Lec 26 - JSON with Python.ipynb

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 "worksheets": [
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   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "from pandas import Series, DataFrame\n",
      "import pandas as pd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Heres an example of what a JSON (JavaScript Object Notation) looks like:\n",
      "json_obj = \"\"\"\n",
      "{   \"zoo_animal\": \"Lion\",\n",
      "    \"food\": [\"Meat\", \"Veggies\", \"Honey\"],\n",
      "    \"fur\": \"Golden\",\n",
      "    \"clothes\": null, \n",
      "    \"diet\": [{\"zoo_animal\": \"Gazelle\", \"food\":\"grass\", \"fur\": \"Brown\"}]\n",
      "}\n",
      "\"\"\""
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Let import json module\n",
      "import json\n",
      "\n",
      "#Lets load json data\n",
      "data = json.loads(json_obj)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Show\n",
      "data"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "{u'clothes': None,\n",
        " u'diet': [{u'food': u'grass', u'fur': u'Brown', u'zoo_animal': u'Gazelle'}],\n",
        " u'food': [u'Meat', u'Veggies', u'Honey'],\n",
        " u'fur': u'Golden',\n",
        " u'zoo_animal': u'Lion'}"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#WE can also convert back to JSON\n",
      "json.dumps(data)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "'{\"food\": [\"Meat\", \"Veggies\", \"Honey\"], \"zoo_animal\": \"Lion\", \"fur\": \"Golden\", \"diet\": [{\"food\": \"grass\", \"zoo_animal\": \"Gazelle\", \"fur\": \"Brown\"}], \"clothes\": null}'"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#We can simply open JSON data after loading with a DataFrame\n",
      "dframe = DataFrame(data['diet'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Show\n",
      "dframe"
     ],
     "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>food</th>\n",
        "      <th>fur</th>\n",
        "      <th>zoo_animal</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> grass</td>\n",
        "      <td> Brown</td>\n",
        "      <td> Gazelle</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "    food    fur zoo_animal\n",
        "0  grass  Brown    Gazelle"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Theres lost of custom selection you can do, based on what you do or dont want in your DataFrame (you can specify columns..etc)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Next up, XML and HTML file format with python!"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
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