.84, 329.63, 332.07, 329.84 +1973, 07, 26860, 1973.5370, 330.87, 330.16, 330.45, 329.77, 330.87, 330.16 +1973, 08, 26891, 1973.6219, 329.31, 330.64, 328.51, 329.87, 329.31, 330.64 +1973, 09, 26922, 1973.7068, 327.51, 330.55, 326.90, 329.95, 327.51, 330.55 +1973, 10, 26952, 1973.7890, 327.18, 330.32, 326.88, 330.01, 327.18, 330.32 +1973, 11, 26983, 1973.8740, 328.16, 330.13, 328.10, 330.04, 328.16, 330.13 +1973, 12, 27013, 1973.9562, 328.64, 329.44, 329.28, 330.06, 328.64, 329.44 +1974, 01, 27044, 1974.0411, 329.35, 329.31, 330.14, 330.09, 329.35, 329.31 +1974, 02, 27075, 1974.1260, 330.71, 330.05, 330.78, 330.11, 330.71, 330.05 +1974, 03, 27103, 1974.2027, 331.48, 330.14, 331.49, 330.14, 331.48, 330.14 +1974, 04, 27134, 1974.2877, 332.65, 330.22, 332.62, 330.18, 332.65, 330.22 +1974, 05, 27164, 1974.3699, 333.09, 330.13, 333.17, 330.21, 333.09, 330.13 +1974, 06, 27195, 1974.4548, 332.25, 330.01, 332.48, 330.26, 332.25, 330.01 +1974, 07, 27225, 1974.5370, 331.18, 330.46, 330.99, 330.31, 331.18, 330.46 +1974, 08, 27256, 1974.6219, 329.39, 330.73, 328.99, 330.36, 329.39, 330.73 +1974, 09, 27287, 1974.7068, 327.43, 330.48, 327.35, 330.41, 327.43, 330.48 +1974, 10, 27317, 1974.7890, 327.37, 330.52, 327.32, 330.46, 327.37, 330.52 +1974, 11, 27348, 1974.8740, 328.46, 330.43, 328.57, 330.52, 328.46, 330.43 +1974, 12, 27378, 1974.9562, 329.57, 330.38, 329.79, 330.58, 329.57, 330.38 +1975, 01, 27409, 1975.0411, 330.40, 330.36, 330.71, 330.65, 330.40, 330.36 +1975, 02, 27440, 1975.1260, 331.40, 330.74, 331.40, 330.73, 331.40, 330.74 +1975, 03, 27468, 1975.2027, 332.04, 330.69, 332.17, 330.81, 332.04, 330.69 +1975, 04, 27499, 1975.2877, 333.31, 330.87, 333.36, 330.91, 333.31, 330.87 +1975, 05, 27529, 1975.3699, 333.97, 331.00, 333.97, 331.00, 333.97, 331.00 +1975, 06, 27560, 1975.4548, 333.60, 331.36, 333.32, 331.10, 333.60, 331.36 +1975, 07, 27590, 1975.5370, 331.90, 331.19, 331.88, 331.20, 331.90, 331.19 +1975, 08, 27621, 1975.6219, 330.06, 331.39, 329.92, 331.29, 330.06, 331.39 +1975, 09, 27652, 1975.7068, 328.56, 331.61, 328.31, 331.38, 328.56, 331.61 +1975, 10, 27682, 1975.7890, 328.34, 331.50, 328.32, 331.47, 328.34, 331.50 +1975, 11, 27713, 1975.8740, 329.49, 331.47, 329.59, 331.55, 329.49, 331.47 +1975, 12, 27743, 1975.9562, 330.76, 331.57, 330.84, 331.63, 330.76, 331.57 +1976, 01, 27774, 1976.0410, 331.75, 331.70, 331.77, 331.71, 331.75, 331.70 +1976, 02, 27805, 1976.1257, 332.57, 331.90, 332.46, 331.79, 332.57, 331.90 +1976, 03, 27834, 1976.2049, 333.50, 332.12, 333.26, 331.87, 333.50, 332.12 +1976, 04, 27865, 1976.2896, 334.58, 332.12, 334.43, 331.95, 334.58, 332.12 +1976, 05, 27895, 1976.3716, 334.88, 331.90, 335.00, 332.02, 334.88, 331.90 +1976, 06, 27926, 1976.4563, 334.33, 332.10, 334.32, 332.11, 334.33, 332.10 +1976, 07, 27956, 1976.5383, 333.05, 332.36, 332.85, 332.19, 333.05, 332.36 +1976, 08, 27987, 1976.6230, 330.94, 332.31, 330.88, 332.28, 330.94, 332.31 +1976, 09, 28018, 1976.7077, 329.30, 332.38, 329.30, 332.39, 329.30, 332.38 +1976, 10, 28048, 1976.7896, 328.94, 332.11, 329.34, 332.50, 328.94, 332.11 +1976, 11, 28079, 1976.8743, 330.31, 332.29, 330.67, 332.63, 330.31, 332.29 +1976, 12, 28109, 1976.9563, 331.68, 332.49, 331.97, 332.77, 331.68, 332.49 +1977, 01, 28140, 1977.0411, 332.93, 332.88, 332.99, 332.93, 332.93, 332.88 +1977, 02, 28171, 1977.1260, 333.42, 332.75, 333.78, 333.10, 333.42, 332.75 +1977, 03, 28199, 1977.2027, 334.70, 333.35, 334.63, 333.27, 334.70, 333.35 +1977, 04, 28230, 1977.2877, 336.07, 333.62, 335.92, 333.45, 336.07, 333.62 +1977, 05, 28260, 1977.3699, 336.75, 333.76, 336.62, 333.63, 336.75, 333.76 +1977, 06, 28291, 1977.4548, 336.27, 334.01, 336.05, 333.81, 336.27, 334.01 +1977, 07, 28321, 1977.5370, 334.92, 334.20, 334.67, 333.98, 334.92, 334.20 +1977, 08, 28352, 1977.6219, 332.75, 334.10, 332.77, 334.15, 332.75, 334.10 +1977, 09, 28383, 1977.7068, 331.59, 334.67, 331.22, 334.31, 331.59, 334.67 +1977, 10, 28413, 1977.7890, 331.16, 334.35, 331.28, 334.45, 331.16, 334.35 +1977, 11, 28444, 1977.8740, 332.40, 334.40, 332.63, 334.60, 332.40, 334.40 +1977, 12, 28474, 1977.9562, 333.85, 334.66, 333.94, 334.73, 333.85, 334.66 +1978, 01, 28505, 1978.0411, 334.97, 334.93, 334.93, 334.87, 334.97, 334.93 +1978, 02, 28536, 1978.1260, 335.39, 334.72, 335.68, 335.01, 335.39, 334.72 +1978, 03, 28564, 1978.2027, 336.64, 335.28, 336.50, 335.12, 336.64, 335.28 +1978, 04, 28595, 1978.2877, 337.76, 335.30, 337.73, 335.25, 337.76, 335.30 +1978, 05, 28625, 1978.3699, 338.01, 335.02, 338.36, 335.37, 338.01, 335.02 +1978, 06, 28656, 1978.4548, 337.90, 335.63, 337.73, 335.49, 337.90, 335.63 +1978, 07, 28686, 1978.5370, 336.54, 335.82, 336.28, 335.59, 336.54, 335.82 +1978, 08, 28717, 1978.6219, 334.68, 336.03, 334.31, 335.70, 334.68, 336.03 +1978, 09, 28748, 1978.7068, 332.76, 335.85, 332.69, 335.79, 332.76, 335.85 +1978, 10, 28778, 1978.7890, 332.55, 335.74, 332.70, 335.89, 332.55, 335.74 +1978, 11, 28809, 1978.8740, 333.92, 335.92, 334.01, 335.98, 333.92, 335.92 +1978, 12, 28839, 1978.9562, 334.95, 335.77, 335.28, 336.08, 334.95, 335.77 +1979, 01, 28870, 1979.0411, 336.23, 336.18, 336.24, 336.19, 336.23, 336.18 +1979, 02, 28901, 1979.1260, 336.76, 336.09, 336.98, 336.30, 336.76, 336.09 +1979, 03, 28929, 1979.2027, 337.96, 336.60, 337.79, 336.41, 337.96, 336.60 +1979, 04, 28960, 1979.2877, 338.88, 336.41, 339.02, 336.54, 338.88, 336.41 +1979, 05, 28990, 1979.3699, 339.47, 336.47, 339.67, 336.66, 339.47, 336.47 +1979, 06, 29021, 1979.4548, 339.29, 337.01, 339.05, 336.80, 339.29, 337.01 +1979, 07, 29051, 1979.5370, 337.73, 337.01, 337.63, 336.93, 337.73, 337.01 +1979, 08, 29082, 1979.6219, 336.09, 337.44, 335.68, 337.07, 336.09, 337.44 +1979, 09, 29113, 1979.7068, 333.92, 337.01, 334.11, 337.22, 333.92, 337.01 +1979, 10, 29143, 1979.7890, 333.86, 337.07, 334.17, 337.36, 333.86, 337.07 +1979, 11, 29174, 1979.8740, 335.29, 337.30, 335.54, 337.52, 335.29, 337.30 +1979, 12, 29204, 1979.9562, 336.73, 337.55, 336.87, 337.68, 336.73, 337.55 +1980, 01, 29235, 1980.0410, 338.01, 337.97, 337.90, 337.84, 338.01, 337.97 +1980, 02, 29266, 1980.1257, 338.36, 337.69, 338.69, 338.01, 338.36, 337.69 +1980, 03, 29295, 1980.2049, 340.07, 338.68, 339.57, 338.17, 340.07, 338.68 +1980, 04, 29326, 1980.2896, 340.76, 338.26, 340.85, 338.33, 340.76, 338.26 +1980, 05, 29356, 1980.3716, 341.47, 338.45, 341.49, 338.48, 341.47, 338.45 +1980, 06, 29387, 1980.4563, 341.17, 338.91, 340.87, 338.63, 341.17, 338.91 +1980, 07, 29417, 1980.5383, 339.56, 338.86, 339.43, 338.76, 339.56, 338.86 +1980, 08, 29448, 1980.6230, 337.60, 338.99, 337.47, 338.89, 337.60, 338.99 +1980, 09, 29479, 1980.7077, 335.88, 339.00, 335.88, 339.01, 335.88, 339.00 +1980, 10, 29509, 1980.7896, 336.02, 339.23, 335.93, 339.13, 336.02, 339.23 +1980, 11, 29540, 1980.8743, 337.10, 339.11, 337.25, 339.23, 337.10, 339.11 +1980, 12, 29570, 1980.9563, 338.21, 339.03, 338.53, 339.34, 338.21, 339.03 +1981, 01, 29601, 1981.0411, 339.24, 339.19, 339.50, 339.44, 339.24, 339.19 +1981, 02, 29632, 1981.1260, 340.48, 339.80, 340.23, 339.54, 340.48, 339.80 +1981, 03, 29660, 1981.2027, 341.38, 340.01, 341.01, 339.63, 341.38, 340.01 +1981, 04, 29691, 1981.2877, 342.50, 340.02, 342.22, 339.72, 342.50, 340.02 +1981, 05, 29721, 1981.3699, 342.91, 339.89, 342.83, 339.80, 342.91, 339.89 +1981, 06, 29752, 1981.4548, 342.25, 339.96, 342.16, 339.89, 342.25, 339.96 +1981, 07, 29782, 1981.5370, 340.49, 339.76, 340.67, 339.97, 340.49, 339.76 +1981, 08, 29813, 1981.6219, 338.43, 339.80, 338.66, 340.06, 338.43, 339.80 +1981, 09, 29844, 1981.7068, 336.69, 339.81, 337.03, 340.16, 336.69, 339.81 +1981, 10, 29874, 1981.7890, 336.86, 340.08, 337.05, 340.26, 336.86, 340.08 +1981, 11, 29905, 1981.8740, 338.36, 340.38, 338.37, 340.37, 338.36, 340.38 +1981, 12, 29935, 1981.9562, 339.61, 340.44, 339.67, 340.48, 339.61, 340.44 +1982, 01, 29966, 1982.0411, 340.75, 340.71, 340.65, 340.59, 340.75, 340.71 +1982, 02, 29997, 1982.1260, 341.61, 340.94, 341.38, 340.69, 341.61, 340.94 +1982, 03, 30025, 1982.2027, 342.70, 341.32, 342.17, 340.78, 342.70, 341.32 +1982, 04, 30056, 1982.2877, 343.57, 341.08, 343.38, 340.87, 343.57, 341.08 +1982, 05, 30086, 1982.3699, 344.14, 341.10, 343.99, 340.96, 344.14, 341.10 +1982, 06, 30117, 1982.4548, 343.35, 341.05, 343.31, 341.04, 343.35, 341.05 +1982, 07, 30147, 1982.5370, 342.06, 341.32, 341.81, 341.11, 342.06, 341.32 +1982, 08, 30178, 1982.6219, 339.81, 341.18, 339.79, 341.19, 339.81, 341.18 +1982, 09, 30209, 1982.7068, 337.98, 341.10, 338.14, 341.28, 337.98, 341.10 +1982, 10, 30239, 1982.7890, 337.86, 341.10, 338.15, 341.37, 337.86, 341.10 +1982, 11, 30270, 1982.8740, 339.26, 341.29, 339.49, 341.49, 339.26, 341.29 +1982, 12, 30300, 1982.9562, 340.49, 341.32, 340.81, 341.62, 340.49, 341.32 +1983, 01, 30331, 1983.0411, 341.38, 341.33, 341.83, 341.77, 341.38, 341.33 +1983, 02, 30362, 1983.1260, 342.52, 341.84, 342.63, 341.94, 342.52, 341.84 +1983, 03, 30390, 1983.2027, 343.10, 341.72, 343.50, 342.11, 343.10, 341.72 +1983, 04, 30421, 1983.2877, 344.94, 342.44, 344.82, 342.30, 344.94, 342.44 +1983, 05, 30451, 1983.3699, 345.76, 342.71, 345.54, 342.49, 345.76, 342.71 +1983, 06, 30482, 1983.4548, 345.32, 343.01, 344.97, 342.68, 345.32, 343.01 +1983, 07, 30512, 1983.5370, 343.98, 343.25, 343.56, 342.86, 343.98, 343.25 +1983, 08, 30543, 1983.6219, 342.38, 343.75, 341.62, 343.03, 342.38, 343.75 +1983, 09, 30574, 1983.7068, 339.87, 343.00, 340.03, 343.19, 339.87, 343.00 +1983, 10, 30604, 1983.7890, 339.99, 343.24, 340.10, 343.33, 339.99, 343.24 +1983, 11, 30635, 1983.8740, 341.15, 343.19, 341.47, 343.48, 341.15, 343.19 +1983, 12, 30665, 1983.9562, 342.99, 343.82, 342.80, 343.62, 342.99, 343.82 +1984, 01, 30696, 1984.0410, 343.70, 343.65, 343.81, 343.75, 343.70, 343.65 +1984, 02, 30727, 1984.1257, 344.50, 343.83, 344.58, 343.89, 344.50, 343.83 +1984, 03, 30756, 1984.2049, 345.28, 343.87, 345.43, 344.01, 345.28, 343.87 +1984, 04, 30787, 1984.2896, 347.05, 344.52, 346.69, 344.14, 347.05, 344.52 +1984, 05, 30817, 1984.3716, 347.43, 344.38, 347.31, 344.26, 347.43, 344.38 +1984, 06, 30848, 1984.4563, 346.80, 344.51, 346.65, 344.38, 346.80, 344.51 +1984, 07, 30878, 1984.5383, 345.39, 344.69, 345.17, 344.50, 345.39, 344.69 +1984, 08, 30909, 1984.6230, 343.28, 344.68, 343.18, 344.62, 343.28, 344.68 +1984, 09, 30940, 1984.7077, 341.07, 344.23, 341.56, 344.74, 341.07, 344.23 +1984, 10, 30970, 1984.7896, 341.35, 344.60, 341.62, 344.86, 341.35, 344.60 +1984, 11, 31001, 1984.8743, 342.98, 345.01, 342.98, 344.99, 342.98, 345.01 +1984, 12, 31031, 1984.9563, 