Week6_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": "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": "code",
   "execution_count": 1,
   "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": [
    "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": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "074a7c808b4f4bd38e2fb082a3281131",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "FileUploadWidget(label='Browse', _dom_classes=('widget_item', 'btn-group'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Uploaded `me.txt` (1.13 kB)\n"
     ]
    }
   ],
   "source": [
    "# This is the uploader widget\n",
    "\n",
    "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": 20,
   "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\", \"in\" \"it\", \"of\", \"and\", \"or\",\"on\", \"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",
    "    # LEARNER CODE START HERE\n",
    "    frequencies =  {}\n",
    "    taken = []\n",
    "    for letter in punctuations:\n",
    "        file_contents =  file_contents.replace(letter,'')\n",
    "    for word in uninteresting_words:\n",
    "        w = ' '+word+' '\n",
    "        file_contents = file_contents.replace(w,' ')\n",
    "    for word in file_contents.split():\n",
    "        if word.lower() not in taken:\n",
    "            taken.append(word.lower())\n",
    "            if word not in frequencies:\n",
    "                frequencies[word] = 1\n",
    "            else:\n",
    "                frequencies[word] += 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": 21,
   "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(file_contents)\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"
  },
  "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": "3.7.4"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}