594 lines
91 KiB
Plaintext
594 lines
91 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"from opytex import texenv\n",
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"%matplotlib inline\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"plt.style.use(\"seaborn-notebook\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import pymath as pm"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Création de graphiques pour les 5e"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Visite de villages"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 89,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[48, 15, 36, 43, 25]"
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]
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},
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"execution_count": 89,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"ds = pm.Dataset.random(5, distrib=\"randint\", rd_args=(10, 50))\n",
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"ds"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 90,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"villes = [\"Chiconi\", \"Sada\", \"Kaweni\", \"Dzaoudzi\", \"Bandrele\"]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 91,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"ind = np.arange(5)\n",
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"width = 0.5"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 92,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# Set the font dictionaries (for plot title and axis titles)\n",
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"title_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'20', 'color':'black', 'weight':'normal',\n",
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" 'verticalalignment':'bottom'} # Bottom vertical alignment for more space\n",
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"axis_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'16', 'color':'black', 'weight':'normal'}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 93,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAAFyCAYAAACKkcLXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkHSHpN9n42dI+ls27fb
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"text/plain": [
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"<matplotlib.figure.Figure at 0x7fca864db9b0>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"fig, ax = plt.subplots()\n",
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"bar = ax.bar(ind, ds, width) \n",
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"\n",
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"ax.set_title('Visites des 5e', **title_font)\n",
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"\n",
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"ax.set_ylabel('Nombre de visiteurs', **axis_font)\n",
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"ax.set_yticks(np.arange(0, 61, 5))\n",
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"ax.set_xticks(ind + width/2)\n",
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"ax.set_xticklabels(villes, **axis_font)\n",
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"\n",
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"ax.yaxis.grid(True)\n",
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"\n",
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"ax.spines['right'].set_visible(False)\n",
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"ax.spines['top'].set_visible(False)\n",
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"\n",
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"ax.yaxis.set_ticks_position('left')\n",
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"ax.xaxis.set_ticks_position('bottom')\n",
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"\n",
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"\n",
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"fig.savefig(\"./graph1.pdf\")\n"
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]
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},
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{
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"cell_type": "markdown",
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|
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"metadata": {
|
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"collapsed": true
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},
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"source": [
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"## Sortie en mer"
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]
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},
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{
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"cell_type": "code",
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|
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"execution_count": 94,
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"metadata": {
|
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"collapsed": false
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},
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|
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"outputs": [
|
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|
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{
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"data": {
|
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"text/plain": [
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|
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"[6, 17, 15, 26, 12]"
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]
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},
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|
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"execution_count": 94,
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"metadata": {},
|
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|
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"output_type": "execute_result"
|
||
|
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}
|
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|
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],
|
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|
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"source": [
|
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|
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"ds = pm.Dataset.random(5, distrib=\"randint\", rd_args=(5, 30))\n",