344.22, 345.05, 344.30, 345.12, 344.22, 345.05 +1985, 01, 31062, 1985.0411, 344.97, 344.92, 345.31, 345.25, 344.97, 344.92 +1985, 02, 31093, 1985.1260, 345.99, 345.31, 346.08, 345.38, 345.99, 345.31 +1985, 03, 31121, 1985.2027, 347.42, 346.04, 346.90, 345.50, 347.42, 346.04 +1985, 04, 31152, 1985.2877, 348.35, 345.83, 348.15, 345.62, 348.35, 345.83 +1985, 05, 31182, 1985.3699, 348.93, 345.86, 348.79, 345.73, 348.93, 345.86 +1985, 06, 31213, 1985.4548, 348.25, 345.93, 348.13, 345.83, 348.25, 345.93 +1985, 07, 31243, 1985.5370, 346.56, 345.82, 346.63, 345.92, 346.56, 345.82 +1985, 08, 31274, 1985.6219, 344.67, 346.06, 344.60, 346.01, 344.67, 346.06 +1985, 09, 31305, 1985.7068, 343.09, 346.24, 342.93, 346.10, 343.09, 346.24 +1985, 10, 31335, 1985.7890, 342.80, 346.07, 342.93, 346.19, 342.80, 346.07 +1985, 11, 31366, 1985.8740, 344.24, 346.29, 344.25, 346.28, 344.24, 346.29 +1985, 12, 31396, 1985.9562, 345.56, 346.39, 345.55, 346.37, 345.56, 346.39 +1986, 01, 31427, 1986.0411, 346.30, 346.25, 346.53, 346.47, 346.30, 346.25 +1986, 02, 31458, 1986.1260, 346.95, 346.27, 347.27, 346.58, 346.95, 346.27 +1986, 03, 31486, 1986.2027, 347.85, 346.46, 348.09, 346.68, 347.85, 346.46 +1986, 04, 31517, 1986.2877, 349.55, 347.03, 349.35, 346.81, 349.55, 347.03 +1986, 05, 31547, 1986.3699, 350.22, 347.14, 350.01, 346.93, 350.22, 347.14 +1986, 06, 31578, 1986.4548, 349.55, 347.23, 349.36, 347.06, 349.55, 347.23 +1986, 07, 31608, 1986.5370, 347.94, 347.20, 347.89, 347.18, 347.94, 347.20 +1986, 08, 31639, 1986.6219, 345.90, 347.29, 345.89, 347.31, 345.90, 347.29 +1986, 09, 31670, 1986.7068, 344.85, 348.02, 344.25, 347.44, 344.85, 348.02 +1986, 10, 31700, 1986.7890, 344.17, 347.45, 344.29, 347.56, 344.17, 347.45 +1986, 11, 31731, 1986.8740, 345.66, 347.71, 345.66, 347.69, 345.66, 347.71 +1986, 12, 31761, 1986.9562, 346.90, 347.74, 347.00, 347.82, 346.90, 347.74 +1987, 01, 31792, 1987.0411, 348.02, 347.98, 348.03, 347.97, 348.02, 347.98 +1987, 02, 31823, 1987.1260, 348.48, 347.79, 348.83, 348.13, 348.48, 347.79 +1987, 03, 31851, 1987.2027, 349.42, 348.02, 349.69, 348.28, 349.42, 348.02 +1987, 04, 31882, 1987.2877, 350.98, 348.45, 351.01, 348.47, 350.98, 348.45 +1987, 05, 31912, 1987.3699, 351.85, 348.76, 351.74, 348.65, 351.85, 348.76 +1987, 06, 31943, 1987.4548, 351.26, 348.92, 351.17, 348.86, 351.26, 348.92 +1987, 07, 31973, 1987.5370, 349.51, 348.77, 349.77, 349.06, 349.51, 348.77 +1987, 08, 32004, 1987.6219, 348.10, 349.49, 347.85, 349.27, 348.10, 349.49 +1987, 09, 32035, 1987.7068, 346.45, 349.62, 346.30, 349.50, 346.45, 349.62 +1987, 10, 32065, 1987.7890, 346.36, 349.65, 346.43, 349.71, 346.36, 349.65 +1987, 11, 32096, 1987.8740, 347.81, 349.87, 347.90, 349.94, 347.81, 349.87 +1987, 12, 32126, 1987.9562, 348.96, 349.81, 349.33, 350.16, 348.96, 349.81 +1988, 01, 32157, 1988.0410, 350.43, 350.39, 350.44, 350.38, 350.43, 350.39 +1988, 02, 32188, 1988.1257, 351.73, 351.04, 351.31, 350.61, 351.73, 351.04 +1988, 03, 32217, 1988.2049, 352.22, 350.79, 352.25, 350.81, 352.22, 350.79 +1988, 04, 32248, 1988.2896, 353.59, 351.02, 353.60, 351.02, 353.59, 351.02 +1988, 05, 32278, 1988.3716, 354.22, 351.12, 354.30, 351.21, 354.22, 351.12 +1988, 06, 32309, 1988.4563, 353.80, 351.48, 353.69, 351.40, 353.80, 351.48 +1988, 07, 32339, 1988.5383, 352.38, 351.66, 352.25, 351.57, 352.38, 351.66 +1988, 08, 32370, 1988.6230, 350.43, 351.85, 350.28, 351.73, 350.43, 351.85 +1988, 09, 32401, 1988.7077, 348.73, 351.92, 348.67, 351.89, 348.73, 351.92 +1988, 10, 32431, 1988.7896, 348.88, 352.18, 348.74, 352.02, 348.88, 352.18 +1988, 11, 32462, 1988.8743, 350.07, 352.13, 350.12, 352.15, 350.07, 352.13 +1988, 12, 32492, 1988.9563, 351.34, 352.18, 351.45, 352.27, 351.34, 352.18 +1989, 01, 32523, 1989.0411, 352.76, 352.71, 352.44, 352.39, 352.76, 352.71 +1989, 02, 32554, 1989.1260, 353.07, 352.38, 353.20, 352.49, 353.07, 352.38 +1989, 03, 32582, 1989.2027, 353.68, 352.27, 354.01, 352.59, 353.68, 352.27 +1989, 04, 32613, 1989.2877, 355.42, 352.87, 355.26, 352.69, 355.42, 352.87 +1989, 05, 32643, 1989.3699, 355.67, 352.56, 355.89, 352.79, 355.67, 352.56 +1989, 06, 32674, 1989.4548, 355.12, 352.77, 355.21, 352.89, 355.12, 352.77 +1989, 07, 32704, 1989.5370, 353.90, 353.15, 353.70, 352.98, 353.90, 353.15 +1989, 08, 32735, 1989.6219, 351.67, 353.07, 351.64, 353.08, 351.67, 353.07 +1989, 09, 32766, 1989.7068, 349.81, 353.00, 349.96, 353.18, 349.81, 353.00 +1989, 10, 32796, 1989.7890, 349.99, 353.30, 349.97, 353.27, 349.99, 353.30 +1989, 11, 32827, 1989.8740, 351.30, 353.37, 351.32, 353.37, 351.30, 353.37 +1989, 12, 32857, 1989.9562, 352.52, 353.37, 352.64, 353.47, 352.52, 353.37 +1990, 01, 32888, 1990.0411, 353.66, 353.62, 353.63, 353.57, 353.66, 353.62 +1990, 02, 32919, 1990.1260, 354.70, 354.00, 354.38, 353.68, 354.70, 354.00 +1990, 03, 32947, 1990.2027, 355.38, 353.98, 355.19, 353.77, 355.38, 353.98 +1990, 04, 32978, 1990.2877, 356.20, 353.64, 356.45, 353.87, 356.20, 353.64 +1990, 05, 33008, 1990.3699, 357.16, 354.04, 357.09, 353.98, 357.16, 354.04 +1990, 06, 33039, 1990.4548, 356.23, 353.87, 356.43, 354.09, 356.23, 353.87 +1990, 07, 33069, 1990.5370, 354.81, 354.06, 354.93, 354.21, 354.81, 354.06 +1990, 08, 33100, 1990.6219, 352.91, 354.31, 352.90, 354.34, 352.91, 354.31 +1990, 09, 33131, 1990.7068, 350.96, 354.17, 351.26, 354.48, 350.96, 354.17 +1990, 10, 33161, 1990.7890, 351.18, 354.50, 351.31, 354.62, 351.18, 354.50 +1990, 11, 33192, 1990.8740, 352.83, 354.91, 352.72, 354.77, 352.83, 354.91 +1990, 12, 33222, 1990.9562, 354.21, 355.06, 354.09, 354.92, 354.21, 355.06 +1991, 01, 33253, 1991.0411, 354.72, 354.68, 355.13, 355.07, 354.72, 354.68 +1991, 02, 33284, 1991.1260, 355.75, 355.05, 355.92, 355.21, 355.75, 355.05 +1991, 03, 33312, 1991.2027, 357.16, 355.74, 356.76, 355.33, 357.16, 355.74 +1991, 04, 33343, 1991.2877, 358.60, 356.03, 358.03, 355.44, 358.60, 356.03 +1991, 05, 33373, 1991.3699, 359.34, 356.21, 358.66, 355.54, 359.34, 356.21 +1991, 06, 33404, 1991.4548, 358.24, 355.88, 357.96, 355.61, 358.24, 355.88 +1991, 07, 33434, 1991.5370, 356.17, 355.42, 356.40, 355.68, 356.17, 355.42 +1991, 08, 33465, 1991.6219, 354.01, 355.42, 354.29, 355.74, 354.01, 355.42 +1991, 09, 33496, 1991.7068, 352.15, 355.37, 352.56, 355.80, 352.15, 355.37 +1991, 10, 33526, 1991.7890, 352.21, 355.55, 352.54, 355.86, 352.21, 355.55 +1991, 11, 33557, 1991.8740, 353.75, 355.83, 353.86, 355.92, 353.75, 355.83 +1991, 12, 33587, 1991.9562, 354.99, 355.84, 355.15, 355.99, 354.99, 355.84 +1992, 01, 33618, 1992.0410, 355.99, 355.94, 356.12, 356.06, 355.99, 355.94 +1992, 02, 33649, 1992.1257, 356.72, 356.02, 356.84, 356.13, 356.72, 356.02 +1992, 03, 33678, 1992.2049, 357.81, 356.36, 357.65, 356.19, 357.81, 356.36 +1992, 04, 33709, 1992.2896, 359.15, 356.55, 358.87, 356.26, 359.15, 356.55 +1992, 05, 33739, 1992.3716, 359.66, 356.53, 359.44, 356.31, 359.66, 356.53 +1992, 06, 33770, 1992.4563, 359.25, 356.90, 358.68, 356.35, 359.25, 356.90 +1992, 07, 33800, 1992.5383, 357.02, 356.30, 357.08, 356.39, 357.02, 356.30 +1992, 08, 33831, 1992.6230, 355.00, 356.44, 354.95, 356.42, 355.00, 356.44 +1992, 09, 33862, 1992.7077, 353.01, 356.25, 353.20, 356.45, 353.01, 356.25 +1992, 10, 33892, 1992.7896, 353.31, 356.64, 353.16, 356.49, 353.31, 356.64 +1992, 11, 33923, 1992.8743, 354.16, 356.25, 354.46, 356.52, 354.16, 356.25 +1992, 12, 33953, 1992.9563, 355.40, 356.25, 355.73, 356.57, 355.40, 356.25 +1993, 01, 33984, 1993.0411, 356.70, 356.66, 356.68, 356.62, 356.70, 356.66 +1993, 02, 34015, 1993.1260, 357.17, 356.46, 357.39, 356.68, 357.17, 356.46 +1993, 03, 34043, 1993.2027, 358.38, 356.95, 358.18, 356.74, 358.38, 356.95 +1993, 04, 34074, 1993.2877, 359.46, 356.88, 359.42, 356.82, 359.46, 356.88 +1993, 05, 34104, 1993.3699, 360.28, 357.13, 360.04, 356.90, 360.28, 357.13 +1993, 06, 34135, 1993.4548, 359.60, 357.21, 359.35, 356.99, 359.60, 357.21 +1993, 07, 34165, 1993.5370, 357.57, 356.81, 357.81, 357.08, 357.57, 356.81 +1993, 08, 34196, 1993.6219, 355.52, 356.94, 355.74, 357.20, 355.52, 356.94 +1993, 09, 34227, 1993.7068, 353.69, 356.93, 354.07, 357.32, 353.69, 356.93 +1993, 10, 34257, 1993.7890, 353.99, 357.34, 354.12, 357.46, 353.99, 357.34 +1993, 11, 34288, 1993.8740, 355.34, 357.44, 355.54, 357.61, 355.34, 357.44 +1993, 12, 34318, 1993.9562, 356.80, 357.66, 356.93, 357.77, 356.80, 357.66 +1994, 01, 34349, 1994.0411, 358.37, 358.32, 358.00, 357.94, 358.37, 358.32 +1994, 02, 34380, 1994.1260, 358.91, 358.21, 358.82, 358.10, 358.91, 358.21 +1994, 03, 34408, 1994.2027, 359.97, 358.54, 359.70, 358.26, 359.97, 358.54 +1994, 04, 34439, 1994.2877, 361.26, 358.67, 361.03, 358.42, 361.26, 358.67 +1994, 05, 34469, 1994.3699, 361.69, 358.53, 361.74, 358.58, 361.69, 358.53 +1994, 06, 34500, 1994.4548, 360.94, 358.56, 361.12, 358.75, 360.94, 358.56 +1994, 07, 34530, 1994.5370, 359.55, 358.79, 359.64, 358.91, 359.55, 358.79 +1994, 08, 34561, 1994.6219, 357.48, 358.90, 357.63, 359.09, 357.48, 358.90 +1994, 09, 34592, 1994.7068, 355.84, 359.09, 356.00, 359.26, 355.84, 359.09 +1994, 10, 34622, 1994.7890, 356.00, 359.36, 356.09, 359.44, 356.00, 359.36 +1994, 11, 34653, 1994.8740, 357.58, 359.69, 357.54, 359.62, 357.58, 359.69 +1994, 12, 34683, 1994.9562, 359.04, 359.90, 358.96, 359.80, 359.04, 359.90 +1995, 01, 34714, 1995.0411, 359.97, 359.92, 360.05, 359.99, 359.97, 359.92 +1995, 02, 34745, 1995.1260, 361.00, 360.30, 360.88, 360.17, 361.00, 360.30 +1995, 03, 34773, 1995.2027, 361.63, 360.20, 361.77, 360.33, 361.63, 360.20 +1995, 04, 34804, 1995.2877, 363.45, 360.85, 363.11, 360.50, 363.45, 360.85 +1995, 05, 34834, 1995.3699, 363.80, 360.63, 363.83, 360.66, 363.80, 360.63 +1995, 06, 34865, 1995.4548, 363.26, 360.87, 363.20, 360.83, 363.26, 360.87 +1995, 07, 34895, 1995.5370, 361.89, 361.13, 361.71, 360.98, 361.89, 361.13 +1995, 08, 34926, 1995.6219, 359.45, 360.88, 359.68, 361.15, 359.45, 360.88 +1995, 09, 34957, 1995.7068, 358.05, 361.31, 358.03, 361.31, 358.05, 361.31 +1995, 10, 34987, 1995.7890, 357.75, 361.13, 358.10, 361.46, 357.75, 361.13 +1995, 11, 35018, 1995.8740, 359.56, 361.68, 359.53, 361.62, 359.56, 361.68 +1995, 12, 35048, 1995.9562, 360.70, 361.56, 360.93, 361.78, 360.70, 361.56 +1996, 01, 35079, 1996.0410, 362.05, 362.00, 361.99, 361.93, 362.05, 362.00 +1996, 02, 35110, 1996.1257, 363.24, 362.54, 362.79, 362.08, 363.24, 362.54 +1996, 03, 35139, 1996.2049, 364.02, 362.56, 363.68, 362.20, 364.02, 362.56 +1996, 04, 35170, 1996.2896, 364.71, 362.08, 364.98, 362.33, 364.71, 362.08 +1996, 05, 35200, 1996.3716, 365.42, 362.24, 365.62, 362.44, 365.42, 362.24 +1996, 