quizzicol · October 10, 2016 11:04
diff --git a/Donald Trump tweet analysis.ipynb b/Donald Trump tweet analysis.ipynb
 {
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Donald Trump tweet analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 375,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import tweepy\n",
    "import json\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('fivethirtyeight')\n",
    "%matplotlib inline\n",
    "\n",
    "pd.options.mode.chained_assignment = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "with open('/mnt/hgfs/Data Science/twitter_creds.json') as json_data:\n",
    "    twitter_creds  = json.load(json_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "auth = tweepy.OAuthHandler(twitter_creds['consumer_key'], twitter_creds['consumer_secret'])\n",
    "auth.set_access_token(twitter_creds['access_token'], twitter_creds['access_secret'])\n",
    "api = tweepy.API(auth)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The tweepy 'user_timeline' method returns an object with a lot of attributes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Thank you to my great supporters in Wisconsin. I heard that the crowd and enthusiasm was unreal!\n",
      "RT @atensnut: Hillary calls Trump's remarks \"horrific\" while she lives with and protects a \"Rapist\".  Her actions are horrific.\n",
      "RT @atensnut: How many times must it be said? Actions speak louder than words. DT said bad things!HRC threatened me after BC raped me.\n",
      "The media and establishment want me out of the race so badly -  I WILL NEVER DROP OUT OF THE RACE, WILL NEVER LET MY SUPPORTERS DOWN! #MAGA\n",
      "Certainly has been an interesting 24 hours!\n",
      "Here is my statement. https://t.co/WAZiGoQqMQ\n",
      "Thoughts &amp; prayers with the millions of people in the path of Hurricane Matthew. Look out for neighbors, and listen… https://t.co/JqjyTiKicD\n",
      "\"@kevcirilli: Trump speaking in exact same tone he did in Waterville Valley on 12/1. The night I first realized he was gonna be GOP nominee\"\n",
      "New National Rasmussen Poll: https://t.co/BnAveA5OuP\n",
      "Thank you Tennessee! #MAGA https://t.co/OoDFmerQ5B\n",
      "VOTE #TrumpPence16 on 11/8/16! https://t.co/12zAk8VmgK\n",
      "'Donald Trump: A President for All Americans' https://t.co/3lU2vrUE3t\n",
      "Volunteer to be a Trump Election Observer. Sign up today!\n",
      "#MakeAmericaGreatAgain\n",
      "https://t.co/ZzFHlsWnh4\n",
      "RT @DonaldJTrumpJr: Great group at our Victory Office in Columbus, Ohio. I'm incredibly grateful to have so many… https://t.co/rLJWCAGRlW\n",
      "RT @IvankaTrump: Thank you Angie Phillips for inviting me to tour your plant Middletown Tube Works. #Ohio https://t.co/fUKiiEIBXT\n",
      "Praying for everyone in Florida. Hoping the hurricane dissipates, but in any event, please be careful.\n",
      "New Virginia poll- thank you! We are going to show the whole world that America is back – BIGGER, and BETTER, and S… https://t.co/2CikEXb0G7\n",
      "Pennsylvania poll just released. Two rallies there on Mon- join me!\n",
      "Ambridge: https://t.co/TujWDWcgd3\n",
      "Wilkes-Barre:… https://t.co/TeIeCttUpP\n",
      "Nation's Immigration And Customs Enforcement Officers (ICE) Make First-Ever Presidential Endorsement:\n",
      "https://t.co/eO1UY5N9J1\n",
      "Such a great honor! \n",
      "https://t.co/vt4AmLdkeP\n"
     ]
    }
   ],
   "source": [
    "for status in api.user_timeline('realDonaldTrump'):\n",
    "    # Process a single status\n",
    "    print(status.text) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>favorited</th>\n",
       "      <th>favoriteCount</th>\n",
       "      <th>replyToSN</th>\n",
       "      <th>created</th>\n",
       "      <th>truncated</th>\n",
       "      <th>replyToSID</th>\n",
       "      <th>id</th>\n",
       "      <th>replyToUID</th>\n",
       "      <th>statusSource</th>\n",
       "      <th>screenName</th>\n",
       "      <th>retweetCount</th>\n",
       "      <th>isRetweet</th>\n",
       "      <th>retweeted</th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>My economic policy speech will be carried live...</td>\n",
       "      <td>False</td>\n",
       "      <td>9214</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-08-08 15:20:44</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>762669882571980801</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>realDonaldTrump</td>\n",
       "      <td>3107</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Join me in Fayetteville, North Carolina tomorr...</td>\n",
       "      <td>False</td>\n",
       "      <td>6981</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-08-08 13:28:20</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>762641595439190016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>realDonaldTrump</td>\n",
       "      <td>2390</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                text favorited  favoriteCount  \\\n",
       "0  My economic policy speech will be carried live...     False           9214   \n",
       "1  Join me in Fayetteville, North Carolina tomorr...     False           6981   \n",
       "\n",
       "  replyToSN              created truncated  replyToSID                  id  \\\n",
       "0       NaN  2016-08-08 15:20:44     False         NaN  762669882571980801   \n",
       "1       NaN  2016-08-08 13:28:20     False         NaN  762641595439190016   \n",
       "\n",
       "   replyToUID                                       statusSource  \\\n",
       "0         NaN  <a href=\"http://twitter.com/download/android\" ...   \n",
       "1         NaN  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "        screenName  retweetCount isRetweet retweeted  longitude  latitude  \n",
       "0  realDonaldTrump          3107     False     False        NaN       NaN  \n",
       "1  realDonaldTrump          2390     False     False        NaN       NaN  "
      ]
     },
     "execution_count": 304,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfRaw = pd.read_csv('./trump_tweets.csv', encoding = 'latin1', engine='python')\n",
    "dfRaw.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1512 entries, 0 to 1511\n",
      "Data columns (total 16 columns):\n",
      "text             1512 non-null object\n",
      "favorited        1512 non-null bool\n",
      "favoriteCount    1512 non-null int64\n",
      "replyToSN        3 non-null object\n",
      "created          1512 non-null object\n",
      "truncated        1512 non-null bool\n",
      "replyToSID       0 non-null float64\n",
      "id               1512 non-null int64\n",
      "replyToUID       3 non-null float64\n",
      "statusSource     1512 non-null object\n",
      "screenName       1512 non-null object\n",
      "retweetCount     1512 non-null int64\n",
      "isRetweet        1512 non-null bool\n",
      "retweeted        1512 non-null bool\n",
      "longitude        5 non-null float64\n",
      "latitude         5 non-null float64\n",
      "dtypes: bool(4), float64(4), int64(3), object(5)\n",
      "memory usage: 147.7+ KB\n"
     ]
    }
   ],
   "source": [
    "dfRaw.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>statusSource</th>\n",
       "      <th>text</th>\n",
       "      <th>created</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>762669882571980801</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>My economic policy speech will be carried live...</td>\n",
       "      <td>2016-08-08 15:20:44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>762641595439190016</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Join me in Fayetteville, North Carolina tomorr...</td>\n",
       "      <td>2016-08-08 13:28:20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   id                                       statusSource  \\\n",
       "0  762669882571980801  <a href=\"http://twitter.com/download/android\" ...   \n",
       "1  762641595439190016  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                text              created  \n",
       "0  My economic policy speech will be carried live...  2016-08-08 15:20:44  \n",
       "1  Join me in Fayetteville, North Carolina tomorr...  2016-08-08 13:28:20  "
      ]
     },
     "execution_count": 306,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = ['id', 'statusSource', 'text', 'created']\n",
    "dfTrump = dfRaw[cols]\n",
    "dfTrump.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We want to be able to identify the tweets by those made from a iPhone and those made by an Android phone.\n",
    "\n",
    "The 'statusSource' attribute has the following unique values in our list of tweets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ '<a href=\"http://twitter.com/download/android\" rel=\"nofollow\">Twitter for Android</a>',\n",
       "       '<a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>',\n",
       "       '<a href=\"http://twitter.com\" rel=\"nofollow\">Twitter Web Client</a>',\n",
       "       '<a href=\"http://twitter.com/#!/download/ipad\" rel=\"nofollow\">Twitter for iPad</a>',\n",
       "       '<a href=\"http://instagram.com\" rel=\"nofollow\">Instagram</a>'], dtype=object)"
      ]
     },
     "execution_count": 307,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfTrump.statusSource.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can identify create a 'device' attribute to capture whether the tweet is from an iPhone or Android device using some Pandas magic.  Adn then we can filter the dataframe to jsut include those devices."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 308,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/quizzicol/anaconda3/lib/python3.5/site-packages/pandas/core/indexing.py:288: 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: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self.obj[key] = _infer_fill_value(value)\n",
      "/home/quizzicol/anaconda3/lib/python3.5/site-packages/pandas/core/indexing.py:465: 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: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self.obj[item] = s\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>statusSource</th>\n",
       "      <th>text</th>\n",
       "      <th>created</th>\n",
       "      <th>device</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>762669882571980801</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>My economic policy speech will be carried live...</td>\n",
       "      <td>2016-08-08 15:20:44</td>\n",
       "      <td>Android</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>762641595439190016</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Join me in Fayetteville, North Carolina tomorr...</td>\n",
       "      <td>2016-08-08 13:28:20</td>\n",
       "      <td>iPhone</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   id                                       statusSource  \\\n",
       "0  762669882571980801  <a href=\"http://twitter.com/download/android\" ...   \n",
       "1  762641595439190016  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                text              created  \\\n",
       "0  My economic policy speech will be carried live...  2016-08-08 15:20:44   \n",
       "1  Join me in Fayetteville, North Carolina tomorr...  2016-08-08 13:28:20   \n",
       "\n",
       "    device  \n",
       "0  Android  \n",
       "1   iPhone  "
      ]
     },
     "execution_count": 308,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfTrump.loc[:,'device'] = 0\n",
    "dfTrump.loc[dfTrump.statusSource.str.contains('Twitter for Android'), 'device'] = 'Android'\n",
    "dfTrump.loc[dfTrump.statusSource.str.contains('Twitter for iPhone'), 'device'] = 'iPhone'\n",
    "dfTrump = dfTrump.loc[dfTrump.device.isin(['Android', 'iPhone']), :]\n",
    "dfTrump.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This gives us 628 tweets from an iPhone and 762 from an Android device"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "device\n",
       "Android    762\n",
       "iPhone     628\n",
       "Name: id, dtype: int64"
      ]
     },
     "execution_count": 309,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfTrump.groupby('device').count()['id']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we need to capture the hour of each tweet so we can see the distrubution of tweets from different devices at different times.\n",
    "\n",
    "Twitter stores times in ['UTC' time](https://dev.twitter.com/faq#47) so to get local time when the tweets were made, we first need to convert the timezone."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>created</th>\n",
       "      <th>id</th>\n",
       "      <th>statusSource</th>\n",
       "      <th>text</th>\n",
       "      <th>device</th>\n",
       "      <th>raw_tweet_time</th>\n",
       "      <th>tweet_hour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-08-08 11:20:44-04:00</td>\n",
       "      <td>762669882571980801</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>My economic policy speech will be carried live...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-08-08 15:20:44</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-08-08 09:28:20-04:00</td>\n",
       "      <td>762641595439190016</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Join me in Fayetteville, North Carolina tomorr...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-08 13:28:20</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    created                  id  \\\n",
       "0 2016-08-08 11:20:44-04:00  762669882571980801   \n",
       "1 2016-08-08 09:28:20-04:00  762641595439190016   \n",
       "\n",
       "                                        statusSource  \\\n",
       "0  <a href=\"http://twitter.com/download/android\" ...   \n",
       "1  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                text   device  \\\n",
       "0  My economic policy speech will be carried live...  Android   \n",
       "1  Join me in Fayetteville, North Carolina tomorr...   iPhone   \n",
       "\n",
       "        raw_tweet_time  tweet_hour  \n",
       "0  2016-08-08 15:20:44          11  \n",
       "1  2016-08-08 13:28:20           9  "
      ]
     },
     "execution_count": 310,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfTrump['raw_tweet_time'] = dfTrump.created\n",
    "dfTrump.created = pd.to_datetime(dfTrump.created)\n",
    "dfTrump = dfTrump.set_index('created').tz_localize('UTC').tz_convert('US/Eastern').reset_index()\n",
    "\n",
    "dfTrump['tweet_hour'] = dfTrump.created.apply(lambda x: x.hour)\n",
    "dfTrump.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use a pivot table to aggregate the tweets by tweet time and device"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>device</th>\n",
       "      <th>Android</th>\n",
       "      <th>iPhone</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tweet_hour</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>22</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "device      Android  iPhone\n",
       "tweet_hour                 \n",
       "0                22      15\n",
       "1                10      10"
      ]
     },
     "execution_count": 312,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfPivot = pd.pivot_table(data=dfTrump[['id', 'tweet_hour', 'device']], index='tweet_hour', columns='device', aggfunc='count', fill_value=0)\n",
    "dfPivot.columns = dfPivot.columns.droplevel()\n",
    "dfPivot.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 323,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.text.Text at 0x7f87c71bd160>,\n",
       " <matplotlib.text.Text at 0x7f87c71b90b8>,\n",
       " None]"
      ]
     },
