IOD_Lab-9_5 (1).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "XXUiceLiLNOv"
   },
   "source": [
    "<div>\n",
    "<img src=https://www.institutedata.com/wp-content/uploads/2019/10/iod_h_tp_primary_c.svg width=\"300\">\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "SmJwFqq5LNOx"
   },
   "source": [
    "# Demo 9.5: Working with Text\n",
    "- Using [NLTK](http://www.nltk.org) (Natural Language Toolkit)\n",
    "- Using [spaCy](https://spacy.io)\n",
    "\n",
    "INSTRUCTIONS:\n",
    "- Run the cells\n",
    "- Observe and understand the results\n",
    "- Answer the questions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "I83eiiJqLNO0"
   },
   "source": [
    "## Import libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:17:23.125143Z",
     "start_time": "2019-06-17T01:17:20.625946Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "-ecJn_1MLNO4"
   },
   "outputs": [],
   "source": [
    "## Import Libraries\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from collections import Counter\n",
    "\n",
    "import regex as re\n",
    "import spacy\n",
    "import nltk"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "OsSgzr8MLNO9"
   },
   "source": [
    "## Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:17:24.800475Z",
     "start_time": "2019-06-17T01:17:24.784516Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "HvyU9ZbtLNPA"
   },
   "outputs": [],
   "source": [
    "## Loading the data\n",
    "\n",
    "input_file = 'ncc-1701-D.txt'\n",
    "\n",
    "with open(input_file, 'r') as f:\n",
    "    text = f.read()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "KF9gBdpALNPE"
   },
   "source": [
    "## Inspect the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:17:28.662206Z",
     "start_time": "2019-06-17T01:17:28.656190Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "-JImxUzrLNPG",
    "outputId": "13ce31ea-531e-4abd-8f21-c726df89bb21",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "USS Enterprise (NCC-1701-D)\n",
      "\n",
      "\"For five hundred years, every ship that has borne the name of the Enterprise has become a legend. This one is no different.\"\n",
      "\n",
      "The USS Enterprise (NCC-1701-D) was a 24th century United Federation of Planets Galaxy Class starship operated by Starfleet, and the fifth Federation ship to bear the name Enterprise. During her career, the Enterprise served as the Federation flagship. The Enterprise was destroyed during the Battle of Veridian III in 2371.\n",
      "\n",
      "==History==\n",
      "===Construction and launch===\n",
      "The Enterprise was built at Utopia Planitia Fleet Yards orbiting Mars in the Solar system. The construction was a massive undertaking, involving thousands of people across disciplines. Construction was supervised by Commander Orfil Quinteros. Dr. Leah Brahms was responsible for much of the Enterprise's warp propulsion system design. Some of the Enterprise's components were derived from technology originally developed on the USS Pegasus.\n",
      "\n",
      "One of the ship's nacelle tube was\n"
     ]
    }
   ],
   "source": [
    "print(text[:1000])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "H5ePf_5bLNPK"
   },
   "source": [
    "## Work the data\n",
    "- if necessary or desired\n",
    "    - remove text or content, e.g. quotes (\") or metadata (===)\n",
    "    - add content or markers, e.g. (#FLAG, --NAME--)\n",
    "    - remove or convert special symbols, e.g. \"é\" to \"e\"\n",
    "    - remove or convert emoticons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:18:07.223561Z",
     "start_time": "2019-06-17T01:18:07.219572Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "BRq7VfoOLNPM"
   },
   "outputs": [],
   "source": [
    "pattern = r'\\,\\.\\(\\)\\==\\==='\n",
    "\n",
    "text = ' '.join(re.split(pattern, text))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'USS Enterprise (NCC-1701-D)\\n\\n\"For five hundred years, every ship that has borne the name of the Enterprise has become a legend. This one is no different.\"\\n\\nThe USS Enterprise (NCC-1701-D) was a 24th century United Federation of Planets Galaxy Class starship operated by Starfleet, and the fifth Federation ship to bear the name Enterprise. During her career, the Enterprise served as the Federation flagship. The Enterprise was destroyed during the Battle of Veridian III in 2371.\\n\\n==History==\\n===Construction and launch===\\nThe Enterprise was built at Utopia Planitia Fleet Yards orbiting Mars in the Solar system. The construction was a massive undertaking, involving thousands of people across disciplines. Construction was supervised by Commander Orfil Quinteros. Dr. Leah Brahms was responsible for much of the Enterprise\\'s warp propulsion system design. Some of the Enterprise\\'s components were derived from technology originally developed on the USS Pegasus.\\n\\nOne of the ship\\'s nacelle tube was the site of a multiple murder-suicide while she was still under construction at Utopia Planitia. A member of the construction team, Walter Pierce, became jealous of a former lover\\'s new relationship. He killed the two officers, Marla Finn and William Hodges, then disposed of their bodies in the plasma stream. Pierce committed suicide in the same manner, leaving a telepathic imprint in a bulkhead that was not discovered until 2370.\\n\\nOn stardate 40759.5, in the year 2363, the Enterprise was launched from Mars. On stardate 41025.5, the Enterprise was commissioned.\\n\\nThese stardates weren\\'t mentioned in dialog; they were from the Enterprise dedication plaque.\\n\\nFinal systems completion and shakedown was conducted at Earth Station McKinley. Captain Jean-Luc Picard took command of the ship on stardate 41148 at the order of Rear Admiral Norah Satie.\\n\\n===Legacy===\\nCommander Riker was upset over the loss of the Enterprise. Having hoped he would one day command the ship, he was disappointed that he never got that opportunity. However, Picard expressed doubt that the Enterprise-D would be the last vessel to carry the name.\\n\\nThe Enterprise was so dear to Worf that, shortly after being reassigned to Deep Space 9 in 2372, he briefly considered resigning from Starfleet. Station commander Captain Benjamin Sisko expressed regret on the loss of the Enterprise and offered his condolences over the destruction of the ship to Worf, saying the Enterprise \"was a good ship.\"\\n\\nCaptain Picard\\'s belief that the Enterprise-D would not be the final ship to bear the name was borne out with the christening of the Class Sovereign USS Enterprise NCC-1701-E, later the same year. In that instance, the legacy of the Enterprise continued with Picard reprising his role as CO and selecting most of the former crew from the Enterprise-D, with the notable exception of Worf due to his most recent assignment to DS9 (though he temporarily joined the Enterprise-E crew on several of their more notable missions).'"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "text1 = text.split()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "xMG9Yim0LNPP"