06, 35231, 1996.4563, 364.97, 362.59, 364.91, 362.55, 364.97, 362.59 +1996, 07, 35261, 1996.5383, 363.65, 362.91, 363.35, 362.65, 363.65, 362.91 +1996, 08, 35292, 1996.6230, 361.48, 362.94, 361.25, 362.74, 361.48, 362.94 +1996, 09, 35323, 1996.7077, 359.45, 362.73, 359.53, 362.83, 359.45, 362.73 +1996, 10, 35353, 1996.7896, 359.61, 362.99, 359.54, 362.91, 359.61, 362.99 +1996, 11, 35384, 1996.8743, 360.76, 362.87, 360.89, 362.98, 360.76, 362.87 +1996, 12, 35414, 1996.9563, 362.33, 363.19, 362.21, 363.06, 362.33, 363.19 +1997, 01, 35445, 1997.0411, 363.19, 363.14, 363.20, 363.14, 363.19, 363.14 +1997, 02, 35476, 1997.1260, 363.99, 363.28, 363.95, 363.23, 363.99, 363.28 +1997, 03, 35504, 1997.2027, 364.56, 363.12, 364.77, 363.31, 364.56, 363.12 +1997, 04, 35535, 1997.2877, 366.36, 363.74, 366.05, 363.42, 366.36, 363.74 +1997, 05, 35565, 1997.3699, 366.80, 363.61, 366.72, 363.53, 366.80, 363.61 +1997, 06, 35596, 1997.4548, 365.63, 363.22, 366.06, 363.67, 365.63, 363.22 +1997, 07, 35626, 1997.5370, 364.47, 363.70, 364.55, 363.82, 364.47, 363.70 +1997, 08, 35657, 1997.6219, 362.50, 363.94, 362.52, 364.00, 362.50, 363.94 +1997, 09, 35688, 1997.7068, 360.19, 363.47, 360.90, 364.20, 360.19, 363.47 +1997, 10, 35718, 1997.7890, 360.78, 364.17, 361.03, 364.41, 360.78, 364.17 +1997, 11, 35749, 1997.8740, 362.43, 364.56, 362.55, 364.66, 362.43, 364.56 +1997, 12, 35779, 1997.9562, 364.28, 365.14, 364.06, 364.91, 364.28, 365.14 +1998, 01, 35810, 1998.0411, 365.33, 365.28, 365.24, 365.18, 365.33, 365.28 +1998, 02, 35841, 1998.1260, 366.15, 365.44, 366.17, 365.45, 366.15, 365.44 +1998, 03, 35869, 1998.2027, 367.31, 365.87, 367.16, 365.70, 367.31, 365.87 +1998, 04, 35900, 1998.2877, 368.61, 365.99, 368.62, 365.98, 368.61, 365.99 +1998, 05, 35930, 1998.3699, 369.30, 366.11, 369.43, 366.24, 369.30, 366.11 +1998, 06, 35961, 1998.4548, 368.88, 366.46, 368.90, 366.50, 368.88, 366.46 +1998, 07, 35991, 1998.5370, 367.64, 366.87, 367.48, 366.74, 367.64, 366.87 +1998, 08, 36022, 1998.6219, 365.78, 367.22, 365.50, 366.98, 365.78, 367.22 +1998, 09, 36053, 1998.7068, 363.90, 367.19, 363.89, 367.20, 363.90, 367.19 +1998, 10, 36083, 1998.7890, 364.23, 367.64, 363.99, 367.39, 364.23, 367.64 +1998, 11, 36114, 1998.8740, 365.46, 367.59, 365.45, 367.56, 365.46, 367.59 +1998, 12, 36144, 1998.9562, 366.97, 367.84, 366.86, 367.71, 366.97, 367.84 +1999, 01, 36175, 1999.0411, 368.15, 368.10, 367.91, 367.85, 368.15, 368.10 +1999, 02, 36206, 1999.1260, 368.87, 368.16, 368.68, 367.96, 368.87, 368.16 +1999, 03, 36234, 1999.2027, 369.59, 368.14, 369.51, 368.04, 369.59, 368.14 +1999, 04, 36265, 1999.2877, 371.14, 368.51, 370.77, 368.13, 371.14, 368.51 +1999, 05, 36295, 1999.3699, 371.00, 367.80, 371.40, 368.19, 371.00, 367.80 +1999, 06, 36326, 1999.4548, 370.35, 367.93, 370.67, 368.26, 370.35, 367.93 +1999, 07, 36356, 1999.5370, 369.27, 368.49, 369.07, 368.33, 369.27, 368.49 +1999, 08, 36387, 1999.6219, 366.93, 368.37, 366.92, 368.40, 366.93, 368.37 +1999, 09, 36418, 1999.7068, 364.64, 367.94, 365.16, 368.47, 364.64, 367.94 +1999, 10, 36448, 1999.7890, 365.13, 368.55, 365.15, 368.55, 365.13, 368.55 +1999, 11, 36479, 1999.8740, 366.68, 368.81, 366.52, 368.64, 366.68, 368.81 +1999, 12, 36509, 1999.9562, 368.00, 368.88, 367.87, 368.72, 368.00, 368.88 +2000, 01, 36540, 2000.0410, 369.14, 369.09, 368.87, 368.81, 369.14, 369.09 +2000, 02, 36571, 2000.1257, 369.46, 368.75, 369.63, 368.91, 369.46, 368.75 +2000, 03, 36600, 2000.2049, 370.51, 369.03, 370.50, 369.00, 370.51, 369.03 +2000, 04, 36631, 2000.2896, 371.66, 369.00, 371.80, 369.11, 371.66, 369.00 +2000, 05, 36661, 2000.3716, 371.83, 368.61, 372.44, 369.23, 371.83, 368.61 +2000, 06, 36692, 2000.4563, 371.69, 369.28, 371.75, 369.36, 371.69, 369.28 +2000, 07, 36722, 2000.5383, 370.12, 369.37, 370.21, 369.49, 370.12, 369.37 +2000, 08, 36753, 2000.6230, 368.12, 369.60, 368.12, 369.64, 368.12, 369.60 +2000, 09, 36784, 2000.7077, 366.62, 369.94, 366.45, 369.79, 366.62, 369.94 +2000, 10, 36814, 2000.7896, 366.73, 370.15, 366.52, 369.93, 366.73, 370.15 +2000, 11, 36845, 2000.8743, 368.29, 370.43, 367.95, 370.07, 368.29, 370.43 +2000, 12, 36875, 2000.9563, 369.52, 370.40, 369.34, 370.20, 369.52, 370.40 +2001, 01, 36906, 2001.0411, 370.28, 370.23, 370.38, 370.32, 370.28, 370.23 +2001, 02, 36937, 2001.1260, 371.50, 370.78, 371.17, 370.44, 371.50, 370.78 +2001, 03, 36965, 2001.2027, 372.12, 370.66, 372.03, 370.55, 372.12, 370.66 +2001, 04, 36996, 2001.2877, 372.86, 370.21, 373.33, 370.67, 372.86, 370.21 +2001, 05, 37026, 2001.3699, 374.02, 370.79, 374.01, 370.79, 374.02, 370.79 +2001, 06, 37057, 2001.4548, 373.31, 370.87, 373.34, 370.92, 373.31, 370.87 +2001, 07, 37087, 2001.5370, 371.62, 370.84, 371.79, 371.05, 371.62, 370.84 +2001, 08, 37118, 2001.6219, 369.55, 371.00, 369.70, 371.20, 369.55, 371.00 +2001, 09, 37149, 2001.7068, 367.96, 371.28, 368.01, 371.35, 367.96, 371.28 +2001, 10, 37179, 2001.7890, 368.09, 371.53, 368.08, 371.50, 368.09, 371.53 +2001, 11, 37210, 2001.8740, 369.68, 371.83, 369.54, 371.67, 369.68, 371.83 +2001, 12, 37240, 2001.9562, 371.24, 372.12, 370.97, 371.83, 371.24, 372.12 +2002, 01, 37271, 2002.0411, 372.44, 372.39, 372.06, 372.00, 372.44, 372.39 +2002, 02, 37302, 2002.1260, 373.08, 372.36, 372.90, 372.17, 373.08, 372.36 +2002, 03, 37330, 2002.2027, 373.52, 372.05, 373.81, 372.33, 373.52, 372.05 +2002, 04, 37361, 2002.2877, 374.85, 372.20, 375.19, 372.52, 374.85, 372.20 +2002, 05, 37391, 2002.3699, 375.55, 372.31, 375.94, 372.71, 375.55, 372.31 +2002, 06, 37422, 2002.4548, 375.40, 372.95, 375.35, 372.92, 375.40, 372.95 +2002, 07, 37452, 2002.5370, 374.02, 373.24, 373.88, 373.13, 374.02, 373.24 +2002, 08, 37483, 2002.6219, 371.48, 372.94, 371.86, 373.36, 371.48, 372.94 +2002, 09, 37514, 2002.7068, 370.70, 374.03, 370.24, 373.59, 370.70, 374.03 +2002, 10, 37544, 2002.7890, 370.25, 373.70, 370.38, 373.82, 370.25, 373.70 +2002, 11, 37575, 2002.8740, 372.08, 374.24, 371.92, 374.05, 372.08, 374.24 +2002, 12, 37605, 2002.9562, 373.78, 374.66, 373.41, 374.28, 373.78, 374.66 +2003, 01, 37636, 2003.0411, 374.68, 374.63, 374.56, 374.50, 374.68, 374.63 +2003, 02, 37667, 2003.1260, 375.62, 374.90, 375.45, 374.72, 375.62, 374.90 +2003, 03, 37695, 2003.2027, 376.11, 374.64, 376.40, 374.91, 376.11, 374.64 +2003, 04, 37726, 2003.2877, 377.65, 374.99, 377.81, 375.12, 377.65, 374.99 +2003, 05, 37756, 2003.3699, 378.35, 375.11, 378.57, 375.33, 378.35, 375.11 +2003, 06, 37787, 2003.4548, 378.13, 375.67, 377.96, 375.53, 378.13, 375.67 +2003, 07, 37817, 2003.5370, 376.60, 375.82, 376.47, 375.72, 376.60, 375.82 +2003, 08, 37848, 2003.6219, 374.48, 375.95, 374.41, 375.91, 374.48, 375.95 +2003, 09, 37879, 2003.7068, 372.98, 376.32, 372.73, 376.09, 372.98, 376.32 +2003, 10, 37909, 2003.7890, 373.00, 376.46, 372.81, 376.26, 373.00, 376.46 +2003, 11, 37940, 2003.8740, 374.35, 376.51, 374.28, 376.42, 374.35, 376.51 +2003, 12, 37970, 2003.9562, 375.69, 376.57, 375.70, 376.56, 375.69, 376.57 +2004, 01, 38001, 2004.0410, 376.79, 376.74, 376.76, 376.70, 376.79, 376.74 +2004, 02, 38032, 2004.1257, 377.37, 376.64, 377.57, 376.84, 377.37, 376.64 +2004, 03, 38061, 2004.2049, 378.39, 376.89, 378.47, 376.95, 378.39, 376.89 +2004, 04, 38092, 2004.2896, 380.50, 377.80, 379.79, 377.07, 380.50, 377.80 +2004, 05, 38122, 2004.3716, 380.62, 377.36, 380.44, 377.19, 380.62, 377.36 +2004, 06, 38153, 2004.4563, 379.55, 377.11, 379.72, 377.30, 379.55, 377.11 +2004, 07, 38183, 2004.5383, 377.76, 377.01, 378.14, 377.42, 377.76, 377.01 +2004, 08, 38214, 2004.6230, 375.83, 377.33, 376.03, 377.56, 375.83, 377.33 +2004, 09, 38245, 2004.7077, 374.05, 377.41, 374.33, 377.71, 374.05, 377.41 +2004, 10, 38275, 2004.7896, 374.22, 377.69, 374.42, 377.87, 374.22, 377.69 +2004, 11, 38306, 2004.8743, 375.84, 378.01, 375.91, 378.05, 375.84, 378.01 +2004, 12, 38336, 2004.9563, 377.44, 378.33, 377.37, 378.24, 377.44, 378.33 +2005, 01, 38367, 2005.0411, 378.34, 378.29, 378.50, 378.44, 378.34, 378.29 +2005, 02, 38398, 2005.1260, 379.61, 378.88, 379.39, 378.65, 379.61, 378.88 +2005, 03, 38426, 2005.2027, 380.08, 378.61, 380.34, 378.85, 380.08, 378.61 +2005, 04, 38457, 2005.2877, 382.05, 379.37, 381.77, 379.07, 382.05, 379.37 +2005, 05, 38487, 2005.3699, 382.24, 378.97, 382.55, 379.28, 382.24, 378.97 +2005, 06, 38518, 2005.4548, 382.08, 379.61, 381.95, 379.50, 382.08, 379.61 +2005, 07, 38548, 2005.5370, 380.66, 379.88, 380.47, 379.72, 380.66, 379.88 +2005, 08, 38579, 2005.6219, 378.67, 380.14, 378.42, 379.93, 378.67, 380.14 +2005, 09, 38610, 2005.7068, 376.42, 379.78, 376.76, 380.14, 376.42, 379.78 +2005, 10, 38640, 2005.7890, 376.80, 380.28, 376.87, 380.34, 376.80, 380.28 +2005, 11, 38671, 2005.8740, 378.31, 380.49, 378.38, 380.54, 378.31, 380.49 +2005, 12, 38701, 2005.9562, 379.96, 380.85, 379.85, 380.72, 379.96, 380.85 +2006, 01, 38732, 2006.0411, 381.37, 381.32, 380.97, 380.91, 381.37, 381.32 +2006, 02, 38763, 2006.1260, 382.02, 381.29, 381.82, 381.08, 382.02, 381.29 +2006, 03, 38791, 2006.2027, 382.56, 381.08, 382.72, 381.23, 382.56, 381.08 +2006, 04, 38822, 2006.2877, 384.36, 381.68, 384.09, 381.38, 384.36, 381.68 +2006, 05, 38852, 2006.3699, 384.92, 381.64, 384.80, 381.53, 384.92, 381.64 +2006, 06, 38883, 2006.4548, 384.03, 381.55, 384.13, 381.67, 384.03, 381.55 +2006, 07, 38913, 2006.5370, 382.28, 381.49, 382.57, 381.82, 382.28, 381.49 +2006, 08, 38944, 2006.6219, 380.48, 381.95, 380.45, 381.97, 380.48, 381.95 +2006, 09, 38975, 2006.7068, 378.81, 382.18, 378.72, 382.11, 378.81, 382.18 +2006, 10, 39005, 2006.7890, 379.06, 382.55, 378.78, 382.26, 379.06, 382.55 +2006, 11, 39036, 2006.8740, 380.14, 382.33, 380.25, 382.41, 380.14, 382.33 +2006, 12, 39066, 2006.9562, 381.66, 382.55, 381.68, 382.56, 381.66, 382.55 +2007, 01, 39097, 2007.0411, 382.58, 382.53, 382.77, 382.71, 382.58, 382.53 +2007, 02, 39128, 2007.1260, 383.71, 382.98, 383.61, 382.86, 383.71, 382.98 +2007, 03, 39156, 2007.2027, 384.34, 382.85, 384.51, 383.01, 384.34, 382.85 +2007, 04, 39187, 2007.2877, 386.23, 383.53, 385.88, 383.16, 386.23, 383.53 +2007, 05, 39217, 2007.3699, 386.41, 383.13, 386.61, 383.32, 386.41, 383.13 +2007, 06, 39248, 2007.4548, 385.87, 383.39, 385.95, 383.48, 385.87, 383.39 +2007, 07, 39278, 2007.5370, 384.44, 383.65, 384.40, 383.64, 384.44, 383.65 +2007, 08, 39309, 2007.6219, 381.84, 383.32, 382.29, 383.81, 381.84, 383.32 +2007, 09, 39340, 2007.7068, 380.86, 384.25, 380.57, 383.97, 380.86, 384.25 +2007, 10, 39370, 2007.7890, 380.86, 384.36, 380.64, 384.13, 380.86, 384.36 +2007, 11, 39401, 2007.8740, 382.36, 384.55, 382.12, 384.28, 