Votacoes-clusters.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "np.set_printoptions(precision=5, suppress=True) # suppress scientific float notation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "from itertools import chain, groupby\n",
    "from quiz import models\n",
    "from quiz.utils import MatrizesDeDadosBuilder\n",
    "\n",
    "# Carrega as informações necessárias para construir as matrizes\n",
    "votacoes = models.Votacao.objects.filter(data__range=['2013-01-01', '2016-12-31']).order_by('proposicao')\n",
    "parlamentares = list(set(chain.from_iterable([[voto.parlamentar for voto in votacao.votos()] for votacao in votacoes])))\n",
    "partidos = list(set([parlamentar.partido for parlamentar in parlamentares]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Gera uma matriz de votos por candidato (na ordem de parlamentares)\n",
    "matriz = MatrizesDeDadosBuilder(votacoes, partidos, parlamentares).gera_matrizes()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Processa a matriz via Numpy e rotaciona (transformando em uma matriz de votos por votação)\n",
    "matriz = np.transpose(np.asmatrix(matriz))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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XRzeDdldj/p+nrcx9Llj0tS8vrurL3O8JH608rpWHpdnpVlaTmlD/uUeq7Fuu0PUuqB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\n719qAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc191ccdfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "clusterizations = linkage(matriz, 'centroid')\n",
    "plt.figure(figsize=(25, 10))\n",
    "plt.title('Dendrograma de Clusterizacao Hierarquica')\n",
    "plt.xlabel('indice')\n",
    "plt.ylabel('distancia')\n",
    "dendrogram(clusterizations, leaf_rotation=90, leaf_font_size=8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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JT5ibf0tM3NXH9ff/GzmfQXZ82dN+Pnw5leI7kvyScyey2nb8797JS26Eeztu2fWcYzmW85kun1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\ncCbty8U59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vm9+Sq6Jt8+oxXHze+LfzrlqqWFVjj/Q8pX4v1Evf/ilHz29zMZSDQdlZ/I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\ncDgcDofD4XA4HA6Hw+FwOAz8fxy0uzHy5xWJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc191185b90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "clusterizations = linkage(matriz, 'average')\n",
    "plt.figure(figsize=(25, 10))\n",
    "plt.title('Dendrograma de Clusterizacao Hierarquica')\n",
    "plt.xlabel('indice')\n",
    "plt.ylabel('distancia')\n",
    "dendrogram(clusterizations, leaf_rotation=90, leaf_font_size=8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# copiado sem-vergonha de https://joernhees.de/blog/2015/08/26/scipy-hierarchical-clustering-and-dendrogram-tutorial/\n",
    "def fancy_dendrogram(*args, **kwargs):\n",
    "    max_d = kwargs.pop('max_d', None)\n",
    "    if max_d and 'color_threshold' not in kwargs:\n",
    "        kwargs['color_threshold'] = max_d\n",
    "    annotate_above = kwargs.pop('annotate_above', 0)\n",
    "\n",
    "    ddata = dendrogram(*args, **kwargs)\n",
    "\n",
    "    if not kwargs.get('no_plot', False):\n",
    "        plt.title('Hierarchical Clustering Dendrogram (truncated)')\n",
    "        plt.xlabel('sample index or (cluster size)')\n",
    "        plt.ylabel('distance')\n",
    "        for i, d, c in zip(ddata['icoord'], ddata['dcoord'], ddata['color_list']):\n",
    "            x = 0.5 * sum(i[1:3])\n",
    "            y = d[1]\n",
    "            if y > annotate_above:\n",
    "                plt.plot(x, y, 'o', c=c)\n",
    "                plt.annotate(\"%.3g\" % y, (x, y), xytext=(0, -5),\n",
    "                             textcoords='offset points',\n",
    "                             va='top', ha='center')\n",
    "        if max_d:\n",
    "            plt.axhline(y=max_d, c='k')\n",
    "    return ddata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc190dcd650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "clusterizations = linkage(matriz, 'average')\n",
    "plt.figure(figsize=(25, 10))\n",
    "plt.title('Dendrograma de Clusterizacao Hierarquica')\n",
    "plt.xlabel('indice')\n",
    "plt.ylabel('distancia')\n",
    "fancy_dendrogram(clusterizations, leaf_rotation=90, leaf_font_size=8,\n",