   },
   "source": [
    "## Helper method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:18:44.351070Z",
     "start_time": "2019-06-17T01:18:44.330126Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "3oIPRH3gLNPQ"
   },
   "outputs": [],
   "source": [
    "# create a bar chart of the frequency of the words in the text\n",
    "def plot_words(tokens, top = 30):\n",
    "    tokens_counter = Counter(tokens)\n",
    "    tok = [t for (t, _) in tokens_counter.most_common()]\n",
    "    val = [v for (_, v) in tokens_counter.most_common()]\n",
    "\n",
    "    plt.figure(figsize = (16, 6))\n",
    "    plt.bar(tok[:top], val[:top])\n",
    "    plt.title('Number of terms: %d' % len(tokens_counter))\n",
    "    plt.xticks(rotation = 90)\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_words(text1, top=30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting en-core-web-sm==3.1.0\n",
      "  Downloading https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.1.0/en_core_web_sm-3.1.0-py3-none-any.whl (13.6 MB)\n",
      "Requirement already satisfied: spacy<3.2.0,>=3.1.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from en-core-web-sm==3.1.0) (3.1.2)\n",
      "Requirement already satisfied: spacy-legacy<3.1.0,>=3.0.7 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (3.0.8)\n",
      "Requirement already satisfied: pydantic!=1.8,!=1.8.1,<1.9.0,>=1.7.4 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (1.8.2)\n",
      "Requirement already satisfied: blis<0.8.0,>=0.4.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (0.7.4)\n",
      "Requirement already satisfied: packaging>=20.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (20.9)\n",
      "Requirement already satisfied: cymem<2.1.0,>=2.0.2 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (2.0.5)\n",
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      "Requirement already satisfied: numpy>=1.15.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (1.19.5)\n",
      "Requirement already satisfied: pathy>=0.3.5 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (0.6.0)\n",
      "Requirement already satisfied: jinja2 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (2.11.3)\n",
      "Requirement already satisfied: tqdm<5.0.0,>=4.38.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (4.59.0)\n",
      "Requirement already satisfied: setuptools in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (52.0.0.post20210125)\n",
      "Requirement already satisfied: murmurhash<1.1.0,>=0.28.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (1.0.5)\n",
      "Requirement already satisfied: requests<3.0.0,>=2.13.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (2.25.1)\n",
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      "Requirement already satisfied: pyparsing>=2.0.2 in c:\\programdata\\anaconda3\\lib\\site-packages (from packaging>=20.0->spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (2.4.7)\n",
      "Requirement already satisfied: smart-open<6.0.0,>=5.0.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from pathy>=0.3.5->spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (5.2.1)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in c:\\programdata\\anaconda3\\lib\\site-packages (from pydantic!=1.8,!=1.8.1,<1.9.0,>=1.7.4->spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (3.7.4.3)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\programdata\\anaconda3\\lib\\site-packages (from requests<3.0.0,>=2.13.0->spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (1.26.4)\n",
      "Requirement already satisfied: chardet<5,>=3.0.2 in c:\\programdata\\anaconda3\\lib\\site-packages (from requests<3.0.0,>=2.13.0->spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (4.0.0)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in c:\\programdata\\anaconda3\\lib\\site-packages (from requests<3.0.0,>=2.13.0->spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (2020.12.5)\n",
      "Requirement already satisfied: idna<3,>=2.5 in c:\\programdata\\anaconda3\\lib\\site-packages (from requests<3.0.0,>=2.13.0->spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (2.10)\n",
      "Requirement already satisfied: click<7.2.0,>=7.1.1 in c:\\programdata\\anaconda3\\lib\\site-packages (from typer<0.4.0,>=0.3.0->spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (7.1.2)\n",
      "Requirement already satisfied: MarkupSafe>=0.23 in c:\\programdata\\anaconda3\\lib\\site-packages (from jinja2->spacy<3.2.0,>=3.1.0->en-core-web-sm==3.1.0) (1.1.1)\n",
      "Installing collected packages: en-core-web-sm\n",
      "Successfully installed en-core-web-sm-3.1.0\n",
      "[+] Download and installation successful\n",
      "You can now load the package via spacy.load('en_core_web_sm')\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-09-18 16:20:54.748615: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found\n",
      "2021-09-18 16:20:54.748650: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\n"
     ]
    }
   ],
   "source": [
    "!python -m spacy download en_core_web_sm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "U1FsFC6yLNPS"
   },
   "source": [
    "## spaCy model invocation and text processing\n",