382.36, 384.55 +2007, 12, 39431, 2007.9562, 383.61, 384.51, 383.55, 384.43, 383.61, 384.51 +2008, 01, 39462, 2008.0410, 385.07, 385.02, 384.64, 384.58, 385.07, 385.02 +2008, 02, 39493, 2008.1257, 385.84, 385.11, 385.46, 384.72, 385.84, 385.11 +2008, 03, 39522, 2008.2049, 385.83, 384.31, 386.40, 384.86, 385.83, 384.31 +2008, 04, 39553, 2008.2896, 386.77, 384.04, 387.76, 385.01, 386.77, 384.04 +2008, 05, 39583, 2008.3716, 388.51, 385.22, 388.46, 385.17, 388.51, 385.22 +2008, 06, 39614, 2008.4563, 388.05, 385.58, 387.78, 385.34, 388.05, 385.58 +2008, 07, 39644, 2008.5383, 386.25, 385.49, 386.23, 385.50, 386.25, 385.49 +2008, 08, 39675, 2008.6230, 384.08, 385.60, 384.12, 385.67, 384.08, 385.60 +2008, 09, 39706, 2008.7077, 383.09, 386.49, 382.42, 385.84, 383.09, 386.49 +2008, 10, 39736, 2008.7896, 382.78, 386.28, 382.50, 386.00, 382.78, 386.28 +2008, 11, 39767, 2008.8743, 384.01, 386.20, 383.99, 386.16, 384.01, 386.20 +2008, 12, 39797, 2008.9563, 385.11, 386.01, 385.43, 386.30, 385.11, 386.01 +2009, 01, 39828, 2009.0411, 386.65, 386.61, 386.52, 386.46, 386.65, 386.61 +2009, 02, 39859, 2009.1260, 387.12, 386.39, 387.37, 386.62, 387.12, 386.39 +2009, 03, 39887, 2009.2027, 388.52, 387.02, 388.27, 386.76, 388.52, 387.02 +2009, 04, 39918, 2009.2877, 389.57, 386.86, 389.66, 386.93, 389.57, 386.86 +2009, 05, 39948, 2009.3699, 390.17, 386.86, 390.40, 387.09, 390.17, 386.86 +2009, 06, 39979, 2009.4548, 389.62, 387.12, 389.75, 387.28, 389.62, 387.12 +2009, 07, 40009, 2009.5370, 388.07, 387.27, 388.22, 387.46, 388.07, 387.27 +2009, 08, 40040, 2009.6219, 386.08, 387.57, 386.14, 387.66, 386.08, 387.57 +2009, 09, 40071, 2009.7068, 384.65, 388.06, 384.45, 387.87, 384.65, 388.06 +2009, 10, 40101, 2009.7890, 384.33, 387.85, 384.57, 388.08, 384.33, 387.85 +2009, 11, 40132, 2009.8740, 386.05, 388.25, 386.13, 388.31, 386.05, 388.25 +2009, 12, 40162, 2009.9562, 387.49, 388.39, 387.64, 388.53, 387.49, 388.39 +2010, 01, 40193, 2010.0411, 388.55, 388.50, 388.82, 388.76, 388.55, 388.50 +2010, 02, 40224, 2010.1260, 390.08, 389.34, 389.73, 388.98, 390.08, 389.34 +2010, 03, 40252, 2010.2027, 391.01, 389.51, 390.69, 389.17, 391.01, 389.51 +2010, 04, 40283, 2010.2877, 392.38, 389.66, 392.12, 389.38, 392.38, 389.66 +2010, 05, 40313, 2010.3699, 393.22, 389.90, 392.89, 389.57, 393.22, 389.90 +2010, 06, 40344, 2010.4548, 392.24, 389.73, 392.24, 389.76, 392.24, 389.73 +2010, 07, 40374, 2010.5370, 390.33, 389.53, 390.69, 389.93, 390.33, 389.53 +2010, 08, 40405, 2010.6219, 388.52, 390.01, 388.57, 390.10, 388.52, 390.01 +2010, 09, 40436, 2010.7068, 386.84, 390.25, 386.84, 390.27, 386.84, 390.25 +2010, 10, 40466, 2010.7890, 387.16, 390.70, 386.90, 390.42, 387.16, 390.70 +2010, 11, 40497, 2010.8740, 388.67, 390.88, 388.38, 390.57, 388.67, 390.88 +2010, 12, 40527, 2010.9562, 389.81, 390.71, 389.82, 390.71, 389.81, 390.71 +2011, 01, 40558, 2011.0411, 391.30, 391.25, 390.90, 390.84, 391.30, 391.25 +2011, 02, 40589, 2011.1260, 391.92, 391.18, 391.72, 390.97, 391.92, 391.18 +2011, 03, 40617, 2011.2027, 392.45, 390.95, 392.61, 391.08, 392.45, 390.95 +2011, 04, 40648, 2011.2877, 393.37, 390.64, 393.97, 391.22, 393.37, 390.64 +2011, 05, 40678, 2011.3699, 394.28, 390.96, 394.69, 391.36, 394.28, 390.96 +2011, 06, 40709, 2011.4548, 393.69, 391.18, 394.01, 391.52, 393.69, 391.18 +2011, 07, 40739, 2011.5370, 392.59, 391.79, 392.45, 391.68, 392.59, 391.79 +2011, 08, 40770, 2011.6219, 390.21, 391.71, 390.32, 391.86, 390.21, 391.71 +2011, 09, 40801, 2011.7068, 389.00, 392.43, 388.60, 392.04, 389.00, 392.43 +2011, 10, 40831, 2011.7890, 388.93, 392.48, 388.69, 392.22, 388.93, 392.48 +2011, 11, 40862, 2011.8740, 390.24, 392.46, 390.21, 392.40, 390.24, 392.46 +2011, 12, 40892, 2011.9562, 391.80, 392.71, 391.69, 392.58, 391.80, 392.71 +2012, 01, 40923, 2012.0410, 393.07, 393.02, 392.82, 392.76, 393.07, 393.02 +2012, 02, 40954, 2012.1257, 393.35, 392.61, 393.70, 392.95, 393.35, 392.61 +2012, 03, 40983, 2012.2049, 394.36, 392.82, 394.69, 393.13, 394.36, 392.82 +2012, 04, 41014, 2012.2896, 396.43, 393.66, 396.11, 393.33, 396.43, 393.66 +2012, 05, 41044, 2012.3716, 396.87, 393.53, 396.87, 393.53, 396.87, 393.53 +2012, 06, 41075, 2012.4563, 395.88, 393.38, 396.23, 393.75, 395.88, 393.38 +2012, 07, 41105, 2012.5383, 394.52, 393.75, 394.71, 393.97, 394.52, 393.75 +2012, 08, 41136, 2012.6230, 392.54, 394.07, 392.64, 394.21, 392.54, 394.07 +2012, 09, 41167, 2012.7077, 391.13, 394.57, 390.98, 394.45, 391.13, 394.57 +2012, 10, 41197, 2012.7896, 391.01, 394.56, 391.15, 394.68, 391.01, 394.56 +2012, 11, 41228, 2012.8743, 392.95, 395.17, 392.73, 394.93, 392.95, 395.17 +2012, 12, 41258, 2012.9563, 394.33, 395.24, 394.27, 395.16, 394.33, 395.24 +2013, 01, 41289, 2013.0411, 395.61, 395.55, 395.45, 395.39, 395.61, 395.55 +2013, 02, 41320, 2013.1260, 396.85, 396.10, 396.37, 395.62, 396.85, 396.10 +2013, 03, 41348, 2013.2027, 397.26, 395.75, 397.35, 395.82, 397.26, 395.75 +2013, 04, 41379, 2013.2877, 398.35, 395.61, 398.79, 396.03, 398.35, 395.61 +2013, 05, 41409, 2013.3699, 399.98, 396.63, 399.58, 396.23, 399.98, 396.63 +2013, 06, 41440, 2013.4548, 398.87, 396.34, 398.94, 396.43, 398.87, 396.34 +2013, 07, 41470, 2013.5370, 397.37, 396.56, 397.40, 396.63, 397.37, 396.56 +2013, 08, 41501, 2013.6219, 395.41, 396.92, 395.27, 396.82, 395.41, 396.92 +2013, 09, 41532, 2013.7068, 393.39, 396.84, 393.55, 397.01, 393.39, 396.84 +2013, 10, 41562, 2013.7890, 393.70, 397.26, 393.63, 397.19, 393.70, 397.26 +2013, 11, 41593, 2013.8740, 395.19, 397.43, 395.16, 397.37, 395.19, 397.43 +2013, 12, 41623, 2013.9562, 396.82, 397.73, 396.64, 397.54, 396.82, 397.73 +2014, 01, 41654, 2014.0411, 397.93, 397.87, 397.77, 397.71, 397.93, 397.87 +2014, 02, 41685, 2014.1260, 398.10, 397.35, 398.64, 397.88, 398.10, 397.35 +2014, 03, 41713, 2014.2027, 399.47, 397.95, 399.56, 398.03, 399.47, 397.95 +2014, 04, 41744, 2014.2877, 401.33, 398.57, 400.97, 398.19, 401.33, 398.57 +2014, 05, 41774, 2014.3699, 401.88, 398.52, 401.71, 398.35, 401.88, 398.52 +2014, 06, 41805, 2014.4548, 401.31, 398.77, 401.03, 398.51, 401.31, 398.77 +2014, 07, 41835, 2014.5370, 399.07, 398.26, 399.44, 398.67, 399.07, 398.26 +2014, 08, 41866, 2014.6219, 397.21, 398.72, 397.28, 398.83, 397.21, 398.72 +2014, 09, 41897, 2014.7068, 395.40, 398.86, 395.52, 399.00, 395.40, 398.86 +2014, 10, 41927, 2014.7890, 395.65, 399.23, 395.60, 399.16, 395.65, 399.23 +2014, 11, 41958, 2014.8740, 397.23, 399.46, 397.12, 399.34, 397.23, 399.46 +2014, 12, 41988, 2014.9562, 398.79, 399.70, 398.62, 399.51, 398.79, 399.70 +2015, 01, 42019, 2015.0411, 399.85, 399.80, 399.76, 399.70, 399.85, 399.80 +2015, 02, 42050, 2015.1260, 400.31, 399.56, 400.65, 399.89, 400.31, 399.56 +2015, 03, 42078, 2015.2027, 401.51, 399.99, 401.61, 400.07, 401.51, 399.99 +2015, 04, 42109, 2015.2877, 403.45, 400.69, 403.05, 400.27, 403.45, 400.69 +2015, 05, 42139, 2015.3699, 404.10, 400.74, 403.85, 400.49, 404.10, 400.74 +2015, 06, 42170, 2015.4548, 402.88, 400.33, 403.25, 400.72, 402.88, 400.33 +2015, 07, 42200, 2015.5370, 401.61, 400.80, 401.74, 400.97, 401.61, 400.80 +2015, 08, 42231, 2015.6219, 399.00, 400.51, 399.69, 401.24, 399.00, 400.51 +2015, 09, 42262, 2015.7068, 397.50, 400.96, 398.06, 401.54, 397.50, 400.96 +2015, 10, 42292, 2015.7890, 398.28, 401.87, 398.27, 401.84, 398.28, 401.87 +2015, 11, 42323, 2015.8740, 400.24, 402.49, 399.94, 402.16, 400.24, 402.49 +2015, 12, 42353, 2015.9562, 401.89, 402.81, 401.58, 402.48, 401.89, 402.81 +2016, 01, 42384, 2016.0410, 402.65, 402.60, 402.86, 402.80, 402.65, 402.60 +2016, 02, 42415, 2016.1257, 404.16, 403.41, 403.87, 403.11, 404.16, 403.41 +2016, 03, 42444, 2016.2049, 404.85, 403.30, 404.96, 403.38, 404.85, 403.30 +2016, 04, 42475, 2016.2896, 407.57, 404.77, 406.48, 403.66, 407.57, 404.77 +2016, 05, 42505, 2016.3716, 407.66, 404.28, 407.29, 403.91, 407.66, 404.28 +2016, 06, 42536, 2016.4563, 407.00, 404.48, 406.66, 404.15, 407.00, 404.48 +2016, 07, 42566, 2016.5383, 404.50, 403.72, 405.12, 404.37, 404.50, 403.72 +2016, 08, 42597, 2016.6230, 402.24, 403.79, 403.01, 404.60, 402.24, 403.79 +2016, 09, 42628, 2016.7077, 401.01, 404.50, 401.31, 404.82, 401.01, 404.50 +2016, 10, 42658, 2016.7896, 401.50, 405.09, 401.45, 405.03, 401.50, 405.09 +2016, 11, 42689, 2016.8743, 403.64, 405.88, 403.02, 405.24, 403.64, 405.88 +2016, 12, 42719, 2016.9563, 404.55, 405.47, 404.53, 405.43, 404.55, 405.47 +2017, 01, 42750, 2017.0411, 406.07, 406.02, 405.69, 405.62, 406.07, 406.02 +2017, 02, 42781, 2017.1260, 406.64, 405.89, 406.57, 405.80, 406.64, 405.89 +2017, 03, 42809, 2017.2027, 407.05, 405.52, 407.51, 405.96, 407.05, 405.52 +2017, 04, 42840, 2017.2877, 408.95, 406.17, 408.92, 406.13, 408.95, 406.17 +2017, 05, 42870, 2017.3699, 409.91, 406.52, 409.67, 406.29, 409.91, 406.52 +2017, 06, 42901, 2017.4548, 409.12, 406.55, 408.98, 406.45, 409.12, 406.55 +2017, 07, 42931, 2017.5370, 407.20, 406.38, 407.38, 406.60, 407.20, 406.38 +2017, 08, 42962, 2017.6219, 405.24, 406.76, 405.19, 406.76, 405.24, 406.76 +2017, 09, 42993, 2017.7068, 403.27, 406.75, 403.41, 406.91, 403.27, 406.75 +2017, 10, 43023, 2017.7890, 403.64, 407.25, 403.47, 407.06, 403.64, 407.25 +2017, 11, 43054, 2017.8740, 405.17, 407.43, 404.98, 407.21, 405.17, 407.43 +2017, 12, 43084, 2017.9562, 406.75, 407.68, 406.46, 407.36, 406.75, 407.68 +2018, 01, 43115, 2018.0411, 408.05, 408.00, 407.58, 407.51, 408.05, 408.00 +2018, 02, 43146, 2018.1260, 408.34, 407.59, 408.44, 407.67, 408.34, 407.59 +2018, 03, 43174, 2018.2027, 409.25, 407.72, 409.37, 407.82, 409.25, 407.72 +2018, 04, 43205, 2018.2877, 410.30, 407.52, 410.80, 408.00, 410.30, 407.52 +2018, 05, 43235, 2018.3699, 411.30, 407.91, 411.59, 408.19, 411.30, 407.91 +2018, 06, 43266, 2018.4548, 410.88, 408.31, 410.96, 408.41, 410.88, 408.31 +2018, 07, 43296, 2018.5370, 408.90, 408.08, 409.43, 408.65, 408.90, 408.08 +2018, 08, 43327, 2018.6219, 407.10, 408.63, 407.33, 408.90, 407.10, 408.63 +2018, 09, 43358, 2018.7068, 405.59, 409.08, 405.66, 409.18, 405.59, 409.08 +2018, 10, 43388, 2018.7890, 405.99, 409.61, 405.84, 409.44, 405.99, 409.61 +2018, 11, 43419, 2018.8740, 408.12, 410.38, 407.48, 409.72, 408.12, 410.38 +2018, 12, 43449, 2018.9562, 409.23, 410.15, 409.07, 409.98, 409.23, 410.15 +2019, 01, 43480, 2019.0411, 410.92, 410.87, 410.30, 410.24, 410.92, 410.87 +2019, 02, 43511, 2019.1260, 411.66, 410.90, 411.25, 410.48, 411.66, 410.90 +2019, 03, 43539, 2019.2027, 412.00, 410.46, 412.25, 410.69, 412.00, 410.46 +2019, 04, 43570, 2019.2877, 413.52, 410.72, 413.73, 410.92, 413.52, 410.72 +2019, 05, 43600, 2019.3699, 414.83, 411.42, 414.54, 411.14, 414.83, 411.42 +2019, 06, 43631, 2019.4548, 413.96, 411.38, 413.91, 411.36, 413.96, 411.38 +2019, 07, 43661, 2019.5370, 411.85, 411.03, 412.36, 411.57, 411.85, 411.03 +2019, 08, 43692, 2019.6219, 410.08, 411.62, 410.22, 411.79, 410.08, 411.62 +2019, 09, 43723, 2019.7068, 408.55, 412.06, 408.49, 412.02, 408.55, 412.06 +2019, 10, 43753, 2019.7890, 408.43, 412.06, 408.62, 412.23, 408.43, 412.06 +2019, 11, 43784, 2019.8740, 410.29, 412.56, 410.21, 412.46, 410.29, 412.56 +2019, 12, 43814, 2019.9562, 411.85, 412.78, 411.76, 412.67, 411.85, 412.78 +2020, 01, 43845, 2020.0410, 413.37, 413.32, 412.95, 412.89, 413.37, 413.32 +2020, 02, 43876, 2020.1257, 414.09, 413.33, 413.87, 413.10, 414.09, 413.33 +2020, 03, 43905, 2020.2049, 414.51, 412.94, 414.89, 413.30, 414.51, 412.94 +2020, 04, 43936, 2020.2896, 416.18, 413.35, 416.35, 413.50, 416.18, 413.35 +2020, 05, 43966, 2020.3716, 417.16, 413.75, -99.99, -99.99, 417.16, 413.75 +2020, 06, 43997, 2020.4563, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 07, 44027, 2020.5383, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 08, 44058, 2020.6230, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 09, 44089, 2020.7077, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 10, 44119, 2020.7896, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 11, 44150, 2020.8743, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 12, 44180, 2020.9563, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 diff --git a/module3/exo3/SARS-COV2.ipynb b/module3/exo3/SARS-COV2.