     "execution_count": 323,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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d3tzQ6ffsqnPiK3g+5Hg+5Fh8hDxNdKOMsC0p+wZ5Z/czJyBqq4BTR4DSS9b9\ngUGQbp3T+cFYsYvIa3k8rWvt2rWYO3euZXvGjBlYuXIlAGDVqlWYOXOmp4fk37w5rSs2EbCdSaut\ngtDr1RsPERF1X3caMNo+Py4RyBxi3SEExJH9MG76X/nzJt0GqVd858dSzNooq4gRkXo8Gpw0NTVh\n27ZtuPvuuy37Fi5ciK1bt2LIkCHYvn07Fi1a5Mkh+TWh1wO2jawkCYjrfObKk6SgIFOneDMhgOpy\n9QZERETdZ9fjpGvBCQBIoxRVuzasAk4elj9H2XTREaZ1EXktj6Z1hYeHo7xc/uEyLi4O27Zt8+Qw\nyKyqzPSB36xXvCkg8CbxSfIAqrKsWxc0IiJSlzKty9keJ7LXjBoP8X/vWXcU5MufMHIspAwn1lMp\nK1NWlkEYDJACAro8JiJyLXaI92fenNJlxopdRES+QZk61Z0bTUNGAuGRHT6sm/GgU4eRQsKAqF7W\nHUYDUF3R9fEQkcsxOPFjwou7w5tJ8Yo0MzZiJCLSHGEwABXK4KQbMyeBQcDIsY4fTM0wVfRylvKa\npxwfEamCwYk/8+YGjGYMToiItK+6Ami36XES1QtSWES3DqXsFm/Zf8dcU/d3ZymyBexu2BGRKhic\n+DNlp14NpHWhkgviiYg0x24xfNdnTcykbAfBSWQ0pJvv7Npx7GZOePOLyBswOPFjyo64khcGJ8q0\nLsGZEyIizRE9bcBoQ0pIBvoNlO+bPtvpbvMdjoHlhIm8AoMTf6bBBfFM6yIi0iDFB/+u9jhRkm67\n17oREwvp9vu7fhBlWhcbMRJ5BY93iCcvooEF8XZrTqoqIIzGruUVExGRulzQ48SWNG02EBYJXDgL\naeKtkLrRo0tKTJF3nOeaEyKvwODET4nmJqCx3rojMFDe8NBLSKFhQESUdayGdqC2CohNUHdgRETk\nNGVaV49nTnQ6SJNu7dEx7Kt1MTgh8ga8/eyvlH+E45O9dzbCLrWLvU6IiDTFhQviXaZXgunGnFl9\nrenGHRGpyks/jZLbaWG9iVkCywkTEWmVMBodpBGrH5xIOp39zS/OnhCpjsGJn9JCpS4zZS4xu8QT\nEWlITQXQrrduR0ZDiohSbzy2lNc+BidEqmNw4q+Ud7G8sQGjGdO6iIi0y8WL4V1JeWOOjRiJ1McF\n8f5K2WzKGyt1mTGti4h6KCMjAzExMdDpdAgKCkJubq7aQ/IbolTRP8QLUroslNc+9johUh2DEz+l\ntbQu23JW6rNKAAAgAElEQVSPTOsioq7S6XTYsWMHYmNj1R6K/3FxpS6XYsUuIq/DtC5/paUF8Uzr\nIqIeEkLAaDSqPQz/pJyN8KLghGldRN6HwYkfEkLYp3V5c3CiXA9TWWr6HsgrNLQZkF/VCiN/JuTF\nJEnC1KlTMWbMGPz9739Xezh+xb7HiTeldSnGorw2EpHHMa3LH9VVA22t1u3QcCAiUr3xXE1EFBAc\nCrS1mLZbW0xNGSOj1R0X4URlCx7/90W0GASuTwnD//thKgJ0ktrDIrKzZ88e9O7dG+Xl5Zg6dSqG\nDh2KCRMmqD0s/+DFC+Ltbn5VlEAYjd7b94vIDzA48UcOFsNLkvd+oJQkybQo/nKRdWdlGYMTL/DX\nI5VoMZhmTPaXNGPHxUb8sJ8XB7rkt3r3Nt0hT0xMxKxZs5Cbm9thcJKXl+fJoXm1Hp8LYURW6SVZ\nmsaRS6UwVNb37LgudG1oOAJbrjRfbNfj6K7/oD0ypsPn8/dDjudDjufDatCgQd16HYMTf6Sl9SZm\n8cmK4KQUSB+o3ngIrQYjDpU2y/ZtOV/P4IS8TlNTE4xGIyIjI9HY2IgtW7bgpZde6vD5OTk5Hhyd\n98rLy+vxuRDVFTAa2q07wiORPWFiD0fmWoaUVOD895btrD7JkAaPcPhcV5wTX8LzIcfzIVdbW9ut\n1zE48UPKBX/eXKnLzL5iVym8d67HPxwrb7HMmph9fakRze1GhAUyJYK8R2lpKWbNmgVJktDe3o55\n8+Zh2rRpag/LP3hzSpdZQm9ZcIKKYqCD4ISI3I/BiT+yWwzvxQ0Yzex6nZSrMw6yyC1ustvX3C6w\n51IjpqR7SfdnIgCZmZk4cuSI2sPwS8rF8N4YnEiJKfKbX+UlvPlFpCLe3vRHFYqyjhqYObEvJ8yK\nKmrbX9LscP/WwgYPj4SIvJY3V+oys2vEyHLCRGpicOKHhGLmRPLm7vBXSHHymRPB4ERVDW0GnKxs\ncfjYroum1C4iIk2kdcUrep2wESORqhic+COmdVEPHSxthqGDtiYtBlNqFxGRUDRg9Kru8FfY3aBT\nNo0kIo9icOJnhKEdqFJ0WFemTHkjpnV5lVxFSlegIkGbqV1EBAAo897u8BbK4IQzJ0SqYnDib6oq\nAKNNyk1MLKSQUPXG46yYOCDApn5DQx1Eq+M1D+R++xWL4ecNjZVtM7WLiIQQ9mldyo7s3iAuEbBt\nulhbDdHqOG2ViNyPwYm/Ud4Rivf+9SYATN164xLkOyvLHD+Z3KqiuR1na9ss2zoJWDAiFsnh1uCx\nxSCwm6ldRP6ttgpoa7Vuh0V4ZfNcKSAQiFOmDnN2nkgtDE78jN1CPw0shrewS+1icKKGAyXyWZOh\ncSGICQnAlHR588VtTO0i8m8OUrokyUuL9LJiF5HX8GhwUltbizlz5mDo0KEYPnw49u/fj+rqakyb\nNg1DhgzB9OnTu91NkpykrNSlhcXwV9hV7FIu7CeP2F8sT6cbmxIOAJiqCE6Y2kXk3+x7nHhhStcV\nymbErNhFpB6PBic/+9nPcNttt+HUqVM4evQorrnmGixduhRTpkxBfn4+Jk+ejCVLlnhySP5HWYXE\nG/N/O6Ks2KVc2E9uJ4RArmLmZGxvU3BybUIoUpjaRURmdj1OvHAxvBlnToi8hseCk7q6Onz99ddY\nsGABACAwMBAxMTHYuHEj5s+fDwCYP38+NmzY4Kkh+SW72QYNzZwwrUt9Fxv0KG5st2wH6yRcl2gq\nqKCTJPxQMXvCql1EfkwLi+HNEhRjYzlhItV4LDgpKChAQkICFixYgFGjRuHJJ59EU1MTSktLkZxs\n+tCZkpKCsjJ+4HQrDad1IZ5pXWpTpnRlJYYiNND6Z2SaIjj5+mIjmvVM7SLyR8q0Lm+eOVH2OmFa\nF5F6PBactLe349ChQ3j22Wdx6NAhREREYOnSpXaL47x2sZyvqFDcDVLeLfJiknLmhGldHqdM6br+\nSkqXmcPUrstM7SLyS8rZBy8OTuyyCJjWRaSawKs/xTX69u2LtLQ05OTkAABmz56NpUuXIjk52TJ7\nUlJSgqSkpE6Pk5eX54nhakJXz4Wkb8N1dTWWbSHpcPBcIXD+gquH5hbBNRUYbrOtL7mEw4pzwN8P\nOVeeD6MA9l2Mgu09jaiaQuTlnZM979rQUJQ0hVi21x0uQmy5d/Sk4e+H1aBBg9QeAvkwhz1OvDk4\nUaacVZRACMEbpl6ioLYNZ2tacX3vcEQFB6g9HHIzjwUnycnJSEtLw+nTpzF48GBs374dw4cPx/Dh\nw7Fy5UosXLgQq1atwsyZMzs9jjm48Xd5eXldPhfiUiFsE2ykhCTkjB3r2oG5kdDrYVxh3Q5qrMPo\n67IgBQYB6N458WWuPh/5Va1o+K7Ish0ZpMPdN16HQJ384h1c3oytX160bJ9oCsHwrKEIC1K3cjl/\nP+RYGZHcqq4asG1kGBoGRMWoN56riYgCQsOBliuzw22tpu8hJk7dcRH2XW7EM9tNge7AXsFYfWsa\nwgLZCcOXeSw4AYC33noL8+bNg16vR//+/fH+++/DYDDg3nvvxXvvvYf09HSsX7/ek0PyL8oc2gQN\n9TgBIAUFAb3igZpK0w4hgOoK715k6UP2K1K6RieH2QUmgDW1q6TJtHDenNo1NT3KI+MkIi+gpR4n\nuJJSnpgCXLCZCS4vYXDiBd49VmX5+kxNG74oqMfdg7w40KUe82hwkpWVhQMHDtjt37ZtmyeH4beU\nC8g1tRjeLC7JGpwApi6+DE48IrdYUUI4Jdzh8yRJwpT0SPzvKWsK4ZbzDQxOiPxJuYZSusyUwUlF\nCTBwmHrjIdS1GnCsokW2bzODE5/HeTF/ouHF8BYJyopdXBTvCXqDwMFS+bqR63uHdfh8ZUPG3ZdY\ntYu6b+3atTh16hQAID8/HxMnTsTNN9+M7777TuWRUUeEYubEmyt1mUmKayIrdqlvf0kTjEK+72Bp\nMy436NUZEHkEgxN/ouUeJ1ewYpc6jle0oMVgvUIkhAWgf0xwh8+/NiEUKRHyql1fsyEjddOLL76I\nuDhTes0vf/lLjB07FpMmTcIzzzyj8sioQ1rqcWLGRoxeZ8+lJof7vyio9/BIyJM8mtZF6hKKP7TK\nuu6aEKeo5sZeJx5h1xU+JbzT/HFJkjClnzy1a2thA6ZlMLWLuq68vBzJycloaWnB7t278dFHHyEo\nKAgJCQlqD406oKUeJxbKdZgMTlQlhMDeDkrRf15Qj0dHxHr1OibqPs6c+BONL4gHYJfWxZkTz7AP\nTjpO6TKbplhjwtQu6q7ExEScOXMGX3zxBcaMGYOQkBC0tLSYytWSd9JSGeEr2IjRu5yubkN5s8Hh\nYwW1bfiuqtXDIyJP4cyJnxBC+Exal+3HEVHJ4MTdmvRGHC+XL0gc29vxYnhbIxJCkBIRiJJGa9Wu\nry81cvaEuuy3v/0tRo8ejYCAAKxbtw6AqZBKVlaWyiMjR0w9TpTVurSQ1qUYo7KJJHlUR7MmZp+f\nq8fQ+FAPjYY8iTMn/qKx3lq/HQCCQ4GoXuqNp7vimdblaYfKmtFuExH2iwpC74igq75OkiS7hfFb\nChtcPTzyA4888giKi4tx8eJFTJ06FQAwbtw4S6BCXqa+Vn69CQkFomPVG4+z4pIA2zSh6goIfZt6\n4/Fzey7LZ+xzkuUz9l+er0e7crU8+QQGJ/7CLqUrWZu5mso1J9XlEEamCrnTfmUJYSdmTcym9pPP\nkuy51IgmpnZRF2VnZyM8PBzh4dbfvaSkJNx+++0qjoo65GAxvBauN5ZeWrY4O6+KhjYDjpbJK0Qu\nGpuISJtmvpUtBruUY/INDE78hXJhnxYXwwOQwsJNnXzN2ttNXXzJbbqz3sTMnNplxqpd1B1nzpyx\n2yeEwLlz5xw8m1SnwfUmFnapXVx3oobcEvmMfUZ0EAb0CsEP+8ln4z8/x6pdvohrTvyEcmGfpMXF\n8GbxSaY0NbOKUvu7XeQSVS3tOF1tTWuQAIzpoPmiI+bUrg9Oyqt2Tee6E3LCww8/DABoa2uzfG12\n/vx5DB8+XI1h0VWIcu31ODGTElIgTh+3bIuKYnj/nI/v2aO4iXVjnwgAwO39o7DxbJ1l/1dFDWjS\nGxEexHvtvoTBib/wgcXwFvHJQNFZ63ZVGQB28XWHvBL5tPqQuBD0Cgno0jGmpUfJgpPdV1K7eDGh\nqxkwYIDDryVJwo033og5c+aoMSy6Gk3PnLCcsNpMJYTlM/bjU003xUYnhyE5PBClTdZCK19daMAd\n/aM9Pk5yHwYn/sIXyghfIcUnySt2VZTxzpabKFO6ru/CrInZ8PgQ9I4IRPGVql2tV1K7OHtCV/PS\nSy8BMC1+nz59usqjIWcpe5xoolKXGYMT1Z2rbUPJleADAEIDJIy+shheJ0m4NTMKK09Y07k3n6tn\ncOJjeOvST/hcWpetSlbscpdcxczJ2N7Orzcxc1y1i3nC5Lzp06dj69ateOyxx3DnnXcCAPLy8vDV\nV1+pPDJyqEzLaV3yQIq9TjxP2RU+JyUMIQHWj6u3Z8pvbO0vaUK5TTBD2sfgxF/4yIJ4AKa0Llts\nxOgWlxv0uFCvt2wH6oDsxK4HJwAwNV1ZtauJVbvIacuXL8ePfvQjDBo0CLt27QIAhIWF4cUXX1R5\nZKRk6nHiQ2ldDE48bo+iv8n4K+tNzAbGhmBIbIhl2yhMZYXJdzA48QPCaLT/AK/hmRNJMXMiKhic\nuIOyhPDIhDCEdXOdiDm1y6zVILDrIqt2kXP+8pe/YNu2bVi0aBF0OtPv4DXXXIP8/HyVR0Z2GuuB\nZpt/28EhQEyceuPpKgdpXUKwl4anNOmNOFwmb/p7Yx/7dOLb+stveLFql29hcOIP6mtMJXfNwiMh\nhXbvDrhXYFqXR9iVEO5GSpeZo9SurUW8mJBz6uvrkZaWBgCWfhl6vR7BwcFqDosccTBrooUeJxZR\nvUxNis1amuTVIcmtDpQ0QW/TWDEtKgj9ou3/nd+SEQWdza9VfnUrzlS3emKI5AFOBSfV1Y77SNTU\n1DjcT15G2Qekl4buYjniIK2Ld7ZcSwiBA4r1Jt1ZDG9rGlO7qJsmTpyIpUuXyva99dZbuPnmm1Ua\nEXXIQQNGLZEkycHsSbHjJ5PLKbvCj3cwawIASeGBGKu4Jm0uYBDpK5wKTtLT0x3u79+/v0sHQ25S\nqwhOomPVGYerREYr7mw1A40N6o3HB52taUNli8GyHR4oYXhCaCevuLph8SHow9Qu6obly5fjk08+\nQUZGBurr6zFkyBCsX78er7/+utpDIwVlpS5JS5W6zJSl9lmxyyOEEPb9TVIjOng2cJtiYfwXBfUw\n8kalT3AqOHF0V7qxsdGS+0teTjlzovHgRJIkID5RvpOpXS6lTOkanRyGIF3PUjNMqV3yi8lWVu0i\nJ/Tu3RsHDhzA+vXrsWbNGqxatQq5ublISdHu2jmfpajUpanF8Fcoq1myYpdnFNbpcbnRmoIerJOQ\nk9xxOvEP+0UiNMB6XSppaseh0uYOn0/a0Wmfk0GDBkGSJDQ3N2Pw4MGyx8rKyjBjxgy3Do5cQyhm\nTqQYbQcnAEypXcUXrNtVZQCYf+4q+4sVJYR7mNJlNjU9EqtOWn8f91xuQqPeiAg2ZKSraG9vR2tr\nK4xGI8aNG4fGRtMd1oiIju+skufZ9zjRXnBil4rGmROPUFbpGp0chrDAjq8N4UE63JwWiS9sKnV9\ndq4eOS66XpF6Og1OVqxYASEE7r77bixfvtyyX5IkJCcnIysry+0DJBfwsZkTAJDikxWNGEuB2DTV\nxuNL2o0CB8uU/U1c88fenNp12aYh466Ljbg1kw0ZqWPHjx/HjBkzEBISgosXL+K+++7Dzp07sWrV\nKqxbt07t4ZEtZVqXxtacAHBQTphrTjxB2d/kxtSrX3du7x8lC062FzVg0dhEhHYS1JD36zQ4MXfk\nvXjxIuLiNL6I2p8p15z4xMyJMq2rjMGJi5yobEGjzUL12JAADOzlmlkpc2qX7ezJtsJ6BifUqR/9\n6Ed45ZVX8NBDDyE21vT3a9KkSXjiiSdUHhnZ8YGZEykhRX7zizMnbtfcbsRBRUqWsr+JI9f3Dkd8\naIBljWSD3ohdFxsxLYPXFC3rNDgxi46OxurVq3HkyBE0NMgXHr/77rtuGRi5kA/OnNhV7KosAwaq\nMxRfk6tM6eodBp0LS4EqU7u+KW6CUQiXvgf5lhMnTuDBBx8EYC0lHBERgeZm5pd7E9FQDzTZfEYI\nCgZ6xas3oO5y0OuE3CuvtBltNiWE+0QEIiM66KqvC9RJuCUjCv/8zlo99vOCegYnGufUvNcjjzyC\nV199FQaDAfHx8bL/yPuJOnnJZym6l0ojcR1JEZwILoh3Gbv+Ji7O3x0WH4JImzUmTe0CpU3tnbyC\n/F1GRgYOHjwo25ebm4uBA3lHwquU25cRlrRYOEd586u6HMLAv1HutNdBlS5n++MoGzLuvdSIqhb+\nvLTMqZmTzz//HGfOnGEwolU+OXOibMTILvGu0NxuxNFyeXfenvY3UZIkCZkxwTheYX2fgto29I64\n+l0y8k+vvvoqbr/9djz99NNoa2vDkiVL8M477+Dvf/97l45jNBqRk5ODvn37YtOmTW4arR/TeI8T\nMykk1NTVvrbKtMNoBKrKNfv9aIGz/U0cGRoXgsyYYBTUtgEA2gWwtbAB9w3R/o1Yf+XULY2+ffuy\nyZ2W+eSaE0VwUsXgxBWOlDXLuvOmRgYiNcr1QUNmjPyY5osKkSN33HEHvvzyS5SXl2PSpEkoLCzE\nxx9/jGnTpnXpOG+++SaGDRvmplGSUJQRljS43sSCqV0eU1TXhgv1est2kE7q0oy9JEm4XbFu8fNz\nLFOvZU7NnDz22GOYNWsWnn/+eSQny6c7x48f75aBkWsIIYB6eVqXT8ycxMQBAYGAeaq9vhaSvlXd\nMfmA3BL3lBBWyoyRL7BncEJXk52djb/+9a/dfv3FixexefNmLF68mM0b3cUHFsNbJKQAZ05aNkV5\nCbgqzj32KmZNspNCEd7F8vK3ZkZhxZFKy/bxihYU1rUhPZotBrTIqeBk2bJlAIBnnnlGtl+SJFy+\nfNnRS8hbNDYA7Ta5l6FhpilrjZMCAoDYBMCmOVawMgijLttfLL9IXO+iEsJKmYoLxjkGJ9SJ+Ph4\nTJw4EZMmTcKkSZNw3XXXOZ2Pbvbcc8/hT3/6E2pra900ShLl2m/AaCYl9pZV7GI5YfdR9je50Ykq\nXUp9IoMwKikMh2zK4H9RUI+ns7gcQYucCk6Ki/mPUrPqquTbvjBrYhafJAtOguoYnPREbasB31XJ\nZ5/GpHTcnbcnlDMn52v1HTyTyLT4fdeuXdi5cyfefPNN1NTUYMKECZg0aRJ++ctfXvX1n3/+OZKT\nk3Hddddhx44dV01TzsvLc9XQNa8r52LI+TOwvZ2RX1WLRo2ey8TmNvS12S47eRwX003fC38/5Hpy\nPvRGIPdyNGAzLxVTU4C8vLNdPtZwXRAO2fwGfnyqHKPbCuDpQpD8/bAaNGhQt17nVHDiKhkZGYiJ\niYFOp0NQUBByc3NRXV2N++67D4WFhcjIyMD69esRExPjyWH5NuVieF9Yb3KFshFjUH11h8+lq8sr\nbZadz0GxwYgLdc+fiNTIIATrJEvpyOpWA2paDegVEuCW9yNtGzBgAAYMGIAFCxbg9OnTWLVqFVas\nWIF///vfTgUne/bswaZNm7B582Y0Nzejvr4eDz/8MFavXu3w+Tk5Oa7+FjQpLy+vS+fC8Bf5DaJr\nJk6GpFwfqBGirRrGbf+ybCdKBqTk5HT5nPi6np6PfZcb0ZZvzcBJCQ/EjPHZXZ4ZBYAhbQZ8+K8C\ny7rJcn0AgjOGIyvRPTfZHOHvh1x3Z6qdSuobNGgQBg8e7PC/Lr2ZTocdO3bg8OHDyM3NBQAsXboU\nU6ZMQX5+PiZPnowlS5Z0/bugjikXw/vazImNYGUgRl2SW+zeEsK2AnQS0qO5KJ6c8/bbb2Pu3Lno\n168fHn74Yej1eqxduxYVFRVOvf6Pf/wjioqKcO7cOXz44YeYPHlyh4EJdY9obgIa6qw7AgNNqbda\nlaCozMUF8W6h7Ao/vk94twITAIgKDsDEvvKUMC6M1yanbouuWLFCtl1cXIwVK1bggQce6NKbCSFg\nNBpl+zZu3IidO3cCAObPn4+bbroJS5cu7dJxqWNC8YFd8uHghDMnPbNf0d/E1SWElTJjgvF9jTUg\nKahtQ3aS5+5wkXY8++yzGDBgAH7729/ijjvuQO/eLOnqdWoq5du9ErTZ48TMrloX09vdYa9yvUlq\n19eb2Lq9fxS2F1kbgW45X49f5SQiKIDlDLTEqeBk+vTpdvumTp2KGTNm4Pnnn3f6zSRJwtSpUxEQ\nEICnnnoKjz/+OEpLSy0VwFJSUlBWxpKwLuWLZYTNEuSV4xicdI8QAlsKG1BYZ133ESgBo5LdGygo\n151wUTx15OLFi9i5cyd27dqFN998E3q93rJA3tw53lnmRfXkYrWK4ETr15qYOCAwCGi/8nexqQGi\nkXfhXelygx4FiuvO2B6uc5zQJwIxwTrUtpluhNe2GbHnciNuSovs0XHJs7qdUB4ZGYmzZ7u2YGnP\nnj3o3bs3ysvLMW3aNAwZMsRu+q6703nUAeUicR/oDm8mxSXJ15wwravLDpU24y+HKmQNEQFgREIo\nIrpYyrGrWE6YnNWnTx/MnTsXc+fOxeHDh/HRRx9hxYoVeO+997ocnJCb1Cj+/vbSdpUkSaczlRMu\nuWDdWVGq3oB80G5FV/ispDBEBvds3WFQgISpGVH46LR1rcPn5+oZnGiMU8HJH//4R9l2U1MTPvvs\nM/zwhz/s0puZp+ITExNx1113ITc3F8nJyZbZk5KSEiQldb54jlUQrJw5F+kFZxBns32+qhZVPnIO\ng2sqMNx2u76Gvx8KHZ2P4lYd/q8sFEcbHDdYHCRVIy/PvRfi5hYdAGvjrPzyBrf//Pj7YdXdKipq\neOONN7Bjxw7s3r0bERERmDRpEv785z9zBsSLCMXMiaTx4ASAKbXLNjgpLwbA1FNXUfY3ubELXeE7\nc3umPDjZdbER9W0GRPUw8CHPcSo4OX78uGw7IiICjz/+OB599FGn36ipqQlGoxGRkZFobGzEli1b\n8NJLL2HGjBlYuXIlFi5ciFWrVmHmzJmdHodVEEycrQhh2Py+bDtzZDb6+8g5FHo9jDbLoQIb6jD6\nuixIga7vaK5Fjn5Hypra8c7RSmwsqIPRQTXVAAmYMzgGz48e6PYc3RHtRrxScNYy+1Wp12F41iiE\nuWnGxlNVVERVGUTuTkgDh0EaOPzqL1CJlvp9HD16FHfddRfeeOMN9O/fX+3hkCM1irL1Wk/rAiAl\npMhm50VlKRCfodZwfEqbwYjcEuVi+J6tNzHLSgxF38ggXGwwpYy1GQW2Fjbg7kGsBKsVTgUna9eu\n7fEblZaWYtasWZAkCe3t7Zg3bx6mTZuGnJwc3HvvvXjvvfeQnp6O9evX9/i9yIYPrzmRgoJMecG1\npouiBAFUVwCJXCyr1NBmwKoT1fjfUzVoMTju8XBzWgR+kp1gl27lLqGBOqTaXEAA4HxdG4bGa7dJ\nqKitgvGnc4CGOghdAKTn/wDdBPs1e9Q1I0aMwIIFC+z2v/76611a90huVKsITnxl5sRWeQmDExc5\nXNaC5nbrtSgxLACDY11z7ZEkCbf1j8K7x6y/k5sL6hmcaIjTa0727duHDz74AJcuXUJqaioeeugh\n3HDDDU6/UWZmJo4cOWK3Py4uDtu2bXP6ONRFynUYvlStCwDik+UXxcoyBic29AaBj76vxbvHqlDT\nanD4nJGJoXhuVAKuU6FSVmaMjwUnOz63llM1GiBWvALR/xpIfdLVHZjGvfLKKw77mfz+979ncOIl\nhLJaV0yc4ydqiaPg5Bp1huJrlFW6xveJcOma49sy5cHJ0bJmtBmMCA7QcAU5P+JUcLJ69Wo899xz\nmD9/PiZPnoyioiLMmDEDf/7znzF//nx3j5F6olaxIN6HZk4AAAlJwLlT1u1KVnsDTBW4DtQF4ZVP\nC3Gh3nH39fToIPw0OwE3p7n2otAVmTHB+Nqmzv05jXeKF8dy5TtammD886+hW7YSUpBnZqR8yVdf\nfQUAMBgM+M9//iPr7H7u3DlERUV19FLyNMXMidRL+8GJlNBbntZVwXLCrqLsb3JjqmtL16dHByM5\nPBClTe0AgHYBFNbpMSg2xKXvQ+7h9IL4LVu2YPTo0ZZ98+bNw9y5cxmceDHR0gy02VRhCgwCwlyT\n0+ktlBW7RGUZ/L3eW0FtG367pwQnKsMB2H/Yjw8NwFNZcbhrYAyCdOqeLV+q2CXa9cCJQ/YPnDsF\nsfotSI9dvZM5yT322GMAgJaWFtkaR0mSkJKSguXLl6s1NFKyW3PiA2ldinL1bMToGiWNepy1+Vsf\nIAHjeru+r9aAXsGW4AQAztS0MTjRCKeCk/LycmRlZcn2jRgxAuXl5W4ZFLmIg/UmPleqOV5x8ajw\n74tHVXM7ntx6ERXN9ilcYYES5g+LxUPDYhHu5jLBzvKl4ATfnwBamhw+JD79J8S1YyCNZXWprigo\nKAAAPPzww+zo7u3s1pxof+YECYq0rsoyQNFImrpOWaVrZGKoWyppDewVLHuvszWtsK0QSd7LqU8o\n48aNw6JFi9Da2goAaG1txeLFizFu3Di3Do56yNfXmwB2OcHicpFKA1GfUQj8dm+pXWBirsC16a4M\nPJUV7zWBCQD0VwQnRfVtaHdURkwDxLH9nT5uXP47CPZJ6BYGJt5N6PXWtVYAIElAlPZ7aklh4UCU\nzSJqQzuCGrRT5c5b7blkv97EHQb2ks+SfF+j4ZtffsapTynvvPMOdu/ejdjYWKSnpyM2Nha7du3C\nO++84+7xUU8o72T5YHAi9Rso33H+tDoD8QIfnKyxuyM1MTUCH92Zjt9cn4SEsG73XHWbqOAAJIRZ\n77JXdeIAACAASURBVJi1G4GLHayR8XbiqDw4kabeDehs7gbW18D4xm8gDI4LExBplt21phekAB/p\nKaGYPQmqq+rgieQMvVFgf0mzbJ+r+psoDewlv/llmjkhLXDq00paWhq++eYbnDlzBpcvX0afPn0w\ncODAq7+QVCXq5YvhJR/qDm+RlgkEBAKGK3mlFSUQ9bWQovyrZODx8hasOFwh2zcwrB3/fVNvBKq8\nruRqMqODUdFsvVgV1LYhw0PljF1FtDQDp+X9oKQ5jwEpqRAf2KyLOHEI4l//gHT/Ux4eIZEbKYMT\nX1hvYpaYAhTkWzaDld8rdcnR8mY06q2pcXGhARgS5551IJkxwZAAy7rUSw3taNIbvSp7gBxz6if0\nn//8B2fOnMHAgQMxceJEDBw4EGfOnMGOHTvcPDzqER/ucWImBQUDfTPlO89/r85gVFLfZsCir4th\nUzIe0cE6PJHa5PWBCQC7QOScFtednDwEtFsXXqJ3GqSkPpBmPQJkXS97qlj/LsS37FR/NZs2bbJ8\nrddrczbNbyjLCPvCepMrJMXMSTBnTnpk7yVl48Vw6Ny0FjY0UIe0KHlTZk1eX/yQU8HJ008/jdBQ\nee+B0NBQPP30024ZFLmIP6w5ASBlDJZtCz9K7RJC4NVvynC5sV22/3fjkxEXpI21G3aL4uu0d/FQ\nlhCWRo41/V+ng+7nv5f3fDAaYXxjMYTy3yfJPPjgg5av4+N96E68DxLKMsK+0OPETNE3K7i2soMn\nkjP2KPqb3Oim9SZmytSuM0zt0gSn0rqKi4vRt29f2b7U1FRcvnzZLYMiF/GDmRMAQOZgYOfn1m0/\nCk4+OVOHrYUNsn33D4nBzWmRyNPI2mtlcHJeg3e27IMT62yJFJsA3c9/D+PLz1ifUFkG41u/g27x\nX3yvgp6LpKSkYMWKFRg2bBja29vt+pyYTZ48WYXRkYyyjLAvdIc3S+SaE1doMxjx8fd1OF1t/fuu\nk4BxblpvYjYwNgRfXbAGRGeqtXd98UdOBSeZmZnYtWsXJk6caNm3Z88epKez67E3U96ZlXx45kTW\n66TAP4KTszWteO2AvJz3kNgQ/Hx0gkoj6h5lxa7zdXoIITTzoV3UVQPnvpPvvDZHtill3wDp7kcg\nPl5p3Zm3C+LTNZBmzHP/IDVo5cqV+K//+i+8+eabaGtrk/U5MZMkCefOnVNhdCRj1x3ed641UkKK\n7PoSzBnPLmkzGLHhTB3e+7Za1nMEAIbHh6JXiHsLJ3DmRJucCk5efPFF3HXXXfjRj36EAQMG4OzZ\ns/jb3/7Gal3ezk/SuqBI68KFsxCGdkgB3ledylWa241YuKsErQbrZTMsUMKyiSkICdDWYr/EsABE\nBOksiyQb9UaUNbUjOSLoKq/0EscV60cyhzi8ESA98AzEiYNAvnXhvFj9F4hh2ZAGDnP3KDVn/Pjx\n2LZtGwBY1jmSl1LO0vvUzIkyrYszJ87QGwQ2nq3D/xyvQokiKDG7JSPS7eMYoCgnfFaDM/P+yKlP\nMXPmzMGGDRtw6dIl/POf/8SlS5ewYcMG3HPPPe4eH/VErbxaly/dzbIl9YoDYm1mC/RtwKVC9Qbk\nAf+dV273R/Y31ychPVpbVa4A093vzGh5IKKlZozK/ibm9SZKUmAQdM8vBcJtLsjt7TD+eRFEU4PD\n15CJOTApKirCvn37cOHCBZVHRLaEYuZE8qXgpFe8qSLkFYHNDabqfOSQ3ijw8fe1mLnxPP6wv8xh\nYBISIOHREbGYM8T9FUTTooIQZFMYpqLZgOoW7ZdzN+74HIaXnobxg+UQeu1cL53l9K3liRMnytK6\nSAP8ZeYEMM2eVFtL6YqC05D6DVBxQO6z5Xw9/u/7Otm+O/pH4Y7+0SqNqOcyY4LxbaV1uv1crR7j\n+qg4oC6wW2+iqM4leyy5D3Q//i8YX3vBurPkAsQ7fwSe+4NmUtk8raSkBPfddx/27duH+Ph4VFZW\nYty4cfjwww/Rp49GflF8mV0pYd9ZEC8FBABxiUB5sXVnRYl9lUg/pzcKfHa2Dv84XmVXoMUsWCfh\nnsExeGR4LBLDPZPZEKSTkBEThO9t1pqcrW1FTqh717q4kzh7CuLN3wJCmPprVZUBP33Fp64f2sr/\nIKcJfRtgezdWFwBEavfD69UoK3b56qL4S/V6vPpNmWxfv6gg/Hpskkojcg2tVuwSZZeBYpu7+IGB\nwLBRnb5GGj8V0i3yWWex6wuIrz51xxB9wtNPP42srCxUV1ejuLgY1dXVyM7OZsVIb6EMTnyolDAA\nu0XxKC9RZxxeqF0AG8/U4u6NhXjFQeVIwBSU3D8kBp/OysCvxiR6LDAxG6RI7dL6onjx9b8Bm+Ig\n4j+fQWxep+KIXM93k/L9XZ0ipSsqBpLOh2NRPygnrDcILPq6GA02DayCdKZ1JlpvKmUXnGgkrUs5\na4LB10IKDbvq66QFv4A4eQQosq6jEO8ugRhyLSTekbWze/duFBcXIyjIlP4XERGB1157DampqSqP\njITR6KAypG8FJ1JibwgctmyLimL4zj3q7jEKgc/O1WPF2UiU68scPidIJ+HuQdF4dEQckjwckNga\n4GOL4sXhvfb73vtviIzBkIZ3fnNMK7T9iYY6ZpfS5YPd4W1Imb4/c/L/jlTKUp8A4LnRCbgmLrSD\nV2iHVoMTdFJCuDNSSCh0v1oKBNv87FpbYPzzQog2bV843SE2NhYnT56U7cvPz0evXr79d00TGmoB\no00Of3gkpGD3dPxWTQJnTmwZhcCvvy7BS3tLUa63r7YVqAPmDI7BprvSsWhskqqBCWBfsetsjUau\nLw6IilKg0EGjaUM7jK/9yvS4D3AqOFmxYoXD/X/9619dOhhyIX9abwIAqekw2lbnqq6AUNbe17A9\nlxqx6qT8ZzqpbwTuHxKj0ohcKzVSvmixqsWA2lbvXrQohIA4fkC2Txo5FuvzazBvcxGW5pZBb+y4\nEaaUNgDSEy/Id57/HmLlG+4Yrqa98MILmDJlChYtWoS3334bixYtwtSpU/HCCy9c/cXkXnY9Tnxr\n1gSAfVpXyUV1xuEl/nG8ClsK7Yt4BOqAewbHYNNdGfjN9UlI8ZKKiwOVaV01bQ57JmmBOLyn4wdr\nq0wBig8skHcqOPnNb37jcP+LL77o0sGQ6wh/acB4hRQQiJZExcJYH5k9KW9qx2/3yO+GJIcH4nfj\nk31mAVygTkK/KI1V7LpwTlaEAaFh+DZ2AJbkluNkZSvW5dfig5Od90SQptwF6QfTrTvikyCNn+Km\nAWvXE088gXXr1qGiogKffvopKioqsGbNGjz55JNqD418eDG8mTLVUij7GvmRry824p2j8p95oATM\nHhSNjTMzsPj6JPT2kqDELCUiEOGB1mtlw5Vy9VokDilSupLlDdJx+jjEu8s8NyA36XSube9e00kw\nGo3Yt2+fLNI8d+4cIiPdX6OauslPGjDaak5OQ3hJkWVbnD8N6bpxKo6o5wxGgRf3lKDaZhZBJwF/\nnJDi9uZVnpYZEywrj1xQ24brkq6+fkMtyhLCGD4aWy/LU7I2n6vHoyM6/rAmSRLw9GKI0yeAtP7Q\n/fR3fvFvtTsmT57MbvBeSFlG2BeDE/S/Rr596TxEcyOksAh1xqOSwro2/GZ3iawpZWSAER/cnomM\nGO8tY6+TJAzoFYLjFS2Wfd/XtGmnl9YVol0PHJVfd3S/WALjur8BB3dbn7f1YxgHDoNu+mxPD9Fl\nOg1OZs82fWPNzc24++67LfslSUJKSgpef/11946Ous/PZk4AoFl5B8EHOsWvPFGN3BJ5Tf2nR8Zj\nVLL3fmjvLq1V7LIrITxyLPYXN8n2na1tw4X6NqRFdXzhliKioFvyHhCb4DMzYeRHFGldkg+mdUnh\nkUCfdODylf5ZQpiuL8Oy1R2YBzXpjfjFDnlBFp0EPJna5NWBidnAXsGy4ORsTRsmpGosuMw/Jq/C\nGhMHDBwG3XN/gPGXDwIl1sqR4u9LITIGQRoyUoWB9lynaV3FxcUoLi7G7NmzLV8XFxfj8uXLOHTo\nEJswejN/W3MCoDkpTbat9YpdR8ub8fZR+V3JMclheHSEb/4stbQoXhjagW8PyvbVXTMapx2UqNx5\nofGqx5PiEhmYkDbZpXX5UANGG9KAobJtcfaUSiPxPCEEXtpbatf49+ejEjA0wrvXBpopF8VrsWKX\nMqVLyr4Bkk4HKTIaul+/DthWimxvh3HZLyFsU481xKk1J+vXr4fRaMSBAwewYcMGAEBLSwtaW7X3\nw/UX/rbmBHAwc3KxQNMLw948VAGDzfx5r5AA/H5CCgJ0vvkhtr+GghOcOSm/gxXdC7lBjsva7rx4\n9eCESLOUaV0+OHMCAFAEJzh70vHzfNCqk9XYViRfAD89IxIPDtVOtbwBikXxWqzYJQ4pFsNn32j5\nUkofCOnHv5M/XlUO42svQOj17h+cizkVnHz33XcYOnQo5syZgwcffBAAsHXrVixYsMCtg6Me8MM1\nJ4awCHnJR0M7cKFAvQH1wNHyZhwua5Hte+XGZNVLMrpTevT/Z++8w6Oo1j/+PbubTe+kEwiEEAgt\nwdCVJoiKiiJiRfypYLte9dpQr/Xeq1yvYsGKDcSKFRRBQJrSQkhCT4D0hPS+Kdvm/P5Ykp0zs7vZ\nTTbZNp/n8Xncs1MOk92dec/7fr+vF9M74LxKhw4dZ3Z7RyIq6RozERmCv1cn2dXtTu885uy89tpr\nJsel0mLHQwWZE+KOmhN4bubk4PlWrM5mA9CkUCWen+xahizCzElBkwZ6C26KzgatrwEK84wDhICk\nsZpa2cWXgVx3B7vj6WzQz17v+wnaGauCk3vuuQePP/44ioqKuppgzZo1C3v37u3TyUn0AmETRg8I\nTgCYaMaYZ2bDnqHjKHaXqrD/fCu4PrQi/PwkG1xOifHDJa5WH2sjPgoZYgOMwRcFUNzsnCs+ouaL\nYyeKtEGd6CnwV7mUPekNL730ksnxf//73/08EwkRIith9yzrMimK7zD9nXcXylu0WPFnJfjP8EFK\nGV6fEQNfF2v8G+6rQCjPREatpyhTOef9xRQ0+wA7MGyUyUVnctsDwDi23xb97VtwOzf15fTsjlXL\nsMeOHcNdd90FAF2RckBAAFpbpRuu0+KBZV2AoRkjzeQFzXbWnbywvwqbC1sAALeMCMHjEyLsenzA\n4IiyS6BTuH2UZ/z9EoKUKFcZLR4LmjRIDnOuhm5U3Q6czmHGapIuQuk+8ze63aWtmD80qK+n5nbs\n3LkTAKDX67Fr1y6RY2RgYKCjpibRiSe4dcFgXIGYeKDiguiY44CiPGBEqmMn1ke06zg8uqcCTRpj\n9prA4BRpyeDDmRkWosThKmNAea5Rg8FBLvJvEZR0kfHTTG5G5ArIHl0J7tFbgJqKrnH6/n9ABw0D\nGZbSp9O0F1YFJ4MGDcLRo0eRmmr8Eh45cgSJiYl9NjGJnkP1ekPXXj6B7tGsrzvIkOGMzSG1o2NX\nXbuuKzABgK9yG3FNYpDdH57Xn2pg/g0jwrwxKdr93LlMMSRYiX3njY5XTqk7OX0U0PECkchY7NeH\nAqjuGgrzkaO+w1jKtf98KzR6Dkq5a602OprORbGOjg7ceeedXeOdjpGrV6921NQkYBBKixbC3FVz\nAkNpF63gOSKdOw3ihsEJpRT/PliNvAZWV/xAajimuXAGP1EUnKhx6SDnb4lB9TrQoweZMXKR6eAE\nAEhQCGRPrQK34g5Ac+FvqNWA+++jkL32pUuUXlp1p3zhhRcwf/58vPLKK9BqtXjjjTdwww034IUX\nXujj6Un0CFWTweqwE/9AEIVr+Xn3GEFZF4rO2K0T7NEasabg3Rz7OmHUtevwS34LM3Z7SqhL1fb2\nBqFjV5ET2gkL+5uQsRORUclaCC9ODsYAX2MJQZuOIrPKvUtA+oLCwkIUFhbi1ltv7fr/wsJCFBQU\nYP/+/bjmmmscPUXPpqMN0PB+F72UgJ/zP+z1mETBqrOb6k6+zm3Eb4XsfWj2IH+Xd4oUdop3GVH8\n2ROAqtn4OjBE/FkUQIaOALn/WXawphLca08Z3CadHKuCk+uuuw4//PADzp49i4kTJ+Lo0aP44osv\ncNVVV/X1/CR6gtBG2ENKugAA0fGsnV5LE1BXbX57G8ipET9c/lnehpxq+z10fpPbCA2vwDfGX4G5\ng934Zi/AFRy7TOlNDgv0JpOi/TBdsMK42wpLYQnTfP75513/z3Ec85+EAxHqTYLD3HohxRNE8ZlV\nbVh1hF10GxKsxEtTo13+bzssVGgn7Hz3F1PQI4KSrtTJIPLumzDLZs4HuepmdvB4Bujnb9txdn2D\n1TUGkydPxqeffoo//vgDa9euxdSpU3t0Qo7jMH78+K4Vr4aGBlx22WVITk7GvHnz0NTU1M0RJLpF\nmGb3FDE8ACKTAYOHsYN20p3kmHFjWp1dZ5fsTJuWw7dn2M//bSNDoXBT62BTCDMnxc1a6JzIUYWq\nmkWrpUWDxqGOV8LlpyAYNcAHM+PZoHJPWavdsnieRlZWFqZMmQJ/f394eXnBy8sLCoWiy6BFwkE0\neYiNcCdCUXxZgUGD5iZUtmrxxJ5KxsI+wEuGVTNi4O9iAnhTJAruLyXNGmj0zr/AQbPZ/iYYPw15\n9Wq8m12LvWUq0ztdgNzxCDBqPHu8jevB/bnV3tO0K1Z92rRaLf71r38hJSUFkZGRAIAdO3bgww8/\ntPmEb731FlJSjOmolStXYs6cOcjLy8Ps2bPxyiuv2HxMCQEe2ICRDxE6dtlBd9Kh43C63nRwklXd\njgOCzuA94adzTWjhiQ+DlTJcN8yzRNTB3nKE+RhXhLQcRbkzOaqcyGRLJgcNw8F2Vg90UZQvvGQE\nE6J94SM3BpbVbTqcrpd6Q/WEpUuXYtasWcjMzERBQQEKCgq6yrskHIiJzIk7QwKCoA7hmaBwnKFT\nvBug1nN4bE8FGgS25/+aFuUSHeCtIUApR7S/UWqtp0BhkxPdX0xAG+sNfbV41CSn4+5tZfj4RAMe\n2lWBnSXmAxSi8ILs8VeB8EjjoEwudnR1MqwKTh577DHs378f7733HjQaQxosOTkZ77zzjk0nKysr\nw2+//Ya77767a2zjxo1YunQpAMMNqLPJo0TPETZgJJ5U1gWY1J30llN1alhqufFOdl2vrIW1HMUX\np9kfi8XJIS5n12gPnLlTPD0q0JuMm4RDFezK6cRoPwAGa+QpsX7Me1JDxp5RXFyM//znPxg5ciQG\nDx7M/CfhOEQ9TtzVRphHW8wg5jUtyHXQTOwHpRSvHKrByTp28eSesWGiDLCrI+x3ku/kneJFWZPE\nkfilTgmV1vhAsv6UYEFaAAkJh+zJ1wGFFxAUAtmL70M2/6a+mK7dsOrJ57vvvsOGDRswc+ZMyGSG\nXeLj41FaWtrNniyPPPII/ve//zF1i1VVVYiKigIAREdHo7raPvoAj8bTMydDhL1Oeh+cHBXoTZJD\nWWHd6Xo1/rCwetEd24taUNlqFKl5ywluSvYMhzUhTh2cCPQm3JgJOCLQHE2KMQYkotIuSXfSI667\n7jps27bN0dOQEOIp3eF5tMUIAmI30J18f7YJG/ObmbHpcf5YPtb9/p5CUbzT604EwQkZPw37z7P3\nkZyaDlS3WRa5k+GjIXvsv5C9/hXImAl2n6a9scpKWKEQb1ZXV4fQUOsfejdv3oyoqCikpqZi9+7d\nZrdzdcGVU+ChPU66GJzEvq4oAVW3g3j33I43R+DUtTApCIcr27GDF5C8n1OHWfEBNmtEKKVYJ1j5\nuDoxCGG+7tsN3hJDgpwzOKF11UB5kXFAJsfp6FFozTP+7cJ85MzK3MVxfiBAlzV0XoMa51VaxAZI\nWglb6OjowHXXXYeLL74Y0dHRzHt8sbxEPyO617jfw6yQ9mg2OKH5p8xs6RqcqO3Aq4drmLFBgV74\n98VRkLnh85gwc3LOiTMnVK8XNV9sHzMZx46JS8x3FKtwy8gQi8cjk2fZdX59iVVPPwsXLsRdd92F\nt956C4BBxP7www9j8eLFVp9o37592LRpE3777Te0t7ejpaUFS5YsQXR0dFf2pLKyskvTYo7MzEyr\nz+numLsWCUUF4IcjhXWNaPCQ69Z5TVJCI+DdcOEHl+NweuuvaIsb0qNjUgpkVQSCn2hU1hRgugL4\nAwGgMPyAFzZr8e7OY5gWYlsN60mVAmcajM5OBBSp+jJkZpb0aL58XPH7olUpABivx4nzDcjMLLPL\nsXtzPcKO7Qf/sUQVm4AfTlUA8OkaS1S248iRI8x+ib7+ONdu/Kn9Yv9pzA5zfMCVlJTU/UZOQkpK\nCqNVlHAOqKgBoyeUdQkyJyUFoOoOEG8f0zs4MZRSvJZZw5Qs+yoIVs2MQaCyezcoV8SlMif5p4AW\nXrm3fyAOBAyFnopbGOwoaek2OHElrApOVq5ciUceeQQJCQnQarWIjo7GnXfeiZdeesnqE7388st4\n+eWXAQB79uzB66+/jvXr1+OJJ57A2rVr8eSTT2LdunVYsGCBxeOkp6dbfU53JjMz0+y10G/6iHk9\nNHU8SJr7Xzf+NdEnjwEO7ux6b4SvHLIefnYKmzRQ5RZ3vQ7wkuHqqWmQywiOkComHb61OQj3zRps\nU7O9j7eXATCWBs0eFIj5U4eb38FKLH1GnJmBrVq8WVrU9bpGr8RFF43odVa1t9eD27eRaY4ZOGUW\nymWh4P/tLk8ZiPQkthzvKt8GvJllvJkUysKRnh7X43nYC1dyRnz++ed7tb9arcb06dOh0Wig0+mw\naNGiXh9TAqKyLhLi/ll6va8/EBkLVJ83DHB6oPgsMHyMYyfWAw5VtIn6d704NQqJIfZtLOxMJAR7\nQUaAThPIilYdVBo9ApwwGKNZgpKucZPxV6XpYCqn2lDaFennHhUXVj1B+fj44P3330dbWxuKi4vR\n2tqK999/H97evf8Ar1ixAtu3b0dycjL++OMPrFixotfH9HiEmpNA94mmrUWoO+mNKF6oNxkb4QP5\nhdKt5WPD4MUr46ps1eGHs2ztriVO13XgkKBHxtIU97/BWyLKTwE/hfGaqrQcatr1FvboeyilIr2J\nZtQE0Y19UjQrgAeAGQPZfieZVW1o0Tj23+OKbN++HXfddReuvvpqAIZgc+fOnd3sZcDb2xu7du1C\ndnY2cnJysGXLFmRkZHS/o4RlRGVd7p85AQAI+52cs6/u5LxKi5cPVeN/h2vQpO6b3wpKKT48xhoa\nXBLnh7mDA/vkfM6Ct1yGQYFsWW2Bk5QOC6FZbH8TjJ8q0pt0bQtYdO1yNawKTp5++mls27YNHR0d\niI+PN6lBsYUZM2Zg06ZNAICwsDDs2LEDeXl52LZtG0JCPO9B2u54uuYE9rUTFvY3GRthTN/HBnhh\n0XB2pfzj4/Vo01rnnf65QGsyPtIXYyJcrzzAnhBCRNaVDtedlBexzTyVPsgJTYKW14MlLkCBuECx\nliQhWImEIOO4jgP2n++99bQnsXr1atx3331ISkrC3r17AQC+vr745z//afUx/PwMgaNarYZOp5P0\njfZAJIj3jOBE2IwRBfYLTiileHxvBb4704Svchvxtz/Koe+DXk8Zle0iLeU9Yz3j7yfMDDljaRdt\nbjB0hudRmDjB4kLd9mIPC050Oh2effZZDBgwAJMmTcITTzyBzZs3u1RZgKdAKWVrFAGPc+sCACQk\ns6+Lz/a4AZ4wc5IawQrr7xodyvSzqO/Q4+vc7j3Ey1u0oh+TO0Z54N/KBM7m2CXqCp+ShkN17E3C\nVNakkxkDWdeu3aXucxPpD958803s2LEDK1as6HKMHDFiBPLy8qw+BsdxSEtLQ3R0NObOnYsJE5zf\nscaZoVot0NpiHJDJgEDPcBgkiaz+yZ6d4ouatTjFs/Q9UafGLwXWZ+OtwZA1YQPLabF+GDXAMxbG\nkkSieCcMTnIOsj21EoZjbyv77DFc0PE+u7odNd24drkKVqVAXn31VQCASqXCvn37sG3bNtxyyy1o\na2uDVuvcDWw8jlYVoON9OH18XVKo12siYwC/AKDtwkNgm8pQIxxlW61/Q4ceRc3Gz7icAGMEP+Dh\nvgrcOjIEn5wwZkHWnmzAouHBCPY2X8f6xekGphPv0GAlpsWZf8D1JOzp2EUpxe7SVuyt9UZUiwbx\ngbY3FBMGJ2TsRBwSNN6cGGMhOIn3ZxzZ/ipvg5ajTEmghHlaWloQHx8PwOjoqNVqoVRa/7eUyWTI\nzs5Gc3Mzrr32Wpw6dcqsyN4VjST6CnPXwqu5HqN5r7W+/jiRnd0/k3IwOS1qjOW9psXncOTgAVBF\n7134djcoAbAPoW9mVGJA3Vn42EkWkdsqR3Y1u2AyXVmNzMyKHh3P5b4vzazpSnZJLTJJsfntbcQe\n12Pw9k3ge99VxiZia14V+I/tE7yb0OGjREmH4YNBAaz96xRmOYHhSic9NV6xKjhRq9U4ePAg9uzZ\ng927dyM3NxczZszAjBkzenRSiT6kWdCx1xOzJrjwAJOQBJzi3SwLz9gcnAizJsNDveFnojHi0lGh\n2HDG2OFdpeWw7mQD/j5+gMnjNqr1+Pkcuxq2dFSoW1o39oShdsycfHemCa9k1ADwwV+/l+Hb+YNs\nsmmmej1w/DAz1joyHbmZrAXlhGjzVtVjB/ggxFuOxgv14yoth+yqdosBjYSR6dOnY+XKlXjmmWe6\nxt5++23MmmW7NWZQUBBmzZqFrVu3mg1OXNFIoi+wZCJBz50Cv3jVKzzKI65bZmYm0qbPhH59DFBj\neJgnnB7jw4NAkkb1+vjf/1kBgM2sNullOKpMwANppu8ntvLBNtaEZWqsHxZf0rOHSFc0XhnQpMEH\n5cZgpJrzRnr6SAt7WI89rgflOHCrn2DGQi+7FgUn2PvWzZNHIqy4BauzjVmwMwjD4+kDe3V+e9LT\nCiuryrqCg4Nx9913IyAgAKtWrUJ5eTk2bdqERx99tEcnlehDhGJ4D9SbdCLSnfRAFC8UPI816LnP\nCQAAIABJREFUowcJVMpFJVlf5zaitt10inVDXiM6eGmTCF85rkhwbyGiLYjKupp7Fpx06Dh8cNQY\nsNe2W1dyx548ly1fCQhChm8849yVFKpEmI/5gEcuI5g+kA1Edkvd4q1m9erV+Omnn5CQkICWlhYk\nJydjw4YNWLVqlVX719bWdt0k29vbsX37dowYMaIvp+z+CLrDe0IDRgahKN4O/U4opThS1W7yvfWn\nG3Fe1ftKlczKNtE53LHZoiUGBnpBKWNLsevN3KsdQkEuqx32C8Ch4OHQ8au8grwQF+iFuYPZDFhW\ndTvqnOnf0kOsCk4ef/xxxMbG4rXXXsPzzz+PN954A0eOHOlxDb9EHyIUw3to5gQAYIdO8d3pTfjc\nnByCcF7evUNP8fHxetF2HToO3+Syqwm3jgyFl1zKmnQSF+gFBe/XqbZd3yOHq18LWtAgcLvZcKbJ\nasMCAKBHD7EDo9ORUcVmTSZa0Jt0ItSd7ClVSb+hVhITE4PDhw9jw4YN+Oqrr7Bu3TpkZGSIGjKa\no6KiArNmzUJqaiomTZqEefPm4corr+zjWbs3tJH9bSMeIobvRCSKt4PupKRFi1ozgme1nuLtbHF/\nC1sROnRNifHDOAv3NXdEISOiBbB8R5uu8BC5dI2diL8q2XvOtFhDWVp8oBIjwowCf44Cf7iBa5dV\nwcm//vUv7NmzB0VFRXjsscdQXV2NSy+91KYO8RL9AxVkTogHBydEKIq30bFLo+dwspb9QUiNNK/f\n8fWSYZlgBeqHs00ob2FXu34paGYemP29ZFiYFGTT3NwdLxkRaUNstXvUc1TkhgYAzRoOP5+zPtUs\n0puMm4RDlazexJIYvpMpMX7Mat35Vp1TCjGdkZycHJSVlWHixIm44YYbMHnyZJSXl+Po0aNW7T9m\nzBhkZWUhJycHx44dY8rDJHqIMHPiAd3h+QiDE5qf2+tjZgps5f0FJcS/F6lEC2a2cKSqHZkenjXp\nZJhATH62wXl+i4XBCUmbKnJ4nMrTp84ZxC58eUxwolKpsGXLFjz33HN47LHH8OabbyIxMRF33nln\nX89PwlYkG2EjgxINDjKdVJWBtln/pT1dr4aGZ+EY7adAtL9lwePCYcGI9TeW9+g4MK4oeo5i/Sm2\nrGhRUrDbduPtDUOC2WtdZGNwsqtUhdIW02UQ6083MjbA5qAaNXA6hxmrSxqPYp5JgoIA46O6X3n0\n9ZJhUgy73e5SqbTLGm677TaR+YpGo8GSJUscNCMJsY2whz3kCjMnJWdBtb17wM2sYh9Ab08JYVbF\nAeD1zFpwPcy4rhE4dE2K9kVqpGdlTToZJnDsym9Um9myf6GqZuDMcWasJGkiKnkuXD5ygot495w5\ngtKuzKp25ypT6wFWBScRERF48cUXwXEcnnvuOVRVVeHIkSNW1/tK9CPNko1wJ8TbB4gdzA4Wn7N6\n/6OC/ibjLGRNOvGSE9wzji1v2FzY0vXDJ3xgVsiAW0ZKvX1MMVTk2GV9vTWlFOtOirMmnVS26rCj\nuMXs+13kHQM0vJtWeBQOIILZZPQAH9EKpzlmxgtKu8pcf4WrPygpKcHQoUOZscTERBQVFTlmQhJS\n5iQ4DBjAKyvU6Wy6vwgxpTeZGO2HR9NZEfzx2g78XmTFb5eA7Op2ZAgyM8J7lSch6nXiJGVdNOcg\nwPHKjgcNw94O9r6RHu0Lb7nxnjM4SMnYCnMU2OniC18W76hff/01AIOY8ODBg3j11Vcxf/58BAd7\nhpe5SyIUxAd59oMvSWAdSGxpxihMn1tblzt/SCBTz8pR4L2jdSYfmK8cEohIv941NXVXetPrJKu6\nAyd4vQLknA7jFaw72tqTDd1qPkxZCGcIHyBscNy6JI7tFn+yTo1qN/Gl70sGDhyIrKwsZiwrKwux\nsbEOmpGEp2tOAJgQxfdcd1LSomUa7PnICUaF+yA9yg+z49nfjbey6tCus143BwAfHmWzJhOjfZHm\noVkTwFTmROMcGsDs/cxLMn4q9pWzgcbUWPbzAABzB7OGOtutWXxzYiwGJ/fccw8AwN9ffCEknBNJ\ncyJA4NgFK0XxlFJR99xUKzu3y2UED6SyN+qdJa1Yf7qReWAGgNtTPPzvY4HeOHZ9zgsCBzeXY8uO\nh7Dm27uxccvf8FTWGswqP4TzVQ2iXiVC6DGBGH7sBGQI+5tYoTfpJMJPgdHh7IrdXsm1q1seeeQR\nLFiwAKtXr8Zvv/2G1atX47rrrsM//vEPR0/Nc2kSlHV5WOYEsK8oXpg1GRvh02WS8tD4AYxBSFWb\nDutN6OnMkVPdjkOVQq2JBwaTPKL9FAjgZbxbtRxTOuUIKKUivYl67BRkC6o4psWK7zlC3cmRqnbU\nd7juwpfFJVuniCIlbEPSnDCQhOGM5au1jl2lLVrUdxhXsXwVBEmh3hb2YJkd74+UcG+m0+8bR1in\nlUvi/ESpZQkjCYKyrnKVFmo9x6SzTZHfqMZe3krTP46tQ1hLDQAgrq0a1xfuwPWFO6AHQXHGcHAz\nZ4CkTgGSRoHwmqjR1hbg7Enm2GVDxqOmzBic+MgJxtrYVXlmfAATpO4pU2HRcCkbbYlly5YhJCQE\nn3zyCUpLSxEfH4/XX38dixYtcvTUPBfhvcbTNCcAyNAR7P2lF3bCwuAkPcr4ADooSIlbRoTgc55e\n8bMTDbh2WLBVmfc1Aoeu9ChfRrPgiRBCkBiiZNoFnGvQIKYbXWmfUngGaOA9J/j44nDIcGg540JA\nfKAXBgWJm88mBCuRFKLE2QsmK3pq0DQuTHLNe4vFT7Ver8euXbssBimzZ8+2+6QkeoGorMuzgxMM\nETh2FZ8F1etB5JYF6MKsyZgBPlDY0M2bEIIHU8Nx3x/nzW6zdJTn3cxtwddLhhh/BSpaDas/HAWK\nm7UY3k2QyDcciFNVYVpVjsnt5KAYWpUH+m0e6LdrAL8AYHQ6SOoUkLTJQGkBW/s7cAj2d/gDMAYn\n46N8bbaAnjHQH+/kGG82GRXtaNNyJpt7ShjuQy+++CKeeeYZ3HDDDY6ejgQMTeLEC2Ee+Hs2TNDE\ns/gcqFYL4mXbA64pvYkweLh7TBg25bd0NXLt0FO8m1OLF6dattM+WtOOA4Js7z0e6tAlZJgwOGlU\n45KBjqsUotkmLIRr2OzHVBNZk07mDA7AWV655fZilXsGJ2q1GnfddZfZ4IQQgoKCgj6ZmEQPaRII\n4j08c4KwCCAwBGi5cF3UHUBlGRA32OJux3qoN+EzKcYP6VG+IutGABgd7o3xVgjsPZ0hwcqu4AQw\n6E4sBSfVbTpsLjRqSxYWbrf+ZG0qIGM3aMZuw2qokj0PGTsRGT2wEBaSGKJEXIAC5SrDv0vDURyo\naMOlgrS8hAG5XI733nsPL7zwgqOnItGJqgngeP04/AJAlJ6XBSYh4UB4JFBXbRjQaYHSfGCobQ0+\ny1RaVPFKirzlBKMHsNczUCnHfePC8EpGTdfYpvwW3JgcgpRw8/cSYdZkfKQv0nvwu+WOCCsX8nth\n7d6k1uOf+ypxujoQd/g14LYelGyLLYSnifQm0+LMB09zBgfifV7T4cOVbWjo0CPUx/XcQC0u1fn7\n+6OgoACFhYUm/5MCE+eCdrQDGt6Kv8IL8PVsvRAhpEe6kxxBjael/iaWzv23NNN1vUtHhRrmJmER\nW0XxX51uRKdO1EuvxbXFu5n3yYIlOD/7RpwLiu/+5BpWH0THTBQFmhNjbA9aCSGYKWjIuLtUcu2y\nxO23344PPvjA0dOQ6KTRw7vD87FDp3hh1mRchA+UJspXFyYFI1Hwm/haZo3ZBeTjNR2i/hj3jvPg\nv5UAoSi+N32n/nOoGn+Vt6FOK8PrR2pxuNKynlEIbW0BTrN9m8qTJuA8b3FOKSNIt1CONzRYyXw+\nDKVdrnlvkeoI3AkTehPpARggNnaKb1brmW6xBIayrp4wLsIX0wVp4vhAL8yKl1bJrWGIyE7Y/M2j\nRaPHD2eNzRVnlx9CsNqYRdH5+IHcch/iHnwSTy9ajcuv/ADPp9+P3+IvRqt/N652MhnOxI1Bi8ZY\n5hXiLeu2xMwcMwTuO3+Vt0JnRd8VTyUjIwMPPfQQEhIScMkll2D69Old/0k4AGGPE08s6bqAPUTx\nwkUPc32TFDIishbOru4w23TvQ0Ffk7RIH4sPt55GYoj4/tKT3+GzDWpsL2b/Bh8crTeztRmOZbDZ\nyIFDsFfLlmRdFOULX4Xlx/a5gp4nO1y0IaMkiHcnJL2JaYTBSWGexc2P1rJZk2Ghyl41Sfx7Wjgy\nKtrQoTd8n+4fFw65DfoVT8YWx64fzzZDpTUGDzcVsSVd9WOnIMbbFwSGzNXzTRpsHjwTmwfPhK+M\nYmu6DgEnM0CPHgROZQO8hmpk8qU40Mx+BtKj/CDrYfCfGumLQKWsK9hpVHM4VtNhVTNHT2TZsmVY\ntmyZo6chcQHq4T1O+JDEFIEo3rbghFKKI5XmxfBCpsT64+I4P/xVblyZfzOrFtMH+jPZlhO1Hdh3\nXqg1CZcWLHmE+SgQ7iNH3QXzGw1HUdqiFd13uuOj4+JAJKu6HZmVbVaX0IlKusaLu8JPi+v+WHMG\nB+ADXilfRkUbmtR6BHu7VmmXxeCkpcW1fZI9DuENQwpOAIgdu9BNr5Oj1eyNIrUHehM+iSHe+GTe\nQPxRosLoAT5S1sQGhDeJ4iYt9BwVBXdaPcWXp43BeWJTCcbUsA8JteNnIObC/1+REIh3smu7+gq0\ncwTfqKOwfOEdwMI7QNXtwKls0NM5hnr6eYuQ8Rf7/epJSVcnXjKCS+L88Vuh8Td2d5lKCk7MsHTp\nUkdPQYKP1OPEiDBzUnQWVKdlnP8scV6lYyxslTKx3kTIIxdF4MD5YlxY70K5SoevchtxB89kRdgN\nPjXCBxOjpd8XIYkhStTxgsNzjWqbgpP8RjV2FJvLXNVbFZyYshDWjJ2CzDz2WcRUfxMhiSHeGBKs\n7Koy0FFD8+drh7mWMF4q63IjaAsrhieeLobvZOBQQMGLw+uqQFuazG5+VODUNc7K/iaWSAn3wYNp\nA6TAxEZCfeQI4a34aDiK863iTvFbilqYBmaLBVkTjE6HekBM10svOcGtI9nvxze5Tei4IFgh3r4g\naVMhu+V+yK69HRqlj8jBzZb+JqaYISj3213aKmWrzUApxUcffYTZs2dj7NixAIC9e/diw4YNDp6Z\nhyJlTrogoQOAUF6plVZjcPqzkswqdnV8bIRPt3bpQ4OVIvvxj483oL7dEOScrOvAn+Vihy4payJm\nWC9F8WuO1cPcr3ZmVbtIT2SSknyjqQIAKH2QOWAkNLwSs1h/BRKCrAt4RaVdZoInZ0YKTtwJoebE\nw7vDd0K8vICBQ9hBM7oTLUdxolbYfFFabXIkQ4LZH2Sh7oSjlGm66KvrwFUlfzLbkMvF/TAWJgXB\nn2ff26DW45eCZtF2AHC0ugNqvfFGEe2vwKDA3vnhT431YxqrlbZoUdQsDrwkgOeeew6ffPIJli9f\njpKSEgCGrvH//e9/HTwzD0WoOfFkQTwAJLKWwraUdnVnIWyOe8eFI1DJNhF870IXeKFD19gIH0yK\nkRy6TCHUndgiis9vFGhNKEWojP0NF2awTCHMmmBMOvZVsxbC0+L8rQ4u5wqcHw9VtqFZrTeztXMi\nBSfuhKQ5MQtJEOpOTAcnZ+rVXdoQABjgK0dsQPdNriT6jqEixy72x39feRtjYHB56V/w1vBWDYPD\nQCaJ+zEFKuVYJPCAX3+qEXoTgkhTFsK9XYUMUMoxQVBb7qrOKn3N2rVr8euvv+Kmm27quu5DhgyR\nHCMdBBWWdXlw5gTonSheKIa3VrAe4i0X9Sv56VwzNuU3Y28Zaz8rZU3MkyTKnKjNbCnm4+PGrEmc\nqgob/3gU27+7Fd9u+weeyP4Yl5YdwJniKmR1kz0R602mifRClvqbCEkMUWIIL8ui44Ddgs+EsyMF\nJ+6E1B3ePFbaCefUiPUm0o+6Y+nOTnjdKd7nnlL8X9kfzPtkzrVmm6LdMjJElL3YZSJAyBAIVu1V\nuy107drjYjeQ/kKv1yMgwLAa2Pl9VKlUXWMS/YywrMuTNScQByfWZk7Oq7RMHyeljGCMDWXEi4eH\nMBlcjgLP769ithkzwAdTpKyJWYYKMiclLdqu8l5LFDZp8HuR8V7x2NHPENdUBgBIbCnD4oJt+O+h\nN7Dj17sR8dRN4NasBN2/A1SwiEzbW4HT2cxYxfCJKG0xLsJ5yYhNZcSEEFw6OJAZ217sWhpyKThx\nI4QfeiJlTrqw1k5Y2N/EHnoTid4hDE4KeMHJ8ZoOpixiVEM+YqvzjRsTAnLZ9WaPHemnwJVD2B/x\ndScbGO1Hi0aPk3Xs52KCnZqYCXUnx2o6UNeuM7O153LllVfiH//4B9Rqw6ompRTPPvssrr76agfP\nzEORyrpYhglF8WdA9d1/j4VZk9EDuteb8PGSEzxy0QCL2yyXsiYW8feSIdbfWB3BUaDIgitkJ/ys\nyeDmclxSmWV229j6EtDfvgX36uPgbp8N/UOLwX30X9CDO0H3/wHoeJ+VmHj8qWe/T2mRPvDzsu1x\nXag7OVjRhhaN65R2ScGJOyGVdZlHmDkpyQfVseVBlFIcFWZOIiW9iaMxlTnpDB6YrAmAeyp2sjtf\ndDFIVKzF498u6OR7ok6NLF6QeqSqHfxKr6HBSkT42afUL9rfCyPCjGUFFMCf5VL2RMiqVatQUVGB\n4OBgNDU1ISAgAMXFxZLmxAFQSk1k6T07OCFhkawoXqMGSgu73e+IQAyf3oOM7IyB/mYzuaPDvTHN\nhnIgT0Uoiu9Od1LUpMHWImMm4uZzv9l2wuKzoJu/AbfyUdDVzzNvGUq6BF3hrXDpEpIUosRgYWlX\nqevcW6TgxJ1oYt26pLIuIyQ4jL156LRAeTGzTUWrjnF88pETJIf1rMmehP2I8lPAV2Fc+VNpOdS2\n61HSrMFOXoOpQI0Kk/JZIbxsnlgILyQxxBuXCPzj1500lq0cqmAfIOxtxynMnuxxoRtIfxEUFISf\nfvoJJSUlOHjwIPLz8/HTTz8hMDCw+50l7EtHG6DhZRK9lICfVF6HoSOYl9aUdonE8D1YDCOE4NH0\nCJhqnbV8nNTXxBqEovjuHLs+Pl7ftWAVrG7B1SV7mPfJ9Xeiau7NOBmaCD1su/66cVOQKSgjtqa/\niRBCiEgY70quXVJw4k5ImRPLdFPalSPobzJqgA+8pGaJDkdGCBIEneKLmjVYf7qRsXD8v5p9kGt5\nYsaIaGD8NKvOsXQUu/L7Z3lblzBSqDext+vNTIHu5GBFG9qtqHn2BNra2vD000/jmmuuwQsvvIDg\n4GBMmDAB0dHRjp6a52KiO7z0AGxKFH/K4vYVrVqUq4zlPF426k34DA/1xrWJQcxYSrg3LpayJlaR\nFCp07DIvii9u1mALL2tyXeEOeOuNwYwmMBTk5nsR+8ATePvmN3Hp1Z/i4alP4oukq1AakQhY+q54\nKZEdOYox5YnyU4hMYaxljkB3csCFSruk4MRNoFoN0MaLimVyICDI/A4eiNCxS9iMUdjHIlXSmzgN\nwtKurKp2/JLPs/2lFAsL2N4m5LLrQeTWdcUdH+mD0eFsluzzUw2oadMxGhcZsd7q01qSQ70R7aeA\nj5xgxkB/PDEhwq7Hd2UeeOAB/PLLLxgxYgS+//57PPbYY46ekoRIDO/ZJV2d2CqKF2ZNRg/whq+i\n549kD6SGI/6CON5bTvDEhAgpaLSSRGFZV4P5zAk/a6LgdLil8Hfm/ZoJs7oacN4zNgwqpT/+irkI\nb469HddNfwW5b2yF7KlVIFffKio3JwuW4M8admFqWmzPnSGHhyq7PhOAoVWC0MnNWZE8Ut2FZkFJ\nV2AwiEyKPRmEdsKCzIlQbzJO6m/iNAiDk7UnG5i+I3Nb8hBQXWLcQK4AmXOt1ccnhGDpqFA8vrey\na+y3whbReUeF+yBQaV3AY8u5354di4GBXr16OHFHtm7diqysLMTExODBBx/E9OnTsXr1akdPy7Np\nlJy6TCLodYJCgyieyE0/ZglLdy6K6l2WI8xXgS+vjEd2dTuSQr0R49+7PkyeREKQF+QE6LylVLbp\n0KLRi37rS5o12FJozJrMKTuAsDbe98HbB3Vp0zHowsv0KF+kRfogm6dhfD9fi3cunQUyaRYAgDY3\nAudOAn4BICPGYf/GIuac0+Js15t0QgjB3MEB+PSEsapme7EK84c6/8K1dCd0F4QlXZLeRITQsYtv\nJ6zS6EUiuLFS5sRpEAYJ/LQ3ANxXyQrhyaRZhs7NNjArPoBZZdJxwHs57IOYvfUmnSSF9m7V1F1p\nbW1FTEwMACA+Ph5NTU0OnpEEbZJ6nJgkPJI1BtB0AGVFZjfPqu5Z80VLBCrlmD4wQApMbEQpl2FQ\nUPe6k09O1HcFMKAU/1fACuHJ7Gug9zUGE4QQ3DOWDd73nW9jGj2ToBCQ8dNARozDeZUWhbxGvArS\n+3vOHIHu5MD5NqhcoLSr3+6GarUakyZNQlpaGsaMGYMXX3wRANDQ0IDLLrsMycnJmDdvnnTz6SnC\n4CRQ6g4vInawQbzZSWMd6IX66eO1HSJHpmBv+66QS/QcYXDCZ5C+GfGnBB3hr7jB5nPIZQRLUtjv\njVbQkNEWr3mJ3qPT6bBr1y7s3LkTO3fuFL3euXNn9weRsC+SjbBJCCGAsLSrwHRpV1WrluljoZAB\n4wZIi2GOZFg3ovjSFg02FxizJql1uUisy2e2IVfdIjruxGhD9oTPh2a6xv8lcGocF+mLgF5m6keE\neWNggDFY1XDUJRwh+y048fb2xq5du5CdnY2cnBxs2bIFGRkZWLlyJebMmYO8vDzMnj0br7zySn9N\nya2gUgPGbiFyBTAokR28oDuR9CbOTXygFxRmym6fbN4HouetBMUlAKPTe3Seq4cGIdRMUOotJxgX\nKX0u+pPIyEjceeeduOuuu3DXXXchPDyceX333Xc7eoqeh7CsS8qcdGFtp3iR3iTcB7429rGQsC/C\n4EQoiv/keAP4CftlhQL74PTpIHGDRcclhGC5IHvyV3kbTtZ2iLbdL+gKbw8baEII5gh6nmx3Adeu\nfv02+PkZLrRarYZOpwMhBBs3bsTSpUsBAEuXLsXPP//cn1NyH6QGjFYhFMV36k6ETl3jpP4mToWX\njDAlV534EA7px7YyY2Teoh4LCH0UMtw0Itjke6kRtjVIk+g9RUVFKCwsNPtfQUGBo6focQjLuhAs\naU46sVYUL2y+aG+TDQnbsdTrpLxFi80FRgOWOFUVJpZmMNvLrrnV7LEnRfuKGjqvOcZ+jzR6DhmV\nbHAytQf9TUwhbMi4r7wNrVrndoTs1zstx3FIS0tDdHQ05s6diwkTJqCqqgpRUVEAgOjoaFRXV/fn\nlNwHKXNiHSZ0JzqOMjWggGd2hud2/Qr98/eC+/JdUL3z1aSaKu16EHmQ11YYB5TeILOu6tV5FieH\nwEcuDm4m2tlCWELCJRGUdRGprMuIMHNSkGvyt1QYnKRLwYnDEfY6Odeo7mr2+8mJeuj4WZOS30Eo\nbyAhCRgzweyxDdoT9nuyt7wVp+qMzx3Z1R1o550kwleO4aE9sxAWMjLMG7H+RmMGjQu4dvVrcCKT\nyZCdnY2ysjJkZGTg5MmTohVOyfquh0g9TqxClDkpPINzjWq08X4UQr3lGGRild6doYf3gr71LHD0\nEOh3H4P+tNbRUxIhDE4IgGvOCeyDL54HEmg682EtId5yXDtM7GYySdKbSEhI3eEtMSAaCOLp1tQd\nwPkiZpPqNh2rNyGSM6QzMDDAC968RalGNYf6Dj3Oq7SMbb2/tg2XF/zB7Euuvq3bZ9fJMX4YM8B8\n9mS/oCv81Fh/uz0PG1y72J4nO0pazGztHDjESjgoKAgzZ87E1q1bERUV1ZU9qaysRGRkpMV9MzMz\n+2mWzg//WgwpLgRfyltQ24BGD7xW3X0+5O2tGMt7TcsKsfnQSQDGh9HBXh04cuRI30ywn7Hm+yLT\nqDHiw5fAT2prf1iLE3EjQL28ze7X3yibFQCMae5ZOA+fnH3MNrmDR6HNwr/Z2t+PsTqCbxEIeqG7\nb4CcQ2vhCWQW2TxtpyUpKcnRU5BwRUSCeKmsqxODKD4FyN7fNUbPnQaJN2odj1SxpTspAyS9iTMg\nlxEMDVbidL1Ra3KuUYPtxS1M1mRpxR4o1LzMV0g4yPTLuz1+Z/bkbzvPd43tKWtFbn0HRoT5YF+5\nQG/Sg67wlpg7OADrThkXFvaVt6FNy8HPST97/Rac1NbWwsvLC8HBwWhvb8f27duxYsUKXHPNNVi7\ndi2efPJJrFu3DgsWLLB4nPT0ngld3Y3MzEzmWuh/ZF2FEtMuAhnrWddKeE3Mof88Gqgx9LMgnB6K\n1nbwg5NZw2OQPsr1M0/WXg9u/WrQJvaBQ9GuQlpDOWRXLu6r6dlMGkeR9Uc5DlW2I9pPgeeackD4\nPeKHjsDIa24wu9pk7fXopC6kAauO1EIpJ1gxOQYThyb39p/gVEjOiBK2QrUaoJW34iqTAb3MVLob\nJHEkKC84QUEuwCs1FYrhL5L0jU7DsBA2OPmzrBUbzxmzJjLK4ab8Lcw+5IobQLysK7+aGuuH0eHe\nOFFnPMeaY/V4YkIE8nnNfuXEkGmxJynh3ojxV0Cl5TBzoD/mDg6El4nyZWeh34KTiooKLF26FBzH\ngeM43HjjjbjyyisxefJkLF68GJ9++ikGDx6MDRs29NeU3AthE0aprMs8CcO7ghMA0BbkATFRXa89\nqb8JLS0A3fi56fc2rgedt9BsE7H+Ri4jeH9OHKradIhQUOCeX5j3eyOEN8VtKaFYMCwIHIVkKy0h\nAYhLugJDQOTSd4MPSRzJXzIBzT/FvC/Sm/RR7yQJ2zGI4o3B99d5jUyLgevrs+BXb3x2gJcSZJ71\ntvWEECwfF46/87Inu0pbEenH3mPHRvRNs9/3Lo1DXICXUwclnfTbU8eYMWOQlZUlGg+4X7+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M7aNUtISLgYTUK3LslKuDv2lhmyx4VBA/HjkLnMe3TDR6DCbJQLQ/dtB/bvYMbIzfeCxA/tdl+Z\n8P505jiQc8C282/+Gsg7xp7/7iesXhQjhIAMHgbZ/Jsgf/I1yN/5EbKH/y1peB2EFJy4OsLMiYum\n2s82qLG1SNX1em95K57fVwXODhmUt7Nq0ag2Bhc+coInJkSYLXGS3Xo/O1B0BnTfNpPbOh2nskT2\nibK7nwDx6b11JSEE5Do2e0J3/wrKExnSn9YCFaX8nS70VPGMbsgSEm6LIHMi9TmxTE51OzblN3e9\n/jDlBuh8efbVbSpQd7Gsb6oHt+YVdjBpFMiCJaZ3EEASRwITBIuC31ivPaHni0G/eIcdnDAdZPoV\nVu0v4XxIwYmrI6yRdNHMyeaCFtHYlqIWvJZZ26sSr5zqdvx0rpkZu3tMGOICvczuQ4Ykg1wyjxmj\nX71nU3dZR8H99Dk7kDqlW8tfWyBT5wCRscYBraarPIFWlIB+/ym7/bxFIEmj7HZ+CQmJ/odSKtac\nSGVdZunQcXjhQBXjbuYXFgbZ4mXMdnTbj6DF5/p3cn0A/ei/7EKpwutCOZf1smbZjYLyqbxjQM7B\n7s/NceBWv8ha5vsHGhbFXEwrKmFECk5cHTcQxOs5is2FzSbf+zq3ER8fbzD5XnfoOIqXM6qZsSFB\nXrg9pftrRG6+D5DxVvsrSkF3/dKjefQXtDRf1PRKtuhOu/5AE7kC5Bq2GRXdsgG0vRXcmv+y9b7B\nYSC3CTQ8EhISrkdHG/vw56UEJJGwWd4/WofiZnYx6/kpUVBcdTMQE28c5Dhwn62yu8ayPwnOzRJr\nDG9cDjJ4mE3HIcNSxCXVVjh30d++AU6z1QLkrsdAwiJtOr+EcyEFJy6OSHMS6Hrd4Q9VtqG23byT\nzntH6/DdGbGLRnd8nduIsw0aZuypSZHwknf/sE5iB4vsA+k3a0D5N2gnQ6j/aI0dYnAfszNkzrUA\nv1dKawu4lY8xTl4AQO54BCQgyO7nl5CQ6GdENsJh0qq0GY7VtOMLgWX99UlBmBTjB+LlBdkdj7A7\n5BxwOdOVTmhzI+K3fMEODh3Z40a7spsE2pPco8CxQ+bPX1EKun41O3jRxT22zJdwHqTgxNVxA83J\nr/lsSdeEKF8EKtmP5iuHarCtSFz6ZY6qVi0+OMreUOcPCcSEaD+rj0FuXG5YIeykrgp063dW79+f\n0LpqpkkiAFRNmdcnDxDExxfkyhvZwaOC9PvodJCZ8+1+bgkJCQcg1JtIYniTqPUcXthfBU5gWf/w\neJ4oe+JMYMwEZj/us1UuUTYshH7yP3i18u7LCgVkf38BRGG+bNoSZNgokYUw941p5y7KceDefQlQ\n81w4/QIgu++fUuDsBkjBiasjLOtyMc2JSqPHrlIVM7ZsbBjenhULH16GgwJ4Zl8lDp5vhTW8llmL\nNp3xBy3AS4ZHLrLNypYMiAK5YjEzRr//BLTdujn0J/TXrwEdryNuTDyaktP67HzkyhsBpbfpNxUK\ns/aNEhISLogb6U1KmjV4fn8lXjxQhfIW+wYEHx6tR6GgnOvZKZEIUBpLhAkhkP3fowD/97G8CHTr\n93adS19DM3aD7vmNGSOL7gZJGN6r44q0J6ezgeOHxeff+r2hNwn//Hc+CjIgqlfnl3AOpODE1WkS\nlDu5WObkjxIVOnidEaP9FLgoyhepkb54dXoM+BVYOg74x54KnKjtMHEkI/vKW7GjhA14HkwLR7iv\n7T1HyfX/B/jwsi3NjaCbvjC/gwOgrS2gv7M3NrJgCSDru683CQ4DmX2N6fcW3G6VfaSEhIRrQAVl\nXcRFMyc6juLhXeexKb8FP59rxtKtpSho0nS/oxWcrO3AulPsYuG1w4IwNdaEZf3QZEN5LA/67Yeg\nLU12mUtfY7CMX8kOJgwHuf7OXh+bDB8NjJ/KjHHffsiev+o86OdvsjumTZU6ubsRLhecuEq/if6A\ndrQDGt6DusLL5USKvwpcuuYPDYTsworSJQP98eJUdhWkXUfx4M5yszeUDh2HlRk1zFhKuDeuTwo2\nuX13kOAwkR0i/Xk9qIlOso6CbvsRaOMFY8Gh/VJzSxbcxq7+AUBEDMjiu/v83BISEv2IKHPimsHJ\nX+WtTGajrkOP5dvKUNjLAEWj5/C8oJwr0k+Bf1jI1pNb7mcXvlqaQL9d06t59Bd0x89AXZVxQK6A\n7O8vgnj1rJxLiCh7cjIL9LghS0IpBffui0BHu/F9X3/I7pfKudwJlwtOkH/a0TNwHkzoTVzpy3le\npUVmVTszdtVQVkA9f2gQHktnf+Ab1Rzu31GOylZxSv7TEw0oUxnHCYBnJkVCLuv5dSELbmMF4O2t\noD+u7fHx7AnVakF/+ZIZI1fe1C+No0jMIJCpbGMx2bInQbx731NFQkLCiRBpTlyzrOvHs+LMRF2H\nHsu3l6GoFwHKR8cbkC/Y/5+TIxGotNAZPXQAyCI200C3bAAtL+rxPPoDqtWA/vAZM0auvBFk6Ai7\nnYMkjzXY4PPozJ7QbT8CxzLY7e94BCQixm7nl3A8Lhec0Izdjp6C8+DiepPfCtmsyZgBPkgIVoq2\nu3VkKO4azf7bqtp0uH9HORo6jC5flWoZ1p5kr8ni5GCkhPfuQZ34BYjS1fS3b0Drqs3s0X/QvVuA\nel6myNtHpJPpS8g9K4C0qYYu9Hc8AjJxRr+dW0JCon8QlnW5oiC+slWLfefbTL5X267Hsu1lKG62\nPUA5XdeBz06wwdvVQwNxSVz3VQzkmtsA/kO1Xgdu7Rs2z6E/EWZNOIUXyMI77H4ekXPXiUxwuzeD\nCq/PuEkgly20+/klHIsLBid7HD0F50GYaneh4IRSil8L2N4mVw0NNLv9A6nhuD6JzaoUNmvx953l\naNNyoJTiqyofaHl59XAfOR5Itc8KH7liMRAWYRzQqEG/+8gux+4plONAN7JNF8mca0GC+s9OmgSF\nQv78u5B/tAWya2/vfgcJCQnXQ3CvIS5Y1rXxXDNTduUlyKbXtuuxbJttAYpWT/H8gSrwZJMY4CvH\nY+kR5nfiQZTeIEsfZgcP7wUVuh86CaayJrXjp4OE2mY2Yw1kRCowbjJ7/jf/CfANaXx8Ibv/OZeq\nGJGwjn4LTsrKyjB79myMGjUKY8aMwdtvvw0AaGhowGWXXYbk5GTMmzcPTU3dCMKKz4JWlffDjJ0f\n2sLqHogLieFP1KqZJlUKGXBZgvnghBCCpyZG4tJBAexx6tR4dE8Ffi1owelWtt710fQBFtPqtkC8\nfQzWwjzozl9A21Rm9ugHsvYBJfnG1zKZqEGihISERK9xcSthPUfx0zl2Meyx9AG4bhi74FXTrsfy\n7eUosTJA+eREvaiX1j8nRSLI2/r7Dpk2FxiZyoxxn64C1Zvv/eUo6M5NQG2lccBLiaopl/fZ+WQ3\n3WPxfbL0YZCo2D47v4Tj6LfgRKFQYNWqVTh58iQOHDiAd999F7m5uVi5ciXmzJmDvLw8zJ49G6+8\n8kq3x6KHpewJALHmxIUyJ8KsyfQ4f4R084MulxG8fHEUJkazmoaDFW14bn8VMzYx2heXWwh2egK5\ndAEQEW0c0KhB9++w6zlsgftpHfOaTJsLEhXnoNlISEi4LS5uJbz/fBuq2oxW6z5ygiuGBOKfkyNx\nrSBAqW7TYZkVAUpevRqfHGevy/whgZgRH2BmD9MQQiC78zF2sPisoXzKiaBaLej3nzBj5LKF0PVh\n42cyMhUYO9H0m6PTQeYt6rNzSziWfgtOoqOjkZpqWB0ICAjAyJEjUVZWho0bN2LpUkM30aVLl+Ln\nn7v/QtJDUnACwITmxDW6w2v0HH4XNFQUCuHNoZTLsGpmLEaGmemxAUMWZsXESLuneonCC2TmVcwY\n3fWrXc9hLfTMCeDkEWaMXNuzrrwSEhIsppq+eSpUqwH4jfZkMtYgxAUQCuHnJQQiUCmHjBA8OzkS\nCxLFAcry7eUobTEdoGg5ihcOVIHXSgvhPnI8PsG6ci4hJGkUyAy2aS396j3HZuYF0F2/ADW8rInC\nC2Th//X5eUXOXQDg7QPZ354H6UO7fAnH4pC/bFFREXJycjB58mRUVVUhKspgFxsdHY3qaitExieP\ngKqau9/O3XHR7vB/lbehSWO0hA5WynCxFeLBTvy9ZHjn0lgMDjJtW3hHSiiGmBDW2wNhcIKTR0Cr\nzvfJuSzB/cxmTTB2IkjiyH6fh4SEW1KQ6+gZOA/Ckq7AEBC5fcpl+4PqNh3+LGcb5y7k6RdlhOC5\nKZG4JpHNtFe16bB8WznKTDRqXHuiAbn1ambsmUmRCLahnEsIWfIgoOSZtzTVizIVjoLqTGdNSHhk\nn5+bjBoPjJnAji35O0j0wD4/t4TjsL0rXS9RqVRYtGgR3nrrLQQEBIhWt61a7eb0KPh+PRpGT+qj\nWboGjSVF4K9f5dfUoykz0+z2zsL6Uj8AxsBivH87jmYfMb+DGe6LJFjZFoBGnTHGHuDFIU1bhMzM\nIjvM1DTD44bCv7yg63XZV2tQdclVFvawL8r6aqTs/wP8b8q5UVPRYuJvn+kCn4f+RLoeRpKSkhw9\nBaeF7t8uBfuduHhJ18ZzzYxgPSlEiTEDWAdHGSF4bnIUOMr23qps02HZ9jJ8PHcg4gIN96zyDhnW\n5LHuZfMSAjBrkG3lXELIgCiQ65aC8hoO0k1fgl52vcMfxOmuX4Fq3iJcP2VNOpHd/yy4lx4AqspB\nLr0W5Mob++3cEo6hX4MTnU6HRYsWYcmSJViwwNDJMyoqqit7UllZichI6yLxIbUlSEx/oC+n69Rk\nZmYi+P/bu+/wqKr0D+Dfc2cmvQfSQwKk0BIChB5aaKIUQXQFKSKw+lPW7gKuq2tbFTsCYkFAEF0L\nRXpXuhAUkBpqCKQBCelt5p7fH5FkzswEApmZO+X9PM8+z86ZO/e+GYc5895zznskcUPKmA7JNXcZ\nbFhBhQ5HT50T2h7pFoN2Te6s3G9M60o8tuUyrpbr4MI43uobieQQj1u/sBHkK38D/6xubVRY+u+I\nePoVq1UMkee/CQ693jY6DnEPTDC6flpaGpKTk60Skz2g90N0y+IjTozv2QI+7h9UBQgAjMoI28cI\nPQDInGPFGfFzPirW1+R/V5XE8J/uweAcWKtX5j6n9K8EZVAEgjzUWJjtDq1e1+vvqsL0zuYZQWAj\nJ4JvXl5XHl5bDb7kE7AX3jHL+e+EyVGTAfeCNQmu5xXmx0IjIc1bBVRVWmUPL6I8q07reuSRR9Cm\nTRs89dRTtW3Dhw/HokWLAACLFy+uTVpuhf++B7zaeLjVqRQa7FJuB53Gpoxi4Ys92keDtoH1rx+5\nlZZ+rlg5Ihrv9wnFKy1KLJ6YAABLGQyo9fL67Ezg1BGLXxcA+PV88G2rxXhGTqQfUYSYU3YmcD5d\n6ShsAjeYPszsaORkX3YZskvrFsK7qhjubl5/oRSVxPBqj2AMMSimkl2qxdRNl/DhwavIqBDv6c7s\n2hT+bmaqCunmXjO9Sw/fuwX8am49r7A8/staQL9CqloNdp/1Rk1uYIxRYuJErJac7N69G9988w22\nbduGDh06oGPHjtiwYQOmT5+OzZs3Iz4+Hlu3bsWMGTMadsKyEqMFwU7HDjdhXHPWcG8Tn0b/sPbU\nSEht5oUgF/nWB5sB8/YFknsLbfwX6yyM5+u+A6r05jo3CakpRUkIMSu+Z7PSIdiGQoOREzva4+Qn\ng4XwA6O8blnmVyUxvNYzGHdFi9O0skq1WHZSvCE4oJkXBkaZuSpkn3uAKL0pl7IMvlWZyl1cWw3+\ng8GoSf8RtBs7sTirTevq2bMndPXU7d6y5c7KsfL9v4Aldbv1gQ6IaatrErQbJBXg1bCKV0o5X1iF\no9fERYR332TjRVsmpQ6DvG9b7WO+cyP45BfANJZZiA8AvKIcfP33QhsbPg5MbbowACHkzvE9m8Ef\neoJGJe10d/ir5VrsyBQXwt8X27AqY2qJ4fWeIeDIwcYLpitm+blKmNnlzqpz3QyTJLDBo8E/r5s6\nzDevBB89xeqFCPiv64HcS3UNajXYfY9YNQbinOy6Dhs/8KvTlnxUG5YY9Pa1+cMlgNkAACAASURB\nVLJ6hnubdA52R6innf6w7tBTLN1cWgwc2GHRS/ItK4FivTuBXj5gA0da9JqEOK2si0DGaaWjUJ5h\nVUg7mdb189kiodRvc18XtG/a8GlBaonhjZ4hGBRleqH79M5BCHC3zP1d1meIWLnrag7wxx6LXKs+\nXKcF/+FLMa7UEWBBtOkhsTzb/jVriove+oQrOU47L1hdbpCc2Ph6E5lzrD1nsLdJS9se6bkZptGA\n9RJ3xpUtOLWL67TgPy8VY7jrfjB3y6+xIcRZ8d00tYsbjJwwOxg5kTnHitPizbD7Ym9/CrFaYngz\nJQQDDRKU1EhPDI5uXHWum2Ge3mApg4Q2efMKi13PFL5jPZCTWdegolETYj32l5y0F8sH8wO/KBOH\nwtSl4g99W19vkpZTbrRDb/9Gll5UGutnUD744G5ww7KbZsL3bBFLOWpcwO550CLXIoTU4Hu2OO3o\nfC2jUsK2n5zszynHpZK6gjkuEsM9Ddzo19CNBGViG380cVchyasa/+kRbPHpfmzQKLHhwA7w/Abs\nA2cGpkdNhoEF06gJsQ67S05Yl77CY2fdLV5dZpic2Pbu8IZTulKbecFTY3cfP1HLNkBE87rHOi34\nzo1mvwznHHzF10Ib6zsUzL+J2a9FCNFz+QKQcUbpKJRluAmjr+1P61phsBC+fzMv+DVig0SNxPB0\npybYPLoFnogsg7eLFdZ+xCcCzVrWPZZ14Ft/tvx1UbOGElkX6xpUarDRk61ybUIAe0xOOvcG9O9Y\nnDuhaJk9pRiuOWE2PHJSXi1jy0Ux3qF2uhBeH2PMaPTEIlW7juwHzp3QvzDYvePNfx1CiBG+984K\ntjgEWTauCmnjU4jzy7XYlin2N6Pi7G8KMWPMaPSEb14BLlu2KiXX6YxHTfreAxYcbtHrEqLP/pIT\nv0AgLkFo4wecb/TEaOTEhjuMbZklKNdbmdjEXYUuVtiPxBpY77vFZPnMcfDMs2a9hrxisdjQpS9Y\neLRZr0EIMc2Z152oy0trEpQbPLzAXO58XyprWH1O3EsrykeDTkHuygXUCKzPPeI627ws4PBvFr0m\n37WpZsTwBkkFdv8Ui16TEEN2l5wAAOvSR3jM91NyYstrTtYYLIS/p7kPVJJjlOdkTUOAhM5CG/9l\nrdnOz8+fAg7tFdqkkRPNdn5CiAkqvSpMl86DXzTvDQd7oS4Vp+Pa+noTzjmWG0zpGhVjekd4e8C8\nfcG6DxDa5E0/Wex6NaMmX4gx9L0HLCTCYtckxBSHSE7w535ww9K6Ds6olLCNjpzklWnxW3aZ0OYI\nU7r0GU/tWgdez54+t4uvFNeaoHUSWKv2Zjk3IaQeiV2Eh846emKUnNj4epODueW4WFy3EF4tAUNb\n2nd/Y7Qwfv+vRhXUzIXv2QxcOl/XIKnA7qe1JsT67DI5QUQLIDSy7rFWC/yxt/7jHZBhtS5bXXOy\n7nwR9GvdtApwRYy/bU8LuF2sW3/AVa8m/bVc4Ghao8/L87KMFtjTqAkhlsd6iHernXXdicbORk4M\nd4RPjfRCgJvV9pq2jDYdjAuvbDP/wnguy+DfG4ya9BkCFtrM7Nci5FbsMjlhjIF1du6pXfYwrYtz\njtVnxTiHOdioCQAwdw+w7v2FNnMsjOfL5gGy3ghMRHMguXejz0sIuTnWtR8g6VVkungWPPOccgEp\nxOgmmA3vcXK9UoetF8Ud4Uc1cEd4W8YYM9psl28y/8J4vmcLoP8ZlyRaa0IUY5fJCWBi3cnBneA6\nbT1HOx6VHWzCeDK/EucKq2ofqxhwV7TjJSeAialde7eCl5fVc/Styb+sNVq7wkaMB5Ps9p8sIXaD\n+fgZT+3a43xTu4zXnNjutK41Z4tQLdeN00d6a9A5xD4Xwhti/YYCak1dQ06mWUbnb6gZNflcvGav\nIWBhUWa7BiG3w35/6bROArz17oqUFAHHDykXjxVxnQ7qMvEOkfBe2AjDhfA9wzwR4G7nQ+z1adcZ\nCAyqe1xRDr5v2x2dimdlgM//r9gY2QKs7z2NCJAQcjuMpnbtdr6pXUbTumzwJhhgeiH8yBgfSHa6\nEN4Q8/E3Hp0358L4fVsB/aIPkgT2AI2aEOXYbXLCVGqwTilCm9PsFl9SCKa/ksPLB0z/rooNqJY5\n1p8XkxN7X5h4M0ylAutzt9B2J1O7eHUV5PdmABV6oy4urpCeextM49LYMAkhDcS6GU7tOgOuv1jY\nCRhOH2Y2OnJy6EoFzhfpLYRnwPCW9re3yc2wQfcJj/m+beCF+fUc3XBcliF/ZzBqkjKYytUTRdld\ncnJZrxKH0W7x+3eAcw6HZ7gplg3uDr83qxQFlXXrJbw0EnpHeCoYkeWxvuLULhzZD34l57bOwRd/\nDJw7KZ538vNg0bGNjI4QcjuYjz+QkCy08T3ONXpiL9O6DBfC94n0QqCjjdK36wSE6S1O12rBt5th\nbeOezcDFM3UNjIE9MLXR5yWkMewuOZm5K6duXmmH7sbzMJ1h0WKhYXJie0PthlO6Bkd7wVVldx+3\n28KatQRatq5r4Bx8x7oGv57v/wV8zTKxsccAoztmhBDrYD0GCo+dbd2JpsT2p3UVVeqwJUNcg3lf\nrGONmgA3FsYb7Bi/aXmjbsjy7EzwT98Ur5MyGEy/OhghCrC7X4t/Xq3AvEM1Nb6ZuyeQaLAB3v5f\nFIjKyoxGTmyrwyiq1OHXTHFNzNAWjtdZmGK0MH77mgZ1HvxqLuRP/iM2BoVBevxlu91AjBB7V1O1\nS6+bvHAa/HKGcgFZEefcuCqkDY6crD1fjEpd3XdsmKcaXUM9FIzIcli/YYBab0QoKwM4dvCOzsUr\nyiG//RygX5FNUtGoCbEJdpecAMCiYwXYk1Xz49d4apfjlxTmBiMnzMbuZm3KKEGVXtWUCC8N2jd1\nu8krHAdLuctod2mcPX7T13CdFvIHM4FivakJKjWk594C83LcdTqE2DrmFwC0ddKpXeWlkLR106ih\ncQHcbWtqrsmF8LG+DrMQ3hDzCwDr0k9o45tX3PZ5OOfgc/4DZJwWzz/hSbDIFo0JkRCzsMvkBABe\n2pWLK2VaMMN9H9L/BC+4qkxQ1mLDIyecc3x/6rrQNrSFt9Pc/Wd+AUDHHkLbreYF8++/BI7/IZ7n\noSfA4hPNHh8hzmry5MkIDg5GYuKt/13ll9eVpWc9Dap2OcvULsPF1n4BNvc9fuRqBc5cF8vVO9pC\neENssMHUrj1bwIuu13O0aXzVEvBdm8TzpgwCGzG+0fERYg52m5wUVOrw0u4c8MAgcZ4/AJ62Q6Go\nrMRwzYkNjZzszS7Dab3OgsF5pnTdIBlO7dq5Aby62uSx/M808B/EXXmR1B3s3gmWCo8QpzRp0iRs\n3LixQcdO35kD7V+jv6xbqji16/wp8OyLlgjRtlw3TE5sb0qX4ahJ7whPBHk42EJ4QwldgOCIusfV\nVUZ7Yt0MP/wb+Ncfi41RsWDT/mNzySdxXnabnADA/pxyLDxaYDy16zcHn9plwyMni4+JsfVv5oVw\nb9sqc2xxyb0BT73pWEXXgT92Gx3Giwogf/gioL/Tr18gpKdfp80WCTGzlJQU+Ps37LsyLbccH/1e\nMwLP/AKBNh2F551iatf1a+JjG9sdvrhKh00XxIXwIx1gR/hbYZIENvBeoY1vbtjCeJ6XVVOqXr/P\n8fSGNON9MDfH2LCSOAa7+wXUKVj8B/Tp4WtIj+kmHnTkN/CKcitGZV2GQ7i2subk+LUK7M8R3/eJ\nbW0jNmtiLq5gKYOENtlgahfnHPLsV4D8K3ovZJCeecNm9xIgxJl8c+I61p+vqVZlVLXLCTZkNNxD\ng9lYcrL+fDEq9BbCh3io0cNBF8IbYv1HiGsbM88BJw/f9DW8sgLy288DxXq/HxiD9Ox/wUIjLRQp\nIXfG7pKT/6aEwM+1LmwdB5654AW5aWjdQVWVwKF9CkRnJTY6cmI4atIp2B3tmjjHQnhDrN8wseHA\nDnC9Be989TdA2k7xNaMmgbU3SLQJIYp5bW8eTuVXgnVPBfSnvJw7AZ5zSbnArMFoWpftJCfVMseS\n4+JNuntjfaCSnGNaEvNvAnQW19vebMd4zjn4/DeBcyfE84x93Ggza0Jsgd1NzgzyUOO1HiF4cntW\nbVtOmQ57wpORcmV1bRs/8GvNDr+OyAb3OblcXI0tF8Uh9oltlI9LMfGJQGgkkJ1Z81hbDb57E9hd\n94OfOWY857dVe7Axj1k/TkJIvSp0HNM2XcBLzUvQPjIW3hfTa5/L/H4h8noMUTA6y4o4fRJN9R5n\nFpXhSlqaYvHo231dg0sldaMkKnA0L72AtLTzVrl+mg28D97NExCzb1vtY93OjTjccQB0JiqqNTmw\nDZEGo/fX45NwPjoRMMPfYgvvhy2h96NObOydbSBtd8kJAPSK8MRDrf3wzYm6OyfLvNojBXrJSdoO\ncJ0OTKVSIkSL4ZyLw7KATewQv+REAfSqB6Olrwt6hjvHELspjDGwvkPBv/20to1vXwPeewjk92YC\n2rpqQPD0rhlaVzvZ2hxCrIxzftub1l2tlvC/4hCkDLoX+HJWbXv4xZNo9uS/zR2izdBt/U54HJnQ\nHlHJyfUcbT1ameO1nzMA1BUZuTfWF4O6xVnl+mlpaUi2gfeBd+gAecv3wJVsAICkrUb7omxIvR4U\njzv2O+QtP4gvjmiOgFc+QaCHV6PjsJX3w1bQ+yEqLCy89UEm2N20rhue7BCI1gGutY8PNm2DYo3e\nj+HCAiD9TwUis7DSEvGHrZs7mKuyU6cKKnRYdUbcSXhCW3+HrTXfUKzvPWLDqSOQ33oOyMkUmqVp\nr4AFhVkxMkKcz9ixY9GjRw+kp6ejWbNmWLhwYb3H3h8nLqzem12Ghd4dxaldZ46D5162VLjKs9E1\nJ+vOFyOzuC4xUUvAI+1sIzZrYioV2MCRQpvhjvH8Wh7kWS8AOr3fDO6ekGZ+AGaGxIQQS7Hb5MRF\nJeHtXiHwUNd0FjpJjT3BScIxDrkhY5HBPGAbmNL1ffp1YWFiU3cVhkTT5oEsOBxoK1b5wZ/7xWOG\nPADWvb8VoyLEOS1btgxZWVmorKzExYsXMWnSpHqPfSG5qdHGsXMvSrjeIkFoc+iqXTZYSlgrc3z5\npxjX8BY+CPNyzlFn1n+EWOY64zRw+igAgFdXQX7neaMkU3r6dbDwaCtGScjts9vkBACa+bjgpW5B\ntY93hBns5HvAEZMT29rjpEIr47uT4rDduNb+0Kice9TkBtZ3aP1PRseCTXrWesEQQhpEo2J4t3co\nmriL04IX+XQSHjv0how2WEp4wwWDURMGTE5QPi6lsMAgILmX0MY31iyM55+/YzR7hD0wFayrg67F\nJQ7FrpMTABjS3Acj/toRdndwB2iZXmdy6Tz45QyFIrMQG1sM//PZIlyv1NU+9tJIGBXrXJsu3gzr\nMQBwcTV+wtUN0nNvg5l6jhCiuKYearzbOxRqvV5yY2hX8aDTx8DzsuBoeHUVUKZX4ESSAG9l9xDR\nmRg1GdrSeUdNbpAG3Sc85rs2Ql75Nfjm5eKBnVLAHqSiK8Q+WC05mTx5MoKDg5GYmFjbVlBQgEGD\nBiE+Ph6DBw++44Uz0zs3RbSPBiUunjjYpI3wnKONnnCDkROmYHKikzmWnhAX54+O84WXi2MVIWgM\n5ukN1rWvcfvfZ4BFtrB+QISQBksKcsc/O9fVrLriHoBDgfHCMQ45tctwSpePv+LFZTZeKEZGUd2o\niYoBk51wrYmRDj2AwOC6x5UV4Is+FI8JiYT0zJu0uS+xG1b7pE6aNAkbN24U2t5++20MGDAAp06d\nQmpqKt566607Ore7RsI7vUPhIjGjqV3yb9vvOGabZDhyouC0rm2ZJUYLE8e0Ur5ymK1hBne2WJ+7\nwVKHKxQNIeR2jI71rR2dB4At4d2F5x0yOTFYp6D0lC6dzPGF4ahJCx9EeDv3qAnw18L4AffWf4Cb\ne80CeC+a0UDsh9WSk5SUFPj7iz+kV61ahYkTJwIAJk6ciJUrV97x+eP8XfFcchPsCDWYE3zyiNFO\nt3atyLCMsDLJCefcaNPFe5r7IMjDLqtTWxRL6Aw2+QWgeTzYXaPBHn8JzMkrmRFiLxhjmNm1KdoG\n1kzB3BZuMLUr/U/wv8q5OgzD9SYKb8C4KaMEFwxHTRKULwZjK9gAg4Xx+s9N+w9YVIyVIyKkcRQd\n48vLy0NwcM1wZEhICPLy8hp1vvvjfNG6dXOk+0bVtklcxtktDnRny2iRojJf0AfzynHsWqXQNr4N\njZrURxo2FqoPv4P02L/AXN2VDocQchtcVRLe6xMKf1cV8jwCcThA3FOD792qUGSWYXhDT8kywqZG\nTe5u7o1IbxeFIrI9rGko0LGncfu9EyGlDFIgIkIax6YmIDb2bjJjDK90C8bBqC5Cu3rtMnBZbtS5\nbQE/dhB8t1gdRqlOw3DUpHe4J1r60eJuQohjCvHUYFafEKgYsDWim/CcbpeDVe0ynG2g4MjJ5owS\nnC+sqn0sOXmFrvpId90vNrTvCjZ+mjLBENJIis7BCQ4ORm5uLoKDg5GTk4OgoKBbviYtLe2Wx/h3\nSIR85EdIqNl7IzI/A3u+/AyuHTs3OmalaK5fQ/xXb0Cjt5mS1tUdx6okyA14T8zpcoWEXZfFfUy6\nqnORlqZ81ZqGfD6cCb0fIno/6sTGxiodgt1JDvbAM52aYElpNzx75Ovadin9COQr2ZCahioYnRkZ\nTetSZo8TmZseNYnyoVETQyy5F9jfHgXftgqIbQfp8X+DqWiaNbFPVv3kcs6F3UuHDx+ORYsWYfr0\n6Vi8eDFGjBhxy3MkJyff8hgkA7/t3YLk9LpKXTG7VyPokSlgavtbQMcryiHPeFgs7QjA5Zk30LGb\n8VCupf28OwdAce3jhCZuGNMrRvF1FGlpaQ37fDgJej9E9H6I7rQ6orMb28oPx681x5+/xSIh/3Rt\n+9GVPyNx6qMKRmYenHPwzPNio0Ij9FsySnDOYNRkCo2a1Esa8xgwhsoFE/tntWldY8eORY8ePZCe\nno5mzZph4cKFmDFjBjZv3oz4+Hhs3boVM2bMMNv13B56HFpW9+c1KczGlTXLb/IK28Q5B5/9CnAh\nXWjP7j0MrFuq1ePJLa3G+gvFQtvEtv6KJyaEEGINjDG81C0IR2JShPaILd+gqvB6Pa+yH/zHr4A/\n9ghtTIERIZlzfH5EHDUZEk2jJoQ4A6uNnCxbtsxk+xYLLVZPTIzFlviBSD1ZV75Y8+OX4ENGgLm6\nWeSalsB/+NJ4F+Lu/ZHTaygiFIhn2cnr0Oot34n01qBvhKcCkRBCiDLc1RIGTngAZb8vg4e2pjCI\nb2UxTn85F62e+5fC0d05eftq8G/miI2hkUDbTqZfYEFbL5bgLI2aEOKUbGpBvDkxxqB5cCoqpbpp\nXD4lV1Hy83cKRnV7+G/bwZfNExujYyE9+RrArP+frrhKh59OFwltE9r4QyXRqAkhxLmERoTg954P\nCm3Ru1eiOjNDoYgahx/aBz7nNaFN6+YBaeaHVt+AUeYcXxiMmgyO8ka0L42aEOIMHDY5AYCUxBZY\n12qI0MaWLwQ3WLthi3jGGcgfviQ2evvVdBTuHorE9NPpQpRW1w2b+LuqMLSF901eQQghjqv1pCnI\nca9bLK6Rtcid/66CEd0Zfv4U5HeeB/QKrkCtwfn7Hwdr1tLq8WzPLMXp63WjJgzAlEQaNSHEWTh0\ncqKWGKT7HkGpum4al3t5ESpXLlUwqlvjRdch//cZoKKsrlGlhvTPd8GCwxWJqUonY9kJcT71mFZ+\ncFM79EeIEELqFeTnhQODpgptocd2o/rQfoUiun38Sjbk1/8BlJcK7ezp11ESFW/1eGrWmojVwgZF\ne6EFjZoQ4jQc/pflkMRI/NRqmNi4agl4UYHpFyiM67SQ35sO5F4S2tnkF8ASlKs0tP58Ma6U62of\nu6kY7o/3VSweQgixBd3vH4k/A8SyzMWfzQLX6ep5he3gJUWQX5sG5F8R2tnDz0BKGaxITL9kliK9\nQBw1mUprTQhxKg6fnLhrJMjDxuG6S930I01lGXQ/LlQwqvrxhR8AR8S7bmzQfWBD7q/nFZYnc47F\nx8VRk5GxvvBzte48ZEIIsTXBXi44POwJoc03+yy0W1YpFFHD8OoqyG89C2SeE9rZ0DFgI8YrE5OJ\nCl0Do7xog19CnIzDJycAMLJ9GJa0Him0yev+B341V6GITJO3rARf863Y2KYD2NTpipbq3XW5VNih\nV8WAca39FIuHEEJsyV2DemBTpLjnVNWSOeAGU6VsBZdl8NkvA8cOik90SwWb9Jxi/c0vl0pxqqBS\naKNRE0Kcj1MkJwFualQPHI1c97ovOZW2CvL3nysYlYifPAQ+/02xsWkIpH++B6ZRduPIRcfEKXAD\no7wQ5mV/m1kSQoglBHtqcGbYY6jQqw7pVlIA3Q8LFIyqfvzr2eA7N4qNrdpDeuZNq1fmqo3JxKjJ\ngGZeiPGnURNCnI1TJCcA8GD7YCxoPVpo41tWgWdfVCgivTiu5EB++3lAq1cpxcUN0syPwPyUvWt0\n5Eo5/sirENomtvVXKBpCCLFNo3vGY1m8uL5R/nkpeG6WQhGZJq/9DnzlYrExLArSix8pugfYjkul\nOJkvjpr8nSp0EeKUnCY5ifR2QWmvobjoGVLbxmQd+LJPFYwK4JUVkN9+FrguVidhT74K1sL6lVIM\nLT4ujpp0DXFHqwD72cSSEEKsIdRTg/wh43HFre7mjUpbDd3ijxSMSsT3bQP/cpbY6BsA6ZW5YD7K\nTdXlnOMzg1GT/s28EEujJoQ4JadJTgBgfEJTfNb2AaGN79wAfv6UIvFwzsHnvAqcPSG0s/unQEoZ\npEhM+n7PLcf2i+Kc6Ydp1IQQQkwa3zEc89uJGzOyPZvBTxxSKKI6/ORhyB+8CHBe1+jmDunfsxUr\nUX/DrstlOEGjJoSQvzhVctK2iRvyO/XHaZ9mQrtsuAu7lfAVi8B3bhAbu/QBG/N/isSj71R+JZ7a\nngW9bgzx/q7oGqrMBpCEEGLrwrw0UKUOw0m/5kK7bsF74LJcz6ssj1/OgPzm00CVXgIgqSA9/w5Y\nTFvF4gJujJqIMwdSIz0RR6MmhDgtp0pOAGBCu0DMayve2cKBHeAnrXtni6ftBF/yidgY2QLS02+A\nScr+Z7lUXI1p2y6jpFrsTB9rH6Bo1TBCCLF1kxOb4KP2E4U2duYY+I71isTDr1+D/NoTQLFYDp79\n34tgyb0UiekGzjk+/P0qjl0zHDUJVCgiQogtcLrkpGeYB7Jbd8fhgDihXV4yB1x/uNuCeOY54+F1\nL5+aBYkeXlaJoT5Xy7X4vy2XcbVc3EBsWlIg+kYqGxshhNi6MC8NIrp1w7awLkI7/3o2eEW5VWPh\nFeWQ33gSyL0stLO//R3SwFFWjcUQ5xwf/X4VSwz20Oob4Yn4ABo1IcSZOV1ywhjDhLYBmNdujPjE\nsYPA4d8sfn1eUgT5rWeAspK6RkkF6YV3wEIjLX79mymu0uHxrZdxqaRaaH+olR8eaUdrTQghpCEm\ntwvAnMRxqJLUdY35eeArv7ZaDFynhfzedODMcaGdpQ4He/Axq8VhCuccs/+4hq8NEhNfFwnPdGqi\nUFSEEFvhdMkJANwV7Y3MqPbYF5QotMtLP7Ho6AnX6SC/PxPIEssXs0nPgrXvZrHrNkSFVsZT27Nw\nuqBKaL+nuTeeTW5C07kIIaSBIrw16JAYh+9i7hba+YpF4NfyLH59zjn4/LeAtJ3iE0ndwR5/SdHv\nc845PvnjmtH+Wb4uEj4bGIFmPi4KRUYIsRVOmZxoVAwPtfbDXMPRkzPHgX3bLHZd/vXHwB97hDbW\nfwTY0DH1vMI6tDLH9J05RvuZ9Ar3wCs9giFRYkIIIbdlSkIAFrUehXxXn7rGygrwpZ/U/yIz4T8u\nAN+8XGxsHg/pn7PA1MptoMs5x9xD17DQIDHxcZEwf2A4TecihABw0uQEAEbF+CAzKNZoXrD8zVxw\nna6eV905eftq8FVLxMb4RLDHXlT0LpbMOV7bm4sdl8SSwUlN3fBO71BoJEpMCCHkdkV4a9A3Phif\ntTEoX799DfiZYxa7rrztZ/Bv5oqNTUNqSgYruKaRc455h/Ox4KiYmHi7SJg/IJz2zyKE1HLa5MTL\nRYXRcb74tO2D0EHvB/il8+C/rjXrtXj6UfB5b4iNgUGQZrwPplFuCJtzjg8PXsXqc8VCe6yfCz7u\nFwZ3tdN+PAghpNEmtwvA6ub9ccZHXE8oL3jPIlOI+aF94HNfFxs9vSG9PAcsIMjs17sd84/k48s/\nxY0WbyQmrQMpMSGE1HHqX59jWvnhkl8k1kX1Ftr5t/PBq6vqedXt4fl5NQvg9c/n4gpp5gdg/sou\n/Ft4rABLT4gLEsM81ZjTPxw+riqFoiKEEMfQzMcFg1r64cNEsbQwThwC9mwx67X4uVOQ33ke0Gnr\nGtUaSC9+CBbZ0qzXul2fHb6Gzw12gPfSSPi0fzjaUGJCCDHg1MlJkIcadzf3xhet70c10/sxfiUb\nfPOKRp+fV1VCfus5oOCq0M6eeEXxja+Wny7EJ3+IG18FuKnw6YBwBHmo63kVIYSQ2zElIQAHQhKx\nM6Sj0C4v/gi8qrKeV90efiUb8uvTgHJxei57+g2wtp3Mco079dmRa5hvKjEZEI62TSgxIYQYc+rk\nBAAmtPVHlmcQVjQfILTzpXMgr152xyMonHPwT98ATh8V2tnIhyH1GXLH8ZrD1oslePM3sWKMl0bC\n3P5hVCmFEELMKMrHBUOivfFRwnho9W+C5WWBr/6m0efnJUWQX5tmfBNs0rOQUgY1+vyN8cWRfMw/\nLCYmnhoJ8/qHox0lJoSQejh9ctLC1wW9IzyxoPV9qFDp/TAvKwFf8C7kaaMg79wALsv1n8QE/vNS\n8O1rxMZOKWDjppkh6jt3IKcMM3fmQNab7uwiMXzYL5QWJBJCiAVMSQhASVY9XAAAEVJJREFUpm84\nfmghJgt86RzI788Ezzx3R+fl1VWQ33oWMHg9GzoWbPi4O47XHBb8mY95h8XR+ZrEJAwJTamvIYTU\nz+mTEwB4uK0/rrn5YWH8SOMncy+Dvz8T8gvjwI/sb9D5+B97wBd/JDaGR0N69r9gKuXWcpy4VoFn\nfslGtV5mIjHg7V4hSA72UCwuQghxZNG+Lhgc5Y0v2tyPQo1n3ROcg+/cAPnJ0ZA/eBH88oUGn5PL\nMvjsl2s2ENbXvX/N3lkKVoFc8Gc+5hwSExMPNcPc/mFIbOquUFSEEHtByQlqyuYmNHHDglaj8Em7\nsShVm7irc/YE5Jcfhe61aeAXTtd7Lp6VAfm9GYD+SIuHF6QXPwLz9LZA9A1zpqAST2zNQmm1OAL0\n725B6NdMufKShBDiDKYmBqDYxQsftH/Y+EnOwXesh/yP+yB/+BL45Yxbno9/PRt850axsXUSpKff\nUPQm2MKj9SUm4WhPiQkhpAEoOQHAGMPDbf0BxrA4/l6MHDwb37cYDJ1k4gv+992Qn/kb5NmvgF/J\nEZ7ipcWQ//sMUKpXmleSID3/Nlh4lIX/CtOulmvx5m95eHDtRRRUivu3PNUxEPfG+CoSFyGEOJPm\nvi4YHO2FtVF98FSPGUj3NdEnyDL4r2sh/2MU5I//DZ5lOkmR13wLvnKx2BgeDWnmh2CuykyZyimt\nxut7czHboNCKu5phTv9wJAVRYkIIaRgqy/SXPhGeiPLRIKOoGvlufpjVYTK+jbkbTxz7FgMu7xMP\n5hx828/guzaCDR0DNuoRwN0D8of/Ai6dFw5lE54C69jTin9JjbJqGV8fL8DXxwtQrjWupz+hjR8e\nbhtg9bgIIcRZTU0MxMYLJdgd2hF7QpLQL2s//n78B8QUZYoHynLNZo2/rgfrczfYA1PBQmv2SuH7\ntoEveFc83i+wZi8THz8r/SV1ckurseBoAVacKYTWYGmmu5phTmo4OlBiQgi5DZSc/EUlMczo3BT/\n2J5V+wWb6R2KGd2eRbtr6Xj66DdIunpCfFFVJfjyRTVlh+MTgbSdwtOszz1gI8Zb6S+oUS1zrDhd\niM+P5ONahemd7kfG+ODpjsrusUIIIc6mxV+jJxsulIAzCdvCu2F7WBekXv4Nfz/xI1oaJSk68O2r\nwX9dB9ZvKNChR806E/0NHN3cIb00Gyw43Kp/S16ZFl8dzcfy00XCOsbasFQMs1PD0DGYEhNCyO2h\n5ERPtzBPLBwciQ8PXsXveeW17UcD4zCl93/QK/sgnjq2DNFFl8QXFhcaJSaIbQv2+EtWW5TIOce2\nzFJ88sdVZBRVmzwmwkuDaR0CMSjKS9HFkoQQ4qxe6haMwkoZe7PLAACcSdga0R3bwrtiwKV9mHri\nB7Qoviy+SNaBb10FbF0ltksqSC/MAotpY6Xoa5KShX8lJVUmkhIACPdS442eITSVixByR2xizcmG\nDRvQqlUrxMXF4Z133lE0lnZN3PDloHB81DcULXz1Sgszhp1hyfhb/3fxesdHcc39JlOi/JtAmvGB\n1eb+Hsorx8MbL+H5X7NNJiZ+rir8s3NTLB8ehcHR3pSYEEKcjq30M55/7Sk1f0A4kvRK6nImYXNk\nDzw48H38q8uTOO9965EQ9n//AuuUYslwa10p0+LdA1cwfOUFfHeq0GRiEuapxsvdgrBiRDQlJoSQ\nO6b4yIksy5g2bRq2bt2KsLAwdO7cGSNGjECrVq0Ui4kxhj6RXugZ7onVZ4vw6eFruFJeM0VKJ6mw\nqnl/bIhMwdgza/FI+iq4V9eNskCtgTTjfbDAIIvHeb6wCrN/v4pfLpWafN5NxTCutR8mtvWHl4ty\n1VsIIURJttbPMMbQNdQDXULc8Vt2GT49ko8jVypqYmUSNkamYHNEDwzM3IOpJ35EdEmW8Tn+9iik\ngSbK35vZtXItFh4rwI/phajUmR4pCfFUY2pCAIa18IFGRTe/CCGNo3hysn//fsTGxiIqqqZyyYMP\nPohVq1YpmpzcoJYYRsb64q7m3lh24joWHiuoLcVbqXbFwlajsKL5AEw+8RNGXdwOlVqD3EdeREmT\nOOBahcXi0snAkmw37D6ZAVN9hcSAe1v64NH2gQjyUPw/MSGEKMpW+xnGGLqFeaJrqAf2Zpdh/uF8\n/HlVL0lploLNkT0wOHMXppz4CVEl2QCAgtT7kDdwokX7GZkDP+S6YUf6BVTcJCmZ0i4Aw1tSUkII\nMR/Ff7levnwZkZGRtY8jIiKwf3/DNju0Fne1hMkJARgZ64Mv/yzAD+nXaxfNX3f1wftJk/BR4njI\nTALPkYB1mTc/oVm4mmztE+GJf3QIREs/088TQoizsfV+hjGGHmGe6B7qgd1ZZZh/+BqOXasEUJOk\nrG/WG5sieiL++nnomIRT/i2A9ZducVZzcAVgnJgEe6gxOcEfI1r6wEVlE7PDCSEORPHk5HYVFhYq\ndm0VgEfjXPBonOWnbDVOBQoLLXdHzVbFxsYq+vmwNfR+iOj9IA2l5OckwQuY27O+/adCrRrLrZSX\nFKP81oc5FPoeEdH7IaL3wzwUv+URHh6Oixcv1j6+dOkSwsOtWxKREEKI46J+hhBC7IfiyUnnzp1x\n5swZZGRkoKqqCt999x2GDx+udFiEEEIcBPUzhBBiPxSf1qVSqTBnzhwMGjQIsixj8uTJaN26tXCM\nr299Q9yEEELIzVE/Qwgh9oNxzk2X4SCEEEIIIYQQK1J8Wtet2MrGWbYkOjoa7du3R4cOHdClSxel\nw7G6yZMnIzg4GImJibVtBQUFGDRoEOLj4zF48GCnW5Bm6j159dVXERERgY4dO6Jjx47YsGGDghFa\n16VLl5Camoq2bdsiISEBs2fPBuC8nxPD9+OTTz4B4NyfEX3Uzxijfob6GUPUz4ionxGZs5+x6ZET\nWZYRFxcnbJz13XffKV6bXmktWrTAwYMH4e/vr3Qoiti1axe8vLwwYcIEHDlyBAAwffp0BAYG4p//\n/CfeeecdFBQU4O2331Y4Uusx9Z68+uqr8Pb2xrPPPqtwdNaXk5ODnJwcJCUloaSkBJ06dcKqVauw\ncOFCp/yc1Pd+/O9//3Paz8gN1M+YRv0M9TOGqJ8RUT8jMmc/Y9MjJ/obZ2k0mtqNs5wd5xyyLCsd\nhmJSUlKMOsxVq1Zh4sSJAICJEydi5cqVSoSmGFPvCVDzWXFGISEhSEpKAgB4eXmhdevWuHTpktN+\nTky9H5cvXwbgvJ+RG6ifMY36GepnDFE/I6J+RmTOfsamkxNTG2fd+EOdGWMMAwcOROfOnfHFF18o\nHY5NyMvLQ3BwMICafyB5eXkKR2Qb5syZg6SkJEyZMsVphpYNXbhwAYcOHUK3bt2Qm5vr9J+TG+9H\n165dAdBnhPoZ06ifMUb9jGnO/h0CUD9jqLH9jE0nJ8S03bt34/fff8e6deswd+5c7Nq1S+mQbA5j\nTOkQFPf444/j3LlzOHToEEJCQpxy2L2kpASjR4/Gxx9/DC8vL6PPhbN9TgzfD/qMkPpQP3Nrzvb9\nYQp9h1A/Y8gc/YxNJye0cZZpoaE1uwQ3bdoUI0eOxP79+xWOSHnBwcHIzc0FUDPvMSgoSOGIlNe0\nadPaL8WpU6fiwIEDCkdkXVqtFqNHj8b48eMxYsQIAM79OTH1fjj7ZwSgfqY+1M8Yc+bvj/o4+3cI\n9TMic/UzNp2c0MZZxsrKylBSUgIAKC0txaZNm9CuXTuFo7I+zrkwh3H48OFYtGgRAGDx4sW1/yic\nieF7kpOTU/v/ly9f7nSfk0ceeQRt2rTBU089VdvmzJ8TU++Hs39GAOpnTKF+pgb1M8aonxFRPyMy\nWz/Dbdz69et5XFwcj4mJ4W+99ZbS4Sju3LlzvH379jwpKYm3a9fOKd+TMWPG8NDQUO7i4sIjIyP5\nV199xfPz83n//v15XFwcHzhwIC8oKFA6TKsy9Z6MHz+eJyQk8Pbt2/MRI0bwnJwcpcO0ml27dnFJ\nkmr/rXTo0IGvX7+eX7t2zSk/J/W9H878GdFH/YyI+hnqZ0yhfkZE/YzInP2MTZcSJoQQQgghhDgP\nm57WRQghhBBCCHEelJwQQgghhBBCbAIlJ4QQQgghhBCbQMkJIYQQQgghxCZQckIIIYQQQgixCZSc\nEEIIIYQQQmwCJSeEWEl6ejo6dOgAX19fzJkz55bHv/rqqxg/frwVIiOEEOIIqJ8hjoCSE+Iwmjdv\njm3btgltixcvRq9evRSKSDRr1iykpqaisLAQ06ZNa9BrGGMWjooQQkhDUT9DiOVRckIcniW+eHU6\n3W2/JiMjA23btjV7LIQQQpRF/Qwh5kPJCXEqJ0+eRL9+/eDv74+EhASsXr269rl+/frhq6++qn1s\neDdMkiTMmzcPcXFxiIuLM3n+n3/+Ge3atUNAQABSU1Nx6tQpAED//v2xfft2PPHEE/Dx8cGZM2eM\nXnvhwgX07dsXvr6+GDx4MK5evSo8/8ADDyA0NBT+/v7o27cvjh8/DgBIS0tDSEgIOOe1xy5fvhxJ\nSUl38A4RQghpDOpnCGkcSk6IQ9P/ItVqtRg2bBjuuusuXLlyBbNnz8ZDDz2E06dP1/t6w7thq1at\nwoEDB2q/sPWlp6dj7NixmD17Nq5cuYIhQ4Zg6NCh0Gq12Lp1K3r16oW5c+eiqKgIMTExRq8fO3Ys\nOnfujKtXr+Kll17C4sWLhefvvvtunD17Fnl5eejYsSMeeughAEBycjKaNGmCTZs21R67dOlSPPzw\nww16jwghhNw56mcIMS9KTohDuffeexEQEFD7vyeeeKL2ub1796K0tBTTp0+HWq1Gv379MHToUHz7\n7bcNPv+LL74IX19fuLq6Gj33/fffY+jQoUhNTYVKpcLzzz+P8vJy7Nmz55bnzczMRFpaGl577TVo\nNBr06tULw4YNE455+OGH4eHhAY1Gg5dffhmHDx9GcXExAGDChAlYsmQJACA/Px8bN27EmDFjGvx3\nEUIIaRjqZ6ifIZZFyQlxKKtWrUJ+fn7t/+bNm1f7XHZ2NiIjI4Xjo6KicPny5QafPyIiot7nsrKy\nEBUVVfuYMYbIyMgGnT8rKwv+/v5wd3cXYrtBlmXMmDEDMTEx8PPzQ/PmzcEYqx2SHzduHNasWYPy\n8nJ8//336N27N4KDgxv8dxFCCGkY6meonyGWRckJcSj6w+uGwsLCkJmZKbRdvHgR4eHhAABPT0+U\nlZXVPpeTk2N0jpstegwLC0NGRobQlpmZedOO5obQ0FAUFBSgvLxciO2Gb775BqtXr8a2bdtw/fp1\nXLhwAZzz2r83LCwM3bt3x08//YSlS5dSaUhCCLEQ6meonyGWRckJcRpdu3aFh4cHZs2aBa1Wi19+\n+QVr1qypHZZOSkrC8uXLUV5ejjNnzmDBggW3df4HHngAa9euxfbt26HVavHee+/Bzc0N3bt3v+Vr\nmzVrhuTkZLzyyiuorq7Grl27hEWUJSUlcHV1hb+/P0pLSzFz5kyjDmz8+PGYNWsWjh49ilGjRt1W\n7IQQQhqP+hlCGo+SE+IwblXKUaPRYPXq1Vi3bh2aNGmCadOmYcmSJYiNjQUAPPPMM9BoNAgJCcGk\nSZMwbty42zp/XFwcli5dimnTpqFp06ZYu3YtVq9eDbVa3aDXL1u2DPv27UNgYCBef/11TJw4sfa5\nCRMmoFmzZggPD0e7du3Qo0cPo9ePHDkSGRkZGDVqFNzc3G56LUIIIbeP+hnqZ4jlMX6z8UlCiF2J\niYnB559/jtTUVKVDIYQQ4oConyGWRiMnhDiIn376CZIkUYdBCCHEIqifIdagVjoAQkjj9evXDydO\nnMDSpUuVDoUQQogDon6GWAtN6yKEEEIIIYTYBJrWRQghhBBCCLEJlJwQQgghhBBCbAIlJ4QQQggh\nhBCbQMkJIYQQQgghxCZQckIIIYQQQgixCZScEEIIIYQQQmzC/wOKRG1DPDveCQAAAABJRU5ErkJg\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f87c7401b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(12,6), facecolor='white')\n",
    "ax[0].plot(dfPivot.index, dfPivot.iPhone, label='iPhone')\n",
    "ax[0].plot(dfPivot.index, dfPivot.Android, label='Android')\n",
    "ax[0].legend(loc='upper right', frameon = False)\n",
    "ax[0].set(ylabel='Tweet count',\n",
    "          xlabel='Hour of day',\n",
    "          axis_bgcolor='white')\n",
    "\n",
    "ax[1].plot(dfPivot.index, dfPivot.iPhone/dfPivot.sum().sum()*100, label='iPhone')\n",
    "ax[1].plot(dfPivot.index, dfPivot.Android/dfPivot.sum().sum()*100, label='Android')\n",
    "ax[1].legend(loc='upper right', frameon = False)\n",
    "ax[1].set(ylabel='Percent of tweets',\n",
    "          xlabel='Hour of day',\n",
    "          axis_bgcolor='white')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "According ot the blog post, Trump frequently quotes tweets of others and manually retweets them.  We can find this like so."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>created</th>\n",
       "      <th>id</th>\n",
       "      <th>statusSource</th>\n",
       "      <th>text</th>\n",
       "      <th>device</th>\n",
       "      <th>raw_tweet_time</th>\n",
       "      <th>tweet_hour</th>\n",
       "      <th>quoted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2016-07-31 16:31:06-04:00</td>\n",
       "      <td>759848885900763141</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>\"@RealJamesWoods:  Without absolutely OWNING t...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-07-31 20:31:06</td>\n",
       "      <td>16</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>2016-07-29 16:04:03-04:00</td>\n",
       "      <td>759117301517996032</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>\"Only a Reagan or a Trump-like figure in the W...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-07-29 20:04:03</td>\n",
       "      <td>16</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     created                  id  \\\n",
       "70 2016-07-31 16:31:06-04:00  759848885900763141   \n",
       "96 2016-07-29 16:04:03-04:00  759117301517996032   \n",
       "\n",
       "                                         statusSource  \\\n",
       "70  <a href=\"http://twitter.com/download/android\" ...   \n",
       "96  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                 text   device  \\\n",
       "70  \"@RealJamesWoods:  Without absolutely OWNING t...  Android   \n",
       "96  \"Only a Reagan or a Trump-like figure in the W...   iPhone   \n",
       "\n",
       "         raw_tweet_time  tweet_hour quoted  \n",
       "70  2016-07-31 20:31:06          16    Yes  \n",
       "96  2016-07-29 20:04:03          16    Yes  "
      ]
     },
     "execution_count": 351,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfTrump['quoted'] = dfTrump.text.apply(lambda x: 'Yes' if x[0] == '\"' else 'No')\n",
    "dfTrump.loc[dfTrump.quoted == 'Yes', :].head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we have the tweets identified by whether they are quoted or not, we can plot the result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f87c6c25a20>"
      ]
     },
     "execution_count": 368,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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VKjg6OiI2NhYA4O7ujqCgILi7u8PAwADLly/n6SUiIiICoMMA4+zsjJMnT1Zq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\nAwwRERHJzv8DKxScCbmuUfYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f87c6c84048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6,6), facecolor='white')\n",
    "df_ = pd.crosstab(dfTrump.device, dfTrump.quoted)\n",
    "df_.reset_index(inplace=True)\n",
    "ax.bar([x for x in df_.index], df_['No'], width = 0.4, color = \"#FC4F30\", label='Not quoted')\n",
    "ax.bar([x+0.5 for x in df_.index], df_['Yes'], width = 0.4, color='#30A2DA', label = 'quoted')\n",
    "ax.set(xticks = [x + 0.5 for x in df_.index], \n",
    "       xticklabels=['Android', 'iPhone'],\n",
    "       ylabel='Number of tweets',\n",
    "       title='Whether tweets start with a quotation mark (\")',\n",
    "       axis_bgcolor = 'white');\n",
    "ax.legend(loc=(1.05, 0.5), frameon=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, so that we only pick up Trump's tweets, we filter out the tweets which are quoted, and we can also see if the tweet contained a pickture link or not"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 371,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>created</th>\n",
       "      <th>id</th>\n",
       "      <th>statusSource</th>\n",
       "      <th>text</th>\n",
       "      <th>device</th>\n",
       "      <th>raw_tweet_time</th>\n",
       "      <th>tweet_hour</th>\n",
       "      <th>quoted</th>\n",
       "      <th>picture</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-08-08 11:20:44-04:00</td>\n",
       "      <td>762669882571980801</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>My economic policy speech will be carried live...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-08-08 15:20:44</td>\n",
       "      <td>11</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-08-08 09:28:20-04:00</td>\n",
       "      <td>762641595439190016</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Join me in Fayetteville, North Carolina tomorr...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-08 13:28:20</td>\n",
       "      <td>9</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-08-07 20:05:54-04:00</td>\n",
       "      <td>762439658911338496</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>#ICYMI: \"Will Media Apologize to Trump?\" https...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-08 00:05:54</td>\n",
       "      <td>20</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-08-07 19:09:08-04:00</td>\n",
       "      <td>762425371874557952</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>Michael Morell, the lightweight former Acting ...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-08-07 23:09:08</td>\n",
       "      <td>19</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-08-07 17:31:46-04:00</td>\n",
       "      <td>762400869858115588</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>The media is going crazy. They totally distort...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-08-07 21:31:46</td>\n",
       "      <td>17</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2016-08-07 09:49:29-04:00</td>\n",
       "      <td>762284533341417472</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>I see where Mayor Stephanie Rawlings-Blake of ...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-08-07 13:49:29</td>\n",
       "      <td>9</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2016-08-06 22:19:37-04:00</td>\n",
       "      <td>762110918721310721</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Thank you Windham, New Hampshire! #TrumpPence1...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-07 02:19:37</td>\n",
       "      <td>22</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2016-08-06 22:03:39-04:00</td>\n",
       "      <td>762106904436961280</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>.@Larry_Kudlow - 'Donald Trump Is the middle-c...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-07 02:03:39</td>\n",
       "      <td>22</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2016-08-06 21:53:45-04:00</td>\n",
       "      <td>762104411707568128</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>I am not just running against Crooked Hillary ...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-08-07 01:53:45</td>\n",
       "      <td>21</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2016-08-06 16:04:08-04:00</td>\n",
       "      <td>762016426102296576</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>#CrookedHillary is not fit to be our next pres...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-06 20:04:08</td>\n",
       "      <td>16</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2016-08-06 14:11:50-04:00</td>\n",
       "      <td>761988164382756864</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>Heading to New Hampshire - will be talking abo...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-08-06 18:11:50</td>\n",
       "      <td>14</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2016-08-06 10:48:14-04:00</td>\n",
       "      <td>761936929902452740</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>Anybody whose mind \"SHORT CIRCUITS\" is not fit...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-08-06 14:48:14</td>\n",
       "      <td>10</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2016-08-06 10:24:43-04:00</td>\n",
       "      <td>761931010548305920</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>Crooked Hillary said loudly, and for the world...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-08-06 14:24:43</td>\n",
       "      <td>10</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2016-08-06 07:53:00-04:00</td>\n",
       "      <td>761892829434183684</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>Hillary Clinton is being badly criticized for ...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-08-06 11:53:00</td>\n",
       "      <td>7</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2016-08-05 23:59:08-04:00</td>\n",
       "      <td>761773576101953536</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Good luck #TeamUSA\\n#OpeningCeremony #Rio2016 ...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-06 03:59:08</td>\n",
       "      <td>23</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2016-08-05 22:57:11-04:00</td>\n",
       "      <td>761757988516401153</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>'Trump is right about violent crime: Its on t...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-06 02:57:11</td>\n",
       "      <td>22</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2016-08-05 22:44:55-04:00</td>\n",
       "      <td>761754898602061824</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Thank you Green Bay, Wisconsin! Governor @Mike...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-06 02:44:55</td>\n",
       "      <td>22</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2016-08-05 18:42:08-04:00</td>\n",
       "      <td>761693803120041986</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Thank you Des Moines, Iowa! Governor @Mike_Pen...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-05 22:42:08</td>\n",
       "      <td>18</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2016-08-05 16:03:29-04:00</td>\n",
       "      <td>761653875413618689</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>#MakeAmericaSafeAgain https://t.co/5yuLKyh8Q6</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-05 20:03:29</td>\n",
       "      <td>16</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2016-08-05 09:08:35-04:00</td>\n",
       "      <td>761549461893984256</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Hillary Clinton has bad judgment and is unfit ...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-05 13:08:35</td>\n",
       "      <td>9</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2016-08-05 06:39:27-04:00</td>\n",
       "      <td>761511930238496772</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>The plane I saw on television was the hostage ...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-08-05 10:39:27</td>\n",
       "      <td>6</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2016-08-04 22:19:22-04:00</td>\n",