    "spaCy does the processing of the text as part of the reading of the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:18:18.119766Z",
     "start_time": "2019-06-17T01:18:16.984471Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "JgM48u-dLNPU"
   },
   "outputs": [],
   "source": [
    "# load spaCy and the English model\n",
    "nlp = spacy.load(\"en_core_web_sm\")\n",
    "\n",
    "# process the text\n",
    "doc = nlp(text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "z8--KeYzLNPW"
   },
   "source": [
    "## Tokenise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:18:58.447329Z",
     "start_time": "2019-06-17T01:18:58.401479Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "-7lVWo5DLNPe",
    "outputId": "b679dc9c-f19f-4ad2-fdbd-9b6755c17bae"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 1| 'USS'\n",
      " 2| 'Enterprise'\n",
      " 3| '('\n",
      " 4| 'NCC-1701'\n",
      " 5| '-'\n",
      " 6| 'D'\n",
      " 7| ')'\n",
      " 8| '\\n\\n'\n",
      " 9| '\"'\n",
      "10| 'For'\n",
      "11| 'five'\n",
      "12| 'hundred'\n",
      "13| 'years'\n",
      "14| ','\n",
      "15| 'every'\n",
      "16| 'ship'\n",
      "17| 'that'\n",
      "18| 'has'\n",
      "19| 'borne'\n",
      "20| 'the'\n",
      "21| 'name'\n",
      "22| 'of'\n",
      "23| 'the'\n",
      "24| 'Enterprise'\n",
      "25| 'has'\n",
      "26| 'become'\n",
      "27| 'a'\n",
      "28| 'legend'\n",
      "29| '.'\n"
     ]
    }
   ],
   "source": [
    "# only show the results\n",
    "# spaCy has done it already\n",
    "for i, t in enumerate(doc):\n",
    "    print('%2d| %r' % (i+1, t.text))\n",
    "    if t.text == '.':\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:19:56.492190Z",
     "start_time": "2019-06-17T01:19:56.488201Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "Gcg4Hkx4LNPh",
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# ANSWER"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "iAtMzEZTLNPj"
   },
   "source": [
    "### Stop Words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:24:08.828052Z",
     "start_time": "2019-06-17T01:24:08.777179Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "zOzudmrILNPq",
    "outputId": "1e58fcfc-674d-42f1-e82a-63f7d61a837a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i | with stop words without\n",
      "--| --------------- ------------\n",
      " 1| 'USS'           'USS'\n",
      " 2| 'Enterprise'    'Enterprise'\n",
      " 3| '('             '('\n",
      " 4| 'NCC-1701'      'NCC-1701'\n",
      " 5| '-'             '-'\n",
      " 6| 'D'             'D'\n",
      " 7| ')'             ')'\n",
      " 8| '\\n\\n'          '\\n\\n'\n",
      " 9| '\"'             '\"'\n",
      "10| 'For'           ''\n",
      "11| 'five'          ''\n",
      "12| 'hundred'       ''\n",
      "13| 'years'         'years'\n",
      "14| ','             ','\n",
      "15| 'every'         ''\n",
      "16| 'ship'          'ship'\n",
      "17| 'that'          ''\n",
      "18| 'has'           ''\n",
      "19| 'borne'         'borne'\n",
      "20| 'the'           ''\n",
      "21| 'name'          ''\n",
      "22| 'of'            ''\n",
      "23| 'the'           ''\n",
      "24| 'Enterprise'    'Enterprise'\n",
      "25| 'has'           ''\n",
      "26| 'become'        ''\n",
      "27| 'a'             ''\n",
      "28| 'legend'        'legend'\n",
      "29| '.'             '.'\n"
     ]
    }
   ],
   "source": [
    "## spaCy\n",
    "print('i | with stop words without')\n",
    "print('--| --------------- ------------')\n",
    "\n",
    "# for all the tokens\n",
    "for i, t in enumerate(doc):\n",
    "    print('%2d| %-15r %r' % (i+1, t.text, ('' if t.is_stop else t.text)))\n",
    "\n",
    "    # break after the first sentence\n",
    "    if t.text == '.':\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:22:05.293365Z",
     "start_time": "2019-06-17T01:22:04.981199Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "B2LoqLmULNPs",
    "outputId": "63f83744-f889-462f-f166-d8add6a03f7e"
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_words(['%r' % t.text for t in doc if not (t.is_stop | t.is_punct)])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "9uqME12uLNPu"
   },
   "source": [
    "### Check Part of Speech"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:22:17.213316Z",
     "start_time": "2019-06-17T01:22:17.169434Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "vD-BrcLALNPz",
    "outputId": "a26b4e4f-095a-4086-a8fe-841cbbfb5b05"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 1|'USS'        : PROPN NNP\n",
      " 2|'Enterprise' : PROPN NNP\n",
      " 3|'('          : PUNCT -LRB-\n",
      " 4|'NCC-1701'   : PROPN NNP\n",
      " 5|'-'          : PUNCT HYPH\n",
      " 6|'D'          : PROPN NNP\n",
      " 7|')'          : PUNCT -RRB-\n",
      " 8|'\\n\\n'       : SPACE _SP\n",
      " 9|'\"'          : PUNCT ``\n",
      "10|'For'        : ADP   IN\n",
      "11|'five'       : NUM   CD\n",
      "12|'hundred'    : NUM   CD\n",
      "13|'years'      : NOUN  NNS\n",
      "14|','          : PUNCT ,\n",
      "15|'every'      : DET   DT\n",
      "16|'ship'       : NOUN  NN\n",
      "17|'that'       : DET   WDT\n",
      "18|'has'        : AUX   VBZ\n",
      "19|'borne'      : VERB  VBN\n",
      "20|'the'        : DET   DT\n",
      "21|'name'       : NOUN  NN\n",
      "22|'of'         : ADP   IN\n",
      "23|'the'        : DET   DT\n",
      "24|'Enterprise' : PROPN NNP\n",
      "25|'has'        : AUX   VBZ\n",
      "26|'become'     : VERB  VBN\n",
      "27|'a'          : DET   DT\n",
      "28|'legend'     : NOUN  NN\n",
      "29|'.'          : PUNCT .\n"
     ]
    }
   ],
   "source": [
    "## spaCy\n",
    "for i, t in enumerate(doc):\n",
    "    print('%2d|%-12r : %-5s %s' % (i+1, t.text, t.pos_, t.tag_))\n",
    "    if t.text == '.':\n",
    "        break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Lemmatisation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:22:53.270758Z",
     "start_time": "2019-06-17T01:22:53.220888Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "448zp9_vLNQC",
    "outputId": "561168c1-3a42-449d-9be3-dd22182459c3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i | Token        Lemma\n",