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..a1b59696d040a6cc6d798cdb04a2849b0ce01feb --- /dev/null +++ b/module3/exo3/SARS-COV2.ipynb @@ -0,0 +1,4447 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import isoweek\n", + "import numpy as np" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "importation des modules" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "outputs": [], + "source": [ + "y = 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\",index_col=1)" + ] + }, + { + "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", + " \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/StateLatLong1/22/201/23/201/24/201/25/201/26/201/27/201/28/20...6/3/206/4/206/5/206/6/206/7/206/8/206/9/206/10/206/11/206/12/20
Country/Region
AfghanistanNaN33.00000065.0000000000000...17267180541896919551203422091721459221422289023546
AlbaniaNaN41.15330020.1683000000000...1184119712121232124612631299134113851416
AlgeriaNaN28.0339001.6596000000000...97339831993510050101541026510382104841058910698
AndorraNaN42.5063001.5218000000000...851852852852852852852852852853
AngolaNaN-11.20270017.8739000000000...86868688919296113118130
Antigua and BarbudaNaN17.060800-61.7964000000000...26262626262626262626
ArgentinaNaN-38.416100-63.6167000000000...19268201972103722020227942362024761259872737328764
ArmeniaNaN40.06910045.0382000000000...10524112211181712364131301332513675141031466915281
AustraliaAustralian Capital Territory-35.473500149.0124000000000...107107107108108108108108108108
AustraliaNew South Wales-33.868800151.2093000000344...3106311031103109311231143117311731153119
AustraliaNorthern Territory-12.463400130.8456000000000...29292929292929292929
AustraliaQueensland-28.016700153.4000000000000...1060106010611061106210621062106310641065
AustraliaSouth Australia-34.928500138.6007000000000...440440440440440440440440440440
AustraliaTasmania-41.454500145.9707000000000...228228228228228228228228228228
AustraliaVictoria-37.813600144.9631000000111...1678168116811685168716871691169917031703
AustraliaWestern Australia-31.950500115.8605000000000...592592596599599599599601602602
AustriaNaN47.51620014.5501000000000...16771168051684316898169021696816979170051703417064
AzerbaijanNaN40.14310047.5769000000000...6260652268607239755378768191853088829218
BahamasNaN25.034300-77.3963000000000...102102102103103103103103103103
BahrainNaN26.02750050.5500000000000...12815132961383514383147631541715731162001666717269
BangladeshNaN23.68500090.3563000000000...55140575636039163026657696850471675748657805281523
BarbadosNaN13.193900-59.5432000000000...92929292929292969696
BelarusNaN53.70980027.9534000000000...45116459814686847751486304945350265510665181652520
BelgiumNaN50.8333004.0000000000000...58685587675890759072592265934859437595695971159819
BeninNaN9.3077002.3158000000000...244261261261261288305305305388
BhutanNaN27.51420090.4336000000000...47474848595959596262
BoliviaNaN-16.290200-63.5887000000000...11638122451272813358136431394914644152811616516929
Bosnia and HerzegovinaNaN43.91590017.6791000000000...2551259426062606260627042728277528322893
BrazilNaN-14.235000-51.9253000000000...584016614941645771672846691758707412739503772416802828828810
BruneiNaN4.535300114.7277000000000...141141141141141141141141141141
..................................................................
Timor-LesteNaN-8.874217125.7275390000000...24242424242424242424
BelizeNaN13.193900-59.5432000000000...18181919191920202020
LaosNaN19.856270102.4954960000000...19191919191919191919
LibyaNaN26.33510017.2283310000000...196209239256256332359378393409
West Bank and GazaNaN31.95220035.2332000000000...457464464464472473481485487489
Guinea-BissauNaN11.803700-15.1804000000000...1339133913681368136813891389138913891460
MaliNaN17.570692-3.9961660000000...1386146114851523153315471586166717221752
Saint Kitts and NevisNaN17.357822-62.7829980000000...15151515151515151515
CanadaNorthwest Territories64.825500-124.8457000000000...5555555555
CanadaYukon64.282300-135.0000000000000...11111111111111111111
KosovoNaN42.60263620.9029770000000...1142114211421142114212631263129813261326
BurmaNaN21.91620095.9560000000000...233236236240242244246248260261
United KingdomAnguilla18.220600-63.0686000000000...3333333333
United KingdomBritish Virgin Islands18.420700-64.6400000000000...8888888888
United KingdomTurks and Caicos Islands21.694000-71.7979000000000...12121212121212121212
MS ZaandamNaN0.0000000.0000000000000...9999999999
BotswanaNaN-22.32850024.6849000000000...40404040404242484848
BurundiNaN-3.37310029.9189000000000...63636383838383838585
Sierra LeoneNaN8.460555-11.7798890000000...90991492994696910011025106210851103
NetherlandsBonaire, Sint Eustatius and Saba12.178400-68.2385000000000...7777777777
MalawiNaN-13.25430834.3015250000000...369393409409438443455455481481
United KingdomFalkland Islands (Malvinas)-51.796300-59.5236000000000...13131313131313131313
FranceSaint Pierre and Miquelon46.885200-56.3159000000000...1111111111
South SudanNaN6.87700031.3070000000000...994994994994131716041604160416701670
Western SaharaNaN24.215500-12.8858000000000...9999999999
Sao Tome and PrincipeNaN0.1863606.6130810000000...484485499499513513514611632639
YemenNaN15.55272748.5163880000000...419453469482484496524560591632
ComorosNaN-11.64550043.3333000000000...132132132141141141141162162163
TajikistanNaN38.86103471.2760930000000...4191428943704453452946094690476348344902
LesothoNaN-29.60998828.2336080000000...4444444444
\n", + "

266 rows × 146 columns

\n", + "
" + ], + "text/plain": [ + " Province/State Lat \\\n", + "Country/Region \n", + "Afghanistan NaN 33.000000 \n", + "Albania NaN 41.153300 \n", + "Algeria NaN 28.033900 \n", + "Andorra NaN 42.506300 \n", + "Angola NaN -11.202700 \n", + "Antigua and Barbuda NaN 17.060800 \n", + "Argentina NaN -38.416100 \n", + "Armenia NaN 40.069100 \n", + "Australia Australian Capital Territory -35.473500 \n", + "Australia New South Wales -33.868800 \n", + "Australia Northern Territory -12.463400 \n", + "Australia Queensland -28.016700 \n", + "Australia South Australia -34.928500 \n", + "Australia Tasmania -41.454500 \n", + "Australia Victoria -37.813600 \n", + "Australia Western Australia -31.950500 \n", + "Austria NaN 47.516200 \n", + "Azerbaijan NaN 40.143100 \n", + "Bahamas NaN 25.034300 \n", + "Bahrain NaN 26.027500 \n", + "Bangladesh NaN 23.685000 \n", + "Barbados NaN 13.193900 \n", + "Belarus NaN 53.709800 \n", + "Belgium NaN 50.833300 \n", + "Benin NaN 9.307700 \n", + "Bhutan NaN 27.514200 \n", + "Bolivia NaN -16.290200 \n", + "Bosnia and Herzegovina NaN 43.915900 \n", + "Brazil NaN -14.235000 \n", + "Brunei NaN 4.535300 \n", + "... ... ... \n", + "Timor-Leste NaN -8.874217 \n", + "Belize NaN 13.193900 \n", + "Laos NaN 19.856270 \n", + "Libya NaN 26.335100 \n", + "West Bank and Gaza NaN 31.952200 \n", + "Guinea-Bissau NaN 11.803700 \n", + "Mali NaN 17.570692 \n", + "Saint Kitts and Nevis NaN 17.357822 \n", + "Canada Northwest Territories 64.825500 \n", + "Canada Yukon 64.282300 \n", + "Kosovo NaN 42.602636 \n", + "Burma NaN 21.916200 \n", + "United Kingdom Anguilla 18.220600 \n", + "United Kingdom British Virgin Islands 18.420700 \n", + "United Kingdom Turks and Caicos Islands 21.694000 \n", + "MS Zaandam NaN 0.000000 \n", + "Botswana NaN -22.328500 \n", + "Burundi NaN -3.373100 \n", + "Sierra Leone NaN 8.460555 \n", + "Netherlands Bonaire, Sint Eustatius and Saba 12.178400 \n", + "Malawi NaN -13.254308 \n", + "United Kingdom Falkland Islands (Malvinas) -51.796300 \n", + "France Saint Pierre and Miquelon 46.885200 \n", + "South Sudan NaN 6.877000 \n", + "Western Sahara NaN 24.215500 \n", + "Sao Tome and Principe NaN 0.186360 \n", + "Yemen NaN 15.552727 \n", + "Comoros NaN -11.645500 \n", + "Tajikistan NaN 38.861034 \n", + "Lesotho NaN -29.609988 \n", + "\n", + " Long 1/22/20 1/23/20 1/24/20 1/25/20 \\\n", + "Country/Region \n", + "Afghanistan 65.000000 0 0 0 0 \n", + "Albania 20.168300 0 0 0 0 \n", + "Algeria 1.659600 0 0 0 0 \n", + "Andorra 1.521800 0 0 0 0 \n", + "Angola 17.873900 0 0 0 0 \n", + "Antigua and Barbuda -61.796400 0 0 0 0 \n", + "Argentina -63.616700 0 0 0 0 \n", + "Armenia 45.038200 0 0 0 0 \n", + "Australia 149.012400 0 0 0 0 \n", + "Australia 151.209300 0 0 0 0 \n", + "Australia 130.845600 0 0 0 0 \n", + "Australia 153.400000 0 0 0 0 \n", + "Australia 138.600700 0 0 0 0 \n", + "Australia 145.970700 0 0 0 0 \n", + "Australia 144.963100 0 0 0 0 \n", + "Australia 115.860500 0 0 0 0 \n", + "Austria 14.550100 0 0 0 0 \n", + "Azerbaijan 47.576900 0 0 0 0 \n", + "Bahamas -77.396300 0 0 0 0 \n", + "Bahrain 50.550000 0 0 0 0 \n", + "Bangladesh 90.356300 0 0 0 0 \n", + "Barbados -59.543200 0 0 0 0 \n", + "Belarus 27.953400 0 0 0 0 \n", + "Belgium 4.000000 0 0 0 0 \n", + "Benin 2.315800 0 0 0 0 \n", + "Bhutan 90.433600 0 0 0 0 \n", + "Bolivia -63.588700 0 0 0 0 \n", + "Bosnia and Herzegovina 17.679100 0 0 0 0 \n", + "Brazil -51.925300 0 0 0 0 \n", + "Brunei 114.727700 0 0 0 0 \n", + "... ... ... ... ... ... \n", + "Timor-Leste 125.727539 0 0 0 0 \n", + "Belize -59.543200 0 0 0 0 \n", + "Laos 102.495496 0 0 0 0 \n", + "Libya 17.228331 0 0 0 0 \n", + "West Bank and Gaza 35.233200 0 0 0 0 \n", + "Guinea-Bissau -15.180400 0 0 0 0 \n", + "Mali -3.996166 0 0 0 0 \n", + "Saint Kitts and Nevis -62.782998 0 0 0 0 \n", + "Canada -124.845700 0 0 0 0 \n", + "Canada -135.000000 0 0 0 0 \n", + "Kosovo 20.902977 0 0 0 0 \n", + "Burma 95.956000 0 0 0 0 \n", + "United Kingdom -63.068600 0 0 0 0 \n", + "United Kingdom -64.640000 0 0 0 0 \n", + "United Kingdom -71.797900 0 0 0 0 \n", + "MS Zaandam 0.000000 0 0 0 0 \n", + "Botswana 24.684900 0 0 0 0 \n", + "Burundi 29.918900 0 0 0 0 \n", + "Sierra Leone -11.779889 0 0 0 0 \n", + "Netherlands -68.238500 0 0 0 0 \n", + "Malawi 34.301525 0 0 0 0 \n", + "United Kingdom -59.523600 0 0 0 0 \n", + "France -56.315900 0 0 0 0 \n", + "South Sudan 31.307000 0 0 0 0 \n", + "Western Sahara -12.885800 0 0 0 0 \n", + "Sao Tome and Principe 6.613081 0 0 0 0 \n", + "Yemen 48.516388 0 0 0 0 \n", + "Comoros 43.333300 0 0 0 0 \n", + "Tajikistan 71.276093 0 0 0 0 \n", + "Lesotho 28.233608 0 0 0 0 \n", + "\n", + " 1/26/20 1/27/20 1/28/20 ... 