    "           annotate_above=9, max_d=10.3,\n",
    "           truncate_mode='lastp', p=10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# testando o cophenet\n",
    "from scipy.cluster.hierarchy import cophenet\n",
    "from scipy.spatial.distance import pdist\n",
    "\n",
    "c, coph_dists = cophenet(clusterizations, pdist(matriz))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from scipy.cluster.hierarchy import fcluster\n",
    "\n",
    "number_of_clusters = 6\n",
    "cluster_results = fcluster(clusterizations, 6, criterion='maxclust')\n",
    "\n",
    "clusters = [[votacoes[index] for index, cluster_id in enumerate(cluster_results) if cluster_id == n+1]\n",
    "            for n in range(number_of_clusters)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Distingue as votações pela proposição\n",
    "votacoes_groups = groupby(votacoes, lambda v: v.proposicao.id)\n",
    "# len([k for k, g in votacoes_groups if len(list(g)) > 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def get_votacoes(proposicao): \n",
    "    return sorted([votacao for votacao in votacoes if votacao.proposicao.id_prop == proposicao],\n",
    "                  key=lambda votacao: votacao.id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def get_voto_parlamentar(votacao, parlamentar):\n",
    "    votos = {voto.parlamentar.id: voto.opcao for voto in votacao.votos()}\n",
    "    return votos.get(parlamentar.id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{u'ABOU ANNI': [None, u'SIM', None, None, None, None, u'SIM', u'SIM', None],\n",
       " u'ADILSON AMADEU': [u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM'],\n",
       " u'ADOLFO QUINTAS': [u'SIM', None, None, None, None, None, None, None, None],\n",
       " u'ALESSANDRO GUEDES': [None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM'],\n",
       " u'ALFREDINHO': [u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM'],\n",
       " u'ANDREA MATARAZZO': [None, None, None, None, None, None, None, None, None],\n",
       " u'ANIBAL DE FREITAS FILHO': [u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None],\n",
       " u'ANTONIO CARLOS RODRIGUES': [None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None],\n",
       " u'ANTONIO DONATO': [u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None],\n",
       " u'ARI FRIEDENBACH': [u'SIM', None, None, None, None, None, None, None, None],\n",
       " u'ARSELINO TATTO': [u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  None,\n",
       "  u'SIM'],\n",
       " u'ATILIO FRANCISCO': [u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None],\n",
       " u'AURELIO NOMURA': [u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None],\n",
       " u'AUR\\xc9LIO MIGUEL': [None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM'],\n",
       " u'CALVO': [u'SIM', None, None, None, None, None, None, None, None],\n",
       " u'CELSO JATENE': [None, None, None, None, None, None, None, None, None],\n",
       " u'CLAUDINHO DE SOUZA': [u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO'],\n",
       " u'CLAUDIO FONSECA': [None,\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None],\n",
       " u'CONTE LOPES': [u'SIM', None, None, None, None, None, None, None, None],\n",
       " u'CORONEL CAMILO': [None,\n",
       "  None,\n",
       "  None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM'],\n",
       " u'CORONEL TELHADA': [None,\n",
       "  None,\n",
       "  None,\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'NAO'],\n",
       " u'DALTON SILVANO': [u'SIM', None, None, None, None, None, None, None, None],\n",
       " u'DAVID SOARES': [u'SIM', None, None, None, None, None, None, None, None],\n",
       " u'EDIR SALES': [None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM'],\n",
       " u'EDUARDO TUMA': [None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM',\n",
       "  u'ABSTENCAO',\n",
       "  None],\n",
       " u'ELISEU GABRIEL': [None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None],\n",
       " u'FLORIANO PESARO': [None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'NAO'],\n",
       " u'FRANCISCO CHAGAS': [None, None, None, None, None, None, None, None, None],\n",