      "--| ------------ ------------\n",
      " 1| 'USS'        'USS'\n",
      " 2| 'Enterprise' 'Enterprise'\n",
      " 3| '('          '('\n",
      " 4| 'NCC-1701'   'NCC-1701'\n",
      " 5| '-'          '-'\n",
      " 6| 'D'          'D'\n",
      " 7| ')'          ')'\n",
      " 8| '\\n\\n'       '\\n\\n'\n",
      " 9| '\"'          '\"'\n",
      "10| 'For'        'for'\n",
      "11| 'five'       'five'\n",
      "12| 'hundred'    'hundred'\n",
      "13| 'years'      'year'\n",
      "14| ','          ','\n",
      "15| 'every'      'every'\n",
      "16| 'ship'       'ship'\n",
      "17| 'that'       'that'\n",
      "18| 'has'        'have'\n",
      "19| 'borne'      'bear'\n",
      "20| 'the'        'the'\n",
      "21| 'name'       'name'\n",
      "22| 'of'         'of'\n",
      "23| 'the'        'the'\n",
      "24| 'Enterprise' 'Enterprise'\n",
      "25| 'has'        'have'\n",
      "26| 'become'     'become'\n",
      "27| 'a'          'a'\n",
      "28| 'legend'     'legend'\n",
      "29| '.'          '.'\n"
     ]
    }
   ],
   "source": [
    "## spaCy\n",
    "print('i | Token        Lemma')\n",
    "print('--| ------------ ------------')\n",
    "for i, t in enumerate(doc):\n",
    "    print('%2d| %-12r %r' % (i+1, t.text, t.lemma_))\n",
    "    if t.text == '.':\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:22:56.143434Z",
     "start_time": "2019-06-17T01:22:55.839376Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "i-7pqVMxLNQD",
    "outputId": "6deff35e-0d28-4351-bbab-7600618eb817"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_words(['%r' % t.lemma_ for t in doc if not (t.is_stop | t.is_punct)])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "RHUdgHM7LNQF"
   },
   "source": [
    "### Entity Recognition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:23:02.688863Z",
     "start_time": "2019-06-17T01:23:02.464460Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "yyOrZ42oLNQH",
    "outputId": "dfcee498-0002-4064-98ca-fa11668978d5",
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0: USS Enterprise (NCC-1701-D)\"\n",
      "================================================================================\n",
      " 1: For five hundred years, every ship that has borne the name of the Enterprise has become a legend.\n",
      "--------------------------------------------------------------------------------\n",
      "DATE       : five hundred years\n",
      "ORG        : Enterprise\n",
      "================================================================================\n",
      " 2: This one is no different.\"\n",
      "================================================================================\n",
      " 3: \n",
      "================================================================================\n",
      " 4: The USS Enterprise (NCC-1701-D) was a 24th century United Federation of Planets Galaxy Class starship operated by Starfleet, and the fifth Federation ship to bear the name Enterprise.\n",
      "--------------------------------------------------------------------------------\n",
      "WORK_OF_ART: The USS Enterprise\n",
      "DATE       : a 24th century\n",
      "ORG        : United Federation of Planets Galaxy\n",
      "PERSON     : Starfleet\n",
      "PRODUCT    : Enterprise\n",
      "================================================================================\n",
      " 5: During her career, the Enterprise served as the Federation flagship.\n",
      "--------------------------------------------------------------------------------\n",
      "ORG        : Enterprise\n",
      "================================================================================\n",
      " 6: The Enterprise was destroyed during the Battle of Veridian III in 2371.\n",
      "--------------------------------------------------------------------------------\n",
      "EVENT      : the Battle of Veridian III\n",
      "DATE       : 2371\n",
      "================================================================================\n",
      " 7: =\n",
      "================================================================================\n",
      " 8: =\n",
      "================================================================================\n",
      " 9: History===\n",
      "================================================================================\n",
      "10: ==\n",
      "================================================================================\n",
      "11: Construction and launch===The Enterprise was built at Utopia Planitia Fleet Yards orbiting Mars in the Solar system.\n",
      "--------------------------------------------------------------------------------\n",
      "ORG        : Utopia Planitia Fleet Yards\n",
      "LOC        : Mars\n",
      "================================================================================\n",
      "12: The construction was a massive undertaking, involving thousands of people across disciplines.\n",
      "--------------------------------------------------------------------------------\n",
      "CARDINAL   : thousands\n",
      "================================================================================\n",
      "13: Construction was supervised by Commander Orfil Quinteros.\n",
      "--------------------------------------------------------------------------------\n",
      "PERSON     : Orfil Quinteros\n",
      "================================================================================\n",
      "14: Dr. Leah Brahms was responsible for much of the Enterprise's warp propulsion system design.\n",
      "--------------------------------------------------------------------------------\n",
      "PERSON     : Leah Brahms\n",
      "ORG        : Enterprise\n",
      "================================================================================\n",
      "15: Some of the Enterprise's components were derived from technology originally developed on the USS Pegasus.\n",
      "--------------------------------------------------------------------------------\n",
      "ORG        : Enterprise\n",
