{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import nltk\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.tokenize import word_tokenize\n",
    "from collections import Counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package punkt to\n",
      "[nltk_data]     C:\\Users\\felix\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package punkt is already up-to-date!\n",
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     C:\\Users\\felix\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# nltk count words\n",
    "nltk.download('punkt')\n",
    "nltk.download('stopwords')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# dataset wocka"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the data from the JSON file\n",
    "data_path = './data/wocka.json'\n",
    "with open(data_path) as f:\n",
    "    data = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>body</th>\n",
       "      <th>category</th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>What do you call a cow with no legs?\\r\\n\\r\\nGr...</td>\n",
       "      <td>Animal</td>\n",
       "      <td>1</td>\n",
       "      <td>Cow With No Legs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>What do you call a cow jumping over a barbed w...</td>\n",
       "      <td>Animal</td>\n",
       "      <td>2</td>\n",
       "      <td>Jumping Cow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>What's black and white and red all over?\\r\\n\\r...</td>\n",
       "      <td>Other / Misc</td>\n",
       "      <td>4</td>\n",
       "      <td>Black, White and Red</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>So, this guy walks into a bar.\\r\\n\\r\\nAnd says...</td>\n",
       "      <td>Bar</td>\n",
       "      <td>5</td>\n",
       "      <td>Guy in a Bar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>If the opposite of pro is con, isn't the oppos...</td>\n",
       "      <td>One Liners</td>\n",
       "      <td>6</td>\n",
       "      <td>Progress</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                body      category  id  \\\n",
       "0  What do you call a cow with no legs?\\r\\n\\r\\nGr...        Animal   1   \n",
       "1  What do you call a cow jumping over a barbed w...        Animal   2   \n",
       "2  What's black and white and red all over?\\r\\n\\r...  Other / Misc   4   \n",
       "3  So, this guy walks into a bar.\\r\\n\\r\\nAnd says...           Bar   5   \n",
       "4  If the opposite of pro is con, isn't the oppos...    One Liners   6   \n",
       "\n",
       "                  title  \n",
       "0      Cow With No Legs  \n",
       "1           Jumping Cow  \n",
       "2  Black, White and Red  \n",
       "3          Guy in a Bar  \n",
       "4              Progress  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create pandas dataframe of the data\n",
    "df = pd.DataFrame(data)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Animal\n",
      "At Work\n",
      "Bar\n",
      "Blond\n",
      "Blonde\n",
      "Children\n",
      "College\n",
      "Gross\n",
      "Insults\n",
      "Knock-Knock\n",
      "Lawyer\n",
      "Lightbulb\n",
      "Medical\n",
      "Men / Women\n",
      "News / Politics\n",
      "One Liners\n",
      "Other / Misc\n",
      "Puns\n",
      "Redneck\n",
      "Religious\n",
      "Sports\n",
      "Tech\n",
      "Yo Mama\n",
      "Yo Momma\n",
      "amount of categories: 24\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#print unique categories\n",
    "categories = df['category'].unique()\n",
    "categories= sorted(categories)\n",
    "for category in categories:\n",
    "    print(category)\n",
    "print('amount of categories:', len(categories))\n",
    "# plot the distribution of categories\n",
    "category_counts = df['category'].value_counts()\n",
    "category_counts.plot(kind='bar')\n",
    "plt.title('Jokes per category')\n",
    "plt.ylabel('Number of jokes')\n",
    "plt.xlabel('Category')\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "stop_words = set(stopwords.words('english'))\n",
    "\n",
    "# get all the jokes\n",
    "jokes = df['body'].values\n",
    "\n",
    "# tokenize the jokes\n",
    "tokenized_jokes = [word_tokenize(joke) for joke in jokes]\n",
    "\n",
    "# remove stop words\n",
    "filtered_jokes = [[word for word in joke if word.lower() not in stop_words] for joke in tokenized_jokes]\n",
    "\n",
    "# count the number of words in each joke\n",
    "word_counts = [len(joke) for joke in filtered_jokes]\n",
    "\n",
    "# plot the distribution of word counts\n",
    "plt.hist(word_counts, bins=100)\n",
    "plt.xlabel('Number of Words')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Distribution of Word Counts in Jokes')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ". 71849\n",
      ", 61789\n",
      "'' 25674\n",
      "`` 23253\n",
      "? 14285\n",
      "! 10304\n",
      ": 10000\n",
      "'s 9615\n",
      "n't 6959\n",
      "-- 5676\n",
      "said 4701\n",
      ") 3969\n",
      "man 3745\n",
      "one 3715\n",
      "* 3580\n",
      "- 3213\n",
      "says 2901\n",
      "get 2802\n",
      "... 2630\n",
      "( 2429\n",
      "like 2314\n",
      "would 2205\n",
      "know 2083\n",
      "'m 2081\n",
      "asked 2054\n",
      "' 1964\n",
      "back 1959\n",
      "'re 1951\n",
      "time 1843\n",
      "go 1835\n",
      "day 1812\n",
      "got 1661\n",
      "first 1497\n",
      "people 1455\n",
      "say 1431\n",
      "could 1419\n",
      "two 1415\n",
      "'ll 1373\n",
      "went 1346\n",
      "take 1301\n",
      "little 1298\n",
      "see 1289\n",
      "; 1260\n",
      "wife 1238\n",
      "going 1207\n",
      "old 1187\n",
      "'ve 1176\n",
      "want 1175\n",
      "woman 1156\n",
      "car 1156\n",
      "replied 1142\n",
      "Well 1139\n",
      "make 1126\n",
      "guy 1122\n",
      "blonde 1117\n",
      "think 1107\n",
      "home 1086\n",
      "$ 1074\n",
      "good 1054\n",
      "Q 1044\n",
      "next 1039\n",
      "around 1025\n",
      "One 1024\n",
      "2 1016\n",
      "right 976\n",
      "ca 975\n",
      "asks 967\n",
      "way 959\n",
      "Yo 953\n",
      "new 952\n",
      "tell 948\n",
      "put 947\n",
      "call 942\n",
      "'d 934\n",
      "1 933\n",
      "came 920\n",
      "3 892\n",
      "told 883\n",
      "boy 877\n",
      "come 834\n",
      "God 826\n",
      "never 818\n",
      "room 816\n",
      "name 816\n",
      "door 808\n",
      "really 806\n",
      "night 803\n",
      "house 800\n",
      "goes 794\n",
      "look 767\n",
      "• 767\n",
      "love 758\n",
      "give 755\n",
      "dog 754\n",
      "work 752\n",
      "still 734\n",
      "called 724\n",
      "years 719\n",
      "last 712\n",
      "Oh 712\n"
     ]
    }
   ],
   "source": [
    "# count the frequency of each word\n",
    "word_freq = Counter()\n",
    "for joke in filtered_jokes:\n",
    "    word_freq.update(joke)\n",
    "\n",
    "# get the most common words\n",
    "most_common = word_freq.most_common(100)\n",
    "\n",
    "for word, count in most_common:\n",
    "    print(word, count)"
   ]
  }
 ],
 "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": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}