18. On-Line Video Challenge.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.simplefilter('ignore')\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>video_id</th>\n",
       "      <th>count</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2303</td>\n",
       "      <td>22</td>\n",
       "      <td>2015-01-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1193</td>\n",
       "      <td>54854</td>\n",
       "      <td>2015-01-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1219</td>\n",
       "      <td>1788779</td>\n",
       "      <td>2015-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1472</td>\n",
       "      <td>234</td>\n",
       "      <td>2015-01-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2947</td>\n",
       "      <td>14407</td>\n",
       "      <td>2015-01-08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   video_id    count       date\n",
       "0      2303       22 2015-01-07\n",
       "1      1193    54854 2015-01-12\n",
       "2      1219  1788779 2015-01-03\n",
       "3      1472      234 2015-01-04\n",
       "4      2947    14407 2015-01-08"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count = pd.read_csv('./data/online_videos/video_count.csv', parse_dates=['date'])\n",
    "count.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 41775 entries, 0 to 41774\n",
      "Data columns (total 3 columns):\n",
      "video_id    41775 non-null int64\n",
      "count       41775 non-null int64\n",
      "date        41775 non-null datetime64[ns]\n",
      "dtypes: datetime64[ns](1), int64(2)\n",
      "memory usage: 979.2 KB\n"
     ]
    }
   ],
   "source": [
    "count.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>video_id</th>\n",
       "      <th>video_length</th>\n",
       "      <th>video_language</th>\n",
       "      <th>video_upload_date</th>\n",
       "      <th>video_quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2374</td>\n",
       "      <td>1760</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-06</td>\n",
       "      <td>480p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1897</td>\n",
       "      <td>489</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-10</td>\n",
       "      <td>720p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2386</td>\n",
       "      <td>1273</td>\n",
       "      <td>Es</td>\n",
       "      <td>2014-12-05</td>\n",
       "      <td>480p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2912</td>\n",
       "      <td>986</td>\n",
       "      <td>Es</td>\n",
       "      <td>2014-12-10</td>\n",
       "      <td>240p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2432</td>\n",
       "      <td>1050</td>\n",
       "      <td>Other</td>\n",
       "      <td>2014-12-10</td>\n",
       "      <td>480p</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   video_id  video_length video_language video_upload_date video_quality\n",
       "0      2374          1760             Cn        2014-12-06          480p\n",
       "1      1897           489             Cn        2014-12-10          720p\n",
       "2      2386          1273             Es        2014-12-05          480p\n",
       "3      2912           986             Es        2014-12-10          240p\n",
       "4      2432          1050          Other        2014-12-10          480p"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature = pd.read_csv('./data/online_videos/video_features.csv', \n",
    "                      parse_dates=['video_upload_date'])\n",
    "feature.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2785 entries, 0 to 2784\n",
      "Data columns (total 5 columns):\n",
      "video_id             2785 non-null int64\n",
      "video_length         2785 non-null int64\n",
      "video_language       2785 non-null object\n",
      "video_upload_date    2785 non-null datetime64[ns]\n",
      "video_quality        2785 non-null object\n",