      "PRODUCT    : the USS Pegasus\n",
      "================================================================================\n",
      "16: One of the ship's nacelle tube was the site of a multiple murder-suicide while she was still under construction at Utopia Planitia.\n",
      "--------------------------------------------------------------------------------\n",
      "CARDINAL   : One\n",
      "PERSON     : nacelle tube\n",
      "ORG        : Utopia Planitia\n",
      "================================================================================\n",
      "17: A member of the construction team, Walter Pierce, became jealous of a former lover's new relationship.\n",
      "--------------------------------------------------------------------------------\n",
      "PERSON     : Walter Pierce\n",
      "================================================================================\n",
      "18: He killed the two officers, Marla Finn and William Hodges, then disposed of their bodies in the plasma stream.\n",
      "--------------------------------------------------------------------------------\n",
      "CARDINAL   : two\n",
      "PERSON     : Marla Finn\n",
      "PERSON     : William Hodges\n",
      "================================================================================\n",
      "19: Pierce committed suicide in the same manner, leaving a telepathic imprint in a bulkhead that was not discovered until 2370.\n",
      "--------------------------------------------------------------------------------\n",
      "DATE       : 2370\n",
      "================================================================================\n",
      "20: On stardate 40759.5, in the year 2363, the Enterprise was launched from Mars.\n",
      "--------------------------------------------------------------------------------\n",
      "CARDINAL   : 40759.5\n",
      "DATE       : the year 2363\n",
      "ORG        : Enterprise\n",
      "LOC        : Mars\n",
      "================================================================================\n",
      "21: On stardate 41025.5, the Enterprise was commissioned.\n",
      "--------------------------------------------------------------------------------\n",
      "CARDINAL   : 41025.5\n",
      "ORG        : Enterprise\n",
      "================================================================================\n",
      "22: These stardates weren't mentioned in dialog; they were from the Enterprise dedication plaque.\n",
      "--------------------------------------------------------------------------------\n",
      "PRODUCT    : Enterprise\n",
      "================================================================================\n",
      "23: Final systems completion and shakedown was conducted at Earth Station McKinley.\n",
      "--------------------------------------------------------------------------------\n",
      "LOC        : Earth Station McKinley\n",
      "================================================================================\n",
      "24: Captain Jean-Luc Picard took command of the ship on stardate 41148 at the order of Rear Admiral Norah Satie.\n",
      "--------------------------------------------------------------------------------\n",
      "PERSON     : Jean-Luc Picard\n",
      "DATE       : 41148\n",
      "PERSON     : Norah Satie\n",
      "================================================================================\n",
      "25: =\n",
      "================================================================================\n",
      "26: ==\n",
      "================================================================================\n",
      "27: Legacy===Commander Riker was upset over the loss of the Enterprise.\n",
      "--------------------------------------------------------------------------------\n",
      "ORG        : Legacy===\n",
      "PERSON     : Riker\n",
      "================================================================================\n",
      "28: Having hoped he would one day command the ship, he was disappointed that he never got that opportunity.\n",
      "--------------------------------------------------------------------------------\n",
      "DATE       : one day\n",
      "================================================================================\n",
      "29: However, Picard expressed doubt that the Enterprise-D would be the last vessel to carry the name.\n",
      "--------------------------------------------------------------------------------\n",
      "PERSON     : Picard\n",
      "LAW        : the Enterprise-D\n",
      "================================================================================\n",
      "30: \n",
      "================================================================================\n",
      "31: The Enterprise was so dear to Worf that, shortly after being reassigned to Deep Space 9 in 2372, he briefly considered resigning from Starfleet.\n",
      "--------------------------------------------------------------------------------\n",
      "ORG        : Deep Space\n",
      "CARDINAL   : 9\n",
      "DATE       : 2372\n",
      "GPE        : Starfleet\n",
      "================================================================================\n",
      "32: Station commander Captain Benjamin Sisko expressed regret on the loss of the Enterprise and offered his condolences over the destruction of the ship to Worf, saying the Enterprise \"was a good ship.\"\n",
      "--------------------------------------------------------------------------------\n",
      "PERSON     : Benjamin Sisko\n",
      "ORG        : Enterprise\n",
      "PERSON     : Worf\n",
      "================================================================================\n",
      "33: Captain Picard's belief that the Enterprise-D would not be the final ship to bear the name was borne out with the christening of the Class Sovereign USS Enterprise NCC-1701-E, later the same year.\n",
      "--------------------------------------------------------------------------------\n",
      "PERSON     : Picard\n",
      "LAW        : the Enterprise-D\n",
      "DATE       : later the same year\n",