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"ds"
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]
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},
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{
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"cell_type": "code",
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|
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"execution_count": 117,
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|
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"metadata": {
|
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|
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"collapsed": true
|
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|
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},
|
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|
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"outputs": [],
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||
|
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"source": [
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"obs = [\"Boutielles\", \"Poisson \\n Clown\", \"Poisson \\n Soldat\", \"Corail \\n Branche\", \"Corail \\n Mou\"]"
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]
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},
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|
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{
|
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|
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"cell_type": "code",
|
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|
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"execution_count": 109,
|
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|
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"metadata": {
|
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|
|
"collapsed": true
|
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|
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},
|
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|
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"outputs": [],
|
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|
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"source": [
|
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|
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"ind = np.arange(5)\n",
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"width = 0.7"
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]
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},
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|
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{
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|
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"cell_type": "code",
|
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|
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"execution_count": 118,
|
||
|
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"metadata": {
|
||
|
|
"collapsed": true
|
||
|
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},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"# Set the font dictionaries (for plot title and axis titles)\n",
|
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|
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"title_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'20', 'color':'black', 'weight':'normal',\n",
|
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|
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" 'verticalalignment':'bottom'} # Bottom vertical alignment for more space\n",
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|
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"axis_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'14', 'color':'black', 'weight':'normal'}"
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|
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]
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|
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},
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{
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"cell_type": "code",
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||
|
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"execution_count": 119,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": false
|
||
|
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},
|
||
|
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"outputs": [
|
||
|
|
{
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||
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"data": {
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|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAfQAAAEtCAYAAAD+55JtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nmZlZF3CHbmZm1gXcoZu
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.figure.Figure at 0x7fca8681f518>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"fig, ax = plt.subplots(figsize = (8,4))\n",
|
||
|
|
"ax.bar(ind, ds, width, color=\"lightgray\")\n",
|
||
|
|
"\n",
|
||
|
|
"ax.set_title('Observations en mer', **title_font)\n",
|
||
|
|
"\n",
|
||
|
|
"ax.set_ylabel('Quantité', **axis_font)\n",
|
||
|
|
"ax.set_yticks(np.arange(0, 31, 2))\n",
|
||
|
|
"ax.set_xticks(ind + width/2)\n",
|
||
|
|
"ax.set_xlim(0, 4.8)\n",
|
||
|
|
"ax.set_xticklabels(obs, **axis_font)\n",
|
||
|
|
"\n",
|
||
|
|
"ax.yaxis.grid(True)\n",
|
||
|
|
"\n",
|
||
|
|
"ax.spines['right'].set_visible(False)\n",
|
||
|
|
"ax.spines['top'].set_visible(False)\n",
|
||
|
|
"\n",
|
||
|
|
"ax.yaxis.set_ticks_position('left')\n",
|
||
|
|
"ax.xaxis.set_ticks_position('bottom')\n",
|
||
|
|
"\n",
|
||
|
|
"\n",
|
||
|
|
"#fig.savefig(\"./fig/graph_poisson.pdf\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": true
|
||
|
|
},
|
||
|
|
"source": [
|
||
|
|
"## Olympiades de math"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 80,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": false
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"[9, 19, 10, 9, 10, 13, 6]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 80,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ds = pm.Dataset.random(7, distrib=\"randint\", rd_args=(2, 30))\n",
|
||
|
|
"ds"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 116,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": false
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"[9, 19, 9, 10, 10, 13, 6]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 116,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ds = pm.Dataset([9, 19, 9, 10, 10, 13, 6])\n",
