FetchCryptocurrencyNews.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Obtain news article"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install -r requirements.txt "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from joblib import Parallel, delayed\n",
    "import joblib\n",
    "import nltk\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "from nltk.corpus import stopwords\n",
    "from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator\n",
    "from collections import defaultdict,Counter\n",
    "import re\n",
    "from nltk.stem import WordNetLemmatizer,PorterStemmer\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nltk.download('stopwords')\n",
    "\n",
    "stop=set(stopwords.words('english'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import packages\n",
    "# Default packages\n",
    "import time\n",
    "import csv\n",
    "import os\n",
    "import json\n",
    "\n",
    "\n",
    "# Preinstalled packages\n",
    "import requests\n",
    "import pandas as pd\n",
    "\n",
    "# URL of our News API\n",
    "base_url = 'https://api.newscatcherapi.com/v2/search?lang=en'\n",
    "\n",
    "# Your API key\n",
    "X_API_KEY = 'YHBKmAH0DbzXSs_h7be46br_kfw3EhBcqXPtCTSg1Qc'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'X_API_KEY' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[1], line 2\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[39m# Put your API key to headers in order to be authorized to perform a call\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m headers \u001b[39m=\u001b[39m {\u001b[39m'\u001b[39m\u001b[39mx-api-key\u001b[39m\u001b[39m'\u001b[39m: X_API_KEY}\n\u001b[0;32m      3\u001b[0m \u001b[39m# Define your desired parameters\u001b[39;00m\n\u001b[0;32m      4\u001b[0m params \u001b[39m=\u001b[39m [\n\u001b[0;32m      5\u001b[0m     {\n\u001b[0;32m      6\u001b[0m         \u001b[39m'\u001b[39m\u001b[39mq\u001b[39m\u001b[39m'\u001b[39m: \u001b[39m'\u001b[39m\u001b[39mBitcoin\u001b[39m\u001b[39m'\u001b[39m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     14\u001b[0m     }\n\u001b[0;32m     15\u001b[0m ]\n",
      "\u001b[1;31mNameError\u001b[0m: name 'X_API_KEY' is not defined"
     ]
    }
   ],
   "source": [
    "# Put your API key to headers in order to be authorized to perform a call\n",
    "headers = {'x-api-key': X_API_KEY}\n",
    "# Define your desired parameters\n",
    "# params = [\n",
    "#     {\n",
    "#         'q': 'Bitcoin',\n",
    "#         'lang': 'en',\n",
    "#         'to_rank': 10000,\n",
    "#         'topic': \"business\",\n",
    "#         'page_size': 100,\n",
    "#         'page': 1,\n",
    "#         'from' : \"2015/01/01\",\n",
    "#         'to': \"2019/12/31\"\n",
    "#     }\n",
    "# ]\n",
    "\n",
    "params = [\n",
    "    {\n",
    "        'q': 'Bitcoin',\n",
    "        'lang': 'en',\n",
    "        'to_rank': 10000,\n",
    "        'topic': \"business\",\n",
    "        'page_size': 100,\n",
    "        'page': 1\n",
    "    }\n",
    "]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Query in use => {'q': 'Bitcoin', 'lang': 'en', 'to_rank': 10000, 'topic': 'business', 'page_size': 100, 'page': 1}\n",
      "Done for page number => 1\n",
      "Proceed extracting page number => 2\n",
      "Done for page number => 2\n",
      "All articles have been extracted\n"
     ]
    }
   ],
   "source": [
    "# Variable to store all found news articles, mp stands for \"multiple queries\"\n",
    "all_news_articles_mp = []\n",
    "\n",
    "# Infinite loop which ends when all articles are extracted\n",
    "for separated_param in params:\n",
    "\n",
    "    print(f'Query in use => {str(separated_param)}')\n",
    "    \n",
    "    while True:\n",
    "        # Wait for 1 second between each call\n",
    "        time.sleep(1)\n",
    "\n",
    "        # GET Call from previous section enriched with some logs\n",
    "        response = requests.get(base_url, headers=headers, params=separated_param)\n",
    "        results = json.loads(response.text.encode())\n",
    "        if response.status_code == 200:\n",
    "            print(f'Done for page number => {separated_param[\"page\"]}')\n",
    "\n",
    "\n",
    "            # Adding your parameters to each result to be able to explore afterwards\n",
    "            for i in results['articles']:\n",
    "                i['used_params'] = str(separated_param)\n",
    "\n",
    "\n",
    "            # Storing all found articles\n",
    "            all_news_articles_mp.extend(results['articles'])\n",
    "\n",
    "            # Ensuring to cover all pages by incrementing \"page\" value at each iteration\n",
    "            separated_param['page'] += 1\n",
    "            if separated_param['page'] > results['total_pages']:\n",
    "                print(\"All articles have been extracted\")\n",
    "                break\n",
    "            else:\n",
    "                print(f'Proceed extracting page number => {separated_param[\"page\"]}')\n",
    "        else:\n",
    "            print(results)\n",
    "            print(f'ERROR: API call failed for page number => {separated_param[\"page\"]}')\n",
    "            break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of extracted articles => 104\n"
     ]
    }
   ],
   "source": [
    "print(f'Number of extracted articles => {str(len(all_news_articles_mp))}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define variables\n",
    "unique_ids = []\n",
    "all_news_articles = []\n",
    "\n",
    "# Iterate on each article and check whether we saw this _id before\n",
    "for article in all_news_articles_mp:\n",
    "    if article['_id'] not in unique_ids:\n",
    "        unique_ids.append(article['_id'])\n",
    "        all_news_articles.append(article)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import data into pandas\n",
    "pandas_table = pd.DataFrame(all_news_articles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>author</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bitcoin phone home: Use crypto to buy sim card...</td>\n",
       "      <td>Joe Hall</td>\n",
       "      <td>2023-08-08 12:55:00</td>\n",
       "      <td>full</td>\n",
       "      <td>https://cointelegraph.com/news/bitcoin-crypto-...</td>\n",
       "      <td>cointelegraph.com</td>\n",
       "      <td>A partnership between crypto marketplace Bitre...</td>\n",
       "      <td>A partnership between crypto e-commerce platfo...</td>\n",
       "      <td>cointelegraph.com</td>\n",
       "      <td>1696</td>\n",
       "      <td>business</td>\n",
       "      <td>US</td>\n",
       "      <td>en</td>\n",
       "      <td>Joe Hall</td>\n",
       "      <td>https://images.cointelegraph.com/images/1200_a...</td>\n",
       "      <td>False</td>\n",
       "      <td>@cointelegraph</td>\n",
       "      <td>11.274632</td>\n",
       "      <td>2e408dca78827908b28d0c6263a5d6b9</td>\n",
       "      <td>{'q': 'Bitcoin', 'lang': 'en', 'to_rank': 1000...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Speed Launches Magento Plugin, Simplifying Bit...</td>\n",
       "      <td>Jay Patel</td>\n",
       "      <td>2023-08-08 14:00:00</td>\n",
       "      <td>full</td>\n",
       "      <td>https://www.einnews.com/pr_news/647944000/spee...</td>\n",
       "      <td>einnews.com</td>\n",
       "      <td>Speed Launches Magento Plugin: Revolutionizing...</td>\n",
       "      <td>Speed Bitcoin Payment Processor\\n\\nSpeed Launc...</td>\n",
       "      <td>einnews.com</td>\n",
       "      <td>3825</td>\n",
       "      <td>business</td>\n",
       "      <td>UA</td>\n",
       "      <td>en</td>\n",
       "      <td>EIN News,Jay Patel</td>\n",
       "      <td>https://img.einnews.com/ampsize/515125/speed-b...</td>\n",
       "      <td>False</td>\n",
       "      <td>@einnews</td>\n",
       "      <td>11.272777</td>\n",