      "================================================================================\n",
      "34: In that instance, the legacy of the Enterprise continued with Picard reprising his role as CO and selecting most of the former crew from the Enterprise-D, with the notable exception of Worf due to his most recent assignment to DS9 (though he temporarily joined the Enterprise-E crew on several of their more notable missions).\n",
      "--------------------------------------------------------------------------------\n",
      "ORG        : Enterprise\n",
      "LAW        : the Enterprise-D\n",
      "================================================================================\n"
     ]
    }
   ],
   "source": [
    "## spaCy\n",
    "for i, s in enumerate(doc.sents):\n",
    "    print('%2d: %s' % (i, re.sub(r'\\n+', '', s.text)))\n",
    "    if s.as_doc().ents:\n",
    "        print('-'*80)\n",
    "        for e in s.as_doc().ents:\n",
    "            print('%-11s: %s' % (e.label_, re.sub(r'\\n+', '', e.text)))\n",
    "    print('='*80)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extra: Using NLTK for NLP\n",
    "\n",
    "### Tokenise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package punkt to C:\\Users\\Chong\n",
      "[nltk_data]     Meng\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Unzipping tokenizers\\punkt.zip.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('punkt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:18:26.276966Z",
     "start_time": "2019-06-17T01:18:26.186212Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "pML63M9KLNPX",
    "outputId": "29a6c627-0eee-4ece-bb34-47eacbbb53ff",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 1| 'USS'\n",
      " 2| 'Enterprise'\n",
      " 3| '('\n",
      " 4| 'NCC-1701-D'\n",
      " 5| ')'\n",
      " 6| \"''\"\n",
      " 7| 'For'\n",
      " 8| 'five'\n",
      " 9| 'hundred'\n",
      "10| 'years'\n",
      "11| ','\n",
      "12| 'every'\n",
      "13| 'ship'\n",
      "14| 'that'\n",
      "15| 'has'\n",
      "16| 'borne'\n",
      "17| 'the'\n",
      "18| 'name'\n",
      "19| 'of'\n",
      "20| 'the'\n",
      "21| 'Enterprise'\n",
      "22| 'has'\n",
      "23| 'become'\n",
      "24| 'a'\n",
      "25| 'legend'\n"
     ]
    }
   ],
   "source": [
    "# use nltk to find tokens\n",
    "tokens = nltk.word_tokenize(text)\n",
    "\n",
    "for i, t in enumerate(tokens[:25]):\n",
    "    print('%2d| %r' % (i+1, t))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:18:48.978316Z",
     "start_time": "2019-06-17T01:18:48.686799Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "G5C3ituYLNPZ",
    "outputId": "db39aade-f506-4b45-ed1e-56327c19e4f7"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_words(tokens)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stop words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to C:\\Users\\Chong\n",
      "[nltk_data]     Meng\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Unzipping corpora\\stopwords.zip.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('stopwords')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:20:00.638483Z",
     "start_time": "2019-06-17T01:20:00.617539Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "BnY2rFzuLNPj",
    "outputId": "f64087cd-8e4b-4df5-fb2d-7b04851bde34",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a, about, above, after, again, against, ain, all, am, an, and, any, are, aren, aren't, as, at, be, because, been, before, being, below, between, both, but, by, can, couldn, couldn't, d, did, didn, didn't, do, does, doesn, doesn't, doing, don, don't, down, during, each, few, for, from, further, had, hadn, hadn't, has, hasn, hasn't, have, haven, haven't, having, he, her, here, hers, herself, him, himself, his, how, i, if, in, into, is, isn, isn't, it, it's, its, itself, just, ll, m, ma, me, mightn, mightn't, more, most, mustn, mustn't, my, myself, needn, needn't, no, nor, not, now, o, of, off, on, once, only, or, other, our, ours, ourselves, out, over, own, re, s, same, shan, shan't, she, she's, should, should've, shouldn, shouldn't, so, some, such, t, than, that, that'll, the, their, theirs, them, themselves, then, there, these, they, this, those, through, to, too, under, until, up, ve, very, was, wasn, wasn't, we, were, weren, weren't, what, when, where, which, while, who, whom, why, will, with, won, won't, wouldn, wouldn't, y, you, you'd, you'll, you're, you've, your, yours, yourself, yourselves\n"
     ]
    }
   ],
   "source": [
    "stopWords = nltk.corpus.stopwords.words('english')\n",
    "\n",
    "stopWords.sort()\n",
    "print(', '.join(stopWords))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "dksPJF7YcI1o"
   },
   "outputs": [],
   "source": [
    "# ANSWER\n",
    "# NOTE: see the `.lower()` method applied to token\n",
    "tokens_no_stop = '' # create a list of tokens withOUT the stop words "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:21:23.469455Z",
     "start_time": "2019-06-17T01:21:23.412608Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "a82KBILRLNPm",
    "outputId": "b33cef88-79ab-4e06-9c0e-9f2a4a588306"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i | with stop words without\n",
      "--| --------------- ------------\n"
     ]
    },
    {
     "ename": "IndexError",
     "evalue": "string index out of range",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-51-49f3900d9a60>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      9\u001b[0m \u001b[1;32mwhile\u001b[0m \u001b[0mi\u001b[0m \u001b[1;33m<\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtokens\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     10\u001b[0m     \u001b[1;31m# same word\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 11\u001b[1;33m     \u001b[1;32mif\u001b[0m \u001b[0mtokens\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mtokens_no_stop\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     12\u001b[0m         \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'%2d| %-15r %r'\u001b[0m \u001b[1;33m%\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtokens\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtokens_no_stop\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     13\u001b[0m         \u001b[0mj\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mIndexError\u001b[0m: string index out of range"
