4c. Matplotlib - Histogram.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = np.random.randn(1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([   5.,   14.,   73.,  145.,  230.,  240.,  164.,   88.,   31.,   10.]),\n",
       " array([-3.23089934, -2.60824166, -1.98558398, -1.3629263 , -0.74026863,\n",
       "        -0.11761095,  0.50504673,  1.12770441,  1.75036209,  2.37301977,\n",
       "         2.99567745]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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S1DhDL0mNM/SS1DhDL0mNM/SS1DhDL0mN+1/g2J4KpX991QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2392ba85898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  1.,   1.,   3.,   4.,   5.,   5.,  17.,  22.,  34.,  38.,  43.,\n",
       "         64.,  64.,  79.,  87.,  73.,  79.,  88.,  73.,  50.,  41.,  35.,\n",
       "         22.,  31.,  18.,   7.,   6.,   5.,   2.,   3.]),\n",
       " array([-3.23089934, -3.02334678, -2.81579422, -2.60824166, -2.4006891 ,\n",
       "        -2.19313654, -1.98558398, -1.77803142, -1.57047886, -1.3629263 ,\n",
       "        -1.15537374, -0.94782118, -0.74026863, -0.53271607, -0.32516351,\n",
       "        -0.11761095,  0.08994161,  0.29749417,  0.50504673,  0.71259929,\n",
       "         0.92015185,  1.12770441,  1.33525697,  1.54280953,  1.75036209,\n",
       "         1.95791465,  2.16546721,  2.37301977,  2.58057233,  2.78812489,\n",
       "         2.99567745]),\n",
       " <a list of 30 Patch objects>)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAADIFJREFUeJzt3X+o3fddx/Hna23ntta5ll5C1hbTP8q0DLVyGdPJENNp\n0WWpf1gqTqIWwsC5TpQtbmBRGVSUMRERwzqJWDZKW2kzprZmHbo/Wnf7Q9c2nS3Trp1pczepW6c4\na9/+cb/DrOb2fk/uOffc877PB4Tz434P5/0lyTOffM8535OqQpK0+F4x7wEkSdNh0CWpCYMuSU0Y\ndElqwqBLUhMGXZKaMOiS1IRBl6QmDLokNXH2Vj7ZhRdeWHv27NnKp5SkhXf//fd/paqWNtpuS4O+\nZ88eVlZWtvIpJWnhJXlyzHYecpGkJgy6JDVh0CWpCYMuSU0YdElqwqBLUhMGXZKaMOiS1IRBl6Qm\ntvSTotKOcvTouO327ZvtHNoxXKFLUhOu0NWbq2TtIK7QJakJgy5JTRh0SWrCoEtSEwZdkpow6JLU\nhEGXpCYMuiQ1YdAlqQmDLklNGHRJasKgS1ITo4Ke5FeTPJLk4SQfT/KqJBckuTvJ48Pl+bMeVpK0\nvg2DnuQi4D3AclW9ETgLuBY4BByrqsuAY8NtSdKcjD3kcjbw6iRnA68B/hXYDxwZfn4EuHr640mS\nxtow6FX1ZeD3gS8BJ4B/r6q7gF1VdWLY7Blg18ymlCRtaMwhl/NZW41fCrweODfJO0/dpqoKqHUe\nfzDJSpKV1dXVKYwsSTqdMYdcrgT+uapWq+q/gduBHwaeTbIbYLg8eboHV9XhqlququWlpaVpzS1J\neokxX0H3JeDNSV4D/CewF1gBvgEcAG4cLu+Y1ZDS/zP2q+W6PK80woZBr6r7ktwKPAC8ADwIHAbO\nA25Jch3wJHDNLAeVJL28UV8SXVU3ADe85O7/Ym21LknaBvykqCQ1YdAlqQmDLklNGHRJasKgS1IT\nBl2SmjDoktSEQZekJgy6JDVh0CWpCYMuSU2MOpeL1N48z6I49rn37ZvtHFp4rtAlqQmDLklNGHRJ\nasKgS1ITBl2SmjDoktSEQZekJgy6JDVh0CWpCYMuSU0YdElqwqBLUhMGXZKaMOiS1IRBl6QmDLok\nNWHQJakJgy5JTRh0SWrCoEtSE35JtLbGPL+EWdohXKFLUhMGXZKaMOiS1IRBl6QmDLokNTEq6Ele\nl+TWJI8lOZ7kh5JckOTuJI8Pl+fPelhJ0vrGrtD/APirqvoe4PuB48Ah4FhVXQYcG25LkuZkw6An\n+S7grcBNAFX1zap6DtgPHBk2OwJcPashJUkbG7NCvxRYBf40yYNJPprkXGBXVZ0YtnkG2DWrISVJ\nGxsT9LOBHwT+uKquAL7BSw6vVFUBdboHJzmYZCXJyurq6mbnlSStY0zQnwaerqr7htu3shb4Z5Ps\nBhguT57uwVV1uKqWq2p5aWlpGjNLkk5jw6BX1TPAU0neMNy1F3gUuBM4MNx3ALhjJhNKkkYZe3Ku\nXwFuTvJK4IvAL7L2j8EtSa4DngSumc2IkqQxRgW9qh4Clk/zo73THUeSdKb8pKgkNWHQJakJgy5J\nTRh0SWrCoEtSEwZdkpow6JLUhEGXpCYMuiQ1YdAlqQmDLklNGHRJasKgS1ITBl2SmjDoktSEQZek\nJgy6JDVh0CWpibHfKSpp3o4eHbfdvn2znUPblit0SWrCoEtSEwZdkpow6JLUhEGXpCYMuiQ1YdAl\nqQmDLklNGHRJasKgS1ITBl2SmjDoktSEQZekJgy6JDVh0CWpCYMuSU34BRfanLFfuiBp5lyhS1IT\nBl2Smhgd9CRnJXkwySeH2xckuTvJ48Pl+bMbU5K0kUmOoV8PHAdeO9w+BByrqhuTHBpuv3/K80ma\nlF8mvWONWqEnuRj4KeCjp9y9HzgyXD8CXD3d0SRJkxh7yOUjwPuAF0+5b1dVnRiuPwPsmuZgkqTJ\nbBj0JG8HTlbV/ettU1UF1DqPP5hkJcnK6urqmU8qSXpZY1bobwHekeRfgE8AP5bkz4Fnk+wGGC5P\nnu7BVXW4qparanlpaWlKY0uSXmrDoFfVb1TVxVW1B7gW+HRVvRO4EzgwbHYAuGNmU0qSNrSZ96Hf\nCLwtyePAlcNtSdKcTPTR/6r6DPCZ4fpXgb3TH0lz58f5pYXkJ0UlqQmDLklNGHRJasKgS1ITBl2S\nmjDoktSE31gk7VSelbEdV+iS1IRBl6QmPOSyk/gJUKk1V+iS1IRBl6QmDLokNWHQJakJgy5JTRh0\nSWrCty1Kmh4/fTpXrtAlqQmDLklNGHRJasKgS1ITBl2SmjDoktSEQZekJgy6JDVh0CWpCYMuSU0Y\ndElqwqBLUhMGXZKaMOiS1IRBl6QmDLokNWHQJakJgy5JTRh0SWrCoEtSE35JdAdjv5hXOhP++VoY\nG67Qk1yS5J4kjyZ5JMn1w/0XJLk7yePD5fmzH1eStJ4xh1xeAH6tqi4H3gz8cpLLgUPAsaq6DDg2\n3JYkzcmGQa+qE1X1wHD968Bx4CJgP3Bk2OwIcPWshpQkbWyiF0WT7AGuAO4DdlXVieFHzwC7pjqZ\nJGkio4Oe5DzgNuC9VfW1U39WVQXUOo87mGQlycrq6uqmhpUkrW9U0JOcw1rMb66q24e7n02ye/j5\nbuDk6R5bVYerarmqlpeWlqYxsyTpNMa8yyXATcDxqvrwKT+6EzgwXD8A3DH98SRJY415H/pbgJ8H\nPp/koeG+DwA3ArckuQ54ErhmNiNKksbYMOhV9Vkg6/x473THkbQjjP2w0r59s52jGT/6L0lNGHRJ\nasJzuWxnnkND0gRcoUtSEwZdkpow6JLUhEGXpCYMuiQ1YdAlqQmDLklNGHRJasKgS1ITBl2SmjDo\nktSEQZekJgy6JDVh0CWpCYMuSU0YdElqwqBLUhMGXZKaMOiS1IRBl6QmDLokNWHQJamJs+c9gCSt\n6+jRcdvt2zfbORaEK3RJasKgS1ITHnKRtPg8NAO4QpekNlyhT9PYVYKk+Wi+kneFLklNuEIfw5W3\npAXgCl2SmjDoktTEzj3k4mEUSZs1SUe24IVWV+iS1MTOXaFL0noW9H/wm1qhJ7kqyReSPJHk0LSG\nkiRN7oxX6EnOAv4IeBvwNPC5JHdW1aPTGu7bLOi/mJK0VTazQn8T8ERVfbGqvgl8Atg/nbEkSZPa\nTNAvAp465fbTw32SpDmY+YuiSQ4CB4ebzyf5wqyfE7gQ+MoWPM8suQ/bg/uwPez0ffjuMRttJuhf\nBi455fbFw33fpqoOA4c38TwTS7JSVctb+ZzT5j5sD+7D9uA+jLOZQy6fAy5LcmmSVwLXAndOZyxJ\n0qTOeIVeVS8keTfw18BZwMeq6pGpTSZJmsimjqFX1aeAT01plmna0kM8M+I+bA/uw/bgPoyQqpr1\nc0iStoDncpGkJtoGPcnvJPnHJA8luSvJ6+c906SS/F6Sx4b9+Iskr5v3TJNK8jNJHknyYpKFepfC\nop/aIsnHkpxM8vC8ZzkTSS5Jck+SR4c/Q9fPe6ZJJXlVkr9P8g/DPvzWTJ+v6yGXJK+tqq8N198D\nXF5V75rzWBNJ8uPAp4cXoH8XoKreP+exJpLke4EXgT8Bfr2qVuY80ijDqS3+iVNObQH87MxObTED\nSd4KPA/8WVW9cd7zTCrJbmB3VT2Q5DuB+4GrF+z3IMC5VfV8knOAzwLXV9W9s3i+tiv0b8V8cC6w\ncP9yVdVdVfXCcPNe1t7rv1Cq6nhVbcWHyaZt4U9tUVV/C/zbvOc4U1V1oqoeGK5/HTjOgn0avdY8\nP9