6/3/20 6/4/20 \\\n", + "Country/Region ... \n", + "Afghanistan 0 0 0 ... 17267 18054 \n", + "Albania 0 0 0 ... 1184 1197 \n", + "Algeria 0 0 0 ... 9733 9831 \n", + "Andorra 0 0 0 ... 851 852 \n", + "Angola 0 0 0 ... 86 86 \n", + "Antigua and Barbuda 0 0 0 ... 26 26 \n", + "Argentina 0 0 0 ... 19268 20197 \n", + "Armenia 0 0 0 ... 10524 11221 \n", + "Australia 0 0 0 ... 107 107 \n", + "Australia 3 4 4 ... 3106 3110 \n", + "Australia 0 0 0 ... 29 29 \n", + "Australia 0 0 0 ... 1060 1060 \n", + "Australia 0 0 0 ... 440 440 \n", + "Australia 0 0 0 ... 228 228 \n", + "Australia 1 1 1 ... 1678 1681 \n", + "Australia 0 0 0 ... 592 592 \n", + "Austria 0 0 0 ... 16771 16805 \n", + "Azerbaijan 0 0 0 ... 6260 6522 \n", + "Bahamas 0 0 0 ... 102 102 \n", + "Bahrain 0 0 0 ... 12815 13296 \n", + "Bangladesh 0 0 0 ... 55140 57563 \n", + "Barbados 0 0 0 ... 92 92 \n", + "Belarus 0 0 0 ... 45116 45981 \n", + "Belgium 0 0 0 ... 58685 58767 \n", + "Benin 0 0 0 ... 244 261 \n", + "Bhutan 0 0 0 ... 47 47 \n", + "Bolivia 0 0 0 ... 11638 12245 \n", + "Bosnia and Herzegovina 0 0 0 ... 2551 2594 \n", + "Brazil 0 0 0 ... 584016 614941 \n", + "Brunei 0 0 0 ... 141 141 \n", + "... ... ... ... ... ... ... \n", + "Timor-Leste 0 0 0 ... 24 24 \n", + "Belize 0 0 0 ... 18 18 \n", + "Laos 0 0 0 ... 19 19 \n", + "Libya 0 0 0 ... 196 209 \n", + "West Bank and Gaza 0 0 0 ... 457 464 \n", + "Guinea-Bissau 0 0 0 ... 1339 1339 \n", + "Mali 0 0 0 ... 1386 1461 \n", + "Saint Kitts and Nevis 0 0 0 ... 15 15 \n", + "Canada 0 0 0 ... 5 5 \n", + "Canada 0 0 0 ... 11 11 \n", + "Kosovo 0 0 0 ... 1142 1142 \n", + "Burma 0 0 0 ... 233 236 \n", + "United Kingdom 0 0 0 ... 3 3 \n", + "United Kingdom 0 0 0 ... 8 8 \n", + "United Kingdom 0 0 0 ... 12 12 \n", + "MS Zaandam 0 0 0 ... 9 9 \n", + "Botswana 0 0 0 ... 40 40 \n", + "Burundi 0 0 0 ... 63 63 \n", + "Sierra Leone 0 0 0 ... 909 914 \n", + "Netherlands 0 0 0 ... 7 7 \n", + "Malawi 0 0 0 ... 369 393 \n", + "United Kingdom 0 0 0 ... 13 13 \n", + "France 0 0 0 ... 1 1 \n", + "South Sudan 0 0 0 ... 994 994 \n", + "Western Sahara 0 0 0 ... 9 9 \n", + "Sao Tome and Principe 0 0 0 ... 484 485 \n", + "Yemen 0 0 0 ... 419 453 \n", + "Comoros 0 0 0 ... 132 132 \n", + "Tajikistan 0 0 0 ... 4191 4289 \n", + "Lesotho 0 0 0 ... 4 4 \n", + "\n", + " 6/5/20 6/6/20 6/7/20 6/8/20 6/9/20 6/10/20 \\\n", + "Country/Region \n", + "Afghanistan 18969 19551 20342 20917 21459 22142 \n", + "Albania 1212 1232 1246 1263 1299 1341 \n", + "Algeria 9935 10050 10154 10265 10382 10484 \n", + "Andorra 852 852 852 852 852 852 \n", + "Angola 86 88 91 92 96 113 \n", + "Antigua and Barbuda 26 26 26 26 26 26 \n", + "Argentina 21037 22020 22794 23620 24761 25987 \n", + "Armenia 11817 12364 13130 13325 13675 14103 \n", + "Australia 107 108 108 108 108 108 \n", + "Australia 3110 3109 3112 3114 3117 3117 \n", + "Australia 29 29 29 29 29 29 \n", + "Australia 1061 1061 1062 1062 1062 1063 \n", + "Australia 440 440 440 440 440 440 \n", + "Australia 228 228 228 228 228 228 \n", + "Australia 1681 1685 1687 1687 1691 1699 \n", + "Australia 596 599 599 599 599 601 \n", + "Austria 16843 16898 16902 16968 16979 17005 \n", + "Azerbaijan 6860 7239 7553 7876 8191 8530 \n", + "Bahamas 102 103 103 103 103 103 \n", + "Bahrain 13835 14383 14763 15417 15731 16200 \n", + "Bangladesh 60391 63026 65769 68504 71675 74865 \n", + "Barbados 92 92 92 92 92 96 \n", + "Belarus 46868 47751 48630 49453 50265 51066 \n", + "Belgium 58907 59072 59226 59348 59437 59569 \n", + "Benin 261 261 261 288 305 305 \n", + "Bhutan 48 48 59 59 59 59 \n", + "Bolivia 12728 13358 13643 13949 14644 15281 \n", + "Bosnia and Herzegovina 2606 2606 2606 2704 2728 2775 \n", + "Brazil 645771 672846 691758 707412 739503 772416 \n", + "Brunei 141 141 141 141 141 141 \n", + "... ... ... ... ... ... ... \n", + "Timor-Leste 24 24 24 24 24 24 \n", + "Belize 19 19 19 19 20 20 \n", + "Laos 19 19 19 19 19 19 \n", + "Libya 239 256 256 332 359 378 \n", + "West Bank and Gaza 464 464 472 473 481 485 \n", + "Guinea-Bissau 1368 1368 1368 1389 1389 1389 \n", + "Mali 1485 1523 1533 1547 1586 1667 \n", + "Saint Kitts and Nevis 15 15 15 15 15 15 \n", + "Canada 5 5 5 5 5 5 \n", + "Canada 11 11 11 11 11 11 \n", + "Kosovo 1142 1142 1142 1263 1263 1298 \n", + "Burma 236 240 242 244 246 248 \n", + "United Kingdom 3 3 3 3 3 3 \n", + "United Kingdom 8 8 8 8 8 8 \n", + "United Kingdom 12 12 12 12 12 12 \n", + "MS Zaandam 9 9 9 9 9 9 \n", + "Botswana 40 40 40 42 42 48 \n", + "Burundi 63 83 83 83 83 83 \n", + "Sierra Leone 929 946 969 1001 1025 1062 \n", + "Netherlands 7 7 7 7 7 7 \n", + "Malawi 409 409 438 443 455 455 \n", + "United Kingdom 13 13 13 13 13 13 \n", + "France 1 1 1 1 1 1 \n", + "South Sudan 994 994 1317 1604 1604 1604 \n", + "Western Sahara 9 9 9 9 9 9 \n", + "Sao Tome and Principe 499 499 513 513 514 611 \n", + "Yemen 469 482 484 496 524 560 \n", + "Comoros 132 141 141 141 141 162 \n", + "Tajikistan 4370 4453 4529 4609 4690 4763 \n", + "Lesotho 4 4 4 4 4 4 \n", + "\n", + " 6/11/20 6/12/20 \n", + "Country/Region \n", + "Afghanistan 22890 23546 \n", + "Albania 1385 1416 \n", + "Algeria 10589 10698 \n", + "Andorra 852 853 \n", + "Angola 118 130 \n", + "Antigua and Barbuda 26 26 \n", + "Argentina 27373 28764 \n", + "Armenia 14669 15281 \n", + "Australia 108 108 \n", + "Australia 3115 3119 \n", + "Australia 29 29 \n", + "Australia 1064 1065 \n", + "Australia 440 440 \n", + "Australia 228 228 \n", + "Australia 1703 1703 \n", + "Australia 602 602 \n", + "Austria 17034 17064 \n", + "Azerbaijan 8882 9218 \n", + "Bahamas 103 103 \n", + "Bahrain 16667 17269 \n", + "Bangladesh 78052 81523 \n", + "Barbados 96 96 \n", + "Belarus 51816 52520 \n", + "Belgium 59711 59819 \n", + "Benin 305 388 \n", + "Bhutan 62 62 \n", + "Bolivia 16165 16929 \n", + "Bosnia and Herzegovina 2832 2893 \n", + "Brazil 802828 828810 \n", + "Brunei 141 141 \n", + "... ... ... \n", + "Timor-Leste 24 24 \n", + "Belize 20 20 \n", + "Laos 19 19 \n", + "Libya 393 409 \n", + "West Bank and Gaza 487 489 \n", + "Guinea-Bissau 1389 1460 \n", + "Mali 1722 1752 \n", + "Saint Kitts and Nevis 15 15 \n", + "Canada 5 5 \n", + "Canada 11 11 \n", + "Kosovo 1326 1326 \n", + "Burma 260 261 \n", + "United Kingdom 3 3 \n", + "United Kingdom 8 8 \n", + "United Kingdom 12 12 \n", + "MS Zaandam 9 9 \n", + "Botswana 48 48 \n", + "Burundi 85 85 \n", + "Sierra Leone 1085 1103 \n", + "Netherlands 7 7 \n", + "Malawi 481 481 \n", + "United Kingdom 13 13 \n", + "France 1 1 \n", + "South Sudan 1670 1670 \n", + "Western Sahara 9 9 \n", + "Sao Tome and Principe 632 639 \n", + "Yemen 591 632 \n", + "Comoros 162 163 \n", + "Tajikistan 4834 4902 \n", + "Lesotho 4 4 \n", + "\n", + "[266 rows x 146 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "importation du datafram" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "outputs": [], + "source": [ + "y=y.drop(columns=['Lat','Long'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "suppression des colonnes 'Lat' et 'Long'" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "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", + " \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/State1/22/201/23/201/24/201/25/201/26/201/27/201/28/201/29/201/30/20...6/3/206/4/206/5/206/6/206/7/206/8/206/9/206/10/206/11/206/12/20
Country/Region
AfghanistanNaN000000000...17267180541896919551203422091721459221422289023546
AlbaniaNaN000000000...1184119712121232124612631299134113851416
AlgeriaNaN000000000...97339831993510050101541026510382104841058910698
AndorraNaN000000000...851852852852852852852852852853
AngolaNaN000000000...86868688919296113118130
Antigua and BarbudaNaN000000000...26262626262626262626
ArgentinaNaN000000000...19268201972103722020227942362024761259872737328764
ArmeniaNaN000000000...10524112211181712364131301332513675141031466915281
AustraliaAustralian Capital Territory000000000...107107107108108108108108108108
AustraliaNew South Wales000034444...3106311031103109311231143117311731153119
AustraliaNorthern Territory000000000...29292929292929292929
AustraliaQueensland000000013...1060106010611061106210621062106310641065
AustraliaSouth Australia000000000...440440440440440440440440440440
AustraliaTasmania000000000...228228228228228228228228228228
AustraliaVictoria000011112...1678168116811685168716871691169917031703
AustraliaWestern Australia000000000...592592596599599599599601602602
AustriaNaN000000000...16771168051684316898169021696816979170051703417064
AzerbaijanNaN000000000...6260652268607239755378768191853088829218
BahamasNaN000000000...102102102103103103103103103103
BahrainNaN000000000...12815132961383514383147631541715731162001666717269
BangladeshNaN000000000...55140575636039163026657696850471675748657805281523
BarbadosNaN000000000...92929292929292969696
BelarusNaN000000000...45116459814686847751486304945350265510665181652520
BelgiumNaN000000000...58685587675890759072592265934859437595695971159819
BeninNaN000000000...244261261261261288305305305388
BhutanNaN000000000...47474848595959596262
BoliviaNaN000000000...11638122451272813358136431394914644152811616516929
Bosnia and HerzegovinaNaN000000000...2551259426062606260627042728277528322893
BrazilNaN000000000...584016614941645771672846691758707412739503772416802828828810
BruneiNaN000000000...141141141141141141141141141141
..................................................................