       "      <td>761386080272875520</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>President Obama refuses to answer question abo...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-05 02:19:22</td>\n",
       "      <td>22</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2016-08-04 22:19:08-04:00</td>\n",
       "      <td>761386025323225088</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Obama's disastrous judgment gave us ISIS, rise...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-05 02:19:08</td>\n",
       "      <td>22</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2016-08-04 22:18:18-04:00</td>\n",
       "      <td>761385812390977536</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>President Obama should ask the DNC about how t...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-05 02:18:18</td>\n",
       "      <td>22</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2016-08-04 22:16:20-04:00</td>\n",
       "      <td>761385317169496064</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>See you tomorrow w/ Gov. @Mike_Pence, Iowa &amp;am...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-05 02:16:20</td>\n",
       "      <td>22</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2016-08-04 18:42:13-04:00</td>\n",
       "      <td>761331433810132992</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Thank you Portland, Maine! \\n#MakeAmericaGreat...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-04 22:42:13</td>\n",
       "      <td>18</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2016-08-04 15:23:41-04:00</td>\n",
       "      <td>761281473492189184</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Happy 226th Birthday to the United States Coas...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-04 19:23:41</td>\n",
       "      <td>15</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2016-08-04 15:16:00-04:00</td>\n",
       "      <td>761279538106097664</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Great meeting all of you. This group knocked o...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-04 19:16:00</td>\n",
       "      <td>15</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2016-08-04 11:17:01-04:00</td>\n",
       "      <td>761219396635361280</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Looking forward to IA &amp;amp; WI with Gov. Pence...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-04 15:17:01</td>\n",
       "      <td>11</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2016-08-03 22:27:52-04:00</td>\n",
       "      <td>761025834350018561</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Thank you Jacksonville, Florida!\\n#MakeAmerica...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-04 02:27:52</td>\n",
       "      <td>22</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1354</th>\n",
       "      <td>2016-01-22 22:08:21-05:00</td>\n",
       "      <td>690732776920743937</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>A wonderful article by a writer who truly gets...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-23 03:08:21</td>\n",
       "      <td>22</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1355</th>\n",
       "      <td>2016-01-22 21:08:41-05:00</td>\n",
       "      <td>690717760205275136</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Is Cruz honest? He is in bed w/ Wall St. &amp;amp;...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-23 02:08:41</td>\n",
       "      <td>21</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1356</th>\n",
       "      <td>2016-01-22 21:04:23-05:00</td>\n",
       "      <td>690716679496679424</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Cruz did not renounce his Canadian citizenship...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-23 02:04:23</td>\n",
       "      <td>21</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1357</th>\n",
       "      <td>2016-01-22 20:34:26-05:00</td>\n",
       "      <td>690709138884661248</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Cruz says I supported TARP, which gave $25 mil...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-23 01:34:26</td>\n",
       "      <td>20</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1358</th>\n",
       "      <td>2016-01-22 20:33:17-05:00</td>\n",
       "      <td>690708850664669185</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>The only reason irrelevant @GlennBeck doesn't ...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-23 01:33:17</td>\n",
       "      <td>20</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1359</th>\n",
       "      <td>2016-01-22 20:32:32-05:00</td>\n",
       "      <td>690708660377513984</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>.@BrentBozell, one of the National Review ligh...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-23 01:32:32</td>\n",
       "      <td>20</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1360</th>\n",
       "      <td>2016-01-16 14:32:40-05:00</td>\n",
       "      <td>688443772565348352</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Wow! Ted Cruz received $487K in campaign contr...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-16 19:32:40</td>\n",
       "      <td>14</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1361</th>\n",
       "      <td>2016-01-16 13:31:39-05:00</td>\n",
       "      <td>688428417235218433</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Departing NH now- great morning with record cr...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-16 18:31:39</td>\n",
       "      <td>13</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1362</th>\n",
       "      <td>2016-01-16 13:26:54-05:00</td>\n",
       "      <td>688427218901532672</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Greatly dishonest of @TedCruz to file a financ...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-16 18:26:54</td>\n",
       "      <td>13</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1363</th>\n",
       "      <td>2016-01-16 13:23:26-05:00</td>\n",
       "      <td>688426349652910080</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>When will @TedCruz give all the New York based...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-16 18:23:26</td>\n",
       "      <td>13</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1364</th>\n",
       "      <td>2016-01-16 13:22:40-05:00</td>\n",
       "      <td>688426156920459264</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Everybody that loves the people of New York, a...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-16 18:22:40</td>\n",
       "      <td>13</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1365</th>\n",
       "      <td>2016-01-16 13:21:03-05:00</td>\n",
       "      <td>688425749129211905</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>If Ted Cruz is so opposed to gay marriage, why...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-16 18:21:03</td>\n",
       "      <td>13</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1366</th>\n",
       "      <td>2016-01-16 11:11:28-05:00</td>\n",
       "      <td>688393139435008000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Ted is the ultimate hypocrite. Says one thing ...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-16 16:11:28</td>\n",
       "      <td>11</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1367</th>\n",
       "      <td>2016-01-16 08:42:54-05:00</td>\n",
       "      <td>688355751463636992</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Great new numbers. Thank you! \\n#MakeAmericaGr...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-16 13:42:54</td>\n",
       "      <td>8</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1368</th>\n",
       "      <td>2016-01-16 08:31:10-05:00</td>\n",
       "      <td>688352797251792896</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>Ted Cruz purposely, and illegally, did not lis...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-01-16 13:31:10</td>\n",
       "      <td>8</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1369</th>\n",
       "      <td>2016-01-08 18:12:35-05:00</td>\n",
       "      <td>685600012043202560</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>#FoxNews Poll - THANK YOU!\\n#MakeAmericaGreatA...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-08 23:12:35</td>\n",
       "      <td>18</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1370</th>\n",
       "      <td>2016-01-08 17:36:09-05:00</td>\n",
       "      <td>685590843181416448</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>#MakeAmericaGreatAgain #Trump2016 https://t.co...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-08 22:36:09</td>\n",
       "      <td>17</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1371</th>\n",
       "      <td>2016-01-08 17:09:20-05:00</td>\n",
       "      <td>685584095120887809</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Love seeing union &amp;amp; non-union members alik...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-08 22:09:20</td>\n",
       "      <td>17</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1372</th>\n",
       "      <td>2016-01-08 17:03:35-05:00</td>\n",
       "      <td>685582649679867904</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>I hope all workers demand that their @Teamster...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-08 22:03:35</td>\n",
       "      <td>17</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1373</th>\n",
       "      <td>2016-01-08 16:20:02-05:00</td>\n",
       "      <td>685571686423461888</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>On my way to South Carolina. Big Crowd--- look...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-08 21:20:02</td>\n",
       "      <td>16</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1374</th>\n",
       "      <td>2016-01-08 10:57:17-05:00</td>\n",
       "      <td>685490467329425408</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>Hank Greenberg, formerly of AIG, gave $10 mill...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-01-08 15:57:17</td>\n",
       "      <td>10</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1377</th>\n",
       "      <td>2016-01-01 01:07:28-05:00</td>\n",
       "      <td>682805320217980929</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Happy New Year from #MarALago! Thank you to my...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-01 06:07:28</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1378</th>\n",
       "      <td>2016-01-01 00:18:23-05:00</td>\n",
       "      <td>682792967736848385</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>#HappyNewYearAmerica! https://t.co/EeQb8PDrUe</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-01 05:18:23</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1379</th>\n",
       "      <td>2015-12-31 22:25:27-05:00</td>\n",
       "      <td>682764544402440192</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>HAPPY NEW YEAR &amp;amp; THANK YOU! https://t.co/Y...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-01-01 03:25:27</td>\n",
       "      <td>22</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1380</th>\n",
       "      <td>2015-12-26 08:00:26-05:00</td>\n",
       "      <td>680734915718176768</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>The Phoenix V.A., it has just been reported, i...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2015-12-26 13:00:26</td>\n",
       "      <td>8</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1381</th>\n",
       "      <td>2015-12-25 16:49:30-05:00</td>\n",
       "      <td>680505672476262400</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>The same people that said I wouldn't run, or t...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2015-12-25 21:49:30</td>\n",
       "      <td>16</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1382</th>\n",
       "      <td>2015-12-25 16:42:39-05:00</td>\n",
       "      <td>680503951440121856</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>.@chucktodd is so dishonest in his reporting.....</td>\n",
       "      <td>Android</td>\n",
       "      <td>2015-12-25 21:42:39</td>\n",
       "      <td>16</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1383</th>\n",
       "      <td>2015-12-25 16:11:23-05:00</td>\n",
       "      <td>680496083072593920</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>@CNN just announced that TRUMP was #1 story of...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2015-12-25 21:11:23</td>\n",
       "      <td>16</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1388</th>\n",
       "      <td>2015-12-14 16:11:12-05:00</td>\n",
       "      <td>676509769562251264</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Another great accolade for @TrumpGolf. Highly ...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2015-12-14 21:11:12</td>\n",
       "      <td>16</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1389</th>\n",
       "      <td>2015-12-14 15:09:15-05:00</td>\n",
       "      <td>676494179216805888</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Record of Health: https://t.co/ZDDDawwYVl\\n#Ma...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2015-12-14 20:09:15</td>\n",
       "      <td>15</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1175 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       created                  id  \\\n",
       "0    2016-08-08 11:20:44-04:00  762669882571980801   \n",
       "1    2016-08-08 09:28:20-04:00  762641595439190016   \n",
       "2    2016-08-07 20:05:54-04:00  762439658911338496   \n",
       "3    2016-08-07 19:09:08-04:00  762425371874557952   \n",
       "4    2016-08-07 17:31:46-04:00  762400869858115588   \n",
       "5    2016-08-07 09:49:29-04:00  762284533341417472   \n",
       "6    2016-08-06 22:19:37-04:00  762110918721310721   \n",
       "7    2016-08-06 22:03:39-04:00  762106904436961280   \n",
       "8    2016-08-06 21:53:45-04:00  762104411707568128   \n",
       "9    2016-08-06 16:04:08-04:00  762016426102296576   \n",
       "10   2016-08-06 14:11:50-04:00  761988164382756864   \n",
       "11   2016-08-06 10:48:14-04:00  761936929902452740   \n",
       "12   2016-08-06 10:24:43-04:00  761931010548305920   \n",
       "13   2016-08-06 07:53:00-04:00  761892829434183684   \n",
       "14   2016-08-05 23:59:08-04:00  761773576101953536   \n",
       "15   2016-08-05 22:57:11-04:00  761757988516401153   \n",
       "16   2016-08-05 22:44:55-04:00  761754898602061824   \n",
       "17   2016-08-05 18:42:08-04:00  761693803120041986   \n",
       "18   2016-08-05 16:03:29-04:00  761653875413618689   \n",
       "19   2016-08-05 09:08:35-04:00  761549461893984256   \n",
       "20   2016-08-05 06:39:27-04:00  761511930238496772   \n",
       "21   2016-08-04 22:19:22-04:00  761386080272875520   \n",
       "22   2016-08-04 22:19:08-04:00  761386025323225088   \n",
       "23   2016-08-04 22:18:18-04:00  761385812390977536   \n",
       "24   2016-08-04 22:16:20-04:00  761385317169496064   \n",
       "25   2016-08-04 18:42:13-04:00  761331433810132992   \n",
       "26   2016-08-04 15:23:41-04:00  761281473492189184   \n",
       "27   2016-08-04 15:16:00-04:00  761279538106097664   \n",
       "28   2016-08-04 11:17:01-04:00  761219396635361280   \n",
       "29   2016-08-03 22:27:52-04:00  761025834350018561   \n",
       "...                        ...                 ...   \n",
       "1354 2016-01-22 22:08:21-05:00  690732776920743937   \n",
       "1355 2016-01-22 21:08:41-05:00  690717760205275136   \n",
       "1356 2016-01-22 21:04:23-05:00  690716679496679424   \n",
       "1357 2016-01-22 20:34:26-05:00  690709138884661248   \n",
       "1358 2016-01-22 20:33:17-05:00  690708850664669185   \n",
       "1359 2016-01-22 20:32:32-05:00  690708660377513984   \n",
       "1360 2016-01-16 14:32:40-05:00  688443772565348352   \n",
       "1361 2016-01-16 13:31:39-05:00  688428417235218433   \n",
       "1362 2016-01-16 13:26:54-05:00  688427218901532672   \n",
       "1363 2016-01-16 13:23:26-05:00  688426349652910080   \n",
       "1364 2016-01-16 13:22:40-05:00  688426156920459264   \n",
       "1365 2016-01-16 13:21:03-05:00  688425749129211905   \n",
       "1366 2016-01-16 11:11:28-05:00  688393139435008000   \n",
       "1367 2016-01-16 08:42:54-05:00  688355751463636992   \n",
       "1368 2016-01-16 08:31:10-05:00  688352797251792896   \n",
       "1369 2016-01-08 18:12:35-05:00  685600012043202560   \n",
       "1370 2016-01-08 17:36:09-05:00  685590843181416448   \n",
       "1371 2016-01-08 17:09:20-05:00  685584095120887809   \n",
       "1372 2016-01-08 17:03:35-05:00  685582649679867904   \n",
       "1373 2016-01-08 16:20:02-05:00  685571686423461888   \n",
       "1374 2016-01-08 10:57:17-05:00  685490467329425408   \n",
       "1377 2016-01-01 01:07:28-05:00  682805320217980929   \n",