       "      <td>3b068f1da08f78cf0742e1f9e77f2a5e</td>\n",
       "      <td>{'q': 'Bitcoin', 'lang': 'en', 'to_rank': 1000...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>I write about the rapidly evolving VC and star...</td>\n",
       "      <td>Kjartan Rist</td>\n",
       "      <td>2023-08-10 13:31:17</td>\n",
       "      <td>full</td>\n",
       "      <td>https://www.forbes.com/sites/kjartanrist/2023/...</td>\n",
       "      <td>forbes.com</td>\n",
       "      <td>Is bitcoin finally breaking free of its associ...</td>\n",
       "      <td>The hype around the bitcoin price rollercoaste...</td>\n",
       "      <td>Copyright 2023 Forbes Media LLC</td>\n",
       "      <td>49</td>\n",
       "      <td>business</td>\n",
       "      <td>US</td>\n",
       "      <td>en</td>\n",
       "      <td>Kjartan Rist</td>\n",
       "      <td>https://imageio.forbes.com/specials-images/ima...</td>\n",
       "      <td>False</td>\n",
       "      <td>@forbes</td>\n",
       "      <td>11.264276</td>\n",
       "      <td>3c007d57c54e73306f8151687f3dc507</td>\n",
       "      <td>{'q': 'Bitcoin', 'lang': 'en', 'to_rank': 1000...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>The deadline for a ruling on Ark's application...</td>\n",
       "      <td>Bob Pisani</td>\n",
       "      <td>2023-08-07 12:30:00</td>\n",
       "      <td>timezone unknown</td>\n",
       "      <td>https://www.nbcphiladelphia.com/news/business/...</td>\n",
       "      <td>nbcphiladelphia.com</td>\n",
       "      <td>The SEC is required to give a thumbs up or thu...</td>\n",
       "      <td>It's put up or shut up time for the SEC on a b...</td>\n",
       "      <td>nbcphiladelphia.com</td>\n",
       "      <td>4181</td>\n",
       "      <td>business</td>\n",
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       "      <td>Bob Pisani,Bob Pisani Cnbc,CNBC</td>\n",
       "      <td>https://media.nbcphiladelphia.com/2023/08/1072...</td>\n",
       "      <td>False</td>\n",
       "      <td>@nbcphiladelphia</td>\n",
       "      <td>11.234709</td>\n",
       "      <td>b406883f25fa7ed168ccc79217cdc176</td>\n",
       "      <td>{'q': 'Bitcoin', 'lang': 'en', 'to_rank': 1000...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Leak Reveals BlackRock's Game-Changing Bitcoin...</td>\n",
       "      <td>Billy Bambrough</td>\n",
       "      <td>2023-08-09 22:45:24</td>\n",
       "      <td>full</td>\n",
       "      <td>https://www.forbes.com/sites/digital-assets/20...</td>\n",
       "      <td>forbes.com</td>\n",
       "      <td>Bitcoin, ethereum and other cryptocurrencies w...</td>\n",
       "      <td>Bitcoin BTC, ethereum and other cryptocurrenci...</td>\n",
       "      <td>Copyright 2023 Forbes Media LLC</td>\n",
       "      <td>49</td>\n",
       "      <td>business</td>\n",
       "      <td>US</td>\n",
       "      <td>en</td>\n",
       "      <td>Billy Bambrough,Senior Contributor</td>\n",
       "      <td>https://imageio.forbes.com/specials-images/ima...</td>\n",
       "      <td>False</td>\n",
       "      <td>@billybambrough</td>\n",
       "      <td>11.230986</td>\n",
       "      <td>ec6029fd5cc4a6ffa0ff4e2633d33b21</td>\n",
       "      <td>{'q': 'Bitcoin', 'lang': 'en', 'to_rank': 1000...</td>\n",
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      "text/plain": [
       "                                               title           author  \\\n",
       "0  Bitcoin phone home: Use crypto to buy sim card...         Joe Hall   \n",
       "1  Speed Launches Magento Plugin, Simplifying Bit...        Jay Patel   \n",
       "2  I write about the rapidly evolving VC and star...     Kjartan Rist   \n",
       "3  The deadline for a ruling on Ark's application...       Bob Pisani   \n",
       "4  Leak Reveals BlackRock's Game-Changing Bitcoin...  Billy Bambrough   \n",
       "\n",
       "        published_date published_date_precision  \\\n",
       "0  2023-08-08 12:55:00                     full   \n",
       "1  2023-08-08 14:00:00                     full   \n",
       "2  2023-08-10 13:31:17                     full   \n",
       "3  2023-08-07 12:30:00         timezone unknown   \n",
       "4  2023-08-09 22:45:24                     full   \n",
       "\n",
       "                                                link            clean_url  \\\n",
       "0  https://cointelegraph.com/news/bitcoin-crypto-...    cointelegraph.com   \n",
       "1  https://www.einnews.com/pr_news/647944000/spee...          einnews.com   \n",
       "2  https://www.forbes.com/sites/kjartanrist/2023/...           forbes.com   \n",
       "3  https://www.nbcphiladelphia.com/news/business/...  nbcphiladelphia.com   \n",
       "4  https://www.forbes.com/sites/digital-assets/20...           forbes.com   \n",
       "\n",
       "                                             excerpt  \\\n",
       "0  A partnership between crypto marketplace Bitre...   \n",
       "1  Speed Launches Magento Plugin: Revolutionizing...   \n",
       "2  Is bitcoin finally breaking free of its associ...   \n",
       "3  The SEC is required to give a thumbs up or thu...   \n",
       "4  Bitcoin, ethereum and other cryptocurrencies w...   \n",
       "\n",
       "                                             summary  \\\n",
       "0  A partnership between crypto e-commerce platfo...   \n",
       "1  Speed Bitcoin Payment Processor\\n\\nSpeed Launc...   \n",
       "2  The hype around the bitcoin price rollercoaste...   \n",
       "3  It's put up or shut up time for the SEC on a b...   \n",
       "4  Bitcoin BTC, ethereum and other cryptocurrenci...   \n",
       "\n",
       "                            rights  rank     topic country language  \\\n",
       "0                cointelegraph.com  1696  business      US       en   \n",
       "1                      einnews.com  3825  business      UA       en   \n",
       "2  Copyright 2023 Forbes Media LLC    49  business      US       en   \n",
       "3              nbcphiladelphia.com  4181  business      US       en   \n",
       "4  Copyright 2023 Forbes Media LLC    49  business      US       en   \n",
       "\n",
       "                              authors  \\\n",
       "0                            Joe Hall   \n",
       "1                  EIN News,Jay Patel   \n",
       "2                        Kjartan Rist   \n",
       "3     Bob Pisani,Bob Pisani Cnbc,CNBC   \n",
       "4  Billy Bambrough,Senior Contributor   \n",
       "\n",
       "                                               media  is_opinion  \\\n",
       "0  https://images.cointelegraph.com/images/1200_a...       False   \n",
       "1  https://img.einnews.com/ampsize/515125/speed-b...       False   \n",
       "2  https://imageio.forbes.com/specials-images/ima...       False   \n",
       "3  https://media.nbcphiladelphia.com/2023/08/1072...       False   \n",
       "4  https://imageio.forbes.com/specials-images/ima...       False   \n",
       "\n",
       "    twitter_account     _score                               _id  \\\n",
       "0    @cointelegraph  11.274632  2e408dca78827908b28d0c6263a5d6b9   \n",
       "1          @einnews  11.272777  3b068f1da08f78cf0742e1f9e77f2a5e   \n",
       "2           @forbes  11.264276  3c007d57c54e73306f8151687f3dc507   \n",
       "3  @nbcphiladelphia  11.234709  b406883f25fa7ed168ccc79217cdc176   \n",
       "4   @billybambrough  11.230986  ec6029fd5cc4a6ffa0ff4e2633d33b21   \n",
       "\n",
       "                                         used_params  \n",
       "0  {'q': 'Bitcoin', 'lang': 'en', 'to_rank': 1000...  \n",
       "1  {'q': 'Bitcoin', 'lang': 'en', 'to_rank': 1000...  \n",
       "2  {'q': 'Bitcoin', 'lang': 'en', 'to_rank': 1000...  \n",
       "3  {'q': 'Bitcoin', 'lang': 'en', 'to_rank': 1000...  \n",
