defeo/jncf.ipynb

## jncf.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sondage JNCF 2020 – 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "conn = sqlite3.connect('reponses.sqlite3')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from dateutil.parser import parse\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Le nombre de participants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num = conn.execute('SELECT COUNT() FROM poll').fetchone()[0]\n",
    "num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "colnames = list(zip(*conn.execute('SELECT * FROM poll').description))[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dates = list(map(parse, colnames[1:]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Le score (somme du # d'étoiles - *n*)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.rcParams[\"figure.figsize\"] = (10,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "score = conn.execute('SELECT %s FROM poll' % ','.join('SUM(`%s` - 1)' % c for c in colnames[1:])).fetchone()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Container object of 50 artists>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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/KIelx1V11ZbePlRVX6qqX1r3+z8oh6XP0/iPTa/7aFW9a53v+yAN6vEnquorVfWxC8bv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\nGEQQAwAYRBADABhEEAMAGOT/A4GOJoilKchDAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9792848588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(dates, score, 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Les \"je ne viendrai pas\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "star1 = conn.execute('SELECT %s FROM poll' % ','.join('SUM(not (`%s` - 1))' % c for c in colnames[1:])).fetchone()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Container object of 50 artists>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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bWvSZtbOSvL+qjh/rV7v7g1X16iTp7muS3JzkkiT3JvmLJD+y4DkBAJbGQmGtu+9Lcv6c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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f97b44983c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(dates, star1, 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Les \"je viendrais\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "star2 = conn.execute('SELECT %s FROM poll' % ','.join('SUM(not (`%s` - 2))' % c for c in colnames[1:])).fetchone()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Container object of 50 artists>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AFtamz6x19wPd/dFp+ytJPpnkyVu1MAAAtugza1W1nOT7knx4je5nVdXHqupdVfWMkxzj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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f97925f2668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(dates, star2, 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Les \"Parfait!\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "star3 = conn.execute('SELECT %s FROM poll' % ','.join('SUM(not (`%s` - 3))' % c for c in colnames[1:])).fetchone()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Container object of 50 artists>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f97925d4f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(dates, star3, 5)"
   ]
  },
  {
   "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}