      "dtypes: datetime64[ns](1), int64(2), object(2)\n",
      "memory usage: 108.9+ KB\n"
     ]
    }
   ],
   "source": [
    "feature.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>video_id</th>\n",
       "      <th>count</th>\n",
       "      <th>date</th>\n",
       "      <th>length</th>\n",
       "      <th>language</th>\n",
       "      <th>upload_date</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2303</td>\n",
       "      <td>22</td>\n",
       "      <td>2015-01-07</td>\n",
       "      <td>1071</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-10</td>\n",
       "      <td>1080p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1193</td>\n",
       "      <td>54854</td>\n",
       "      <td>2015-01-12</td>\n",
       "      <td>770</td>\n",
       "      <td>Other</td>\n",
       "      <td>2014-12-07</td>\n",
       "      <td>720p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1219</td>\n",
       "      <td>1788779</td>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>904</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-12</td>\n",
       "      <td>240p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1472</td>\n",
       "      <td>234</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>157</td>\n",
       "      <td>Other</td>\n",
       "      <td>2014-12-10</td>\n",
       "      <td>240p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2947</td>\n",
       "      <td>14407</td>\n",
       "      <td>2015-01-08</td>\n",
       "      <td>446</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-19</td>\n",
       "      <td>480p</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   video_id    count       date  length language upload_date quality\n",
       "0      2303       22 2015-01-07    1071       Cn  2014-12-10   1080p\n",
       "1      1193    54854 2015-01-12     770    Other  2014-12-07    720p\n",
       "2      1219  1788779 2015-01-03     904       Cn  2014-12-12    240p\n",
       "3      1472      234 2015-01-04     157    Other  2014-12-10    240p\n",
       "4      2947    14407 2015-01-08     446       Cn  2014-12-19    480p"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# merge data\n",
    "data = pd.merge(left=count, right=feature, on='video_id', how='left')\n",
    "data = data.rename(columns={'video_length': 'length', \n",
    "                            'video_language': 'language', \n",
    "                            'video_upload_date': 'upload_date', \n",
    "                            'video_quality': 'quality'})\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Processing and Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>video_id</th>\n",
       "      <th>count</th>\n",
       "      <th>date</th>\n",
       "      <th>length</th>\n",
       "      <th>language</th>\n",
       "      <th>upload_date</th>\n",
       "      <th>quality</th>\n",
       "      <th>interval</th>\n",
       "      <th>dayofweek</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2303</td>\n",
       "      <td>22</td>\n",
       "      <td>2015-01-07</td>\n",
       "      <td>1071</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-10</td>\n",
       "      <td>1080p</td>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1193</td>\n",
       "      <td>54854</td>\n",
       "      <td>2015-01-12</td>\n",
       "      <td>770</td>\n",
       "      <td>Other</td>\n",
       "      <td>2014-12-07</td>\n",
       "      <td>720p</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1219</td>\n",
       "      <td>1788779</td>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>904</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-12</td>\n",
       "      <td>240p</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1472</td>\n",
       "      <td>234</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>157</td>\n",
       "      <td>Other</td>\n",
       "      <td>2014-12-10</td>\n",
       "      <td>240p</td>\n",
