Word_Cloud_utf-8''C1M6L2_Final_Project_V3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Final Project - Word Cloud"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this project, you'll create a \"word cloud\" from a text by writing a script.  This script needs to process the text, remove punctuation, ignore case and words that do not contain all alphabets, count the frequencies, and ignore uninteresting or irrelevant words.  A dictionary is the output of the `calculate_frequencies` function.  The `wordcloud` module will then generate the image from your dictionary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Installing /opt/conda/lib/python3.6/site-packages/fileupload/static -> fileupload\n",
      "Up to date: /home/jovyan/.local/share/jupyter/nbextensions/fileupload/extension.js\n",
      "Up to date: /home/jovyan/.local/share/jupyter/nbextensions/fileupload/widget.js\n",
      "Up to date: /home/jovyan/.local/share/jupyter/nbextensions/fileupload/fileupload/widget.js\n",
      "- Validating: \u001b[32mOK\u001b[0m\n",
      "\n",
      "    To initialize this nbextension in the browser every time the notebook (or other app) loads:\n",
      "    \n",
      "          jupyter nbextension enable fileupload --user --py\n",
      "    \n",
      "Enabling notebook extension fileupload/extension...\n",
      "      - Validating: \u001b[32mOK\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "# Here are all the installs and imports you will need for your word cloud script and uploader widget\n",
    "\n",
    "!pip install wordcloud\n",
    "!pip install fileupload\n",
    "!pip install ipywidgets\n",
    "!jupyter nbextension install --py --user fileupload\n",
    "!jupyter nbextension enable --py fileupload\n",
    "\n",
    "import wordcloud\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "from IPython.display import display\n",
    "import fileupload\n",
    "import io\n",
    "import sys"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the input text of your script, you will need to provide a file that contains text only.  For the text itself, you can copy and paste the contents of a website you like.  Or you can use a site like [Project Gutenberg](https://www.gutenberg.org/) to find books that are available online.  You could see what word clouds you can get from famous books, like a Shakespeare play or a novel by Jane Austen. Save this as a .txt file somewhere on your computer.\n",
    "<br><br>\n",
    "Now you will need to upload your input file here so that your script will be able to process it.  To do the upload, you will need an uploader widget.  Run the following cell to perform all the installs and imports for your word cloud script and uploader widget.  It may take a minute for all of this to run and there will be a lot of output messages. But, be patient. Once you get the following final line of output, the code is done executing. Then you can continue on with the rest of the instructions for this notebook.\n",
    "<br><br>\n",
    "**Enabling notebook extension fileupload/extension...**\n",
    "<br>\n",
    "**- Validating: <font color =green>OK</font>**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Whew! That was a lot. All of the installs and imports for your word cloud script and uploader widget have been completed. \n",
    "<br><br>\n",
    "**IMPORTANT!** If this was your first time running the above cell containing the installs and imports, you will need save this notebook now. Then under the File menu above,  select Close and Halt. When the notebook has completely shut down, reopen it. This is the only way the necessary changes will take affect.\n",
    "<br><br>\n",
    "To upload your text file, run the following cell that contains all the code for a custom uploader widget. Once you run this cell, a \"Browse\" button should appear below it. Click this button and navigate the window to locate your saved text file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dbac0fc7b68c487087c4c410bf4f0408",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "FileUploadWidget(label='Browse', _dom_classes=('widget_item', 'btn-group'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def _upload():\n",
    "\n",
    "    _upload_widget = fileupload.FileUploadWidget()\n",
    "\n",
    "    def _cb(change):\n",
    "        global file_contents\n",
