{
 "metadata": {
  "name": "",
  "signature": "sha256:1c9c0d174dc331d2feb2d83313cdd1b55ff0be3459b17d693386fc33f646bd3b"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "**Work in Progress**"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# read population in\n",
      "import json\n",
      "import requests\n",
      "from pandas import DataFrame\n",
      "\n",
      "# pop_json_url holds a \n",
      "pop_json_url = \"https://gist.github.com/rdhyee/8511607/raw/f16257434352916574473e63612fcea55a0c1b1c/population_of_countries.json\"\n",
      "pop_list= requests.get(pop_json_url).json()\n",
      "\n",
      "df = DataFrame(pop_list)\n",
      "df[:5]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>0</th>\n",
        "      <th>1</th>\n",
        "      <th>2</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 1</td>\n",
        "      <td>         China</td>\n",
        "      <td> 1385566537</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 2</td>\n",
        "      <td>         India</td>\n",
        "      <td> 1252139596</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 3</td>\n",
        "      <td> United States</td>\n",
        "      <td>  320050716</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 4</td>\n",
        "      <td>     Indonesia</td>\n",
        "      <td>  249865631</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 5</td>\n",
        "      <td>        Brazil</td>\n",
        "      <td>  200361925</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 3 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 1,
       "text": [
        "   0              1           2\n",
        "0  1          China  1385566537\n",
        "1  2          India  1252139596\n",
        "2  3  United States   320050716\n",
        "3  4      Indonesia   249865631\n",
        "4  5         Brazil   200361925\n",
        "\n",
        "[5 rows x 3 columns]"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Q: What is the relationship between `s` and the population of China?\n",
      "\n",
      "    s = sum(df[df[1].str.startswith('C')][2])\n",
      "    \n",
      "1. `s` is **greater** than the population of China\n",
      "1. `s` is the **same** as the population of China\n",
      "1. `s` is **less** than the population of China\n",
      "1. `s` is not a number.\n",
      "\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from pandas import DataFrame, Series, Index\n",
      "import numpy as np\n",
      "\n",
      "s1 = Series(np.arange(1,4))\n",
      "s1"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "0    1\n",
        "1    2\n",
        "2    3\n",
        "dtype: int64"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Q:  What is\n",
      "    \n",
      "    s1.apply(lambda k: 2*k).sum()\n",
      "   "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Q: What is `s1.cumsum()[1]`?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    }
   ],
   "metadata": {}
  }
 ]
}