notebooks/unit04/unit04_05.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook was prepared by Cayetano Benavent, 2016."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Matplotlib: plotting 03"
   ]
  },
  {
   "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": "markdown",
   "metadata": {},
   "source": [
    "## Histograms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Building histograms:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mean = 500\n",
    "std = 50\n",
    "size = 1000\n",
    "data = np.random.normal(loc=mean, scale=std, size=size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f31e152a898>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYwAAAEZCAYAAACEkhK6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f31e14f2a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(data)\n",
    "plt.title(\"Histogram\")\n",
    "plt.xlabel(\"Data\")\n",
    "plt.ylabel(\"Freq\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Personalizing color and number of bins:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f31e1406278>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYwAAAEZCAYAAACEkhK6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nasXAkCS1YmBIklr5/+zzEy/ZWS3FAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f31e152eb00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_bins = 20\n",
    "plt.hist(data, n_bins, facecolor='green', alpha=0.5)\n",
    "plt.title(\"Histogram\")\n",
    "plt.xlabel(\"Data\")\n",
    "plt.ylabel(\"Freq\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f31e1336278>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZYAAAEZCAYAAAC0HgObAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nxczMkvr/01Q7Fm6YbCoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f31e13f4550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_bins = 20\n",
    "plt.hist(data, n_bins, normed=1, facecolor='green', alpha=0.5)\n",
    "plt.title(\"Histogram\")\n",
    "plt.xlabel(\"Data\")\n",
    "plt.ylabel(\"density\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Adding a line showing the expected distribution:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 296.03321004  312.90794192  329.78267379  346.65740566  363.53213754\n",
      "  380.40686941  397.28160128  414.15633315  431.03106503  447.9057969\n",
      "  464.78052877  481.65526065  498.52999252  515.40472439  532.27945626\n",
      "  549.15418814  566.02892001  582.90365188  599.77838376  616.65311563\n",
      "  633.5278475 ]\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYsAAAEZCAYAAABmTgnDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRDJSsRARkYz+HyD8QdXEvjU/AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f31e131df28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.mlab as mlab\n",
    "\n",
    "n_bins = 20\n",
    "n, bins, patches = plt.hist(data, n_bins, normed=1, facecolor='green', alpha=0.5)\n",
    "print(bins)\n",
    "y = mlab.normpdf(bins, mean, std)\n",
    "l = plt.plot(bins, y, 'r--', linewidth=1.5)\n",
    "plt.title(\"Histogram\")\n",
    "plt.xlabel(\"Data\")\n",
    "plt.ylabel(\"density\")\n",
    "plt.subplots_adjust(left=0.15)\n"
   ]
  }
 ],
 "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": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}