Timor-LesteNaN000000000...24242424242424242424
BelizeNaN000000000...18181919191920202020
LaosNaN000000000...19191919191919191919
LibyaNaN000000000...196209239256256332359378393409
West Bank and GazaNaN000000000...457464464464472473481485487489
Guinea-BissauNaN000000000...1339133913681368136813891389138913891460
MaliNaN000000000...1386146114851523153315471586166717221752
Saint Kitts and NevisNaN000000000...15151515151515151515
CanadaNorthwest Territories000000000...5555555555
CanadaYukon000000000...11111111111111111111
KosovoNaN000000000...1142114211421142114212631263129813261326
BurmaNaN000000000...233236236240242244246248260261
United KingdomAnguilla000000000...3333333333
United KingdomBritish Virgin Islands000000000...8888888888
United KingdomTurks and Caicos Islands000000000...12121212121212121212
MS ZaandamNaN000000000...9999999999
BotswanaNaN000000000...40404040404242484848
BurundiNaN000000000...63636383838383838585
Sierra LeoneNaN000000000...90991492994696910011025106210851103
NetherlandsBonaire, Sint Eustatius and Saba000000000...7777777777
MalawiNaN000000000...369393409409438443455455481481
United KingdomFalkland Islands (Malvinas)000000000...13131313131313131313
FranceSaint Pierre and Miquelon000000000...1111111111
South SudanNaN000000000...994994994994131716041604160416701670
Western SaharaNaN000000000...9999999999
Sao Tome and PrincipeNaN000000000...484485499499513513514611632639
YemenNaN000000000...419453469482484496524560591632
ComorosNaN000000000...132132132141141141141162162163
TajikistanNaN000000000...4191428943704453452946094690476348344902
LesothoNaN000000000...4444444444
\n", + "

266 rows × 144 columns

\n", + "
" + ], + "text/plain": [ + " Province/State 1/22/20 1/23/20 \\\n", + "Country/Region \n", + "Afghanistan NaN 0 0 \n", + "Albania NaN 0 0 \n", + "Algeria NaN 0 0 \n", + "Andorra NaN 0 0 \n", + "Angola NaN 0 0 \n", + "Antigua and Barbuda NaN 0 0 \n", + "Argentina NaN 0 0 \n", + "Armenia NaN 0 0 \n", + "Australia Australian Capital Territory 0 0 \n", + "Australia New South Wales 0 0 \n", + "Australia Northern Territory 0 0 \n", + "Australia Queensland 0 0 \n", + "Australia South Australia 0 0 \n", + "Australia Tasmania 0 0 \n", + "Australia Victoria 0 0 \n", + "Australia Western Australia 0 0 \n", + "Austria NaN 0 0 \n", + "Azerbaijan NaN 0 0 \n", + "Bahamas NaN 0 0 \n", + "Bahrain NaN 0 0 \n", + "Bangladesh NaN 0 0 \n", + "Barbados NaN 0 0 \n", + "Belarus NaN 0 0 \n", + "Belgium NaN 0 0 \n", + "Benin NaN 0 0 \n", + "Bhutan NaN 0 0 \n", + "Bolivia NaN 0 0 \n", + "Bosnia and Herzegovina NaN 0 0 \n", + "Brazil NaN 0 0 \n", + "Brunei NaN 0 0 \n", + "... ... ... ... \n", + "Timor-Leste NaN 0 0 \n", + "Belize NaN 0 0 \n", + "Laos NaN 0 0 \n", + "Libya NaN 0 0 \n", + "West Bank and Gaza NaN 0 0 \n", + "Guinea-Bissau NaN 0 0 \n", + "Mali NaN 0 0 \n", + "Saint Kitts and Nevis NaN 0 0 \n", + "Canada Northwest Territories 0 0 \n", + "Canada Yukon 0 0 \n", + "Kosovo NaN 0 0 \n", + "Burma NaN 0 0 \n", + "United Kingdom Anguilla 0 0 \n", + "United Kingdom British Virgin Islands 0 0 \n", + "United Kingdom Turks and Caicos Islands 0 0 \n", + "MS Zaandam NaN 0 0 \n", + "Botswana NaN 0 0 \n", + "Burundi NaN 0 0 \n", + "Sierra Leone NaN 0 0 \n", + "Netherlands Bonaire, Sint Eustatius and Saba 0 0 \n", + "Malawi NaN 0 0 \n", + "United Kingdom Falkland Islands (Malvinas) 0 0 \n", + "France Saint Pierre and Miquelon 0 0 \n", + "South Sudan NaN 0 0 \n", + "Western Sahara NaN 0 0 \n", + "Sao Tome and Principe NaN 0 0 \n", + "Yemen NaN 0 0 \n", + "Comoros NaN 0 0 \n", + "Tajikistan NaN 0 0 \n", + "Lesotho NaN 0 0 \n", + "\n", + " 1/24/20 1/25/20 1/26/20 1/27/20 1/28/20 1/29/20 \\\n", + "Country/Region \n", + "Afghanistan 0 0 0 0 0 0 \n", + "Albania 0 0 0 0 0 0 \n", + "Algeria 0 0 0 0 0 0 \n", + "Andorra 0 0 0 0 0 0 \n", + "Angola 0 0 0 0 0 0 \n", + "Antigua and Barbuda 0 0 0 0 0 0 \n", + "Argentina 0 0 0 0 0 0 \n", + "Armenia 0 0 0 0 0 0 \n", + "Australia 0 0 0 0 0 0 \n", + "Australia 0 0 3 4 4 4 \n", + "Australia 0 0 0 0 0 0 \n", + "Australia 0 0 0 0 0 1 \n", + "Australia 0 0 0 0 0 0 \n", + "Australia 0 0 0 0 0 0 \n", + "Australia 0 0 1 1 1 1 \n", + "Australia 0 0 0 0 0 0 \n", + "Austria 0 0 0 0 0 0 \n", + "Azerbaijan 0 0 0 0 0 0 \n", + "Bahamas 0 0 0 0 0 0 \n", + "Bahrain 0 0 0 0 0 0 \n", + "Bangladesh 0 0 0 0 0 0 \n", + "Barbados 0 0 0 0 0 0 \n", + "Belarus 0 0 0 0 0 0 \n", + "Belgium 0 0 0 0 0 0 \n", + "Benin 0 0 0 0 0 0 \n", + "Bhutan 0 0 0 0 0 0 \n", + "Bolivia 0 0 0 0 0 0 \n", + "Bosnia and Herzegovina 0 0 0 0 0 0 \n", + "Brazil 0 0 0 0 0 0 \n", + "Brunei 0 0 0 0 0 0 \n", + "... ... ... ... ... ... ... \n", + "Timor-Leste 0 0 0 0 0 0 \n", + "Belize 0 0 0 0 0 0 \n", + "Laos 0 0 0 0 0 0 \n", + "Libya 0 0 0 0 0 0 \n", + "West Bank and Gaza 0 0 0 0 0 0 \n", + "Guinea-Bissau 0 0 0 0 0 0 \n", + "Mali 0 0 0 0 0 0 \n", + "Saint Kitts and Nevis 0 0 0 0 0 0 \n", + "Canada 0 0 0 0 0 0 \n", + "Canada 0 0 0 0 0 0 \n", + "Kosovo 0 0 0 0 0 0 \n", + "Burma 0 0 0 0 0 0 \n", + "United Kingdom 0 0 0 0 0 0 \n", + "United Kingdom 0 0 0 0 0 0 \n", + "United Kingdom 0 0 0 0 0 0 \n", + "MS Zaandam 0 0 0 0 0 0 \n", + "Botswana 0 0 0 0 0 0 \n", + "Burundi 0 0 0 0 0 0 \n", + "Sierra Leone 0 0 0 0 0 0 \n", + "Netherlands 0 0 0 0 0 0 \n", + "Malawi 0 0 0 0 0 0 \n", + "United Kingdom 0 0 0 0 0 0 \n", + "France 0 0 0 0 0 0 \n", + "South Sudan 0 0 0 0 0 0 \n", + "Western Sahara 0 0 0 0 0 0 \n", + "Sao Tome and Principe 0 0 0 0 0 0 \n", + "Yemen 0 0 0 0 0 0 \n", + "Comoros 0 0 0 0 0 0 \n", + "Tajikistan 0 0 0 0 0 0 \n", + "Lesotho 0 0 0 0 0 0 \n", + "\n", + " 1/30/20 ... 6/3/20 6/4/20 6/5/20 6/6/20 \\\n", + "Country/Region ... \n", + "Afghanistan 0 ... 17267 18054 18969 19551 \n", + "Albania 0 ... 1184 1197 1212 1232 \n", + "Algeria 0 ... 9733 9831 9935 10050 \n", + "Andorra 0 ... 851 852 852 852 \n", + "Angola 0 ... 86 86 86 88 \n", + "Antigua and Barbuda 0 ... 26 26 26 26 \n", + "Argentina 0 ... 19268 20197 21037 22020 \n", + "Armenia 0 ... 10524 11221 11817 12364 \n", + "Australia 0 ... 107 107 107 108 \n", + "Australia 4 ... 3106 3110 3110 3109 \n", + "Australia 0 ... 29 29 29 29 \n", + "Australia 3 ... 1060 1060 1061 1061 \n", + "Australia 0 ... 440 440 440 440 \n", + "Australia 0 ... 228 228 228 228 \n", + "Australia 2 ... 1678 1681 1681 1685 \n", + "Australia 0 ... 592 592 596 599 \n", + "Austria 0 ... 16771 16805 16843 16898 \n", + "Azerbaijan 0 ... 6260 6522 6860 7239 \n", + "Bahamas 0 ... 102 102 102 103 \n", + "Bahrain 0 ... 12815 13296 13835 14383 \n", + "Bangladesh 0 ... 55140 57563 60391 63026 \n", + "Barbados 0 ... 92 92 92 92 \n", + "Belarus 0 ... 45116 45981 46868 47751 \n", + "Belgium 0 ... 58685 58767 58907 59072 \n", + "Benin 0 ... 244 261 261 261 \n", + "Bhutan 0 ... 47 47 48 48 \n", + "Bolivia 0 ... 11638 12245 12728 13358 \n", + "Bosnia and Herzegovina 0 ... 2551 2594 2606 2606 \n", + "Brazil 0 ... 584016 614941 645771 672846 \n", + "Brunei 0 ... 141 141 141 141 \n", + "... ... ... ... ... ... ... \n", + "Timor-Leste 0 ... 24 24 24 24 \n", + "Belize 0 ... 18 18 19 19 \n", + "Laos 0 ... 19 19 19 19 \n", + "Libya 0 ... 196 209 239 256 \n", + "West Bank and Gaza 0 ... 457 464 464 464 \n", + "Guinea-Bissau 0 ... 1339 1339 1368 1368 \n", + "Mali 0 ... 1386 1461 1485 1523 \n", + "Saint Kitts and Nevis 0 ... 15 15 15 15 \n", + "Canada 0 ... 5 5 5 5 \n", + "Canada 0 ... 11 11 11 11 \n", + "Kosovo 0 ... 1142 1142 1142 1142 \n", + "Burma 0 ... 233 236 236 240 \n", + "United Kingdom 0 ... 3 3 3 3 \n", + "United Kingdom 0 ... 8 8 8 8 \n", + "United Kingdom 0 ... 12 12 12 12 \n", + "MS Zaandam 0 ... 9 9 9 9 \n", + "Botswana 0 ... 40 40 40 40 \n", + "Burundi 0 ... 63 63 63 83 \n", + "Sierra Leone 0 ... 909 914 929 946 \n", + "Netherlands 0 ... 7 7 7 7 \n", + "Malawi 0 ... 369 393 409 409 \n", + "United Kingdom 0 ... 13 13 13 13 \n", + "France 0 ... 1 1 1 1 \n", + "South Sudan 0 ... 994 994 994 994 \n", + "Western Sahara 0 ... 9 9 9 9 \n", + "Sao Tome and Principe 0 ... 484 485 499 499 \n", + "Yemen 0 ... 419 453 469 482 \n", + "Comoros 0 ... 132 132 132 141 \n", + "Tajikistan 0 ... 4191 4289 4370 4453 \n", + "Lesotho 0 ... 4 4 4 4 \n", + "\n", + " 6/7/20 6/8/20 6/9/20 6/10/20 6/11/20 6/12/20 \n", + "Country/Region \n", + "Afghanistan 20342 20917 21459 22142 22890 23546 \n", + "Albania 1246 1263 1299 1341 1385 1416 \n", + "Algeria 10154 10265 10382 10484 10589 10698 \n", + "Andorra 852 852 852 852 852 853 \n", + "Angola 91 92 96 113 118 130 \n", + "Antigua and Barbuda 26 26 26 26 26 26 \n", + "Argentina 22794 23620 24761 25987 27373 28764 \n", + "Armenia 13130 13325 13675 14103 14669 15281 \n", + "Australia 108 108 108 108 108 108 \n", + "Australia 3112 3114 3117 3117 3115 3119 \n", + "Australia 29 29 29 29 29 29 \n", + "Australia 1062 1062 1062 1063 1064 1065 \n", + "Australia 440 440 440 440 440 440 \n", + "Australia 228 228 228 228 228 228 \n", + "Australia 1687 1687 1691 1699 1703 1703 \n", + "Australia 599 599 599 601 602 602 \n", + "Austria 16902 16968 16979 17005 17034 17064 \n", + "Azerbaijan 7553 7876 8191 8530 8882 9218 \n", + "Bahamas 103 103 103 103 103 103 \n", + "Bahrain 14763 15417 15731 16200 16667 17269 \n", + "Bangladesh 65769 68504 71675 74865 78052 81523 \n", + "Barbados 92 92 92 96 96 96 \n", + "Belarus 48630 49453 50265 51066 51816 52520 \n", + "Belgium 59226 59348 59437 59569 59711 59819 \n", + "Benin 261 288 305 305 305 388 \n", + "Bhutan 59 59 59 59 62 62 \n", + "Bolivia 13643 13949 14644 15281 16165 16929 \n", + "Bosnia and Herzegovina 2606 2704 2728 2775 2832 2893 \n", + "Brazil 691758 707412 739503 772416 802828 828810 \n", + "Brunei 141 141 141 141 141 141 \n", + "... ... ... ... ... ... ... \n", + "Timor-Leste 24 24 24 24 24 24 \n", + "Belize 19 19 20 20 20 20 \n", + "Laos 19 19 19 19 19 19 \n", + "Libya 256 332 359 378 393 409 \n", + "West Bank and Gaza 472 473 481 485 487 489 \n", + "Guinea-Bissau 1368 1389 1389 1389 1389 1460 \n", + "Mali 1533 1547 1586 1667 1722 1752 \n", + "Saint Kitts and Nevis 15 15 15 15 15 15 \n", + "Canada 5 5 5 5 5 5 \n", + "Canada 11 11 11 11 11 11 \n", + "Kosovo 1142 1263 1263 1298 1326 1326 \n", + "Burma 242 244 246 248 260 261 \n", + "United Kingdom 3 3 3 3 3 3 \n", + "United Kingdom 8 8 8 8 8 8 \n", + "United Kingdom 12 12 12 12 12 12 \n", + "MS Zaandam 9 9 9 9 9 9 \n", + "Botswana 40 42 42 48 48 48 \n", + "Burundi 83 83 83 83 85 85 \n", + "Sierra Leone 969 1001 1025 1062 1085 1103 \n", + "Netherlands 7 7 7 7 7 7 \n", + "Malawi 438 443 455 455 481 481 \n", + "United Kingdom 13 13 13 13 13 13 \n", + "France 1 1 1 1 1 1 \n", + "South Sudan 1317 1604 1604 1604 1670 1670 \n", + "Western Sahara 9 9 9 9 9 9 \n", + "Sao Tome and Principe 513 513 514 611 632 639 \n", + "Yemen 484 496 524 560 591 632 \n", + "Comoros 141 141 141 162 162 163 \n", + "Tajikistan 4529 4609 4690 4763 4834 4902 \n", + "Lesotho 4 4 4 4 4 4 \n", + "\n", + "[266 rows x 144 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "outputs": [], + "source": [ + "Belgique=y.loc[['Belgium'],:]\n", + "Chine=y.loc[['China'],:]\n", + "France=y.loc[['France'],:]\n", + "Allemagne=y.loc[['Germany'],:]\n", + "Iran=y.loc[['Iran'],:]\n", + "Italie=y.loc[['Italy'],:]\n", + "Japon=y.loc[['Japan'],:]\n", + "Hollande_et_colonies=y.loc[['Netherlands'],:]\n", + "Portugal=y.loc[['Portugal'],:]\n", + "Espagne=y.loc[['Spain'],:]\n", + "RoyaumeUni_et_colonies=y.loc[['United Kingdom'],:]\n", + "CoréeduSud=y.loc[['Korea, South'],:]\n", + "EtatsUnis=y.loc[['US'],:]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "récupération des régions d'intérêt sauf pour Hong Kong" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "outputs": [], + "source": [ + "France_metropolitaine=France[France.isnull().any(axis=1)]\n", + "RoyaumeUnis=RoyaumeUni_et_colonies[RoyaumeUni_et_colonies.isnull().any(axis=1)]\n", + "Hollande=Hollande_et_colonies[Hollande_et_colonies.isnull().any(axis=1)]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "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", + "
Province/State1/22/201/23/201/24/201/25/201/26/201/27/201/28/201/29/201/30/20...6/3/206/4/206/5/206/6/206/7/206/8/206/9/206/10/206/11/206/12/20
Country/Region
FranceNaN002333455...188836185986186538187067187360187458187599187996188354188918
\n", + "

1 rows × 144 columns

\n", + "
