{
 "metadata": {
  "name": "",
  "signature": "sha256:d60699d2037465d2556437c80b211ae4c60dd1ad4e52e2029eca5468427fe64a"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Indexing And Slicing Numpy Arrays\n",
      "\n",
      "- **Author:** [Chris Albon](http://www.chrisalbon.com/), [@ChrisAlbon](https://twitter.com/chrisalbon)\n",
      "- **Date:** -\n",
      "- **Repo:** [Python 3 code snippets for data science](https://github.com/chrisalbon/code_py)\n",
      "- **Note:**"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Import modules"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Create a 2x2 array"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "battle_deaths = [[344, 2345], [253, 4345]]\n",
      "deaths = np.array(battle_deaths)\n",
      "deaths"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "array([[5341, 2345],\n",
        "       [ 253, 4345]])"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Select the top row, second item"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "deaths[0, 1]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "2345"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Select the second column"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "deaths[:, 1]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "array([2345, 4345])"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Select the second row"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "deaths[1, :]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "array([ 253, 4345])"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Create an array of civilian deaths"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "civilian_deaths = np.array([4352, 233, 3245, 256, 2394])\n",
      "civilian_deaths"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 23,
       "text": [
        "array([4352,  233, 3245,  256, 2394])"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Find the index of battles with less than 500 deaths"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "few_civ_deaths = np.where(civilian_deaths < 500)\n",
      "few_civ_deaths"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 24,
       "text": [
        "(array([1, 3]),)"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Find the number of civilian deaths in battles with less than 500 deaths"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "civ_deaths = civilian_deaths[few_civ_deaths]\n",
      "civ_deaths"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 22,
       "text": [
        "array([233, 256])"
       ]
      }
     ],
     "prompt_number": 22
    }
   ],
   "metadata": {}
  }
 ]
}