       "1378 2016-01-01 00:18:23-05:00  682792967736848385   \n",
       "1379 2015-12-31 22:25:27-05:00  682764544402440192   \n",
       "1380 2015-12-26 08:00:26-05:00  680734915718176768   \n",
       "1381 2015-12-25 16:49:30-05:00  680505672476262400   \n",
       "1382 2015-12-25 16:42:39-05:00  680503951440121856   \n",
       "1383 2015-12-25 16:11:23-05:00  680496083072593920   \n",
       "1388 2015-12-14 16:11:12-05:00  676509769562251264   \n",
       "1389 2015-12-14 15:09:15-05:00  676494179216805888   \n",
       "\n",
       "                                           statusSource  \\\n",
       "0     <a href=\"http://twitter.com/download/android\" ...   \n",
       "1     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "3     <a href=\"http://twitter.com/download/android\" ...   \n",
       "4     <a href=\"http://twitter.com/download/android\" ...   \n",
       "5     <a href=\"http://twitter.com/download/android\" ...   \n",
       "6     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "7     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "8     <a href=\"http://twitter.com/download/android\" ...   \n",
       "9     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "10    <a href=\"http://twitter.com/download/android\" ...   \n",
       "11    <a href=\"http://twitter.com/download/android\" ...   \n",
       "12    <a href=\"http://twitter.com/download/android\" ...   \n",
       "13    <a href=\"http://twitter.com/download/android\" ...   \n",
       "14    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "15    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "16    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "17    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "18    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "19    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "20    <a href=\"http://twitter.com/download/android\" ...   \n",
       "21    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "22    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "23    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "24    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "25    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "26    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "27    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "28    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "29    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "...                                                 ...   \n",
       "1354  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1355  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1356  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1357  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1358  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1359  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1360  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1361  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1362  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1363  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1364  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1365  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1366  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1367  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1368  <a href=\"http://twitter.com/download/android\" ...   \n",
       "1369  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1370  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1371  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1372  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1373  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1374  <a href=\"http://twitter.com/download/android\" ...   \n",
       "1377  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1378  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1379  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1380  <a href=\"http://twitter.com/download/android\" ...   \n",
       "1381  <a href=\"http://twitter.com/download/android\" ...   \n",
       "1382  <a href=\"http://twitter.com/download/android\" ...   \n",
       "1383  <a href=\"http://twitter.com/download/android\" ...   \n",
       "1388  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1389  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                   text   device  \\\n",
       "0     My economic policy speech will be carried live...  Android   \n",
       "1     Join me in Fayetteville, North Carolina tomorr...   iPhone   \n",
       "2     #ICYMI: \"Will Media Apologize to Trump?\" https...   iPhone   \n",
       "3     Michael Morell, the lightweight former Acting ...  Android   \n",
       "4     The media is going crazy. They totally distort...  Android   \n",
       "5     I see where Mayor Stephanie Rawlings-Blake of ...  Android   \n",
       "6     Thank you Windham, New Hampshire! #TrumpPence1...   iPhone   \n",
       "7     .@Larry_Kudlow - 'Donald Trump Is the middle-c...   iPhone   \n",
       "8     I am not just running against Crooked Hillary ...  Android   \n",
       "9     #CrookedHillary is not fit to be our next pres...   iPhone   \n",
       "10    Heading to New Hampshire - will be talking abo...  Android   \n",
       "11    Anybody whose mind \"SHORT CIRCUITS\" is not fit...  Android   \n",
       "12    Crooked Hillary said loudly, and for the world...  Android   \n",
       "13    Hillary Clinton is being badly criticized for ...  Android   \n",
       "14    Good luck #TeamUSA\\n#OpeningCeremony #Rio2016 ...   iPhone   \n",
       "15    'Trump is right about violent crime: Its on t...   iPhone   \n",
       "16    Thank you Green Bay, Wisconsin! Governor @Mike...   iPhone   \n",
       "17    Thank you Des Moines, Iowa! Governor @Mike_Pen...   iPhone   \n",
       "18        #MakeAmericaSafeAgain https://t.co/5yuLKyh8Q6   iPhone   \n",
       "19    Hillary Clinton has bad judgment and is unfit ...   iPhone   \n",
       "20    The plane I saw on television was the hostage ...  Android   \n",
       "21    President Obama refuses to answer question abo...   iPhone   \n",
       "22    Obama's disastrous judgment gave us ISIS, rise...   iPhone   \n",
       "23    President Obama should ask the DNC about how t...   iPhone   \n",
       "24    See you tomorrow w/ Gov. @Mike_Pence, Iowa &am...   iPhone   \n",
       "25    Thank you Portland, Maine! \\n#MakeAmericaGreat...   iPhone   \n",
       "26    Happy 226th Birthday to the United States Coas...   iPhone   \n",
       "27    Great meeting all of you. This group knocked o...   iPhone   \n",
       "28    Looking forward to IA &amp; WI with Gov. Pence...   iPhone   \n",
       "29    Thank you Jacksonville, Florida!\\n#MakeAmerica...   iPhone   \n",
       "...                                                 ...      ...   \n",
       "1354  A wonderful article by a writer who truly gets...   iPhone   \n",
       "1355  Is Cruz honest? He is in bed w/ Wall St. &amp;...   iPhone   \n",
       "1356  Cruz did not renounce his Canadian citizenship...   iPhone   \n",
       "1357  Cruz says I supported TARP, which gave $25 mil...   iPhone   \n",
       "1358  The only reason irrelevant @GlennBeck doesn't ...   iPhone   \n",
       "1359  .@BrentBozell, one of the National Review ligh...   iPhone   \n",
       "1360  Wow! Ted Cruz received $487K in campaign contr...   iPhone   \n",
       "1361  Departing NH now- great morning with record cr...   iPhone   \n",
       "1362  Greatly dishonest of @TedCruz to file a financ...   iPhone   \n",
       "1363  When will @TedCruz give all the New York based...   iPhone   \n",
       "1364  Everybody that loves the people of New York, a...   iPhone   \n",
       "1365  If Ted Cruz is so opposed to gay marriage, why...   iPhone   \n",
       "1366  Ted is the ultimate hypocrite. Says one thing ...   iPhone   \n",
       "1367  Great new numbers. Thank you! \\n#MakeAmericaGr...   iPhone   \n",
       "1368  Ted Cruz purposely, and illegally, did not lis...  Android   \n",
       "1369  #FoxNews Poll - THANK YOU!\\n#MakeAmericaGreatA...   iPhone   \n",
       "1370  #MakeAmericaGreatAgain #Trump2016 https://t.co...   iPhone   \n",
       "1371  Love seeing union &amp; non-union members alik...   iPhone   \n",
       "1372  I hope all workers demand that their @Teamster...   iPhone   \n",
       "1373  On my way to South Carolina. Big Crowd--- look...   iPhone   \n",
       "1374  Hank Greenberg, formerly of AIG, gave $10 mill...  Android   \n",
       "1377  Happy New Year from #MarALago! Thank you to my...   iPhone   \n",
       "1378      #HappyNewYearAmerica! https://t.co/EeQb8PDrUe   iPhone   \n",
       "1379  HAPPY NEW YEAR &amp; THANK YOU! https://t.co/Y...   iPhone   \n",
       "1380  The Phoenix V.A., it has just been reported, i...  Android   \n",
       "1381  The same people that said I wouldn't run, or t...  Android   \n",
       "1382  .@chucktodd is so dishonest in his reporting.....  Android   \n",
       "1383  @CNN just announced that TRUMP was #1 story of...  Android   \n",
       "1388  Another great accolade for @TrumpGolf. Highly ...   iPhone   \n",
       "1389  Record of Health: https://t.co/ZDDDawwYVl\\n#Ma...   iPhone   \n",
       "\n",
       "           raw_tweet_time  tweet_hour quoted          picture  \n",
       "0     2016-08-08 15:20:44          11     No  No picture/link  \n",
       "1     2016-08-08 13:28:20           9     No  No picture/link  \n",
       "2     2016-08-08 00:05:54          20     No  No picture/link  \n",
       "3     2016-08-07 23:09:08          19     No  No picture/link  \n",
       "4     2016-08-07 21:31:46          17     No  No picture/link  \n",
       "5     2016-08-07 13:49:29           9     No  No picture/link  \n",
       "6     2016-08-07 02:19:37          22     No  No picture/link  \n",
       "7     2016-08-07 02:03:39          22     No  No picture/link  \n",
       "8     2016-08-07 01:53:45          21     No  No picture/link  \n",
       "9     2016-08-06 20:04:08          16     No  No picture/link  \n",
       "10    2016-08-06 18:11:50          14     No  No picture/link  \n",
       "11    2016-08-06 14:48:14          10     No  No picture/link  \n",
       "12    2016-08-06 14:24:43          10     No  No picture/link  \n",
       "13    2016-08-06 11:53:00           7     No  No picture/link  \n",
       "14    2016-08-06 03:59:08          23     No  No picture/link  \n",
       "15    2016-08-06 02:57:11          22     No  No picture/link  \n",
       "16    2016-08-06 02:44:55          22     No  No picture/link  \n",
       "17    2016-08-05 22:42:08          18     No  No picture/link  \n",
       "18    2016-08-05 20:03:29          16     No  No picture/link  \n",
       "19    2016-08-05 13:08:35           9     No  No picture/link  \n",
       "20    2016-08-05 10:39:27           6     No  No picture/link  \n",
       "21    2016-08-05 02:19:22          22     No  No picture/link  \n",
       "22    2016-08-05 02:19:08          22     No  No picture/link  \n",
       "23    2016-08-05 02:18:18          22     No  No picture/link  \n",
       "24    2016-08-05 02:16:20          22     No  No picture/link  \n",
       "25    2016-08-04 22:42:13          18     No  No picture/link  \n",
       "26    2016-08-04 19:23:41          15     No  No picture/link  \n",
       "27    2016-08-04 19:16:00          15     No  No picture/link  \n",
       "28    2016-08-04 15:17:01          11     No  No picture/link  \n",
       "29    2016-08-04 02:27:52          22     No  No picture/link  \n",
       "...                   ...         ...    ...              ...  \n",
       "1354  2016-01-23 03:08:21          22     No  No picture/link  \n",
       "1355  2016-01-23 02:08:41          21     No  No picture/link  \n",
       "1356  2016-01-23 02:04:23          21     No  No picture/link  \n",
       "1357  2016-01-23 01:34:26          20     No  No picture/link  \n",
       "1358  2016-01-23 01:33:17          20     No  No picture/link  \n",
       "1359  2016-01-23 01:32:32          20     No  No picture/link  \n",
       "1360  2016-01-16 19:32:40          14     No  No picture/link  \n",
       "1361  2016-01-16 18:31:39          13     No  No picture/link  \n",
       "1362  2016-01-16 18:26:54          13     No  No picture/link  \n",
       "1363  2016-01-16 18:23:26          13     No  No picture/link  \n",
       "1364  2016-01-16 18:22:40          13     No  No picture/link  \n",
       "1365  2016-01-16 18:21:03          13     No  No picture/link  \n",
       "1366  2016-01-16 16:11:28          11     No  No picture/link  \n",
       "1367  2016-01-16 13:42:54           8     No  No picture/link  \n",
       "1368  2016-01-16 13:31:10           8     No  No picture/link  \n",
       "1369  2016-01-08 23:12:35          18     No  No picture/link  \n",
       "1370  2016-01-08 22:36:09          17     No  No picture/link  \n",
       "1371  2016-01-08 22:09:20          17     No  No picture/link  \n",
       "1372  2016-01-08 22:03:35          17     No  No picture/link  \n",
       "1373  2016-01-08 21:20:02          16     No  No picture/link  \n",
       "1374  2016-01-08 15:57:17          10     No  No picture/link  \n",
       "1377  2016-01-01 06:07:28           1     No  No picture/link  \n",
       "1378  2016-01-01 05:18:23           0     No  No picture/link  \n",
       "1379  2016-01-01 03:25:27          22     No  No picture/link  \n",
       "1380  2015-12-26 13:00:26           8     No  No picture/link  \n",
       "1381  2015-12-25 21:49:30          16     No  No picture/link  \n",
       "1382  2015-12-25 21:42:39          16     No  No picture/link  \n",
       "1383  2015-12-25 21:11:23          16     No  No picture/link  \n",
       "1388  2015-12-14 21:11:12          16     No  No picture/link  \n",
       "1389  2015-12-14 20:09:15          15     No  No picture/link  \n",
       "\n",
       "[1175 rows x 9 columns]"
      ]
     },
     "execution_count": 371,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfPict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 378,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# capture just the non-quoted tweets\n",
    "dfPict = dfTrump.loc[dfTrump.quoted == 'No', :]\n",
    "\n",
    "dfPict.loc[:,'picture'] = \"No picture/link\"\n",
    "dfPict.loc[dfPict.text.str.contains('t.co'), 'picture'] = 'Picture/link'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 379,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>created</th>\n",
       "      <th>id</th>\n",
       "      <th>statusSource</th>\n",
       "      <th>text</th>\n",
       "      <th>device</th>\n",
       "      <th>raw_tweet_time</th>\n",
       "      <th>tweet_hour</th>\n",
       "      <th>quoted</th>\n",
       "      <th>picture</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-08-08 11:20:44-04:00</td>\n",
       "      <td>762669882571980801</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/android\" ...</td>\n",
       "      <td>My economic policy speech will be carried live...</td>\n",
       "      <td>Android</td>\n",
       "      <td>2016-08-08 15:20:44</td>\n",
       "      <td>11</td>\n",
       "      <td>No</td>\n",
       "      <td>No picture/link</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-08-08 09:28:20-04:00</td>\n",
       "      <td>762641595439190016</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Join me in Fayetteville, North Carolina tomorr...</td>\n",
       "      <td>iPhone</td>\n",
       "      <td>2016-08-08 13:28:20</td>\n",
       "      <td>9</td>\n",
       "      <td>No</td>\n",
       "      <td>Picture/link</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    created                  id  \\\n",
       "0 2016-08-08 11:20:44-04:00  762669882571980801   \n",
       "1 2016-08-08 09:28:20-04:00  762641595439190016   \n",
       "\n",
       "                                        statusSource  \\\n",
       "0  <a href=\"http://twitter.com/download/android\" ...   \n",
       "1  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                text   device  \\\n",
       "0  My economic policy speech will be carried live...  Android   \n",
       "1  Join me in Fayetteville, North Carolina tomorr...   iPhone   \n",
       "\n",
       "        raw_tweet_time  tweet_hour quoted          picture  \n",
       "0  2016-08-08 15:20:44          11     No  No picture/link  \n",
       "1  2016-08-08 13:28:20           9     No     Picture/link  "
      ]
     },
     "execution_count": 379,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfPict.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>picture</th>\n",
       "      <th>device</th>\n",
       "      <th>No picture/link</th>\n",
       "      <th>Picture/link</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Android</td>\n",
       "      <td>543</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>iPhone</td>\n",
       "      <td>199</td>\n",
       "      <td>423</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "picture   device  No picture/link  Picture/link\n",