       "4  {'q': 'Bitcoin', 'lang': 'en', 'to_rank': 1000...  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pandas_table.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'I write about the rapidly evolving VC and start-up sector in Europe'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pandas_table['title'][2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "      <th>0</th>\n",
       "      <td>Role of Bitcoin in the global financial system</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SEC Delays Decision on ARK Invest's Bitcoin ET...</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>I write about the rapidly evolving VC and star...</td>\n",
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       "      <th>3</th>\n",
       "      <td>Speed Launches Magento Plugin, Simplifying Bit...</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Bitcoin Trends To Watch In 2023: Nostr, Ordina...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               title\n",
       "0     Role of Bitcoin in the global financial system\n",
       "1  SEC Delays Decision on ARK Invest's Bitcoin ET...\n",
       "2  I write about the rapidly evolving VC and star...\n",
       "3  Speed Launches Magento Plugin, Simplifying Bit...\n",
       "4  Bitcoin Trends To Watch In 2023: Nostr, Ordina..."
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pandas_table[['title']]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(104, 1)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Shape of dataframe after dropping duplicates:  (104, 1)\n"
     ]
    }
   ],
   "source": [
    "df.drop_duplicates()\n",
    "print(\" Shape of dataframe after dropping duplicates: \", df.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Null Values in each column:\n",
      "    column name  Total missing  Percent missing\n",
      "0        title              0              0.0\n"
     ]
    }
   ],
   "source": [
    "#Null values\n",
    "\n",
    "null= df.isnull().sum().sort_values(ascending=False)\n",
    "total =df.shape[0]\n",
    "percent_missing= (df.isnull().sum()/total).sort_values(ascending=False)\n",
    "\n",
    "missing_data= pd.concat([null, percent_missing], axis=1, keys=['Total missing', 'Percent missing'])\n",
    "\n",
    "missing_data.reset_index(inplace=True)\n",
    "missing_data= missing_data.rename(columns= { \"index\": \" column name\"})\n",
    " \n",
    "print (\"Null Values in each column:\\n\", missing_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10, 5))\n",
    "\n",
    "headline_length = pandas_table['title'].str.len()\n",
    "ax.hist(headline_length, color='#17C37B')\n",
    "ax.set_title('Characters in Headlines')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,(ax1)=plt.subplots(figsize=(15,5))\n",
    "\n",
    "headline_length=pandas_table['title'].str.split().map(lambda x: len(x))\n",
    "ax1.hist(headline_length,color='#17C37B')\n",
    "ax1.set_title('Positive Sentiments')\n",
    "\n",
    "fig.suptitle('Words in a Headline')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Computing\\AppData\\Local\\Temp\\ipykernel_15284\\1251642903.py:4: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(word.map(lambda x: np.mean(x)),ax=ax1,color='#17C37B')\n"
     ]
    },
    {
     "data": {
      "image/png": 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oqKhjjt+3b5+Sk5N12WWXubY5nUdX7nJzc9Pu3buVkJBQ4xxPT095enqehfQAgKYsr6pUH2RuliQNC0pURxYSsMSDsSN0pKJAi7O36eZd72lx11vUxS/a6lgAAABohiwdiebh4aFevXppxYoVrm1Op1MrVqzQgAEDjjm+Q4cO2rZtmzZv3ux6XH755TrvvPO0efNmbtUEANQJh+nUexkbVOasUoxnkEaGdrQ6UrNlM2x6rt1YnRsYp2JHha7fMUeHyvOsjgUAAIBmyPKJXaZMmaKJEyeqd+/e6tu3r5599lmVlJRo8uTJkqQJEyaoZcuWmjlzpry8vNSlS5ca5wcFBUnSMdsBADhdK3L36EB5rjwNN10X1VtuRqOa/aDJ8bS5aXbH63TF1te1qzRD122fo0+736YgN2+rowEAAKAZsbxEu/rqq5WVlaWHHnpI6enp6tGjh5YuXepabODgwYOy2fjhBQBQP/aXZeurvN2SpDER3RTm7mtxIkhSoJu33u08QZdueUVJZVmatOMdvd9lkrxs7lZHAwAAQDNhmKZpWh2iPhUWFiowMFAFBQUKCAiwOg4ANElz09dbHeG0lDoq9fShVSqoLlcv/xhdE3mO1ZGanBuj+pzR+TtLMnTF1tdU6CjXuPDumtVunAzDqKN0AAAAaI5OtitiiBcAAJJM09QHmZtVUF2uMHdfjQ7vanUkHEdH30i90fFa2WXTh1lb9L/D31gdCQAAAM0EJRoAAJI2FB3SzyVHZJeh6yN7c5tgAzY4KEEzEy6VJM1M+UqfZW+3OBEAAACaA0o0AECzV1Bdpo+zt0mSLgzpoFZeQdYGQq0mRPfVrS2OruR9954PtaU41eJEAAAAaOoo0QAAzZppmvowc7PKndWK8QzSsOBEqyPhJD0cd5HOC26rMmeVJu54R0cqCq2OBAAAgCaMEg0A0KytLzqoXaWZcjNsujqyp+wG/zU2Fm6GXa+0v1rtfCKUXlmkiTveUYmj0upYAAAAaKL4SQEA0GzlVZXqk6yfJUkjQzoo0oNVmxubADcvze10g0LcfLS1JE33JC1UM1t4HAAAAPWEEg0A0Cz9uhpnhVmt1p7BGhLEbZyNVRuvEL3Z8Tq5G3Z9mv2znj/8rdWRAAAA0ARRogEAmqUfClOUVJbluo3TZhhWR8IZ6BcYq8fiR0mSHk/5Sity91icCAAAAE0NJRoAoNnJrSrVZ9lHb+O8JLSTIjz8LU6EujAhuq9ujOotU6bu2L1A+8uyrY4EAACAJoQSDQDQrJimqYVZW1RpOhTnFaJzA+OtjoQ69O/4S9XHv7UKHeWatPNdFVdXWB0JAAAATQQlGgCgWdlSnKrdpZmyy6ZxET24jbOJ8bS56fWO1yrKw197SjN1954P5TSdVscCAABAE0CJBgBoNkodlfr4l9s4Lwhpx22cTVSkh79md7xOHoZdS3J36plDX1sdCQAAAE0AJRoAoNn4PGeHih0VinD303nBrMbZlJ3jH6MnEy+XJD11cJVW5rHQAAAAAM4MJRoAoFnYX5atdYUpkqRxET3kZtgtToSz7drIXpoQ1VemTN25+wMdLM+zOhIAAAAaMUo0AECTV2069GHmFklSv4A2ivMOtTgR6suj8Zeop18r5VeX6ZZd76ncWWV1JAAAADRSlGgAgCZvZW6SsqqK5W/31KjQzlbHQT3ytLnptQ7XKMTNR1uL0/TAvs+sjgQAAIBGihINANCkZVYWaWVekiTpirCu8ra7W5wI9a2VV5Beaj9ehgzNy9igd9M3WB0JAAAAjRAlGgCgyTJNUwuztsohpzr6RKqbXwurI8EiQ4MTdV+bCyRJ0/Z9qq3FaRYnAgAAQGNDiQYAaLI2F6dqX1m23A27Rod3k2EYVkeChf7SaohGhHRQhVmtm3e+q/zqMqsjAQAAoBGhRAMANEnlzip9lv2zJOn84LYKcfexOBGsZjNsmtVurNp4BetQRb7u2bNQpmlaHQsAAACNBCUaAKBJWp67W4WOCoW5+2poUKLVcdBABLp569UO18jDsGtp7k69lrbW6kgAAABoJCjRAABNTnpFodbk75d0dDEBd5vd4kRoSLr7tdTDcRdLkh5N/lIbiw5bnAgAAACNASUaAKBJMU1Ti7O3ySlTnX2j1ME30upIaIBuiu6nUaGdVWU6dPuu91XA/GgAAACoBSUaAKBJ2fLLYgJuhk2Xh3W1Og4aKMMw9EzbK13zo/0taRHzowEAAOAPUaIBAJqMcmeVPs3eLkm6ILgdiwngDwW4eemV9tfI3bDri5wdeuPID1ZHAgAAQANGiQYAaDK+yt2jQke5QllMACeph39LPRx3kSRp+oGl2sT8aAAAADgBSjQAQJOQWVmk1fn7JEmjWUwAp+Dm6P4aFdrpl/nR5jM/GgAAAI6LEg0A0CR8mr1dTpnq6BPJYgI4JYZh6Om2VyrGM0gHK/I0hfnRAAAAcByUaACARm9XSYZ2lWbILkOXhXWxOg4aoUA3b73a4ej8aJ/n7NDsIz9aHQkAAAANDCUaAKBRc5hOfZr9syTp3KB4hXv4WZwIjVVP/1Z6KHakJGn6gSXaXJRqcSIAAAA0JJRoAIBG7fuCA8qsKpav3UPDg9tbHQeN3C0tBujikI6qNB26fff7KqwutzoSAAAAGghKNABAo1XiqNDy3N2SpItCOsrb7m5xIjR2hmHomXZjFOMZpJRy5kcDAADA/6FEAwA0Wl/m7lKZs0rRHgHqG9DG6jhoIoLcvPXKL/OjfZazXW8yPxoAAABEiQYAaKTSKwr1Q0GyJOmKsK6yGYa1gdCknOPfSv+KHSFJmn5gqXaUpFucCAAAAFajRAMANDqmaerj7G0yJXXxjVaCT5jVkdAE3dZioIYHt1eFWa3bd81XqaPS6kgAAACwECUaAKDR2Vmaob1l2XIzbLo0rLPVcdBEGYahZ9uNUaSHv5LKsvTIgSVWRwIAAICFKNEAAI2Kw3Tqs+ztkqTBgfEKdfe1OBGasjB3X81qN1aGDM1JX6/Pf3nvAQAAoPmhRAMANCo/FCQrq6pYvjYPnRfczuo4aAaGBCXqz60GSZL+vnexUivyrQ0EAAAAS1CiAQAajTJHlZbn7pYkjQjtIG+7u8WJ0Fzc13q4evi1VH51mf68+wM5TKfVkQAAAFDPKNEAAI3Gqrw9KnFWKsLdT/0C2lgdB82Iu82ul9uPl5/dUz8UpujZQ19bHQkAAAD1jBINANAo5FaVanXBfknSqLDOshv8F4b6FesdqicSLpMk/ffgKq0rTLE4EQAAAOoTP4EAABqFJTk7VG06legdpo4+kVbHQTM1LqKHxoV3l1Om7ti9QAXVZVZHAgAAQD2hRAMANHgHy/O0uThVhqRLwzrLMAyrI6EZm5lwmWK9QpRaUaCpez+WaZpWRwIAAEA9OK0Sbf/+/XWdAwCA4zJNU59l/yxJOsc/Ri09g6wNhGbP381LL7UfLzfDpk+zf9Z7GRusjgQAAIB6cFolWmJios477zy98847Ki8vr+tMAAC4/FxyRAfKc+Vu2HVxaEer4wCSpJ7+rXRfm+GSpAf2f66k0iyLEwEAAOBsO60SbePGjerWrZumTJmiqKgo3X777Vq3bl1dZwMANHMO06kvcnZIkoYEJSjQzdviRMD/+XPLQRoSlKAyZ5Xu2L1AFc5qqyMBAADgLDqtEq1Hjx567rnnlJaWptmzZ+vIkSMaNGiQunTpoqefflpZWfw2FgBw5n4sTFF2VYl87R4aFpxodRygBpth06x24xTi5qOfS47oseRlVkcCAADAWXRGCwu4ublpzJgx+uCDD/Tkk09q7969mjp1qmJiYjRhwgQdOXKkrnICAJqZCme1lufuliRdGNxeXjZ3ixMBx4r08Nez7cZIkl5N+15f/fKeBQAAQNNzRiXaTz/9pDvvvFPR0dF6+umnNXXqVO3bt0/Lly9XWlqarrjiirrKCQBoZr7N36diR4VC3X3VLzDW6jjACY0I6aBbogdIkv6atFAZlUUWJwIAAMDZ4HY6Jz399NN68803tXv3bl1yySWaM2eOLrnkEtlsRzu5uLg4vfXWW4qNja3LrACAZqK4ukLf5CVJki4O6Sg344x+54MGZG76eqsjnBXx3qGK9gjQkcpCjds2W7e0GCCbYfzhOTdG9amndAAAAKgLp/VTyUsvvaTrrrtOKSkpWrx4sS699FJXgfariIgIvfHGG3USEgDQvCzP260K06EYzyB182thdRygVu42u66P6i13w66ksix9m7/P6kgAAACoY6c1Em358uVq3br1McWZaZo6dOiQWrduLQ8PD02cOLFOQgIAmo+symL9UJAsSRoV2llGLaN5gIYi0sNfV4R10YdZW7QkZ4cSvEMV4xVsdSwAAADUkdMaiZaQkKDs7Oxjtufm5iouLu6MQwEAmq+luTvllKkOPpFK8AmzOg5wSvoGtFFX32g5ZerdjA0qd1ZZHQkAAAB15LRKNNM0j7u9uLhYXl5eZxQIANB8HSzP09biNBmSLg7taHUc4JQZhqFxET0U5Oat7KoSLc7aZnUkAAAA1JFTup1zypQpko5+g/jQQw/Jx8fHtc/hcOjHH39Ujx496jQgAKB5ME1Tn2dvlySd4x+jFp6BFicCTo+P3UPXRfbSS6lrtKHokNr7RKinfyurYwEAAOAMndJItE2bNmnTpk0yTVPbtm1zfbxp0ybt2rVL3bt311tvvXXKIV544QXFxsbKy8tL/fr107p160547MKFC9W7d28FBQXJ19dXPXr00Ny5c0/5OQEADcuu0kztL8+Rm2HTyJAOVscBzkicd6iGB7eXJH2UuUU5VSUWJwIAAMCZOqWRaKtWrZIkTZ48Wc8995wCAgLOOMD8+fM1ZcoUvfzyy+rXr5+effZZjRw5Urt371ZERMQxx4eEhOiBBx5Qhw4d5OHhoc8++0yTJ09WRESERo4cecZ5AAD1z2ma+iLn6Ci0cwPjFezuU8sZQMN3QUg77S3L0oHyXL2bvkF3thoku3FaM2kAAACgATDME01wVk/69eunPn366Pnnn5ckOZ1OxcTE6O6779b9999/Utc455xzNGrUKD366KO1HltYWKjAwEAVFBTUSQkIADjW3PT1p3T8+sKDWpC5Sd42d93fZrh87B5nKRlQv/KqSvXMoa9V5qzS+cFtdXFoJ9e+G6P6WBcMAAAALifbFZ30SLQxY8borbfeUkBAgMaMGfOHxy5cuPCkrllZWakNGzZo2rRprm02m03Dhw/X2rVraz3fNE2tXLlSu3fv1pNPPnlSzwkAaFiqnA59mbtTknR+cDsKNDQpwe4+GhfRQ3PT12tVXpLaeocr0Sfc6lgAAAA4DSddogUGBsowDNef60J2drYcDociIyNrbI+MjNSuXbtOeF5BQYFatmypiooK2e12vfjii7rwwguPe2xFRYUqKipcHxcWFtZJdgBA3VhTsF8F1eUKcvPWuYFxVscB6lw3vxbqF9BGPxam6L2MjZrSeph87Z5WxwIAAMApOukS7c033zzun63g7++vzZs3q7i4WCtWrNCUKVMUHx+vYcOGHXPszJkzNX369PoPCQCoVamjUqvykiRJI0M6yN1mtzgRcHZcHtZFB8pylFlVrAWZmzUpqq/VkQAAAHCKTmt227KyMpWWlro+TklJ0bPPPqtly5ad0nXCwsJkt9uVkZFRY3tGRoaioqJOeJ7NZlNiYqJ69Oihv//97xo3bpxmzpx53GOnTZumgoIC1+PQoUOnlBEAcPaszEtSmbNKUR4BOsc/xuo4wFnjYXPT9VG9ZZdNO0rS9X3BAasjAQAA4BSdVol2xRVXaM6cOZKk/Px89e3bV//97391xRVX6KWXXjrp63h4eKhXr15asWKFa5vT6dSKFSs0YMCAk76O0+msccvmb3l6eiogIKDGAwBgvbyqUn1XsF+SNCq0k2y/TBkANFUtPAM1KuzowgKf5WzXzpJ0ixMBAADgVJxWibZx40YNHjxYkvThhx8qKipKKSkpmjNnjv73v/+d0rWmTJmi1157TW+//bZ27typO+64QyUlJZo8ebIkacKECTUWHpg5c6aWL1+u/fv3a+fOnfrvf/+ruXPn6oYbbjidlwIAsMiXubtUbTqV4B2m9j4RVscB6sWgwHh19IlUtenUn3YvUKmj0upIAAAAOEknPSfab5WWlsrf31+StGzZMo0ZM0Y2m039+/dXSkrKKV3r6quvVlZWlh566CGlp6erR48eWrp0qWuxgYMHD8pm+7+ur6SkRHfeeacOHz4sb29vdejQQe+8846uvvrq03kpAAALpFUUaGPR0dvrR4V2ci1cAzR1hmFofGRPPX1wlXaXZuqRA0v1n8TLrY4FAACAk2CYpmme6kndunXTLbfcoiuvvFJdunTR0qVLNWDAAG3YsEGjRo1SenrDvT2hsLBQgYGBKigo4NZOADhL5qav/8P9b6T9oF2lGeru10I3RPWpp1RAw7GnNFOvpa2VJM3ucJ0u+eU2TwAAANS/k+2KTut2zoceekhTp05VbGys+vXr55q/bNmyZerZs+fpJQYANAv7SrO1qzRDNhm6KKSj1XEAS7TzidCfWx6dGmPK3kVKrci3NhAAAABqdVol2rhx43Tw4EH99NNPWrp0qWv7BRdcoGeeeabOwgEAmhbTNPV5znZJUv/AWIV5+FmcCLDOfW0uUHe/lsqvLtNduz+Uw3RaHQkAAAB/4LRKNEmKiopSz549a8xX1rdvX3Xo0KFOggEAmp5tJUd0qCJfHoZdw4PbWR0HsJSHzU0vtx8vX7uH1hYm63+HvrE6EgAAAP7AaZVoJSUlevDBBzVw4EAlJiYqPj6+xgMAgN9zmE4tzdkhSRoalCh/Ny+LEwHWi/MO1cz4yyRJTx1cpXWFp7ZAEwAAAOrPaa3Oecstt+ibb77RjTfeqOjoaFZVAwDUal3hQWVVlcjX7qEhwQlWxwEajKsieuib/L36KGuL7ti9QMt7/Fkh7j5WxwIAAMDvnFaJtmTJEn3++ec699xz6zoPAKAJqnRWa3nuLknS8OD28rK5W5wIaDgMw9CTCZdrU9Fh7S/P0T1JC/V2x+v5JSUAAEADc1q3cwYHByskJKSuswAAmqjV+ftU5KhQiJuP+gfGWh0HaHD83Dz1aodr5Gm4aVnuLr2a9r3VkQAAAPA7p1WiPfroo3rooYdUWlpa13kAAE1MiaNCq/L2SpIuCu0oN+O017QBmrQuftF6JP5iSdK/k5dpY9FhixMBAADgt07rds7//ve/2rdvnyIjIxUbGyt395q35WzcuLFOwgEAGr8VuXtUYVarpWeguvu1tDoO0KBNiuqr7/L367Oc7frTrvla3vNOBbp5Wx0LAAAAOs0SbfTo0XUcAwDQFOVWlej7ggOSpEtCO8nGHE/AHzIMQ/9tO1pbi9N0sCJPU5IW6/UO1zA/GgAAQANwWiXaww8/XNc5AABN0Je5u+SQqbbe4WrnE2F1HKBRCHTz1isdrtblW1/T5znb9Vb6Ok2O7md1LAAAgGbvtCemyc/P1+uvv65p06YpNzdX0tHbOFNTU+ssHACg8UqrKNCmX+Z0uiS0k8VpgMalp38rPRg7UpL08P4v9HPxEYsTAQAA4LRKtK1bt6pdu3Z68skn9dRTTyk/P1+StHDhQk2bNq0u8wEAGqklOTtkSurh11KtvIKsjgM0Ore2GKCRIR1UaTp02673VVxdYXUkAACAZu20SrQpU6Zo0qRJSkpKkpeXl2v7JZdcom+//bbOwgEAGqe9pVnaVZopmwyNDO1odRygUTIMQ8+2HaOWnoHaX56jf+z7WKZpWh0LAACg2TqtEm39+vW6/fbbj9nesmVLpaenn3EoAEDjZZqmvsjZIUkaEBirMHdfixMBjVewu49ebn+17LJpUdZWvZuxwepIAAAAzdZplWienp4qLCw8ZvuePXsUHh5+xqEAAI3XZznbdagiXx6GXRcEt7M6DtDo9Qlorftjh0uSHtj/mXaWZFicCAAAoHk6rRLt8ssv14wZM1RVVSXp6O0GBw8e1H333aexY8fWaUAAQONR5XRoZvJySdLQoET5u3nVcgaAk/HnloN0XnBblTurdduu91XiqLQ6EgAAQLNzWiXaf//7XxUXFys8PFxlZWUaOnSoEhMT5e/vr8cee6yuMwIAGol3MzZof3mOfO0eGhKcYHUcoMmwGTbNajdOUR7+SirL0rR9n1odCQAAoNlxO52TAgMDtXz5cn333XfasmWLiouLdc4552j48OF1nQ8A0EiUOCr01MGVkqQLg9vLy+ZucSKgaQlz99WL7cdr3LbZWpC5Sf0D2ui6qN5WxwIAAGg2TrlEczqdeuutt7Rw4UIlJyfLMAzFxcUpKipKpmnKMIyzkRMA0MC9mvq9sqqK1cYrWP0CY62OAzRJAwPjdH+b4Xo8Zbmm7ftMXfxaqJtfC6tjAQAANAundDunaZq6/PLLdcsttyg1NVVdu3ZV586dlZKSokmTJunKK688WzkBAA1YdlWJXkhdI0ma1uZCuRmnNVsAgJNwV6vBujC4vSrMat2y8z3lV5dZHQkAAKBZOKWfct566y19++23WrFihTZt2qT33ntP77//vrZs2aKvvvpKK1eu1Jw5c85WVgBAA/Xcoa9V7KhQN98Wujysi9VxgCbNZtg0q/04tfYM1sGKPN29+0M5TafVsQAAAJq8UyrR3nvvPf3zn//Ueeedd8y+888/X/fff7/mzZtXZ+EAAA1fSnmu3jqyTpL0r7gRsjEKDTjrgty89UbHa+VpuGl53m49f3i11ZEAAACavFP6SWfr1q266KKLTrj/4osv1pYtW844FACg8fhPygpVmQ4NDUrQkKBEq+MAzUZXvxaamXCpJOmJlK+0On+fxYkAAACatlMq0XJzcxUZGXnC/ZGRkcrLyzvjUACAxuHn4iP6KOvoL08eiB1pcRqg+bkuqreujTxHTpn60+4FSqsosDoSAABAk3VKJZrD4ZCb24kX9LTb7aqurj7jUACAxuGxlGWSpCvDu7FCIGCRx+MvUxffaOVUleimne+q3FlldSQAAIAm6cSN2HGYpqlJkybJ09PzuPsrKirqJBQAoOFbk79Pq/KS5GbYdF/rC6yOAzRb3nZ3vdHxWl20+SVtLk7V/Xs/1TNtr5RhGFZHAwAAaFJOqUSbOHFircdMmDDhtMMAABoH0zT1aPLRUWgTovoq1jvU4kRA89bGK0SvdLha1/z8tt7P3Kju/i01Obqf1bEAAACalFMq0d58882zlQMA0Igszt6qLcWp8rV76G8xw6yOA0DSkKBE/St2pGYkL9WD+z9XR59I9Q+MtToWAABAk3FKc6IBAFDurNJjycslSXe1HKxwDz+LEwH41R0tz9UVYV1VbTp1y673WGgAAACgDlGiAQBOyetpP+hwRb6iPQJ0e8tzrY4D4DcMw9DTba9UJ58oZVeV6Oad77HQAAAAQB2hRAMAnLTsqhI9d+hrSdL9bYbLx+5haR4Ax/K1e+jNTtcpyM1bm4oP6769n8g0TatjAQAANHqUaACAk/bfgytV5KhQV99oXRXRw+o4AE6gjVeIXm4/XjYZmp+5SS+lfmd1JAAAgEaPEg0AcFKSSrM058h6SdLDcRfLZvBfCNCQDQtuqxnxl0iSHk3+Ustyd1mcCAAAoHHjJyAAwEl5NPlLOeTUiJAOGhQUb3UcACfh5uj+ujGqt0yZumP3Au0sybA6EgAAQKNFiQYAqNWa/P1alrtLdtn0YOxIq+MAOEmGYejx+Ms0MDBOJY5KTdgxV9lVJVbHAgAAaJQo0QAAf8hpOjXjwFJJ0oToPmrrE25xIgCnwt1m1+sdrlWsV4gOVeTrlp3vqtJZbXUsAACARocSDQDwhz7M3KKtJWnyt3vq763PtzoOgNMQ4u6jOZ1ukL/dUz8UpuheVuwEAAA4ZZRoAIATKnVUambKcknSX2OGKczd1+JEAE5XO58IvdLhatlk6P3MjXru8DdWRwIAAGhUKNEAACf0Sup3OlJZqFaeQbqlRX+r4wA4Q+cHt9NjCZdKkp5I+UofZm62NhAAAEAjQokGADiuzMoizTq8WpL0QOyF8rK5W5wIQF2YHN1Pd7YcJEn6W9IircnfZ3EiAACAxoESDQBwXP9JWaFSZ6V6+rXS6LBuVscBUIf+FTtCl4d1UZXp0E0739POkgyrIwEAADR4lGgAgGPsLMnQuxkbJEnT4y+WYRgWJwJQl2yGTf9rN1b9Atqo0FGuG3bMUXpFodWxAAAAGjRKNADAMWYkL5VTpkaFdlbfgDZWxwFwFnjZ3PVWx+uV6B2m1IoC3bBjroqqy62OBQAA0GBRogEAavg6L0mr8pLkbtj1YOwIq+MAOIuC3X00r/MEhbn76ueSI5q0c57KnVVWxwIAAGiQKNEAAC4O06npB5ZKkm6K7qdY71CLEwE429p4hejdzhPlZ/fUdwUH9KddC1RtOqyOBQAA0OBQogEAXN7P2KidpRkKcvPWPTHDrI4DoJ5082uhOZ1ukKfhpqW5O/X3pMVymk6rYwEAADQolGgAAElSUXW5nkj5SpL0t5hhCnb3sTgRgPo0MDBOr3a4WnbZND9zk6Yf+FKmaVodCwAAoMGgRAMASJKePvS1sqqKleAdpsnR/ayOA8ACI0M76pm2V0qSXkn7Tv87/I3FiQAAABoOSjQAgPaVZev1tLWSpOlxF8vD5mZxIgBWGR/ZUzPiLpEkzUz5SrPTfrA4EQAAQMNAiQYA0MP7l6jKdOiC4HYaHtLe6jgALHZby4H62y/zIv5z/2d6+8g6awMBAAA0AJRoANDMrcjdo6/ydsvNsGlG/CVWxwHQQNzb+gLd2XKQJOm+fZ9obvp6ixMBAABYixINAJqxSme1HjrwhSTplhYDlOAdZnEiAA2FYRh6MHakbm9xriTpH3s/1rvpP1mcCgAAwDqUaADQjL2R9oP2lWUrzN1XU2LOszoOgAbGMAw9EneRbm0xQJL0970f6/2MjRanAgAAsAYlGgA0U1mVxXr60CpJ0j/bjFCAm5fFiQA0RIZhaEbcJbopur9Mmfpb0iLNp0gDAADNECUaADRTM1OWq8hRoW5+LXRNZE+r4wBowAzD0GPxozQxqq9Mmfpr0kK9eeRHq2MBAADUqwZRor3wwguKjY2Vl5eX+vXrp3XrTrwC1GuvvabBgwcrODhYwcHBGj58+B8eDwA41qaiw3rvl5Ekj8VfKpvRIP47ANCAGYahmQmX6ubo/pKkafs+1axD31icCgAAoP5Y/lPT/PnzNWXKFD388MPauHGjunfvrpEjRyozM/O4x3/99de69tprtWrVKq1du1YxMTEaMWKEUlNT6zk5ADRODtOp+/d9KlOmxoV3V5+A1lZHAtBI2Ayb/h0/Sn+LGSZJeixluf6d/KVM07Q2GAAAQD0wTIu/6+nXr5/69Omj559/XpLkdDoVExOju+++W/fff3+t5zscDgUHB+v555/XhAkTaj2+sLBQgYGBKigoUEBAwBnnB4DGZs6Rdbp33yfyt3vqu173KMLDv86fY276+jq/JtDU3BjVx+oIZ+TFw2s0I3mpJGlCVF89kcCoVgAA0DidbFdk6Xc6lZWV2rBhg4YPH+7aZrPZNHz4cK1du/akrlFaWqqqqiqFhIQcd39FRYUKCwtrPACgucquKtHjKcslSfe1GX5WCjQAzcOdrQbpqcQrZMjQnPR1umvPh6p0VlsdCwAA4KyxtETLzs6Ww+FQZGRkje2RkZFKT08/qWvcd999atGiRY0i7rdmzpypwMBA1yMmJuaMcwNAY/V48jLlV5eps2+UJkX3tToOgEbuhqg+eqn9VXIzbFqYtVXXbZ+jguoyq2MBAACcFY16zP0TTzyh999/X4sWLZKXl9dxj5k2bZoKCgpcj0OHDtVzSgBoGDYUHtK7GRskSTMTLpObYbc4EYCmYHR4N83pdIN87R5aU7Bfl219TQfL86yOBQAAUOcsLdHCwsJkt9uVkZFRY3tGRoaioqL+8NynnnpKTzzxhJYtW6Zu3bqd8DhPT08FBATUeABAc3N0MYFPJElXR/RU34A2FicC0JScH9xOn3S9VdEeAdpTmqlRW17R5iIWfQIAAE2LpSWah4eHevXqpRUrVri2OZ1OrVixQgMGDDjhef/5z3/06KOPaunSperdu3d9RAWARm1O+nptKzmiALuX/hU70uo4AJqgzn7R+rz77erkE6WsqmJdue11fZmz0+pYAAAAdcby2zmnTJmi1157TW+//bZ27typO+64QyUlJZo8ebIkacKECZo2bZrr+CeffFIPPvigZs+erdjYWKWnpys9PV3FxcVWvQQAaNCyKov1RPLRxQTubzNc4R5+FicC0FS18AzUx91u0XlBbVXmrNKkne/q+cOrZfFi8AAAAHXC8hLt6quv1lNPPaWHHnpIPXr00ObNm7V06VLXYgMHDx7UkSNHXMe/9NJLqqys1Lhx4xQdHe16PPXUU1a9BABo0KYfWKICR7m6+kZrIosJADjL/N28NKfTDboxqrdMmfp38pe6ffd8lTgqrI4GAABwRgyzmf1qsLCwUIGBgSooKGB+NABN3rf5ezX+57dkyNDn3W/XOf6t6uV556avr5fnARqzG6P6WB3hrDJNU2+nr9OD+79QlelQB59IvdnxOsV5h1odDQAAoIaT7YosH4kGADg7yhxVum/vp5KkydH96q1AAwBJMgxDk6L7aWHXmxXh7qddpRkaufklLc/dbXU0AACA00KJBgBN1HOHv9aB8hxFefhrWpvhVscB0Ez1CWit5T3/rD7+rVXoKNeEHe/oyZSvVG06rI4GAABwSijRAKAJ2lWSoRcOr5EkPRZ/qfzdvCxOBKA5i/Tw10ddb9Kk6H4yZeqZQ1/ryq1v6GB5ntXRAAAATholGgA0MU7Tqfv2faIq06ERIR10SWgnqyMBgDxsbnoi4TK93H68/O2eWl90UBdsel6Ls7ZaHQ0AAOCkUKIBQBPzbsYG/ViYIh+bhx6Pv1SGYVgdCQBcRod304qed6m3f4yKHBX60+4F+uuej1RczeqdAACgYaNEA4AmJKuyWI8e+FKSdF+bC9TKK8jaQABwHK29grW42y2aEnOebDI0P3OTLtj8vL7L3291NAAAgBOiRAOAJuTB/Z+rwFGubr4tdHOL/lbHAYATcjPsurfNBVrY9Wa19AxUSnmexv48W/fu/ViF1eVWxwMAADgGJRoANBFLc3ZqcfY22WTo/7W9Qm6G3epIAFCr/oGxWtXzbk2I6itJmpO+XkM3/k/Lc3dbnAwAAKAmN6sDAADOXH51me7b94kk6c5Wg9Tdr6XFiQDUZm76eqsjNChd/aL1p5bn6sPMzTpSWagbd8xVT79WujSsswKa0QrDN0b1sToCAAA4AUaiAUAT8PD+L5RRWaRE7zBNbX2+1XEA4LQkeIfpbzHDNDQoUYakTcWH9Z+UFfo6b6+qTafV8QAAQDNHiQYAjdzKvD2an7lJhgw903aMvGzuVkcCgNPmYXPTpWGddXerIYrxDFKFWa3Pc7br6YMrtbMkw+p4AACgGaNEA4BGrKi6XP/Y+7Ek6dYWA9QnoLXFiQCgbsR4BeuuVkM0PqKn/Oyeyqoq0ewjP+iNtB+UWVlkdTwAANAMMScaADRijyYvU2pFgdp4Beu+NsOtjgMAdcpmGOoT0Fpd/aL1Ve4ercnfp12lGdp9MEPn+MdoREh7hbj7Wh0TAAA0E5RoANBIrcnfrznp6yRJ/028Ur52D4sTAcDZ4WVz16VhndUvoI0+z9mu7SXp2lB0SJuLDqtvQBtdENJOgW7eVscEAABNHCUaADRCJY4K/X3vIknShKi+GhQUb3EiADj7wj38NCm6nw6W52lpzk4llWVpbWGy1hcd1ICAOA0JTlAQZRoAADhLKNEAoBF65MASpZTnqaVnoB6MHWF1HACoV629gnVby4HaV5qtJbk7lVKeq9UF+/R9wX719G+lYcFtFenhb3VMAADQxFCiAUAjszx3t+am/yRJeq7tWPm7eVmcCACskeATpj97D9Lu0kytykvS/vIc/VR0SD8VHVIn3ygNC0pUrFeIDMOwOioAAGgCKNEAoBHJqSrRlKSjt3He1mIgt3ECaPYMw1AH30h18I3UwfJcrcrbq+0lR7SjJF07StLV0jNQAwLi1NO/pTxsfOsLAABOH99JAEAjYZqm7tv7ibKqitXWO1zT2lxodSQAaFBae4VoYnRfZVYW6Zv8fdpYdEipFQX6MGuzPsv5Wb39W2tAYKwiuNUTAACcBko0AGgkPsraos9ytsvNsOn59uPkbXe3OhIANEgRHv66KqKHLgntpJ8KD2ptYbJyqkq0pmC/1hTsV6xXiHr7x6ibX0v+LQUAACeNEg0AGoHUinz9c99nkqQpMeepu19LixMBQMPna/fQ0OBEDQ5KUFJpltYWHtCOknQll+cquTxXi7O3qbNvlHr5x6idT4Tshs3qyAAAoAGjRAOABs5pOnXPnoUqdJTrHP9W+kvMEKsjAUCjYjMMtfeNUHvfCBVUl2lT0WH9VHRIGZVF2lKcpi3FafK1eaiLX7S6+rVQoneYZYXa3PT1ljxvQ3VjVB+rIwAA4EKJBgAN3Ktpa7W6YL+8be6a1W6c3Ay71ZEAoNEKdPPWsOC2GhqUqLTKAm0oPKSNxYdV4qjUj4Up+rEwRT42d3X2/b9Czd3Gv7sAAIASDQAatC3FqXoseZkk6ZG4i5XgHWZxIgBoGgzDUEvPILUMD9KosM7aX5ajrcVp+rnkiIodFVpfdFDriw7K3bCrnU+4OvlGqYNPpALcvKyODgAALEKJBgANVHF1hf60a4GqTIdGhXbSBG5pAYCzwm7Y1NYnXG19wnWl2U37y7K1tThNO0rSVeAo1/aSdG0vSZcktfIMUjufcLX1DlcbrxBGqQEA0IxQogFAA3X/vk90oDxHLT0D9VTiaBmGYXUkAGjybIahRJ9wJf5SqKVVFmhHSYZ2lqTrUEW+Dv/yWJmXJDfDpjivUCX6hKmtd7haegbJxr/VAAA0WZRoANAALcjYpA+ztsgmQy+2u0rB7j5WRwKAZsd1y6dnkC4Maa/C6nLtLs3U3rIs7S3NUqGjQkllWUoqy9IS7ZS3zV0J3mFK9A5TW59whbv78QsQAACaEEo0AGhg9pVl6/59n0qSprY+X/0CY60NBACQJAW4ealPQGv1CWgt0zSVWVWspNIs7S3L0r6ybJU5q/RzyRH9XHLk6PF2L8V5hyjWK0SxXqGK9gywbNVPAABw5ijRAKABqXBW60+75qvUWamBgXH6a8xQqyMBAI7DMAxFevgr0sNfg4Li5TCdSq0o0N7SoyPTkstzVego15biNG0pTpMkeRh2tfYKVpxXqGK9Q9TaK1heNneLXwkAADhZlGgA0IA8euBLbSs5omA3b73Q7ipGLABAI2E3bGrtFazWXsE6X+1U5XToUEWeDpTlKrk8V8nlOSp3VmtvWbb2lmVLeZIhqYVnoGukWpx3iALdvK1+KQAA4AQo0QCggVictVWvH1krSXqu7VhFewZYnAgAcLrcbXbFe4cp3jtMkuQ0TWVWFulAeY6Sy3N1oCxXedWlSq0oUGpFgb4rOCBJCnbzVuwvI9XivEIV6eHPYgUAADQQlGgA0ADsLs3UlKTFkqS7Ww3RiNAO1gYCANQpm2EoyjNAUZ4BGhAYJ0kqqC5Tclmuq1hLqyhQXnWZ8ooPa1PxYUmSt8396Ei1X0q1Vp5BcrfZrXwpAAA0W5RoAGCx4uoK3bLzPZU6KzUoMF73tbnA6kgAgHoQ6Oat7v4t1d2/pSSp3Fmlg+V5rmLtYHmeypxV2lmaoZ2lGZIku2yK8QpSnFeI4rxD1cYrRD52DytfBgAAzQYlGgBYyDRN/W3vIiWVZSnaI0AvtR8vN4MRBgDQHHnZ3NXOJ0LtfCIkSQ7TqSMVhUdHqpXlan95joodFb/MsZarVfl7JUlRHv5K8A5Tone4ErzD5G1nsQIAAM4GSjQAsNBraWv1afbPcjNseq3DNQr38LM6EgCggbAbNrXyClIrryANDkqQaZrKqSrRgV8WKjhQlqusqmKlVxYpvbJI3xUckCGplWeQEr3DlegTpjivUG7/BACgjlCiAYBFfixI1ozkpZKkR+IuVu+A1hYnAgA0ZIZhKMzDT2Eefurzy/8ZxdUVOlCec3TVz9IsZVYV61BFvg5V5GtVfpLcDJvaeIWorXe42vqEqaVnECs/AwBwmijRAMACRyoKdeuu91VtOnVleDfdHN3f6kgAgEbIz81TXf1aqKtfC0lHFytIKs1ylWoFjnLtK8vWvrJsLc2VvGxuau8ToY4+UergGyFfu6fFrwAAgMaDEg0A6lmpo1ITd76jzKpidfCJ1FOJV8gwDKtjAQCagEA3b/UOaK3eAa1lmqayqopdpdq+smyVOau0pThNW4rTZEhq7RWijj6R6uIXpUiPAKvjAwDQoFGiAUA9Mk1TU5IWaWtxmkLcfPR2p+sZBQAAOCsMw1CEh78iPPx1blC8nKapg+V52lWaoR0l6TpSWaiU8lyllOdqae5ORbj7qatfC3Xza6FojwB+wQMAwO9QogFAPXru8DdanL1NboZNr3e8Vm28QqyOBABoJmyGoVjvEMV6h+ii0I7KryrTztJ07ShJV9Iv86mtyNujFXl7FOruq+5+LXSOfytGqAEA8AtKNACoJ19k79ATKV9JkmYmXKaBgXEWJwIANGdB7t4aEBinAYFxKnNUaUdpurYVp2l3aaZyqkq0Mi9JK/OS1NIzUD39WqmnfysFuHlZHRsAAMtQogFAPdhRkq679nwoSbo5ur9ujOpjcSIAAP6Pt91dvfxj1Ms/RhXOau0sydCm4sPaVZKh1IoCpVYU6POc7WrrHa6+gW3U2TdabqzyCQBoZijRAOAsy6os1oQd76jUWakhQQmaHn+x1ZEAADghT5ubevi3VA//lipxVGhLcZo2Fh1SSnme9pRlaU9ZlnztHurj31r9AtoozMPP6sgAANQLSjQAOItKHBW6fsccHa7IV5xXqF5pf7XcDLvVsQAAOCm+dk8NDIzTwMA4ZVeV6KfCg1pfmKJCR4W+zt+rr/P3KtE7TAMD49TZN1o2FiMAADRhlGgAcJZUmw7dtmu+ayXOdztPULC7j9WxAAA4LWHuvrootKMuDGmvnSUZ+rEwWbtLM7W3LFt7y7IV4uajQUHx6hPQWl42d6vjAgBQ5yjRAOAsME1T9+39RCvy9sjb5q53Ot+oOO9Qq2MBAHDG7IZNXfyi1cUvWnlVpfqhMFk/FCQrt7pUn2T/rC9zdqlvQGsNCkpQCL88AgA0IZRoAHAWPHPoa83L2CCbDL3cfrzO8Y+xOhIAAHUu2N1HF4d20gXB7bSh6LDW5O9TZlWxVhfs13cFB9TTv5XOD26rCA9/q6MCAHDGKNEAoI7MTV8vSVpfeFALMjdJkq4I76rMqmLXPgAAmiIPm5sGBMaqX0Ab7SnN1Lf5+5RUlqUNRYe0seiQuvm11PnBbdXCM9DqqAAAnDZKNACoQ7tKMvRh5mZJ0nlBbTUwMM7aQAAA1CObYaiDb6Q6+EbqYHmeVuTt0Y6SdG0pTtWW4lR19o3SyJCOivYMsDoqAACnjBINAOrI/rJszUlfL6dM9fRrpYtCO1odCQAAy7T2Ctbk6H5KqyjQyrw92lqcpu0l6dpRkq4efq00MrSDQt19rY4JAMBJo0QDgDqwuShVs9N+VJXpUAefSI2P7CmbYVgdCwAAy7XwDNQNUX2UWVmkZbm7tKU4TZuKD2tLcar6BbTR8JD2CnDzsjomAAC1okQDgDO0syRD125/SxVmtRK8wzQhqo/cDJvVsQAAaFAiPPx1Q1QfDSvP15LcndpTmqm1hcn6qeiQhgYl6LzgtvKw8eMJAKDh4qc8ADgDB8pydPXPbyqvukwxnkGaFN1X7ja71bEAAGiwWnkF6dYWA/SnlueqjVewqkyHvsrboydTVmhD4SE5TdPqiAAAHBclGgCcptSKfF3185vKrCpWR59I3dJigLxs7lbHAgCgUUjwDtOfWw7WhKg+CnHzUaGjXO9nbtTzh79Vclmu1fEAADgGJRoAnIa0igJdte1NHa7IV7xXqBZ0mSwfu4fVsQAAaFQMw1BXvxaa2vp8XRzaUZ6GXYcq8vVC6mq9l7FBWZXFVkcEAMDF8hLthRdeUGxsrLy8vNSvXz+tW7fuhMdu375dY8eOVWxsrAzD0LPPPlt/QQHgF4fL83Xltte1vzxHrTyDtKDLZIV7+FkdCwCARsvdZtf5we10b5vh6uPfWoakjUWHde6GZ/XWkR/lMJ1WRwQAwNoSbf78+ZoyZYoefvhhbdy4Ud27d9fIkSOVmZl53ONLS0sVHx+vJ554QlFRUfWcFgCkg+V5unLb60opz1Mbr2At6nqzWnkFWR0LAIAmIcDNS+Mje+ruVkPUyjNQhY5y3b/vU43a8oq2FqdZHQ8A0MwZpmndzJ39+vVTnz599Pzzz0uSnE6nYmJidPfdd+v+++//w3NjY2N1zz336J577jml5ywsLFRgYKAKCgoUEBBwutEBNEPJZTka+/NspVYUKM4rVB91vUktPANd++emr7cwHQAATYvTNFVtOvVEynIVOSpkk6Gbovvr/jbD5efmaXU8AEATcrJdkWUj0SorK7VhwwYNHz78/8LYbBo+fLjWrl1bZ89TUVGhwsLCGg8AOFX7y7I1ZtsbSq0oUKJ3mBZ1vblGgQYAAOqWzTB0c4v+WtPrHl0Z3k1OmXr9yFoN3fQ/fZ2XZHU8AEAzZFmJlp2dLYfDocjIyBrbIyMjlZ6eXmfPM3PmTAUGBroeMTExdXZtAM3DrpIMjdn2htIqC9XOJ0ILu96sKE9GsgIAUB8iPfz1UvvxWtBlklp7Biu1okDXbH9bf93zkfKry6yOBwBoRixfWOBsmzZtmgoKClyPQ4cOWR0JQCOyvvCgRm97XemVRergE6mPutykCA9/q2MBANDsDAlK1Kpz7tatLQbIkKH5mZs0ZMNz+jx7u9XRAADNhGUlWlhYmOx2uzIyMmpsz8jIqNNFAzw9PRUQEFDjAQAnY3nubo3/+U3lV5epj39rLep6M6twAgBgIV+7hx6NH6VPut2qRO8wZVYV6+Zd7+mO3QuUV1VqdTwAQBNnWYnm4eGhXr16acWKFa5tTqdTK1as0IABA6yKBQCSpPkZGzVpxzyVOas0PLi95neZpGB3H6tjAQAASX0CWuurnn/WX1oNkV02LcraqvM2zdIq5koDAJxFlt7OOWXKFL322mt6++23tXPnTt1xxx0qKSnR5MmTJUkTJkzQtGnTXMdXVlZq8+bN2rx5syorK5WamqrNmzdr7969Vr0EAE3QC4dX669JC+WQU+MjeurNjtfJx+5hdSwAAPAbXjZ3/TN2hD7tfqsSvMOUXlmka7e/rXv3fqISR6XV8QAATZCblU9+9dVXKysrSw899JDS09PVo0cPLV261LXYwMGDB2Wz/V/Pl5aWpp49e7o+fuqpp/TUU09p6NCh+vrrr+s7PoAmptp06JH9S/X6kaMrBN/ZcpAejB0pwzAsTgYAAE7kHP8YLe9xpx5LXqY3jvygOenr9G3+Xj3fbpx6B7S2Oh4AoAkxTNM0rQ5RnwoLCxUYGKiCggLmRwPgUlRdrtt3L9DKvD2SpIdiL9KdrQad0jXmpq8/G9EAAGi2bozqc0rHr87fp3uSFiq1okB22fT31ufprzFDZTea/HpqAIAzcLJdEf+bAGj2Dpbn6bKtr2ll3h5529z1eodrT7lAAwAA1hsclKBVPe/WmPBucsip/xxcoXHbZiu1It/qaACAJoASDUCztqHwkC7Z8rJ2lWYowt1Pi7reokvDOlsdCwAAnKYANy+92H68ZrUbK1+7h9YWJuuCTS/oi+wdVkcDADRylGgAmq2FmVs0Ztsbyq4qURffaC3p8Sf18G9pdSwAAFAHroroqa96/Fk9/Foqv7pMN+16V/fu/VilLDoAADhNlGgAmp0qp0MP7v9cd+75QBVmtUaEdNDH3W5RS88gq6MBAIA6FOcdqk+63ao/txwsSZqTvl4XbXlZO0rSLU4GAGiMKNEANCuZlUW66ufZei3t6Aqcf2k1RG92vE6+dk+LkwEAgLPBw+amB+NGakGXSYpw99Oe0kxdvPllvZ62Vs1sjTUAwBmiRAPQbKwvPKgLN7+oHwpT5G/31Jsdr9M/Y0ewYhcAAM3AkKBErTznbg0Pbq8Ks1r/2v+5Jux4R9lVJVZHAwA0EvzkCKDJM01Tb6T9oCu3va6MyiK184nQ0h536OLQTlZHAwAA9SjM3VdzO92gf8ePkodh1/K83bpg0/Nak7/P6mgAgEaAEg1Ak5ZXVaqbdr6rB/Z/pmrTqSvCumpJ99uV4B1mdTQAAGABwzB0S4sBWtL9T2rrHa6MyiJd9fNb+k/KCjlMp9XxAAANGCUagCZrbcEBXbDpeS3J3Sl3w65H4y7Ry+3HM/8ZAABQZ79ofdnjDl0X2UumTD19aJXGbZutIxWFVkcDADRQlGgAmpxq06H/pKzQ2G2zlVZZqATvMH3e/Xbd2nKgDMOwOh4AAGggfOweerrtlXqx3VXytXtobWGyLtj0vL7K3W11NABAA0SJBqBJSSnP1dhts/X0oVVyytQ1EedoWY871M2vhdXRAABAAzUmoruW97hTXXyjlVtdqht2zNWMA0tV5XRYHQ0A0IBQogFoEkzT1Jwj63T+puf1Y2GK/Oyeeqn9VXq23Rhu3wQAALWK9w7TZ91v003R/SVJL6au0RXbXtPB8jyLkwEAGgpKNACNXmpFvq7Z/pbu3feJShyV6h/QRit6/llXhne3OhoAAGhEvGzuejzhUr3R4VoF2r20seiwhm96QZ9nb7c6GgCgAaBEA9Bomaap9zI2aNjGWfomf5+8bG6aEXeJFna9WW28QqyOBwAAGqlRYZ21vOefdY5/KxU6ynXzrvc0bd+nKndWWR0NAGAhSjQAjVJKea6u3zFXf0tapCJHhXr5x+irHn/WbS0HymbwTxsAADgzrb2C9XHXW/XnloMlSW8e+VGXbnlV+8qyLU4GALAKP2kCaFSqnA49f3i1hm2cpZV5e+Rh2PVA7Ah90u1WJfqEWx0PAAA0Ie42ux6MG6l5nSYoxM1HP5cc0YjNL+qjzM1WRwMAWIASDUCjsbHokEZufkn/Tv5SZc4qDQyM08qed+nuVkNkZ/QZAAA4Sy4IaacVPe/SgIBYlTgq9ec9H+pvSQtV4qi0OhoAoB7xUyeABi+vqlT37/tUo7a8qh2l6Qp289azbcfooy43MfoMAADUi2jPAH3Y9Sb9PeY8GTL0XsZGXbzlZe0sybA6GgCgnlCiAWiwHKZTc46s07kbntVbR36UKVPjwntoda97dE3kOTIMw+qIAACgGbEbNv2jzQX6oMtkRXr4a09ppi7e8pLmpf8k0zStjgcAOMso0QA0SD8WJGvk5pd0775PlFtdqvY+Efqwy2Q9336cwtx9rY4HAACasUFB8fqqx591XlBblTur9fe9i3XH7gUqqi63OhoA4CwyzGb2K5PCwkIFBgaqoKBAAQEBVscBGr256evr9Hp5VaX6ImeHNhenSpK8be4aEdJeAwLjmPcMAIBm5saoPlZH+ENO06kXUtfoieSv5JBTsV4heqXD1eru19LqaACAU3CyXZFbPWYCgBMqdVRqZV6SvivYr2rTKUNS34A2uii0o/zsnlbHAwAAOIbNsOnuVkPUPyBWf9o9X8nlubp0y6t6OO4i3Rzdn6knAKCJoUQDYKlq06Hv8g9oRd4elTmrJEkJ3mG6NLSzWnkFWRsOAADgJPQJaK2vevxZU5IWaUnuTv1r/+f6Nn+f/ps4WuEeflbHAwDUEUo0AJZwmqY2Fh3SstzdyqsulSRFefhrVGhntfeJ4De3AACgUQl299HsjtfpjSM/aMaBpVqWu0vnbZqlZ9qO0YUh7a2OBwCoA5RoAOqV0zS1tThNy3J3KauqWJIUYPfSRaEd1Mu/tWyUZwAAoJEyDEO3tBiggYFxunP3B9pVmqEbd8zVxKi+ejjuIvnYPayOCAA4A5RoAOqFaZr6ueSIluXuVnploSTJx+auYcFtdW5gnDxs/HMEAACahk6+UVra4096PHm5Xk37Xm+nr9N3Bfv1QvurWHQAABoxfmoFcFY5fynPVubtUWpFgSTJy+amIUGJGhwULy+bu8UJAQAA6p6XzV0z4i/RBcHt9Jekj7S3LFujtryiv7YaqntihsndZrc6IgDgFFGiATgrHKZTW4pTtTIvSRmVRZIkD8OuwUEJGhKUwO0MAACgWRganKhVPe/WvXs/1mc52/XfQ6u0LHeX/tdurDr6RlkdDwBwCijRANSpatOhDYWHtTJvj3J/WTDAy+amcwPjNTgoXr52T4sTAgAA1K8Qdx+91uEafZz9s6bt+0TbSo5oxOaXNLX1efpzq8FyMxiVBgCNASUagDpR6qjU2oJkfVewX0WOCkmSr81Dg4MSNDAwTt52btsEAADNl2EYGh3eVQMDY/WPvR/ry9xdmpnylZbk7NQzba9kVBoANAKUaADOSG5VqVbn79O6whRVmg5JUqCbl4YEJap/QBsWDAAAAPiNCA9/vdXxen2YtVn/2ve5Nhen6sLNL+quVoN1T8ww5osFgAaMn24BnDLTNLWuMEWvH/lBn2dvl1OmJCnaI0BDgxPVw6+l7IbN4pQAAAANk2EYuiqipwYHJuif+z/TFzk79Oyhb/Rp9nb9v8QrNDAwzuqIAIDjMEzTNK0OUZ8KCwsVGBiogoICBQQEWB0HaFTKnVX6OGub3kj7QVtL0lzb23qHa1hwotp6h8swDAsTAgCApuTGqD5WR6gXn2dv1z/3f+ZajOmGyN76V9xIBbl5W5wMAJqHk+2KGIkGoFYp5bl6N32D3sn4STlVJZKOLhYwNry7Ij0CFO1JIQ0AAHC6RoV11qCgeD2WvExz0tfrnYyf9EXODv0rdoSuiTxHNkb4A0CDwEg0AMdV5XToy9xdeid9vb7J3yfzl1s2W3gEaHJ0P10f1Uch7j6am77e4qQAAABNx/6yHC3M2uIalRbjGaQrw7vpn7EjLE4GAE0XI9EAnJbkshzNy9ig9zM2Kquq2LV9aFCCbojqo4tDO7IMOwAAwFkS7x2qv8UM0/cFB7Qsd5cOVeRr1uFvlVNVommxIxTm7mt1RABotijRAKjSWa0lOTs1L+MnfZu/z7U93N1P10aeo+ujequNV4iFCQEAAJoPu2HT4KAEdfdrqS9ydmhD0SHNy9igT7J/1l9aDdEtLQbK284qngBQ37idE2jGdpdman7GRs3P3OSa68yQoWHBibohsrdGhHSQu+2PR51xOycAAMDZlVyWq9X5+1wLO7XwCNC9bYbrqogerIgOAHWA2zkBHFd6RaEWZW3Vwqwt2lZyxLU90sNf10X20rWRvdTaK9jChAAAAPitWO8QPRB7oRZlbdXMlK90uCJf9yQt1Cup3+lfsSN1fnBbVkgHgHpAiQY0A0XV5foiZ4c+ytqi1fn7XYsEuBk2nR/cTtdF9tLwkHbMdQYAANBA2Qybxkb00Kiwznoz7Uc9e+hr7SzN0PU75qiXf4ymtj5fw4ISKdMA4CyiRAOaqCqnQ6vyk/RR5hYty92lMmeVa1/fgNYaG95Dl4V1UYi7j4UpAQAAcCq8bO66o9UgXRN5jv53+Fu9eeQHbSg6pGu3v61z/Fvp7zHnMzINAM4S5kQDmpAqp0M/FCbrs+zt+jT7Z+VWl7r2JXqHaWx4d42J6F6niwQwJxoAAMDZd2NUn+Nuz6ws0guH12hO+jrXL017+rXSXa0G66LQjsyZBgAn4WS7Iko0oJErd1bp27x9+jxnu5bl7lJedZlrX7i7n64M76axEd3VzbfFWfmNJCUaAADA2XeiEu1XWZXFeiF1td4+8n9lWmvPYN3WcqCuiThHfm6e9RETABolSrQToERDU1BcXaGv8vboi5ztWpG3RyWOSte+EDcfXRzaUZeGddHgoPizPs8ZJRoAAMDZV1uJ9qusymK9cWSt3j6yzvXL1QC7l26I6q3J0f0UwwJSAHAMSrQToERDY5VVWayv8nbri+wd+iZ/rypNh2tfC48AXRLaWZeEdVLfgNb1ukAAJRoAAMDZd7Il2q9KHZX6IHOzXk37XvvKsiVJhgwNC0rU9VG9NSKkvTxsTJENANLJd0X8qwk0UNWmQxsKD2lVfpJW5iVpa3Fajf3xXqEaFdZZl4R2Ug+/lkweCwAAABcfu4cmRvfVjVG99VXeHr2W+r1WF+zXqvwkrcpPUpi7r8ZH9NS1kb3U1ifc6rgA0ChQogENSFpFgb7OO1qafZu/T4WO8hr7u/pG6+LQTroktJPa+0RQnAEAAOAP2QybRoR00IiQDjpQlqP3Mjbo/YyNyqwq1oupa/Ri6hp18Y3WFWFddHl41zpdgAoAmhpu5wQsVOqo1IaiQ1qZl6RVeUnaVZpRY3+wm7eGBbfVeUFtNSw4UREe/hYlPTFu5wQAADj7TvV2zj9S5XRoRd4ezUv/Savyk1RtOl37evq10hXhXTUipL3ivcPq7DnrEt9//p+6fF8AzRm3cwINUGF1udYXHtQPhcn6oSBZm4tTVfWbuc0MGTrHv5XOC26r84PbqrtfS5YlBwAAQJ1yt9l1UWhHXRTaUblVpfoiZ7sWZ23T9wUHtKn4sDYVH9YjB5Yo3itUF4S00wXB7TQgME6ezKEGoJnjX0HgLMqpKtGPBSmu0uznkiNyqubgzygPfw0JStT5wW01JChRIe4+FqUFAABAcxPi7qMbovrohqg+yqws0mfZ2/V5znb9WJii/eU52p+2Vq+lrZWPzUP9Atqof2Ab9Q+IVQ//VpRqAJod/tUD6kils1q7SzO1pThVm4tSta7ooPaUZh5zXKxXiPoHxKp/YKwGBMaqtWcwc5sBAADAchEe/rqpRX/d1KK/iqrLtTp/v1bk7daKvD1KryxyLUogSZ6Gm3r6t1KfgNbq5tdC3fxa8H0tgCaPEg04DdWmQ3tKs7S5KFVbilO1tThNO0rSVWFWH3Ns+//f3r0HR1XffRz/nL1mc+eSK3JTbnIXUJpob0rLIDIy40OBh1aEUtuptkaKHbAFsYII1k4QLZSOIzNaSq0zpH2cIsXMQEtFINjwoFVBFMMlF5Fkc9/L2fP8sZuFNMGEPsBZ4vs1s3PO+f3O2f2ezI9l97u/S3K2vpQeTZhNTh+kPC9z8QEAACCxpbmSdGffkbqz70hZlqX3mqv1pv9jveU/obfqT+hsqCk62qL+RPyaDGeSxqTma3Rqnob5snSDr6+GJGepjzvFvhsBgMuIJBrQhbpwi4421+hoc43ea6rW4cbTerepSi2RUIdzM5xJGpfWT+NS++mm1Ot0S8ZA9eVDAwAAAK5hhmFoZEquRqbkalF+gSzL0vGWs3qr/oTKG07rf5vO6P2mavnNVu31f6S9/o/aXd/L5dMNvr7qn9RL/bwZ6ufNVD9Phvp5M5TtSVNvd/I1Mw+wZVkKWxEFLVOhiKmgFVYwYrY/ju+bCkWix8GIqVBs23ZNyDJlWhGFrYgismRaEZlWbKuIIm37sfo2hs739lt2/H86lLsMh9yGU26HUx7DKY/DKY/h6rQs2elWstOjFKdXyQ63UmL7KU5P7NgbL8twJSnD5VOGM0luh/Pq/dGBBEISDYg5G2qKJ8uONn8a368JNXZ6fprTG+u6Hk2ajU/N18Ck3nRhBwAAQI9mGIaGJGdpSHKWvh1bHbJtapMjjWf0blOVjrec1YctZ3UqUKfacIvKGk6qrOFk588nQ71cPvVxp6iPO1m9XMlKcXqV6vIq1elRqtOrFIdHXodLbodT/2w4JafhkOuCxJslS5YV3UaPY/uxMkvR0SQhK6JQxFTYisSP220jsXMsU8EOCbCwQpb5bzMcX33WBRFErI7RhCxTLQpJZoeqyybZ4VFmW1ItvvUp0+VTuitJmW3lzvP1vd3JynT55GEuPVzDaL34wghbpioD9aporVVFoFYnW+tU0Vqrk4FaHWv+VOfCzRe9tp83Q8OSszXMl61xqfkal9ZPg5N6y3GN/GIGAAAAXEkeh0tjUvM1JjW/XXmzGdTHLZ/pw5azOh3w63SgTmcCfp0O+HUqUKdz4WZZsnQu3Kxz4WYda7HpBv4DTjliPbraeni5Ovb+uuDYbTjlcbhi2+ixy3DIKYechiGnEd065IjvO2P1hnG+p9mFSbT/yhrfLqlnxXq0hSxTgVjyr/Mec6YCkZBaIiE1mUE1mUE1R4Jqbts3g2qKnN+vN1tVH25VgxmQpOi5waDOBOsv+e+W4vQo0+VTb1c0qdbLnaxMV7J6u33KdCWrl8unXq7kWHlbfZJcBr3fYL+ESKI9//zzevrpp1VVVaVx48Zpw4YNuuWWWy56/h//+EctX75cJ06c0NChQ7V27VrdeeedVzFiJJqIFdFnoWZ9GmpUdbBBNcEGnQn4dTIQTZRVtNbqTNCvsBW56HMYMjQgKVPDfNnRhFlyloYlZ2uoL0upLu9VvBsAAACgZ0h2ejQqNU+jUvM6rQ9bpmpDLTobatJnoSadCzerNtSsRjOgRjOgJjMY3wYjYQUsUxWt5+LDIC1Jhs4nmAzDiB+3jQ9pK3MZTrkNR3TriG1jiazz5dFjj+H63ASZ23AmxBDU3Ks833LYMtUQDsgfblFduFX+cIv8ZmvsuEX14fP7/nCL/OFW+cOtqgs3qy7cKktWPGl3OuC/pNdOdybFk2q94ttooq2tl1s0+eaLl2e4kuj4gMvK9iTaH/7wBy1evFibNm3S5MmTVVxcrKlTp+qDDz5QdnZ2h/PffPNNzZ07V2vWrNFdd92lrVu3aubMmXr77bc1evRoG+4AV0LEiqjeDKguFH2zjb7ptuhcLFFWE2xQdbBRNaFowuzTYJNMXTxB1sZjOHWdN1P9kzI1IKmX+nt7aUBSL13v66shvr5Kdnquwt0BAAAAkKKJrSxPqrI8qd2+5qWqg1cwInwel+GMJq/cyZd8bdt3vNpQs2rDLaoNNasuHN0/F4p+36sNN6su1KJz4VhdqEX1ZqskRXvDma2qCNR2+zUNGcp0JUWTarHkWlsCLsPlU5rTqzSnV6muJKU6PUpzJinVGR1GnBYrowccLmRYVieDqK+iyZMn6+abb9Zzzz0nSYpEIurfv79+9KMfaenSpR3Onz17tpqamvTaa6/Fy770pS9p/Pjx2rRpU5evV19fr4yMDPn9fqWns0ri5RCxIgrEuggHItFH0DLVaobiXYCjj8D5bbvyoOrDrdE3zNgvFm2/UlyqPu4U5bjTlO1JVY4nTQOSokmyAd5e6p/US7meNH6JuMz4EAMAAHDlfSc29xj4/HmhL0K7CFtmtGNFW/It1luxLr7fEv8uWXvBOU1m8LK8vs/hVmo82eY9v+/0Ksnhks/hUZLTpSSHWz6HO771OWN1Dle03Nm+Pslxvncj31Ht191cka090YLBoA4dOqRly5bFyxwOh6ZMmaJ9+/Z1es2+ffu0ePHidmVTp05VSUnJlQw1oW2p3K9mMxRbwaX9ii7x/X8ri8S6P7db9UXnV39pOz8QS4y1dZ0OREIKRsxosuyCVWWulLYJKzNjvxxkunzKcqfGk2TZnjRlu9OU40lTX3cKq8QAAAAAQA/iMpzq605RX3fKJV0XjIRjibaWeNLtwh5v/nCLGs2AGsIBNcSGDzeasf1wQAErLElqic0d9+lFFpy7HNrm12sbXtxhDj3DKZfDER1ebDjldrhi8+kZcrSbP++CYznkMBxyGIacitY7YuVt5zt0wVx8sWOHDBlGbKu24dCGHLFh0W31Thn679xJV+xvkqhsTaKdPXtWpmkqJyenXXlOTo7ef//9Tq+pqqrq9PyqqqpOzw8EAgoEAvFjvz867rq+/tInQExUT/7rNdWFW+0OIy4p9g/d63ApxeFVSmzZ5OjSyR4lOzxKcXiU7IwuoZwcy+S3rezSNnY93eWTtzsrt1iSAlJLoEnX0DykPUZLw5X7zwQAAABR9ck95/vL/xefP8+jXXy+JEl5SlKekSS5FX10UzASVqMZVKPZqqZwdERVgxlUU6Rtvr5QdHEGM6RAJKyWSEitVtuxqZZIUK2RsFrNUHQbq4/uh9u9VkRS6HLe+FXgMhy6K3mY3WFcNm05oq4Ga9o+J9qVtmbNGj3++OMdyvv3729DNAAAAABw6b5vdwBISLQL2ClD6+wO4bJraGhQRkbGRettTaL17dtXTqdT1dXV7cqrq6uVm5vb6TW5ubmXdP6yZcvaDf+MRCI6d+6c+vTpI8MwOr0GPUd9fb369++vkydPMgceLop2gu6gnaA7aCfoDtoJukIbQXfQTtAdtJPusSxLDQ0Nys/P/9zzbE2ieTweTZw4UaWlpZo5c6akaJKrtLRUDz74YKfXFBQUqLS0VEVFRfGyXbt2qaCgoNPzvV6vvF5vu7LMzMzLET