The Experiment!!.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Data Source**\n",
    "\n",
    "Sample: https://drive.google.com/open?id=1JCc61aKBLUdSAMkS8hQlSTI2JwB4KZCD (~6.0 MB)      \n",
    "Full: https://drive.google.com/open?id=1JMOwbdvA0XXN6IaWPAhSnzIxAWworlVS (~65.0 MB)\n",
    "\n",
    "\n",
    "Data Also available in pendrive, ask me for it :)\n",
    "\n",
    "\n",
    "*Target Variable Name = 'label'*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv('../cbga/stratified_sample_labeled_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['area', 'bottom', 'centroid_x', 'centroid_y',\n",
       "       'comma_separated_numbers_present', 'height', 'is_text', 'label', 'left',\n",
       "       'number', 'pos', 'possible_row_merger', 'right', 'table', 'text',\n",
       "       'text_length', 'top', 'width', 'filename'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
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       "...                           ...\n",
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       "\n",
       "[6068 rows x 1 columns]"
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     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
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    "data[['top', 'right', 'label', 'pos']].groupby(['top', 'right', 'label']).count()"
   ]
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   "source": [
    "### Inspiration: https://github.com/pgmpy/pgmpy_notebook/tree/master/notebooks"
   ]
  },
  {
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   "execution_count": null,
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