       "0        Android              543            10\n",
       "1         iPhone              199           423"
      ]
     },
     "execution_count": 381,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ = pd.crosstab(dfPict.device, dfPict.picture)\n",
    "df_.reset_index(inplace=True)\n",
    "df_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 603,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f879e0835c0>"
      ]
     },
     "execution_count": 603,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HDm23DwZOqao7quoa4Apgv3HUKUmS+me+5xAtrqqVAFV1E7C4bd8RuG5gvxva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\nJEm9ZyCSJEm99/8B6ALntuSPYb8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f879e108a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6,6))\n",
    "df_ = pd.crosstab(dfPict.device, dfPict.picture)\n",
    "df_.reset_index(inplace=True)\n",
    "ax.bar([x for x in df_.index], df_['No picture/link'], width = 0.4, color = \"#FC4F30\", label='No picture/link')\n",
    "ax.bar([x+0.5 for x in df_.index], df_['Picture/link'], width = 0.4, color='#30A2DA', label = 'Picture/link')\n",
    "ax.set(xticks = [x + 0.5 for x in df_.index], \n",
    "       xticklabels=['Android', 'iPhone'],\n",
    "       ylabel='Number of tweets',\n",
    "       axis_bgcolor = 'white');\n",
    "ax.legend(loc=(1.05, 0.5), frameon=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we do a comparisson of words in the tweets.  For this we remove all twitter hyperlinks, tweets contianing ^\" etc.  We also want to remove stop words.\n",
    "\n",
    "We want to keep all the words in context so we're going to create a new exploded dataframe where we repeat each row (tweet) for every row in the tweet.\n",
    "\n",
    "This code is a bit messy so see the comments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 606,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import re   # regex library\n",
    "from nltk.corpus import stopwords    # a list of stop words\n",
    "\n",
    "# first, remove all string containing ^\"\n",
    "dfWords = dfTrump.loc[~dfTrump.text.str.contains('^\"'), :]\n",
    "\n",
    "# next, remove all twitter hyperlinks\n",
    "dfWords.text = dfWords.text.apply(lambda x: re.sub(r\"https://t.co/[A-Za-z\\\\d]+|&amp;\", '', x, flags=re.MULTILINE))\n",
    "\n",
    "# create a temporaty dataframe to explode the rows into\n",
    "dfTemp = pd.DataFrame()\n",
    "\n",
    "# iterate over each row in the dataframe of tweets\n",
    "for i, row in dfWords.iterrows():\n",
    "    \n",
    "    # capture the row and converti it to a data frame\n",
    "    df_ = pd.DataFrame(row).T\n",
    "    \n",
    "    # create a list of the words in the tweet's text, removing stop words\n",
    "    stop_words = stopwords.words('english')\n",
    "    stop_words.append(['i', 'thank', 'the', '-'])\n",
    "    text = [word.lower() for word in df_.text.values[0].split() if word.lower() not in stop_words]\n",
    "    \n",
    "    # iterate over all the tweet's words, and add a new row to the data frame containing all the tweet\n",
    "    # information for each word\n",
    "    \n",
    "    for word in text:\n",
    "        df_['word'] = word\n",
    "        if len(dfTemp) > 0:\n",
    "            dfTemp = pd.concat([dfTemp, df_], ignore_index=True, axis=0)\n",
    "        else:\n",
    "            dfTemp = df_\n",
    "\n",
    "dfWords = dfTemp.copy(deep=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 607,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12548"
      ]
     },
     "execution_count": 607,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dfWords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 608,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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8iFdeeQXnzp1DmzZt8NFHHyE6Ohpff/01UlNTERUVhblz5wIAxo0bh2XLluHk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\n29YAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f879e02fa90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6,6), facecolor='white')\n",
    "df_ = dfWords.groupby('word').count().sort_values('created', ascending=False).iloc[:20, :]\n",
    "df_.reset_index(inplace=True)\n",
    "y_ticks = [y for y in df_.index[::-1]]\n",
    "ax.barh(y_ticks, df_.created)\n",
    "ax.set(yticks = y_ticks,\n",
    "       yticklabels = df_.word,\n",
    "       axis_bgcolor = 'white');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 609,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import math\n",
    "dfWordsPivot = pd.pivot_table(dfWords.loc[:, ['created', 'word', 'device']], \n",
    "                             columns='word', index='device', aggfunc='count', fill_value=0)\n",
    "                              \n",
    "dfWordsPivot.columns = dfWordsPivot.columns.droplevel()\n",
    "dfWordsPivot = dfWordsPivot.T\n",
    "dfWordsPivot = dfWordsPivot.loc[dfWordsPivot.sum(axis=1)>5, :]   # get words that have been used at least 5 times\n",
    "dfWordsPivot = dfWordsPivot + 1  # add one to every value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 610,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>device</th>\n",
       "      <th>Android</th>\n",
       "      <th>iPhone</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>word</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>#americafirst</th>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#crookedhillary</th>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#fitn</th>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#imwithyou</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#inprimary</th>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "device           Android  iPhone\n",
       "word                            \n",
       "#americafirst          1      28\n",
       "#crookedhillary        1      17\n",
       "#fitn                  1       9\n",
       "#imwithyou             1      21\n",
       "#inprimary             1      11"
      ]
     },
     "execution_count": 610,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfWordsPivot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 611,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "dfWordsPivot = dfWordsPivot.loc[~dfWordsPivot.index.str.contains('@'), :]\n",
    "dfWordsPivot['logratio'] = dfWordsPivot.apply(lambda x: math.log2((x.Android/dfWordsPivot.Android.sum()) / (x.iPhone/dfWordsPivot.iPhone.sum())), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 612,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>word</th>\n",
       "      <th>created</th>\n",
       "      <th>id</th>\n",
       "      <th>statusSource</th>\n",
       "      <th>text</th>\n",
       "      <th>device</th>\n",
       "      <th>raw_tweet_time</th>\n",
       "      <th>tweet_hour</th>\n",
       "      <th>quoted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>again!</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>get</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>you!</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>ted</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>would</td>\n",
       "      <td>43</td>\n",
       "      <td>43</td>\n",
       "      <td>43</td>\n",
       "      <td>43</td>\n",
       "      <td>43</td>\n",
       "      <td>43</td>\n",
       "      <td>43</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      word  created  id  statusSource  text  device  raw_tweet_time  \\\n",
       "15  again!       48  48            48    48      48              48   \n",
       "16     get       47  47            47    47      47              47   \n",
       "17    you!       47  47            47    47      47              47   \n",
       "18     ted       45  45            45    45      45              45   \n",
       "19   would       43  43            43    43      43              43   \n",
       "\n",
       "    tweet_hour  quoted  \n",
       "15          48      48  \n",
       "16          47      47  \n",
       "17          47      47  \n",
       "18          45      45  \n",
       "19          43      43  "
      ]
     },
     "execution_count": 612,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 613,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f879db7af28>"
      ]
     },
     "execution_count": 613,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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WrYvMzMwyuVXIypUr4e/vr9YEnDlzBvPmzSvyAoyXadSokdrPN/D0QqKSeN3PlUKhgI2N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\nTcmpD0oeuyReCKG5pMirguqILXtcwcHBu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5k9ezZhYWG8+eabhISE8Pnnnze4Uln/HCdP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\nZgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f879df4b470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6,12), facecolor='white')\n",
    "df_ = dfWordsPivot.sort_values('logratio', ascending=True).reset_index()\n",
    "df_ = df_.loc[abs(df_.logratio) > 2.2, :]\n",
    "df_.reset_index(inplace=True)\n",
    "y_ticks = [y+0.5 for y in df_.index]\n",
    "ax.barh(df_.loc[df_.logratio > 0, :].index, df_.loc[df_.logratio > 0, 'logratio'], label = 'Android', color = \"#FC4F30\")\n",
    "ax.barh(df_.loc[df_.logratio < 0, :].index, df_.loc[df_.logratio < 0, 'logratio'], label = 'iPhone', color='#30A2DA')\n",
    "ax.set(yticks=y_ticks,\n",
    "      yticklabels = df_.word,\n",
    "      ylim=(min(y_ticks), max(y_ticks)+0.5),\n",
    "      axis_bgcolor = 'white',\n",
    "      title='Words most likely from an Android or iPhone');\n",
    "ax.legend(loc=(1.05, 0.5), frameon=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sentiment analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is using the NRC word-asociation lexicon. http://www.saifmohammad.com/WebDocs/README-NRC-Lex.txt\n",
    "\n",
    "The NRC emotion lexicon is a list of words and their associations with\n",
    "eight emotions (anger, fear, anticipation, trust, surprise, sadness,\n",
    "joy, and disgust) and two sentiments (negative and positive)\n",
    "\n",
    "**FORMAT**\n",
    "\n",
    "Each line has the following format:\n",
    "TargetWord<tab>AffectCategory<tab>AssociationFlag\n",
    "\n",
    "TargetWord is a word for which emotion associations are provided.\n",
    "\n",
    "AffectCategory is one of eight emotions (anger, fear, anticipation,\n",
    "trust, surprise, sadness, joy, or disgust) or one of two polarities\n",
    "(negative or positive).\n",
    "\n",
    "AssociationFlag has one of two possible values: 0 or 1.  0 indicates\n",
    "that the target word has no association with affect category,\n",
    "whereas 1 indicates an association.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 614,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>AffectCategory</th>\n",
       "      <th>anger</th>\n",
       "      <th>anticipation</th>\n",
       "      <th>disgust</th>\n",
       "      <th>fear</th>\n",
       "      <th>joy</th>\n",
       "      <th>negative</th>\n",
       "      <th>positive</th>\n",
       "      <th>sadness</th>\n",
       "      <th>surprise</th>\n",
       "      <th>trust</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TargetWord</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>aback</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>abacus</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>abandon</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>abandoned</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>abandonment</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "AffectCategory  anger  anticipation  disgust  fear  joy  negative  positive  \\\n",
       "TargetWord                                                                    \n",
       "aback               0             0        0     0    0         0         0   \n",
       "abacus              0             0        0     0    0         0         0   \n",
       "abandon             0             0        0     1    0         1         0   \n",
       "abandoned           1             0        0     1    0         1         0   \n",
       "abandonment         1             0        0     1    0         1         0   \n",
       "\n",
       "AffectCategory  sadness  surprise  trust  \n",
       "TargetWord                                \n",
       "aback                 0         0      0  \n",
       "abacus                0         0      1  \n",
       "abandon               1         0      0  \n",
       "abandoned             1         0      0  \n",
       "abandonment           1         1      0  "
      ]
     },
     "execution_count": 614,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfNRC = pd.read_csv('./NRC-emotion-lexicon-wordlevel-alphabetized-v0.92.txt', sep='\\t', skiprows=45)\n",
    "dfNRC.columns = ['TargetWord', 'AffectCategory', 'AssociationFlag']\n",
    "dfNRC = pd.pivot_table(dfNRC, index='TargetWord', columns='AffectCategory', values='AssociationFlag', fill_value=0)\n",
    "dfNRC.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 615,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Android</th>\n",
       "      <th>iPhone</th>\n",
       "      <th>logratio</th>\n",
       "      <th>anger</th>\n",
       "      <th>anticipation</th>\n",
       "      <th>disgust</th>\n",
       "      <th>fear</th>\n",
       "      <th>joy</th>\n",
       "      <th>negative</th>\n",
       "      <th>positive</th>\n",
       "      <th>sadness</th>\n",
       "      <th>surprise</th>\n",
       "      <th>trust</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>allowed</th>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>1.487718</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>back</th>\n",
       "      <td>11</td>\n",
       "      <td>17</td>\n",
       "      <td>-0.947668</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bad</th>\n",
       "      <td>39</td>\n",
       "      <td>11</td>\n",
       "      <td>1.506334</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>badly</th>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>3.265325</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beat</th>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>2.417329</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Android  iPhone  logratio  anger  anticipation  disgust  fear  joy  \\\n",
       "allowed        7       2  1.487718      0             0        0     0    0   \n",
       "back          11      17 -0.947668      0             0        0     0    0   \n",
       "bad           39      11  1.506334      1             0        1     1    0   \n",
       "badly         12       1  3.265325      0             0        0     0    0   \n",
       "beat          20       3  2.417329      0             0        0     0    0   \n",
       "\n",
       "         negative  positive  sadness  surprise  trust  \n",
       "allowed         0         0        0         0      0  \n",
       "back            0         0        0         0      0  \n",
       "bad             1         0        1         0      0  \n",
       "badly           1         0        1         0      0  \n",
       "beat            0         0        0         0      0  "
      ]
     },
     "execution_count": 615,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfWordsPivot = dfWordsPivot.merge(dfNRC, left_index=True, right_index=True, how='inner')\n",
    "dfWordsPivot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 625,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f879ed003c8>"
      ]
     },
     "execution_count": 625,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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NaOhorzJnIsLqbNU90qXMmfTF1Hlc+5Pp13x6T/J5QCqVC2tw88++wiMBmjCuL19ApuU6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\niFzx/wOXIO2BgMkSpgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f879e0ebba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "clrs = [\"#a0e3b7\", \"#26496d\", \"#32e195\", \"#3337a6\", \"#d1bfec\", \"#88075f\", \"#f59ae7\", \"#338821\", \"#48b6ea\", \"#4115d0\"]\n",
    "fig, ax = plt.subplots(figsize=(6,6))\n",
    "ax.scatter(dfWordsPivot.anger, dfWordsPivot.logratio, color = clrs[0])\n",
    "ax.scatter(dfWordsPivot.anticipation+0.1, dfWordsPivot.logratio, color = clrs[1])\n",
    "ax.scatter(dfWordsPivot.disgust+0.2, dfWordsPivot.logratio, color = clrs[2])\n",
    "ax.scatter(dfWordsPivot.fear+0.3, dfWordsPivot.logratio, color = clrs[3])\n",
    "ax.scatter(dfWordsPivot.joy+0.4, dfWordsPivot.logratio, color = clrs[4])\n",
    "ax.scatter(dfWordsPivot.negative+0.5, dfWordsPivot.logratio, color = clrs[5])\n",
    "ax.scatter(dfWordsPivot.positive+0.6, dfWordsPivot.logratio, color = clrs[6])\n",
    "ax.scatter(dfWordsPivot.sadness+0.7, dfWordsPivot.logratio, color = clrs[7])\n",
    "ax.scatter(dfWordsPivot.surprise+0.8, dfWordsPivot.logratio, color = clrs[8])\n",
    "ax.scatter(dfWordsPivot.trust+0.9, dfWordsPivot.logratio, color = clrs[9])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [Root]",
   "language": "python",
   "name": "Python [Root]"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
 }