6uIenp6bxhoEu0E3QH7QTdQTtBd9BO0BXaCLqDdoLuoJ107fN6oLWxfTjn4sWLNX/+fE2aNEm33HKLiouL1dTUpAULFkiS7r33XvXr109r1qyRJD300EP66le/qmeeeUbTp0/Xtm3bVFZWps2bN9t5GwAAAAAAAOjBbE+izZ49W59++qlWrFihqqoqjR8/Xq+//np88YCKigo5HOeXey0sLNTWrVv185//XI8++qiGDh2qkpISjR492q5bAAAAAAAAQA9nexJNkh588MGLDt/cvXt3h7JZs2Zp1qxZVzgq9ARer1ePPfZYhyG9wIVoJ+gO2gm6g3aC7qCdoCu0EXQH7QTdQTu5vAyrq/U7AQAAAAAAgC84R9enAAAAAAAAAF9sJNEAAAAAAACALpBEAwAAAAAAALpAEg0AAAAAAADoAkk09EgbN27U2LFjlZ6ervT0dBUUFGjHjh12h4UE9tRTT8kwDBUVFdkdChLIypUrZRhGu8eIESPsDgsJ6PTp0/r2t7+tPn36yOfzacyYMSorK7M7LCSQQYMGdXg/MQxDDzzwgN2hIYGYpqnly5dr8ODB8vl8uuGGG/TEE0+IteDw7xoaGlRUVKSBAwfK5/OpsLBQBw8etDss2Ohvf/ubZsyYofz8fBmGoZKSknb1lmVpxYoVysvLk8/n05QpU3Ts2DF7gr2GkURDj3Tdddfpqaee0qFDh1RWVqbbb79dd999t9599127Q0MCOnjwoH7zm99o7NixdoeCBDRq1ChVVlbGH3v37rU7JCSY2tpa3XrrrXK73dqxY4f+9a9/6ZlnnlGvXr3sDg0J5ODBg+3eS3bt2iVJmjVrls2RIZGsXbtWGzdu1HPPPaf33ntPa9eu1bp167Rhwwa7Q0OCWbRokXbt2qWXXnpJR44c0Te/+U1NmTJFp0+ftjs02KSpqUnjxo3T888/32n9unXr9Oyzz2rTpk3av3+/UlJSNHXqVLW2tl7lSK9thsXPGviC6N27t55++ml997vftTsUJJDGxkZNmDBBv/71r7Vq1SqNHz9excXFdoeFBLFy5UqVlJSovLzc7lCQwJYuXap//OMf+vvf/253KLiGFBUV6bXXXtOxY8dkGIbd4SBB3HXXXcrJydELL7wQL7vnnnvk8/n08ssv2xgZEklLS4vS0tL0pz/9SdOnT4+XT5w4UdOmTdOqVatsjA6JwDAMbd++XTNnzpQU7YWWn5+vn/zkJ1qyZIkkye/3KycnR1u2bNGcOXNsjPbaQk809HimaWrbtm1qampSQUGB3eEgwTzwwAOaPn26pkyZYncoSFDHjh1Tfn6+rr/+es2bN08VFRV2h4QE8+c//1mTJk3SrFmzlJ2drZtuukm//e1v7Q4LCSwYDOrll1/WwoULSaChncLCQpWWluro0aOSpMOHD2vv3r2aNm2azZEhkYTDYZmmqaSkpHblPp+PHvPo1Mcff6yqqqp233kyMjI0efJk7du3z8bIrj0uuwMArpQ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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,(ax1)=plt.subplots(figsize=(15,5))\n",
    "\n",
    "word=pandas_table['title'].str.split().apply(lambda x : [len(i) for i in x])\n",
    "sns.distplot(word.map(lambda x: np.mean(x)),ax=ax1,color='#17C37B')\n",
    "ax1.set_title('Headline')\n",
    "\n",
    "fig.suptitle('Average word length in each Headline')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_corpus(target):\n",
    "    corpus=[]\n",
    "    \n",
    "    for x in pandas_table['title'].str.split():\n",
    "        for i in x:\n",
    "            corpus.append(i)\n",
    "    return corpus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.array(stop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "comment_words = '' \n",
    "stopwords = set(STOPWORDS) \n",
    "  \n",
    "\n",
    "for val in stop: \n",
    "      \n",
    "    # typecaste each val to string \n",
    "    val = str(val) \n",
    "  \n",
    "    # split the value \n",
    "    tokens = val.split() \n",
    "      \n",
    "    # Converts each token into lowercase \n",
    "    for i in range(len(tokens)): \n",
    "        tokens[i] = tokens[i].lower() \n",
    "      \n",
    "    comment_words += \" \".join(tokens)+\" \"\n",
    "  \n",
    "wordcloud = WordCloud(width = 800, height = 800, \n",
    "                background_color ='white',\n",
    "                stopwords = stopwords, \n",
    "                min_font_size = 10).generate(comment_words) \n",
    "  \n",
    "# plot the WordCloud image                        \n",
    "plt.figure(figsize = (8, 8), facecolor = \"white\") \n",
    "plt.imshow(wordcloud) \n",
    "plt.axis(\"off\") \n",
    "plt.tight_layout(pad = 0) \n",
    "  \n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 10 artists>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corpus=create_corpus(\"title\")\n",
    "\n",
    "dic=defaultdict(int)\n",
    "for word in corpus:\n",
    "    if word in stop:\n",
    "        dic[word]+=1     \n",
    "        \n",
    "top=sorted(dic.items(), key=lambda x:x[1],reverse=True)[:10] \n",
    "x,y=zip(*top)\n",
    "plt.bar(x,y, color='#17C37B')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 1 artists>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "corpus=create_corpus(\"title\")\n",
    "\n",
    "dic=defaultdict(int)\n",
    "import string\n",
    "special = string.punctuation\n",
    "for i in (corpus):\n",
    "    if i in special:\n",
    "        dic[i]+=1\n",
    "        \n",
    "x,y=zip(*dic.items())\n",
    "plt.bar(x,y,color='#17C37B')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "counter=Counter(corpus)\n",
    "most=counter.most_common()\n",
    "x=[]\n",
    "y=[]\n",
    "for word,count in most[:40]:\n",
    "    if (word not in stop) :\n",
    "        x.append(word)\n",
    "        y.append(count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=y,y=x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def find_hash(text):\n",
    "    line=re.findall(r'(?<=#)\\w+',text)\n",
    "    return \" \".join(line)\n",
    "df['hash']=df['title'].apply(lambda x:find_hash(x))\n",
    "temp=df['hash'].value_counts()[:][1:11]\n",
    "df.head()\n",
    "\n",
    "temp= temp.to_frame().reset_index().rename(columns={'index':'Hashtag','hash':'count'})\n",
    "sns.barplot(x=\"Hashtag\",y=\"count\", data = temp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def mentions(text):\n",
    "    line=re.findall(r'(?<=@)\\w+',text)\n",
    "    return \" \".join(line)\n",
    "df['mentions']=df['title'].apply(lambda x:mentions(x))\n",
    "\n",
    "temp=df['mentions'].value_counts()[:][1:11]\n",
    "temp =temp.to_frame().reset_index().rename(columns={'index':'Mentions','mentions':'count'})\n",
    "\n",
    "sns.barplot(x=\"Mentions\",y=\"count\", data = temp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Computing\\AppData\\Local\\Temp\\ipykernel_15284\\20215729.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['title']=df['title'].apply(lambda x:remove_urls(x))\n",
      "C:\\Users\\Computing\\AppData\\Local\\Temp\\ipykernel_15284\\20215729.py:10: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['title']=df['title'].apply(lambda x:remove_html(x))\n"
     ]
    }
   ],
   "source": [
    "#Remove Urls and HTML links\n",
    "def remove_urls(text):\n",
    "    url_remove = re.compile(r'https?://\\S+|www\\.\\S+')\n",
    "    return url_remove.sub(r'', text)\n",
    "df['title']=df['title'].apply(lambda x:remove_urls(x))\n",
    "\n",
    "def remove_html(text):\n",
    "    html=re.compile(r'<.*?>')\n",
    "    return html.sub(r'',text)\n",
    "df['title']=df['title'].apply(lambda x:remove_html(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Computing\\AppData\\Local\\Temp\\ipykernel_15284\\1215840115.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['title']=df['title'].apply(lambda x:lower(x))\n",
      "C:\\Users\\Computing\\AppData\\Local\\Temp\\ipykernel_15284\\1215840115.py:12: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['title']=df['title'].apply(lambda x:remove_num(x))\n"
     ]
    }
   ],
   "source": [
    "# Lower casing\n",
    "def lower(text):\n",
    "    low_text= text.lower()\n",
    "    return low_text\n",
    "df['title']=df['title'].apply(lambda x:lower(x))\n",
    "\n",
    "\n",
    "# Number removal\n",
    "def remove_num(text):\n",
    "    remove= re.sub(r'\\d+', '', text)\n",
    "    return remove\n",
    "df['title']=df['title'].apply(lambda x:remove_num(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Computing\\AppData\\Local\\Temp\\ipykernel_15284\\185697248.py:9: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['title']=df['title'].apply(lambda x:punct_remove(x))\n",
      "C:\\Users\\Computing\\AppData\\Local\\Temp\\ipykernel_15284\\185697248.py:14: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['title']=df['title'].apply(lambda x:remove_stopwords(x))\n"
     ]
    }
   ],
   "source": [
    "#Remove stopwords & Punctuations\n",
    "from nltk.corpus import stopwords\n",
    "\", \".join(stopwords.words('english'))\n",
    "STOPWORDS = set(stopwords.words('english'))\n",
    "\n",
    "def punct_remove(text):\n",
    "    punct = re.sub(r\"[^\\w\\s\\d]\",\"\", text)\n",
    "    return punct\n",
    "df['title']=df['title'].apply(lambda x:punct_remove(x))\n",
    "\n",