|
||
|
|
"ds"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 117,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": true
|
||
|
|
},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"villes = [\"Sada\", \"Majicavo\", \"Chiconi\", \"Kaweni1\", \"Bandrélé\", \"Bouéni\", \"Pamandzi\"]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 118,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": false
|
||
|
|
},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"ind = np.arange(7)\n",
|
||
|
|
"width = 0.7"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 119,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": true
|
||
|
|
},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"# Set the font dictionaries (for plot title and axis titles)\n",
|
||
|
|
"title_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'20', 'color':'black', 'weight':'normal',\n",
|
||
|
|
" 'verticalalignment':'bottom'} # Bottom vertical alignment for more space\n",
|
||
|
|
"axis_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'14', 'color':'black', 'weight':'normal'}"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 120,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": false
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAfgAAAEcCAYAAAAr/abrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nHI+ZdU/Q3mOvrUsmvJN
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.figure.Figure at 0x7fd89a852470>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"fig, ax = plt.subplots(figsize = (8,4))\n",
|
||
|
|
"ax.bar(ind, ds, width, color=\"lightgray\")\n",
|
||
|
|
"\n",
|
||
|
|
"ax.set_title('Olympiades de Mathématiques', **title_font)\n",
|
||
|
|
"\n",
|
||
|
|
"ax.set_ylabel('Nombre de médailles', **axis_font)\n",
|
||
|
|
"ax.set_yticks(np.arange(0, max(ds)+2, 2))\n",
|
||
|
|
"ax.set_xticks(ind + width/2)\n",
|
||
|
|
"ax.set_xlim(0, 6.8)\n",
|
||
|
|
"ax.set_xticklabels(villes, **axis_font)\n",
|
||
|
|
"\n",
|
||
|
|
"ax.yaxis.grid(True)\n",
|
||
|
|
"\n",
|
||
|
|
"ax.spines['right'].set_visible(False)\n",
|
||
|
|
"ax.spines['top'].set_visible(False)\n",
|
||
|
|
"\n",
|
||
|
|
"ax.yaxis.set_ticks_position('left')\n",
|
||
|
|
"ax.xaxis.set_ticks_position('bottom')\n",
|
||
|
|
"\n",
|
||
|
|
"fig.savefig(\"./fig/graph_medailles.pdf\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 121,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": false
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/html": [
|
||
|
|
"<div>\n",
|
||
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
||
|
|
" <thead>\n",
|
||
|
|
" <tr style=\"text-align: right;\">\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th>Nombre de cadeaux</th>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>Villes</th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" </thead>\n",
|
||
|
|
" <tbody>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>Sada</th>\n",
|
||
|
|
" <td>9</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>Majicavo</th>\n",
|
||
|
|
" <td>19</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>Chiconi</th>\n",
|
||
|
|
" <td>9</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>Kaweni1</th>\n",
|
||
|
|
" <td>10</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>Bandrélé</th>\n",
|
||
|
|
" <td>10</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>Bouéni</th>\n",
|
||
|
|
" <td>13</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>Pamandzi</th>\n",
|
||
|
|
" <td>6</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" </tbody>\n",
|
||
|
|
"</table>\n",
|
||
|
|
"</div>"
|
||
|
|
],
|
||
|
|
"text/plain": [
|
||
|
|
" Nombre de cadeaux\n",
|
||
|
|
"Villes \n",
|
||
|
|
"Sada 9\n",
|
||
|
|
"Majicavo 19\n",
|
||
|
|
"Chiconi 9\n",
|
||
|
|
"Kaweni1 10\n",
|
||
|
|
"Bandrélé 10\n",
|
||
|
|
"Bouéni 13\n",
|
||
|
|
"Pamandzi 6"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 121,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"df = pd.DataFrame(data=list(ds), index=villes,columns=['Nombre de cadeaux'])\n",
|
||
|
|
"df.index.name=\"Villes\"\n",
|
||
|
|
"df"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 122,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": false
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"\\begin{tabular}{lrrrrrrr}\n",
|
||
|
|
"\\toprule\n",
|
||
|
|
"Villes & Sada & Majicavo & Chiconi & Kaweni1 & Bandrélé & Bouéni & Pamandzi \\\\\n",
|
||
|
|
"\\midrule\n",
|
||
|
|
"Nombre de cadeaux & 9 & 19 & 9 & 10 & 10 & 13 & 6 \\\\\n",
|
||
|
|
"\\bottomrule\n",
|
||
|
|
"\\end{tabular}\n",
|
||
|
|
"\n"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"print(df.T.to_latex())"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 123,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": true
|
||
|
|
},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"\n",
|
||
|
|
"title_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'23', 'color':'black', 'weight':'normal',\n",
|
||
|
|
" 'verticalalignment':'bottom'} # Bottom vertical alignment for more space\n",
|
||
|
|
"axis_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'14', 'color':'black', 'weight':'normal'}"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 124,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": false
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
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|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.figure.Figure at 0x7fd89a629940>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ax = df.plot(kind='bar', color='lightgrey', figsize=(12,4), rot=0, fontsize=20)\n",
|
||
|
|
"\n",
|
||
|
|
"ax.set_title('Olympiades de Mathématiques', **title_font)\n",
|
||
|
|
"\n",
|
||
|
|
"ax.set_yticks(np.arange(0, max(ds)+2, 2))\n",
|
||
|
|
"ax.set_xlabel('')\n",
|
||
|
|
"#ax.set_xticks(ind + width/2)\n",
|
||
|
|
"ax.yaxis.grid(True)\n",
|
||
|
|
"\n",
|
||
|
|
"ax.spines['right'].set_visible(False)\n",
|
||
|
|
"ax.spines['top'].set_visible(False)\n",
|
||
|
|
"ax.yaxis.set_ticks_position('left')\n",
|
||
|
|
"ax.xaxis.set_ticks_position('bottom')\n",
|
||
|
|
"\n",
|
||
|
|
"fig = ax.get_figure()\n",
|
||
|
|
"fig.savefig(\"./fig/graph_medailles.pdf\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": true
|
||
|
|
},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": true
|
||
|
|
},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": true
|
||
|
|
},
|
||
|
|
"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": "3.5.1"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 0
|
||
|
|
}
|