    "        decoded = io.StringIO(change['owner'].data.decode('utf-8'))\n",
    "        filename = change['owner'].filename\n",
    "        print('Uploaded `{}` ({:.2f} kB)'.format(\n",
    "            filename, len(decoded.read()) / 2 **10))\n",
    "        file_contents = decoded.getvalue()\n",
    "\n",
    "    _upload_widget.observe(_cb, names='data')\n",
    "    display(_upload_widget)\n",
    "\n",
    "_upload()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The uploader widget saved the contents of your uploaded file into a string object named *file_contents* that your word cloud script can process. This was a lot of preliminary work, but you are now ready to begin your script. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write a function in the cell below that iterates through the words in *file_contents*, removes punctuation, and counts the frequency of each word.  Oh, and be sure to make it ignore word case, words that do not contain all alphabets and boring words like \"and\" or \"the\".  Then use it in the `generate_from_frequencies` function to generate your very own word cloud!\n",
    "<br><br>\n",
    "**Hint:** Try storing the results of your iteration in a dictionary before passing them into wordcloud via the `generate_from_frequencies` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_frequencies(file_contents):\n",
    "    # Here is a list of punctuations and uninteresting words you can use to process your text\n",
    "    punctuations = '''!()-[]{};:'\"\\,<>./?@#$%^&*_~'''\n",
    "    uninteresting_words = [\"the\", \"a\", \"to\", \"if\", \"is\", \"it\", \"of\", \"and\", \"or\", \"an\", \"as\", \"i\", \"me\", \"my\", \\\n",
    "    \"we\", \"our\", \"ours\", \"you\", \"your\", \"yours\", \"he\", \"she\", \"him\", \"his\", \"her\", \"hers\", \"its\", \"they\", \"them\", \\\n",
    "    \"their\", \"what\", \"which\", \"who\", \"whom\", \"this\", \"that\", \"am\", \"are\", \"was\", \"were\", \"be\", \"been\", \"being\", \\\n",
    "    \"have\", \"has\", \"had\", \"do\", \"does\", \"did\", \"but\", \"at\", \"by\", \"with\", \"from\", \"here\", \"when\", \"where\", \"how\", \\\n",
    "    \"all\", \"any\", \"both\", \"each\", \"few\", \"more\", \"some\", \"such\", \"no\", \"nor\", \"too\", \"very\", \"can\", \"will\", \"just\"]\n",
    "    \n",
    "    frequencies={}\n",
    "    file_contents=file_contents.split()\n",
    "    str1=\"\"\n",
    "    \n",
    "    for word in file_contents:\n",
    "        str1= ''.join(ch for ch in word if ch.isalpha())\n",
    "        if str1.lower() not in uninteresting_words:\n",
    "            \n",
    "            if str1.lower() not in frequencies:\n",
    "                frequencies[str1.lower()]=1\n",
    "            else:\n",
    "                frequencies[str1.lower()]+=1\n",
    "    \n",
    "    \n",
    "    #wordcloud\n",
    "    cloud = wordcloud.WordCloud()\n",
    "    cloud.generate_from_frequencies(frequencies)\n",
    "    return cloud.to_array()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you have done everything correctly, your word cloud image should appear after running the cell below.  Fingers crossed!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "# Display your wordcloud image\n",
    "\n",
    "myimage = calculate_frequencies(\"William Shakespeare (bapt. 26 April 1564 – 23 April 1616) was an English playwright, poet, and actor, widely regarded as the greatest writer in the English language and the world's greatest dramatist \")\n",
    "plt.imshow(myimage, interpolation = 'nearest')\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If your word cloud image did not appear, go back and rework your `calculate_frequencies` function until you get the desired output.  Definitely check that you passed your frequecy count dictionary into the `generate_from_frequencies` function of `wordcloud`. Once you have correctly displayed your word cloud image, you are all done with this project. Nice work!"
   ]
  }
 ],
 "metadata": {
  "coursera": {
   "course_slug": "python-crash-course",
   "graded_item_id": "Z5d28",
   "launcher_item_id": "eSjyd"
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  "widgets": {
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    "version_major": 2,
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 },
 "nbformat": 4,
 "nbformat_minor": 2
}