cdf.py

import numpy as np
import matplotlib.pyplot as plt

data = np.random.randn(100)
data = np.sort(data)
cdf = (np.arange(len(data))+1.0)/len(data)
'''C.D.F.
C.D.F. is the number of points smaller then the current value.
For each value in the data, increment up by 1/len(data). 
'''

plt.figure()
plt.plot(data, cdf)
plt.show()

Cumulative distribution function.ipynb

{
 "metadata": {
  "name": "",
  "signature": "sha256:ee8e469e14ab92c28feda1e4366ed99446af59bdc4782b377027c1dd4ad10649"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Cumulative distribution function (cdf)\n",
      "If you have coninuous data, do not use historgrams. Present them with cdf's. Here is a simple way to plot a cdf."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "import matplotlib.pyplot as plt\n",
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data = np.random.randn(100)\n",
      "data = np.sort(data)\n",
      "cdf = (np.arange(len(data))+1.0)/len(data)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Cdf is the number of points smaller then the current value. For each value in the data, increment up by 1/len(data). This makes sences: at half way, the probability of getting that value or less should be `.5`; at the end of the list, the probability of getting that value or less should be `1`."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.figure()\n",
      "plt.plot(data, cdf)\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x10e1c6cd0>"
       ]
      }
     ],
     "prompt_number": 3
    }
   ],
   "metadata": {}
  }
 ]
}