     ]
    }
   ],
   "source": [
    "## NLTK\n",
    "i = 0\n",
    "j = 0\n",
    "\n",
    "print('i | with stop words without')\n",
    "print('--| --------------- ------------')\n",
    "\n",
    "# for all the tokens\n",
    "while i < len(tokens):\n",
    "    # same word\n",
    "    if tokens[i] == tokens_no_stop[j]:\n",
    "        print('%2d| %-15r %r' % (i+1, tokens[i], tokens_no_stop[j]))\n",
    "        j += 1\n",
    "    # not the same word\n",
    "    else:\n",
    "        print('%2d| %-15r' % (i+1, tokens[i]))\n",
    "\n",
    "    # next word\n",
    "    i += 1\n",
    "    # break after the first sentence\n",
    "    if tokens[i-1] == '.':\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:24:39.503538Z",
     "start_time": "2019-06-17T01:24:39.498514Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "uPtOoiwuLNPo"
   },
   "outputs": [],
   "source": [
    "# Create plot of words without stopword\n",
    "# ANSWER"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check Part of Speech"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:22:10.130223Z",
     "start_time": "2019-06-17T01:22:10.100306Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "KRupju0sLNPv"
   },
   "outputs": [],
   "source": [
    "# define PoS\n",
    "pos_list = {\n",
    "    'CC':   'coordinating conjunction',\n",
    "    'CD':   'cardinal digit',\n",
    "    'DT':   'determiner',\n",
    "    'EX':   'existential there (like: \"there is\" ... think of it like \"there exists\")',\n",
    "    'FW':   'foreign word',\n",
    "    'IN':   'preposition/subordinating conjunction',\n",
    "    'JJ':   'adjective \"big\"',\n",
    "    'JJR':  'adjective, comparative \"bigger\"',\n",
    "    'JJS':  'adjective, superlative \"biggest\"',\n",
    "    'LS':   'list marker 1)',\n",
    "    'MD':   'modal could, will',\n",
    "    'NN':   'noun, singular \"desk\"',\n",
    "    'NNS':  'noun plural \"desks\"',\n",
    "    'NNP':  'proper noun, singular \"Harrison\"',\n",
    "    'NNPS': 'proper noun, plural \"Americans\"',\n",
    "    'PDT':  'predeterminer \"all the kids\"',\n",
    "    'POS':  'possessive ending parent\"s',\n",
    "    'PRP':  'personal pronoun I, he, she',\n",
    "    'PRP$': 'possessive pronoun my, his, hers',\n",
    "    'RB':   'adverb very, silently,',\n",
    "    'RBR':  'adverb, comparative better',\n",
    "    'RBS':  'adverb, superlative best',\n",
    "    'RP':   'particle give up',\n",
    "    'TO':   'to go \"to\" the store.',\n",
    "    'UH':   'interjection errrrrrrrm',\n",
    "    'VB':   'verb, base form take',\n",
    "    'VBD':  'verb, past tense took',\n",
    "    'VBG':  'verb, gerund/present participle taking',\n",
    "    'VBN':  'verb, past participle taken',\n",
    "    'VBP':  'verb, sing. present, non-3d take',\n",
    "    'VBZ':  'verb, 3rd person sing. present takes',\n",
    "    'WDT':  'wh-determiner which',\n",
    "    'WP':   'wh-pronoun who, what',\n",
    "    'WP$':  'possessive wh-pronoun whose',\n",
    "    'WRB':  'wh-abverb where, when',\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
      "[nltk_data]     C:\\Users\\Chong Meng\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Unzipping taggers\\averaged_perceptron_tagger.zip.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('averaged_perceptron_tagger')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:22:13.969590Z",
     "start_time": "2019-06-17T01:22:13.665232Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "asqUoCHgLNPx",
    "outputId": "6e3cab17-f736-49f3-ce62-8e759d72ac35",
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 1|'USS'        : NNP  proper noun, singular \"Harrison\"\n",
      " 2|'Enterprise' : NNP  proper noun, singular \"Harrison\"\n",
      " 3|'('          : (    -\n",
      " 4|'NCC-1701-D' : NNP  proper noun, singular \"Harrison\"\n",
      " 5|')'          : )    -\n",
      " 6|\"''\"         : ''   -\n",
      " 7|'For'        : IN   preposition/subordinating conjunction\n",
      " 8|'five'       : CD   cardinal digit\n",
      " 9|'hundred'    : CD   cardinal digit\n",
      "10|'years'      : NNS  noun plural \"desks\"\n",
      "11|','          : ,    -\n",
      "12|'every'      : DT   determiner\n",
      "13|'ship'       : NN   noun, singular \"desk\"\n",
      "14|'that'       : WDT  wh-determiner which\n",
      "15|'has'        : VBZ  verb, 3rd person sing. present takes\n",
      "16|'borne'      : VBN  verb, past participle taken\n",
      "17|'the'        : DT   determiner\n",
      "18|'name'       : NN   noun, singular \"desk\"\n",
      "19|'of'         : IN   preposition/subordinating conjunction\n",
      "20|'the'        : DT   determiner\n",
      "21|'Enterprise' : NNP  proper noun, singular \"Harrison\"\n",
      "22|'has'        : VBZ  verb, 3rd person sing. present takes\n",
      "23|'become'     : VBN  verb, past participle taken\n",
      "24|'a'          : DT   determiner\n",
      "25|'legend'     : NN   noun, singular \"desk\"\n"
     ]
    }
   ],
   "source": [
    "## nltk\n",
    "tagged = nltk.pos_tag(tokens)\n",
    "\n",
    "for i, t in enumerate(tagged[:25]):\n",
    "    print('%2d|%-12r : %-4s %s' % (i+1, t[0], t[1], (pos_list[t[1]] if t[1] in pos_list else '-')))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "_n9qMgyULNP1"
   },
   "source": [
    "### Stemming"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:22:29.259531Z",
     "start_time": "2019-06-17T01:22:29.243588Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "pL1vRUzxLNP2"
   },
   "outputs": [],
   "source": [
    "## nltk\n",
    "ps = nltk.porter.PorterStemmer()\n",
    "stemmed = ' '.join([ps.stem(word) for word in text.split()])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "2d9a6QazLNP4"
   },
   "source": [
    "### Lemmatisation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package wordnet to C:\\Users\\Chong\n",