" + ], + "text/plain": [ + " Province/State 1/22/20 1/23/20 1/24/20 1/25/20 1/26/20 \\\n", + "Country/Region \n", + "France NaN 0 0 2 3 3 \n", + "\n", + " 1/27/20 1/28/20 1/29/20 1/30/20 ... 6/3/20 6/4/20 \\\n", + "Country/Region ... \n", + "France 3 4 5 5 ... 188836 185986 \n", + "\n", + " 6/5/20 6/6/20 6/7/20 6/8/20 6/9/20 6/10/20 6/11/20 \\\n", + "Country/Region \n", + "France 186538 187067 187360 187458 187599 187996 188354 \n", + "\n", + " 6/12/20 \n", + "Country/Region \n", + "France 188918 \n", + "\n", + "[1 rows x 144 columns]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "France_metropolitaine" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "HongKong=Chine.iloc[[12],:]\n", + "Chine=Chine.drop(index='Hong Kong')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "suppression des colonies et isolation de Hong Kong de la Chine" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "outputs": [], + "source": [ + "Belgique=Belgique.drop(columns=['Province/State'])\n", + "Chine=Chine.drop(columns=['Province/State'])\n", + "France_metropolitaine=France_metropolitaine.drop(columns=['Province/State'])\n", + "Allemagne=Allemagne.drop(columns=['Province/State'])\n", + "Iran=Iran.drop(columns=['Province/State'])\n", + "Italie=Italie.drop(columns=['Province/State'])\n", + "Japon=Japon.drop(columns=['Province/State'])\n", + "Hollande=Hollande.drop(columns=['Province/State'])\n", + "Portugal=Portugal.drop(columns=['Province/State'])\n", + "Espagne=Espagne.drop(columns=['Province/State'])\n", + "RoyaumeUnis=RoyaumeUnis.drop(columns=['Province/State'])\n", + "CoréeduSud=CoréeduSud.drop(columns=['Province/State'])\n", + "EtatsUnis=EtatsUnis.drop(columns=['Province/State'])\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "source": [ + "Suppression des colonnes province/etat sauf pour Hong Kong" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "outputs": [], + "source": [ + "SommeChine=Chine.sum()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1/22/20 548\n", + "1/23/20 643\n", + "1/24/20 920\n", + "1/25/20 1406\n", + "1/26/20 2075\n", + "1/27/20 2877\n", + "1/28/20 5509\n", + "1/29/20 6087\n", + "1/30/20 8141\n", + "1/31/20 9802\n", + "2/1/20 11891\n", + "2/2/20 16630\n", + "2/3/20 19716\n", + "2/4/20 23707\n", + "2/5/20 27440\n", + "2/6/20 30587\n", + "2/7/20 34110\n", + "2/8/20 36814\n", + "2/9/20 39829\n", + "2/10/20 42354\n", + "2/11/20 44386\n", + "2/12/20 44759\n", + "2/13/20 59895\n", + "2/14/20 66358\n", + "2/15/20 68413\n", + "2/16/20 70513\n", + "2/17/20 72434\n", + "2/18/20 74211\n", + "2/19/20 74619\n", + "2/20/20 75077\n", + " ... \n", + "5/14/20 84029\n", + "5/15/20 84038\n", + "5/16/20 84044\n", + "5/17/20 84054\n", + "5/18/20 84063\n", + "5/19/20 84063\n", + "5/20/20 84063\n", + "5/21/20 84063\n", + "5/22/20 84081\n", + "5/23/20 84084\n", + "5/24/20 84095\n", + "5/25/20 84102\n", + "5/26/20 84103\n", + "5/27/20 84106\n", + "5/28/20 84106\n", + "5/29/20 84123\n", + "5/30/20 84128\n", + "5/31/20 84146\n", + "6/1/20 84154\n", + "6/2/20 84161\n", + "6/3/20 84160\n", + "6/4/20 84171\n", + "6/5/20 84177\n", + "6/6/20 84186\n", + "6/7/20 84191\n", + "6/8/20 84195\n", + "6/9/20 84198\n", + "6/10/20 84209\n", + "6/11/20 84216\n", + "6/12/20 84228\n", + "Length: 143, dtype: int64\n" + ] + } + ], + "source": [ + "print(SommeChine)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "outputs": [], + "source": [ + "HongKong=HongKong.drop(columns='Province/State')" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "'str' object is not callable", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\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[0mHongKong\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrename\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Conutry/Region'\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/util/_decorators.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 125\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0mwraps\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 126\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 127\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 128\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 129\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mPY2\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;36mrename\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 3025\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'axis'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3026\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'mapper'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3027\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrename\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3028\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3029\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0mAppender\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_shared_docs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'fillna'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0m_shared_doc_kwargs\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;36mrename\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 882\u001b[0m \u001b[0mlevel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_level_number\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 883\u001b[0m result._data = result._data.rename_axis(f, axis=baxis, copy=copy,\n\u001b[0;32m--> 884\u001b[0;31m level=level)\n\u001b[0m\u001b[1;32m 885\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_clear_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 886\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;36mrename_axis\u001b[0;34m(self, mapper, axis, copy, level)\u001b[0m\n\u001b[1;32m 3089\u001b[0m \"\"\"\n\u001b[1;32m 3090\u001b[0m \u001b[0mobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdeep\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3091\u001b[0;31m \u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_transform_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmapper\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\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 3092\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3093\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;36m_transform_index\u001b[0;34m(index, func, level)\u001b[0m\n\u001b[1;32m 5078\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mMultiIndex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_tuples\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnames\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnames\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5079\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5080\u001b[0;31m \u001b[0mitems\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5081\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mIndex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5082\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;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 5078\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mMultiIndex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_tuples\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnames\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnames\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5079\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5080\u001b[0;31m \u001b[0mitems\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5081\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mIndex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5082\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mTypeError\u001b[0m: 'str' object is not callable" + ] + } + ], + "source": [ + "HongKong.rename('Conutry/Region')" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "outputs": [], + "source": [ + "Belgique=Belgique.T\n", + "France=France_metropolitaine.T\n", + "Allemagne=Allemagne.T\n", + "Iran=Iran.T\n", + "Italie=Italie.T\n", + "Japon=Japon.T\n", + "Hollande=Hollande.T\n", + "Portugal=Portugal.T\n", + "Espagne=Espagne.T\n", + "RoyaumeUnis=RoyaumeUnis.T\n", + "CoreeduSud=CoréeduSud.T\n", + "EtatsUnis=EtatsUnis.T\n", + "HongKong=HongKong.T" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "source": [ + "https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.drop.html#pandas.DataFrame.drop\n", + "https://pandas.pydata.org/pandas-docs/stable/user_guide/visualization.html#other-plots\n", + "https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#indexing-with-list-with-missing-labels-is-deprecated\n", + "https://pandas.pydata.org/pandas-docs/stable/user_guide/index.html#user-guide" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pd.concat([Belgique,France,Allemagne,Iran,Italie,Japon,Hollande,Portugal,Espagne,RoyaumeUnis,CoreeduSud,EtatsUnis,HongKong,SommeChine],axis=1).plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Plotter,\n", + "SommeChine=0\n", + "HongKong=China" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "hideCode": false, + "hidePrompt": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pd.concat([Belgique,France,Allemagne,Iran,Italie,Japon,Hollande,Portugal,Espagne,RoyaumeUnis,CoreeduSud,EtatsUnis,HongKong,SommeChine],axis=1).plot(logy=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "plotter en log,\n", + "SommeChine=0\n", + "HongKong=China" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pd.concat([Belgique,SommeChine],axis=1).plot(logy=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "La suite c est pas encore important" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "df=pd.concat([Belgique],axis=1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "plt.figure();\n", + "\n", + "Belgique.plot(label='dates').set(y_label(\"nombredemalades\"))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure();\n", + "\n", + "Belgique.plot(style='k--', label='Series');" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "a=pd.concat([Belgique,France,Allemagne,Iran,Italie,Japon,Hollande,Portugal,Espagne,RoyaumeUnis,CoreeduSud,EtatsUnis],axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "a.plot().set_xlabel('dates')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "axes = pyplot.gca()\n", + "axes.set_xlabel('axe des x')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv(\"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv\",index_col=1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df=df.drop(columns=['Lat','Long'])\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "Belgique1=df.loc[['Belgium'],:]\n", + "Chine1=df.loc[['China'],:]\n", + "France1=df.loc[['France'],:]\n", + "Allemagne1=df.loc[['Germany'],:]\n", + "Iran1=df.loc[['Iran'],:]\n", + "Italie1=df.loc[['Italy'],:]\n", + "Japon1=df.loc[['Japan'],:]\n", + "Hollande_et_colonies1=df.loc[['Netherlands'],:]\n", + "Portugal1=df.loc[['Portugal'],:]\n", + "Espagne1=df.loc[['Spain'],:]\n", + "RoyaumeUni_et_colonies1=df.loc[['United Kingdom'],:]\n", + "CoréeduSud1=df.loc[['Korea, South'],:]\n", + "EtatsUnis1=df.loc[['US'],:]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "France1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "France_metropolitaine=France1[France1.isnull().any(axis=1)]\n", + "RoyaumeUnis=RoyaumeUni_et_colonies1[RoyaumeUni_et_colonies1.isnull().any(axis=1)]\n", + "Hollande=Hollande_et_colonies1[Hollande_et_colonies1.isnull().any(axis=1)]\n", + "HongKong1=Chine1.iloc[[12],:]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "France1=France1.T" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "F=France1.groupby(level=0, axis=1).sum()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_code_all_hidden": false, + "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 +} diff --git a/module3/exo3/Untitled.ipynb b/module3/exo3/Untitled.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..7fec51502cbc3200b3d0ffc6bbba1fe85e197f3d --- /dev/null +++ b/module3/exo3/Untitled.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/module3/exo3/exercice_fr.ipynb b/module3/exo3/exercice_fr.ipynb deleted file mode 100644 index 0bbbe371b01e359e381e43239412d77bf53fb1fb..0000000000000000000000000000000000000000 --- a/module3/exo3/exercice_fr.ipynb +++ /dev/null @@ -1,25 +0,0 @@ -{ - "cells": [], - "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": "3.6.3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} -