w8Z/g1sxa1DTpAkg8leQr4OeA35z3PJv0S8JfzHmIH8dQW20iSPcAVwH3znWRySc5K8hBwEri7\nqma2Dwsd9CR/k+Th0/zaD1BVH6yqS4CbgXfPd9rT22gfhm0+CLzA2n5sO2P2QTpTSc4DbgPe+5L/\neS+EqvqfqvoB1v6H/aYkMzv8tdBfcFFVV47c9GbW3i9/wwzHOSMb7UOSXwDeDuytbfqCxwS/D4tk\n1KktNFvDcefbgJur6vZ5z7MZVfVcknuAq4CZvFC90Cv0l5PkslNu7gcem9csZyrJVcD7gHdU1X/M\ne54dxlNbzNnwguJNwPGq+vC85zkTSZa+9e60JK9m7UX2mbWo87tcbgPewNo7LJ4E3lVVC7XCSvIE\n8B3AV4e77l3Ad+r8NPCHwBLwHPBQVf3EfKcaJ8lPAh/h/05t8aE5jzSRJB8HfpS1s/w9C9xQVTfN\ndagJJPkR4O+Az7P29xjgA8Mn1BdCku8DjrD2Z+gVwC1V9dsze76uQZeknabtIRdJ2mkMuiQ1YdAl\nqQmDLklNGHRJasKgS1ITBl2SmjDoktTE/wItpv1eZ4q54AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2392bd7c438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(data, bins=30, alpha=0.3,color='red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  2.,   0.,   0.,   1.,   0.,   0.,   3.,   8.,   6.,  13.,  11.,\n",
       "         18.,  25.,  34.,  32.,  38.,  45.,  62.,  64.,  65.,  62.,  54.,\n",
       "         67.,  70.,  53.,  49.,  51.,  56.,  33.,  21.,  12.,  19.,  15.,\n",
       "          3.,   4.,   2.,   0.,   1.,   0.,   1.]),\n",
       " array([-3.9172731 , -3.58586361, -3.25445411, -2.92304462, -2.59163513,\n",
       "        -2.26022564, -1.92881614, -1.59740665, -1.26599716, -0.93458767,\n",
       "        -0.60317817, -0.27176868,  0.05964081,  0.3910503 ,  0.72245979,\n",
       "         1.05386929,  1.38527878,  1.71668827,  2.04809776,  2.37950726,\n",
       "         2.71091675,  3.04232624,  3.37373573,  3.70514523,  4.03655472,\n",
       "         4.36796421,  4.6993737 ,  5.0307832 ,  5.36219269,  5.69360218,\n",
       "         6.02501167,  6.35642117,  6.68783066,  7.01924015,  7.35064964,\n",
       "         7.68205914,  8.01346863,  8.34487812,  8.67628761,  9.0076971 ,\n",
       "         9.3391066 ]),\n",
       " <a list of 40 Patch objects>)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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vJvlYkqm4xHTal5VI8owkn0lyT/f995ZJ17SSJGcluSvJxyddy0qSnJvkxu578N4kL550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\nMdQlqSGGuiQ1xFCXpIb8P4f0vT4Zp/VOAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2392d0a9550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x1 = np.random.normal(0,0.8, 1000)\n",
    "x2 = np.random.normal(-2,1,1000)\n",
    "x3 = np.random.normal(3, 2, 1000)\n",
    "\n",
    "argdict = dict(alpha=0.3, bins=40)\n",
    "\n",
    "plt.hist(x1, **argdict, color='red')\n",
    "plt.hist(x2, **argdict, color='yellow')\n",
    "plt.hist(x3, **argdict)\n"
   ]
  },
  {
   "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": "3.5.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}