       " u'GEORGE HATO': [None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM'],\n",
       " u'GILSON BARRETO': [u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'ABSTENCAO',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'NAO'],\n",
       " u'GOULART': [None, None, None, None, u'NAO', u'SIM', u'SIM', None, u'SIM'],\n",
       " u'JAIR TATTO': [u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  None,\n",
       "  u'SIM'],\n",
       " u'JAMIL MURAD': [None, None, None, None, None, None, None, None, None],\n",
       " u'JEAN MADEIRA': [u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  u'NAO',\n",
       "  None,\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM'],\n",
       " u'JONAS CAMISA NOVA': [u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None],\n",
       " u'JOSE AMERICO': [None,\n",
       "  None,\n",
       "  None,\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM'],\n",
       " u'JOSELITO': [u'SIM', None, None, None, None, None, None, None, None],\n",
       " u'JOS\\xc9 POLICE NETO': [u'NAO',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'NAO',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO'],\n",
       " u'JULIANA CARDOSO': [u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM'],\n",
       " u'LA\\xc9RCIO BENKO': [None,\n",
       "  None,\n",
       "  None,\n",
       "  u'NAO',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM'],\n",
       " u'MARCO AURELIO CUNHA': [None,\n",
       "  None,\n",
       "  None,\n",
       "  u'NAO',\n",
       "  u'NAO',\n",
       "  None,\n",
       "  u'SIM',\n",
       "  u'ABSTENCAO',\n",
       "  u'SIM'],\n",
       " u'MARCOS BELIZ\\xc1RIO': [None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  u'NAO',\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None],\n",
       " u'MARQUITO': [None, None, u'SIM', None, None, u'SIM', u'SIM', None, u'SIM'],\n",
       " u'MARTA COSTA': [None,\n",
       "  None,\n",
       "  None,\n",
       "  u'NAO',\n",
       "  u'NAO',\n",
       "  None,\n",
       "  u'SIM',\n",
       "  u'ABSTENCAO',\n",
       "  u'SIM'],\n",
       " u'MILTON LEITE': [None, None, None, u'SIM', None, u'SIM', None, None, None],\n",
       " u'M\\xc1RIO COVAS NETO': [None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO'],\n",
       " u'NABIL BONDUKI': [u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM'],\n",
       " u'NATALINI': [None, u'SIM', None, None, None, None, u'NAO', None, u'NAO'],\n",
       " u'NELO RODOLFO': [None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None],\n",
       " u'NETINHO DE PAULA': [None,\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None],\n",
       " u'NOEMI NONATO': [u'SIM', None, None, None, None, None, None, None, None],\n",
       " u'ORLANDO SILVA': [None, None, None, None, None, None, u'NAO', None, u'SIM'],\n",
       " u'OTA': [u'SIM', None, None, None, None, None, None, None, None],\n",
       " u'PATR\\xcdCIA BEZERRA': [u'NAO',\n",
       "  None,\n",
       "  None,\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'NAO'],\n",
       " u'PAULO FIORILO': [u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM'],\n",
       " u'PAULO FRANGE': [u'SIM',\n",
       "  None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM'],\n",
       " u'PR. EDEMILSON CHAVES': [u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None],\n",
       " u'QUITO FORMIGA': [None, u'SIM', u'SIM', None, None, None, None, None, None],\n",
       " u'REIS': [u'SIM', u'SIM', u'SIM', None, u'NAO', u'SIM', u'NAO', None, u'SIM'],\n",
       " u'RICARDO NUNES': [None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM'],\n",
       " u'RICARDO TEIXEIRA': [u'SIM', None, None, None, None, None, None, None, None],\n",
       " u'RICARDO YOUNG': [None, None, None, None, None, None, None, None, None],\n",
       " u'ROBERTO TRIPOLI': [None, None, None, None, None, None, u'SIM', None, None],\n",
       " u'RODOLFO DESPACHANTE': [None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None],\n",
       " u'SALOM\\xc3O PEREIRA': [None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None,\n",
       "  None],\n",
       " u'SANDRA TADEU': [u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None],\n",
       " u'SENIVAL MOURA': [u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  None],\n",