      "[nltk_data]     Meng\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package wordnet is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('wordnet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:22:33.219077Z",
     "start_time": "2019-06-17T01:22:31.251647Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "OAbriUsXLNP7",
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "## nltk\n",
    "wl = nltk.stem.WordNetLemmatizer()\n",
    "lemma = ' '.join([wl.lemmatize(word) for word in text.split()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:22:40.296601Z",
     "start_time": "2019-06-17T01:22:40.251721Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "yVIqX7HBLNP9",
    "outputId": "26f47e5f-7927-4ceb-e7aa-148b1a0d6798"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i | Stem           Lemma\n",
      "--| -------------- ------------\n",
      " 1| 'uss'          'USS'       \n",
      " 2| 'enterpris'    'Enterprise'\n",
      " 3| '(ncc-1701-d)'   '(NCC-1701-D)'\n",
      " 4| '\"for'         '\"For'      \n",
      " 5| 'five'         'five'      \n",
      " 6| 'hundr'        'hundred'   \n",
      " 7| 'years,'       'years,'    \n",
      " 8| 'everi'        'every'     \n",
      " 9| 'ship'         'ship'      \n",
      "10| 'that'         'that'      \n",
      "11| 'ha'           'ha'        \n",
      "12| 'born'         'borne'     \n",
      "13| 'the'          'the'       \n",
      "14| 'name'         'name'      \n",
      "15| 'of'           'of'        \n",
      "16| 'the'          'the'       \n",
      "17| 'enterpris'    'Enterprise'\n",
      "18| 'ha'           'ha'        \n",
      "19| 'becom'        'become'    \n",
      "20| 'a'            'a'         \n",
      "21| 'legend.'      'legend.'   \n"
     ]
    }
   ],
   "source": [
    "## nltk\n",
    "dot = stemmed.find('.') + 1\n",
    "sl = stemmed[:dot].split()\n",
    "dot = lemma.find('.') + 1\n",
    "ll = lemma[:dot].split()\n",
    "\n",
    "print('i | Stem           Lemma')\n",
    "print('--| -------------- ------------')\n",
    "for i, p in enumerate(zip(sl, ll)):\n",
    "    print('%2d| %-12r   %-12r' % (i+1, p[0], p[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:22:47.305414Z",
     "start_time": "2019-06-17T01:22:47.017187Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "eG4yOgwVLNP-",
    "outputId": "70476f16-7ac6-4c40-e39f-7a6547c11fec"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_words(stemmed.split())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:22:50.433861Z",
     "start_time": "2019-06-17T01:22:50.144603Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "uEJR57TYLNQA",
    "outputId": "e96f9bb4-cdfc-432c-b0af-bcdb3a6c2c6c",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_words(lemma.split())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Entity recognition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package maxent_ne_chunker to C:\\Users\\Chong\n",
      "[nltk_data]     Meng\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package maxent_ne_chunker is already up-to-date!\n",
      "[nltk_data] Downloading package words to C:\\Users\\Chong\n",
      "[nltk_data]     Meng\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Unzipping corpora\\words.zip.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('maxent_ne_chunker')\n",
    "nltk.download('words')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-17T01:22:59.142869Z",
     "start_time": "2019-06-17T01:22:58.754906Z"
    },
    "colab": {},
    "colab_type": "code",
    "id": "sw6fYdgXLNQG",
    "outputId": "a83ea9db-825d-4031-8112-f022b71f565b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ORGANIZATION: USS Enterprise\n",
      "ORGANIZATION: Enterprise\n",
      "ORGANIZATION: USS Enterprise\n",
      "PERSON      : United Federation\n",
      "ORGANIZATION: Planets Galaxy\n",
      "PERSON      : Starfleet\n",
      "ORGANIZATION: Enterprise\n",
      "ORGANIZATION: Federation\n",
      "ORGANIZATION: Battle\n",
      "GPE         : Veridian\n",
      "ORGANIZATION: Utopia Planitia Fleet\n",
      "PERSON      : Mars\n",
      "ORGANIZATION: Solar\n",
      "ORGANIZATION: Commander Orfil Quinteros\n",
      "PERSON      : Brahms\n",
      "ORGANIZATION: Enterprise\n",
      "ORGANIZATION: Enterprise\n",
      "ORGANIZATION: USS Pegasus\n",
      "ORGANIZATION: Utopia Planitia\n",
      "PERSON      : Walter Pierce\n",
      "PERSON      : Marla Finn\n",
      "PERSON      : William Hodges\n",
      "PERSON      : Pierce\n",
      "ORGANIZATION: Enterprise\n",
      "PERSON      : Mars\n",
      "ORGANIZATION: Enterprise\n",
      "ORGANIZATION: Enterprise\n",
      "FACILITY    : Earth Station McKinley\n",
      "PERSON      : Captain Jean-Luc Picard\n",
      "ORGANIZATION: Rear Admiral Norah Satie\n",
      "ORGANIZATION: Commander Riker\n",
      "ORGANIZATION: Enterprise\n",
      "PERSON      : Picard\n",
      "PERSON      : Deep Space\n",
      "GPE         : Starfleet\n",
      "PERSON      : Captain Benjamin Sisko\n",
      "ORGANIZATION: Enterprise\n",
      "GPE         : Worf\n",
      "ORGANIZATION: Enterprise\n",
      "PERSON      : Picard\n",
      "ORGANIZATION: Class Sovereign\n",
      "ORGANIZATION: Enterprise\n",
      "PERSON      : Picard\n",
      "ORGANIZATION: CO\n",
      "GPE         : Worf\n",
      "ORGANIZATION: DS9\n"
     ]
    }
   ],
   "source": [
    "## nltk\n",
    "entities = nltk.chunk.ne_chunk(tagged)\n",
    "\n",
    "for e in entities:\n",
    "    s = re.sub(r'[\\(\\)]', '', str(e))\n",
    "    if s.find('/NNP') > 0:\n",
    "        t = s.split()[0]\n",
    "        n = ' '.join([re.sub(r'/NNP', '', x) for x in s.split()[1:]])\n",
    "        print('%-12s: %s' % (t, n))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "RERADKgNFq9T"
   },
   "source": [
    "\n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "\n",
    "> > > > > > > > > © 2021 Institute of Data\n",
    "\n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "name": "IOD_Lab-9_5.ipynb",
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   "language": "python",
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   "types_to_exclude": [
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