DATA602 Dispersion Plot.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from yellowbrick.text import DispersionPlot\n",
    "from os import path\n",
    "\n",
    "d = path.dirname(\"D:/sentiment analysis/JFK/jfk_post_73b.txt\")\n",
    "# Read the whole text.\n",
    "text = open(path.join(d, 'D:/sentiment analysis/JFK/jfk_post_73b.txt')).read()\n",
    "\n",
    "# Create a list of words from the corpus text\n",
    "text1 = [text.split()]\n",
    "\n",
    "# Choose words whose occurence in the text will be plotted\n",
    "target_words = ['airport', 'noise', 'runway', 'flights']\n",
    "\n",
    "# Create the visualizer and draw the plot\n",
    "visualizer = DispersionPlot(target_words)\n",
    "visualizer.fit(text1)\n",
    "visualizer.poof()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}