    "def remove_stopwords(text):\n",
    "    \"\"\"custom function to remove the stopwords\"\"\"\n",
    "    return \" \".join([word for word in str(text).split() if word not in STOPWORDS])\n",
    "df['title']=df['title'].apply(lambda x:remove_stopwords(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Computing\\AppData\\Local\\Temp\\ipykernel_15284\\426118252.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['title']=df['title'].apply(lambda x:remove_mention(x))\n",
      "C:\\Users\\Computing\\AppData\\Local\\Temp\\ipykernel_15284\\426118252.py:9: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['title']=df['title'].apply(lambda x:remove_hash(x))\n"
     ]
    }
   ],
   "source": [
    "#Remove mentions and hashtags\n",
    "def remove_mention(x):\n",
    "    text=re.sub(r'@\\w+','',x)\n",
    "    return text\n",
    "df['title']=df['title'].apply(lambda x:remove_mention(x))\n",
    "def remove_hash(x):\n",
    "    text=re.sub(r'#\\w+','',x)\n",
    "    return text\n",
    "df['title']=df['title'].apply(lambda x:remove_hash(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Computing\\AppData\\Local\\Temp\\ipykernel_15284\\3169671107.py:14: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['title']=df['title'].apply(lambda x:remove_space(x))\n"
     ]
    }
   ],
   "source": [
    "#Remove extra white space left while removing stuff\n",
    "def remove_space(text):\n",
    "    space_remove = re.sub(r\"\\s+\",\" \",text).strip()\n",
    "    return space_remove\n",
    "def stemming(text):\n",
    "    ps = PorterStemmer()\n",
    "    \n",
    "    return\" \".join([ps.stem(word) for word in str(text).split()])\n",
    "    \n",
    "def lemmatizing(text):\n",
    "    wordnet_lemmatizer = WordNetLemmatizer()\n",
    "    \n",
    "    return\" \".join([wordnet_lemmatizer.lemmatize(word) for word in str(text).split()])\n",
    "df['title']=df['title'].apply(lambda x:remove_space(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('bitcoin', 37),\n",
       " ('crypto', 22),\n",
       " ('us', 10),\n",
       " ('price', 9),\n",
       " ('paypal', 9),\n",
       " ('etf', 8),\n",
       " ('global', 7),\n",
       " ('sec', 7),\n",
       " ('digital', 7),\n",
       " ('stablecoin', 7),\n",
       " ('ethereum', 6),\n",
       " ('cryptocurrency', 6),\n",
       " ('best', 6),\n",
       " ('el', 6),\n",
       " ('salvador', 6),\n",
       " ('social', 6),\n",
       " ('media', 6),\n",
       " ('press', 6),\n",
       " ('free', 6),\n",
       " ('payments', 5)]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from collections import Counter\n",
    "comment_words = '' \n",
    "stopwords = set(STOPWORDS) \n",
    "\n",
    "for val in df.title: \n",
    "      \n",
    "    # typecaste each val to string \n",
    "    val = str(val) \n",
    "  \n",
    "    # split the value \n",
    "    tokens = val.split() \n",
    "      \n",
    "    # Converts each token into lowercase \n",
    "    for i in range(len(tokens)): \n",
    "        tokens[i] = tokens[i].lower() \n",
    "      \n",
    "    comment_words += \" \".join(tokens)+\" \"\n",
    "split_it = comment_words.split()\n",
    "Counter = Counter(split_it)\n",
    "number=20\n",
    "most_occur = Counter.most_common(number)\n",
    "most_occur"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Word'>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfm = pd.DataFrame(most_occur, columns = ['Word', 'Count'])\n",
    "dfm.plot.bar(x='Word',y='Count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Computing\\AppData\\Local\\Temp\\ipykernel_15284\\1483629935.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['title']=df['title'].apply(lambda x:stemming(x))\n"
     ]
    }
   ],
   "source": [
    "df['title']=df['title'].apply(lambda x:stemming(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax1 = plt.subplots( figsize=[30, 15])\n",
    "\n",
    "comment_words = '' \n",
    "stopwords = set(STOPWORDS) \n",
    "\n",
    "for val in df.title: \n",
    "      \n",
    "    # typecaste each val to string \n",
    "    val = str(val) \n",
    "  \n",
    "    # split the value \n",
    "    tokens = val.split() \n",
    "      \n",
    "    # Converts each token into lowercase \n",
    "    for i in range(len(tokens)): \n",
    "        tokens[i] = tokens[i].lower() \n",
    "      \n",
    "    comment_words += \" \".join(tokens)+\" \"\n",
    "\n",
    "words= []\n",
    "tokens=comment_words.split()\n",
    "\n",
    "for x in tokens:\n",
    "    if x not in comment_words:\n",
    "        words.append(x)\n",
    "\n",
    "words=   \" \".join(words) \n",
    "\n",
    "wordcloud1 = WordCloud(width = 800, height = 800, \n",
    "                background_color ='white',\n",
    "                colormap=\"Greens\",\n",
    "                stopwords = stopwords, \n",
    "                min_font_size = 10).generate(words) \n",
    "\n",
    "ax1.imshow(wordcloud1)\n",
    "ax1.axis('off')\n",
    "ax1.set_title('Positive Sentiment',fontsize=35);\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define functions\n",
    "def generate_ngrams(text, n_gram=1):\n",
    "    token = [token for token in text.lower().split(' ') if token != '' if token not in STOPWORDS]\n",
    "    ngrams = zip(*[token[i:] for i in range(n_gram)])\n",
    "    return [' '.join(ngram) for ngram in ngrams]\n",
    "\n",
    "N = 30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>hash</th>\n",
       "      <th>mentions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>role bitcoin global financi system</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sec delay decis ark invest bitcoin etf gather ...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>write rapidli evolv vc startup sector europ</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>speed launch magento plugin simplifi bitcoin p...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>bitcoin trend watch nostr ordin lightn network...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>creat sustain blockchain ecosystem public good...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>best site buy x follow cheap price</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>farmskin promo code get free case signup bonus</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>financi regul affect investor</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>fidel vs robinhood invest platform best</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>104 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 title hash mentions\n",
       "0                   role bitcoin global financi system              \n",
       "1    sec delay decis ark invest bitcoin etf gather ...              \n",
       "2          write rapidli evolv vc startup sector europ              \n",
       "3    speed launch magento plugin simplifi bitcoin p...              \n",
       "4    bitcoin trend watch nostr ordin lightn network...              \n",
       "..                                                 ...  ...      ...\n",
       "99   creat sustain blockchain ecosystem public good...              \n",
       "100                 best site buy x follow cheap price              \n",
       "101     farmskin promo code get free case signup bonus              \n",
       "102                      financi regul affect investor              \n",
       "103            fidel vs robinhood invest platform best              \n",
       "\n",
       "[104 rows x 3 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
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    }
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    "df"
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  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('extracted_news_articles_processed.csv', encoding='utf-8', sep=',')"
   ]
  }
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