       " u'SOUZA SANTOS': [u'SIM', None, None, None, None, None, None, None, None],\n",
       " u'TONINHO PAIVA': [u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None],\n",
       " u'TONINHO VESPOLI': [None,\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  None,\n",
       "  u'NAO'],\n",
       " u'USHITARO KAMIA': [None, None, None, None, None, None, None, None, None],\n",
       " u'VALDECIR CABRABOM': [None,\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  None,\n",
       "  u'SIM',\n",
       "  None,\n",
       "  None,\n",
       "  None],\n",
       " u'VAV\\xc1': [u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  u'SIM',\n",
       "  u'NAO',\n",
       "  None,\n",
       "  u'SIM'],\n",
       " u'WADIH MUTRAN': [u'SIM', None, u'SIM', u'SIM', None, None, None, None, None]}"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pe_eles = ['PL-236-2016', 'PL-415-2012', 'PL-349-2014',\n",
    "           'PL-529-2014', 'PL-65-2014', 'PL-209-2011',\n",
    "           'PDL-6-2013', 'PL-254-2010', 'PL-236-2013']\n",
    "votacoes_selecionadas = [get_votacoes(pe_ele)[-1] for pe_ele in pe_eles]\n",
    "\n",
    "{p.nome: [get_voto_parlamentar(votacao, p) for votacao in votacoes_selecionadas]\n",
    " for p in parlamentares}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Votação #1363 2013-06-05\n",
      "\n",
      "AUTORIZA O PODER EXECUTIVO A INSTITUIR SERVIÇO SOCIAL AUTÔNOMO DENOMINADO AGÊNCIA SÃO PAULO DE DESENVOLVIMENTO - ADE SAMPA; INSTITUI O PROGRAMA PARA A VALORIZAÇÃO DE INICIATIVAS TECNOLÓGICAS - VAI TEC, NO ÂMBITO DA ADE SAMPA; MODIFICA DISPOSITIVOS DA LEI Nº 14.517, DE 16 DE OUTUBRO DE 2007. \n",
      "\n",
      "Encerramento da discussão ao PL 236/2013 DO EXECUT... - APROVADO EM SEGUNDA DISCUSSÃO E VOTAÇÃO NA FORMA DO TEXTO ORIGINAL COM EMENDA Nº 14 DA LIDERANÇA DO GOVERNO.  O PROJETO VOLTARÁ PARA A COMISSÃO DE JUSTIÇA PARA ELABORAÇÃO DO PARECER DE REDAÇÃO FINAL.\n",
      "\n",
      "Aprovado NAO 5 SIM 35\n",
      "\n",
      "\n",
      "\n",
      "Votação #1362 2013-06-05\n",
      "\n",
      "AUTORIZA O PODER EXECUTIVO A INSTITUIR SERVIÇO SOCIAL AUTÔNOMO DENOMINADO AGÊNCIA SÃO PAULO DE DESENVOLVIMENTO - ADE SAMPA; INSTITUI O PROGRAMA PARA A VALORIZAÇÃO DE INICIATIVAS TECNOLÓGICAS - VAI TEC, NO ÂMBITO DA ADE SAMPA; MODIFICA DISPOSITIVOS DA LEI Nº 14.517, DE 16 DE OUTUBRO DE 2007. \n",
      "\n",
      "PL 236 /2013, DO EXECUTIVO - APROVADO EM SEGUNDA DISCUSSÃO E VOTAÇÃO NA FORMA DO TEXTO ORIGINAL COM EMENDA Nº 14 DA LIDERANÇA DO GOVERNO.  O PROJETO VOLTARÁ PARA A COMISSÃO DE JUSTIÇA PARA ELABORAÇÃO DO PARECER DE REDAÇÃO FINAL.\n",
      "\n",
      "Aprovado NAO 9 SIM 35\n",
      "\n",
      "\n",
      "\n",
      "Votação #1359 2013-06-05\n",
      "\n",
      "AUTORIZA O PODER EXECUTIVO A INSTITUIR SERVIÇO SOCIAL AUTÔNOMO DENOMINADO AGÊNCIA SÃO PAULO DE DESENVOLVIMENTO - ADE SAMPA; INSTITUI O PROGRAMA PARA A VALORIZAÇÃO DE INICIATIVAS TECNOLÓGICAS - VAI TEC, NO ÂMBITO DA ADE SAMPA; MODIFICA DISPOSITIVOS DA LEI Nº 14.517, DE 16 DE OUTUBRO DE 2007. \n",
      "\n",
      "Bloco de emendas ao PL 236 /2013, DO EXECUTIVO - APROVADO EM SEGUNDA DISCUSSÃO E VOTAÇÃO NA FORMA DO TEXTO ORIGINAL COM EMENDA Nº 14 DA LIDERANÇA DO GOVERNO.  O PROJETO VOLTARÁ PARA A COMISSÃO DE JUSTIÇA PARA ELABORAÇÃO DO PARECER DE REDAÇÃO FINAL.\n",
      "\n",
      "Aprovado NAO 9 SIM 31\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from collections import Counter\n",
    "for votacao in get_votacoes('PL-236-2013'):\n",
    "    contador = Counter([v.opcao for v in votacao.votos()])\n",
    "    votos = ' '.join(['{} {}'.format(k, v) for k,v in contador.iteritems()])\n",
    "    \n",
    "    print 'Votação #{}'.format(votacao.id_vot) + ' ' + votacao.data.isoformat() + '\\n'\n",
    "    print votacao.proposicao.ementa + '\\n'\n",
    "    print votacao.descricao + '\\n' \n",
    "    print votacao.resultado + ' ' + votos + '\\n\\n\\n'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<Votacao: [2016-06-15] PL 236 /2016 , do EXECUTIVO - >]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_votacoes('PL-236-2016')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x.get?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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