jbzdak/foo

## foo
{
 "metadata": {
  "name": "matplotlib-text-in-corner"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "np.random.seed(1234)\n",
      "fig, ax = plt.subplots(1)\n",
      "x = 30*np.random.randn(10000)\n",
      "mu = x.mean()\n",
      "median = np.median(x)\n",
      "sigma = x.std()\n",
      "textstr = '$\\mu=%.2f$\\n$\\mathrm{median}=%.2f$\\n$\\sigma=%.2f$'%(mu, median, sigma)\n",
      "\n",
      "ax.hist(x, 50)\n",
      "# these are matplotlib.patch.Patch properties\n",
      "props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)\n",
      "\n",
      "# place a text box in upper left in axes coords\n",
      "ax.text(0.05, 0.95, textstr, transform=ax.transAxes, fontsize=14,\n",
      "        verticalalignment='top', bbox=props)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 1,
       "text": [
        "<matplotlib.text.Text at 0x2829110>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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WIiLSIk2G/d133016enqdbcnJycTGxpKbm8vEiRNJTk4GICcnh1WrVpGTk0N6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\n"
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "np.random.seed(1234)\n",
      "fig, ax = plt.subplots(1)\n",
      "x = 30*np.random.randn(10000)\n",
      "mu = x.mean()\n",
      "median = np.median(x)\n",
      "sigma = x.std()\n",
      "textstr = '$\\mu=%.2f$\\n$\\mathrm{median}=%.2f$\\n$\\sigma=%.2f$'%(mu, median, sigma)\n",
      "\n",
      "ax.hist(x, 50)\n",
      "# these are matplotlib.patch.Patch properties\n",
      "props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)\n",
      "\n",
      "# place a text box in upper left in axes coords\n",
      "ax.text(0.05, 0.05, textstr, transform=ax.transAxes, fontsize=14,\n",
      "        verticalalignment='bottom', bbox=props)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "<matplotlib.text.Text at 0x2bf8d90>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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5hs99iYjv8Ok7+3+9+yHXnTMO+1f5X9O/X18GDuhXb7vWjh9/xtqsbLp08ePJ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\n"
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "np.random.seed(1234)\n",
      "fig, ax = plt.subplots(1)\n",
      "x = 30*np.random.randn(10000)\n",
      "mu = x.mean()\n",
      "median = np.median(x)\n",
      "sigma = x.std()\n",
      "textstr = '$\\mu=%.2f$\\n$\\mathrm{median}=%.2f$\\n$\\sigma=%.2f$'%(mu, median, sigma)\n",
      "\n",
      "ax.hist(x, 50)\n",
      "# these are matplotlib.patch.Patch properties\n",
      "props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)\n",
      "\n",
      "# place a text box in upper left in axes coords\n",
      "ax.text(0.95, 0.95, textstr, transform=ax.transAxes, fontsize=14,\n",
      "        verticalalignment='top', horizontalalignment='right', bbox=props)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "<matplotlib.text.Text at 0x2fd88d0>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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X25aYmEhUVBS5ublMnTqVxMREAHJyckhOTiYnJ4f09HTmzp1LbW2te2ouIiIt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\nBBT2IiImoLAXETEBhb2IiAn8f0KvqlqfhLGSAAAAAElFTkSuQmCC\n"
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "np.random.seed(1234)\n",
      "fig, ax = plt.subplots(1)\n",
      "x = 30*np.random.randn(10000)\n",
      "mu = x.mean()\n",
      "median = np.median(x)\n",
      "sigma = x.std()\n",
      "textstr = '$\\mu=%.2f$\\n$\\mathrm{median}=%.2f$\\n$\\sigma=%.2f$'%(mu, median, sigma)\n",
      "\n",
      "ax.hist(x, 50)\n",
      "# these are matplotlib.patch.Patch properties\n",
      "props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)\n",
      "\n",
      "# place a text box in upper left in axes coords\n",
      "ax.text(0.95, 0.05, textstr, transform=ax.transAxes, fontsize=14,\n",
      "        horizontalalignment='right', bbox=props)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "<matplotlib.text.Text at 0x34692d0>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}