       "      <td>25</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2947</td>\n",
       "      <td>14407</td>\n",
       "      <td>2015-01-08</td>\n",
       "      <td>446</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-19</td>\n",
       "      <td>480p</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   video_id    count       date  length language upload_date quality  \\\n",
       "0      2303       22 2015-01-07    1071       Cn  2014-12-10   1080p   \n",
       "1      1193    54854 2015-01-12     770    Other  2014-12-07    720p   \n",
       "2      1219  1788779 2015-01-03     904       Cn  2014-12-12    240p   \n",
       "3      1472      234 2015-01-04     157    Other  2014-12-10    240p   \n",
       "4      2947    14407 2015-01-08     446       Cn  2014-12-19    480p   \n",
       "\n",
       "   interval  dayofweek  \n",
       "0        28          2  \n",
       "1        36          0  \n",
       "2        22          5  \n",
       "3        25          6  \n",
       "4        20          3  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# extract time interval information\n",
    "data['interval'] = (data['date'] - data['upload_date']).apply(lambda x: x.days)\n",
    "\n",
    "# extract video play day of week\n",
    "data['dayofweek'] = data['date'].apply(lambda x: x.dayofweek)\n",
    "\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of count\n",
    "warnings.filterwarnings('ignore')\n",
    "hist_kws={'histtype': 'bar', 'edgecolor':'black', 'alpha': 0.2}\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8, 4))\n",
    "sns.distplot(data['count'], ax=ax, hist_kws=hist_kws)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of length\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "sns.distplot(data['length'], ax=ax, hist_kws=hist_kws)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of length\n",
    "sns.jointplot(x='length', y='count', data=data, kind='scatter', size=6)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of language\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "sns.countplot(x='language', data=data, ax=ax[0])\n",
    "ax[0].set_title('Count Plot of language', fontsize=16)\n",
    "\n",
    "sns.barplot(x='language', y='count', data=data, ax=ax[1])\n",
    "ax[1].set_title('Count vs. language', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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szScI35zvTNi225DkEd39I0n+LsmLkqSqHp7k1CQ/NOq8oaoOqqqDkvxWJpPHhyd51iibJK9M8uoxCbw1yel78V4AANg1xyf5++7+bJKTk1w44hcmOWUcn5zkop64KsmhVfXQJCcm2dDd27r71kzmkOvGtUO6+wPd3UkumtPWfH0AALCAvZYg7O73J9k2J/Zn3X3HOL0qyZHj+OQkF3f317v700k2ZfJr8TFJNnX39d39jSQXJzl5LCV5UpK3j/omgQAA+5dTk/z+OH5wd9+cJOPzQSN+RJIbpupsHrGdxTfPE99ZH99WVWdU1caq2rh169Y9uDUAgJVlOd9B+LNJ3jmOd3Vy+IAkt00lG6cnh3djMggAsO+MV7/8VJL/s1DReWK9G/FF6e7zunttd69dvXr1YqsBAKx4y5IgrKr/nOSOJG/dHpqn2JJNDk0GAQD2qZOSfKS7Pz/OPz+WB2d83jLim5McNVXvyCQ3LRA/cp74zvoAALibs846K6eddlrOOuus5R7KfmHVvu5w7EL31CTHj3fHJDueBGYH8S9k8o6aVeMpwunyS+Yx/+mipW6Snfjwr5+23EMAAJbGs/Kd5cVJclmS9UleMT4vnYo/r6ouzmRDktu7++aquiLJf5/amOSEJC/q7m1V9eWqOjbJB5OcluT1C/QBAHA3W7ZsyY033rjcw9hv7NMnCKtqXZIXJvmp7v7q1KXLkpxaVfeqqodlsiPdh5JcnWTN2LH44EzeZXPZSCy+J8nTR32TQACA/UBV3TfJk5P84VT4FUmeXFXXjWuvGPHLk1yfyfun/3eSX0iS7t6W5KWZzAWvTvKSEUuSn0/yxlHn7/OdV9bsqA8AABaw154grKrfT/LEJA+sqs1Jzslk1+J7Jdkw2WckV3X3v+/uT1bVJUmuyWTp8Zndfedo53lJrkhyUJILuvuTo4sXJrm4ql6W5KNJzt9b9wIAwOKMH4EfMCf2xUx2NZ5btpOcuYN2LkhywTzxjUkeMU983j4AAFjYXksQdvez5gnvMInX3S9P8vJ54pdn8uvy3Pj1mexyDAAAAADspuXcxRgAAAAAWGYShAAAAAAwwyQIAQAAAGCGSRACAAAAwAyTIAQAAACAGSZBCAAAAAAzTIIQAAAAAGbYquUeAAAAAKx0Z511VrZs2ZKHPOQhedWrXrXcw4El9b9++R3LPYRddtsXvvLtzwNt/M/7jZ9c8jYlCAEAAGAv27JlS2688cblHgbAvCwxBgAAAIAZJkEIAAAAADNMghAAAAAAZpgEIQAAAADMMAlCAAAAAJhhEoQAAAAAMMMkCAEAAABghq1a7gEAAABL76yzzsqWLVvykIc8JK961auWezgAwH5MghAAAFagLVu25MYbb1zuYQAABwAJQgAAAABmyv0OPuQun7NOghAAAACAmXLcP3vacg9hv2KTEgAAAACYYRKEAAAAADDDLDEGAADggHLc649b7iHssoNvOzj3yD1yw203HHDj/6vn/9VyD2G/YYd4VioJQgAAAIBFsEM8K5UlxgAAAAAwwzxBCAAAC3jMf7pouYewy+7/hS/noCSf+8KXD6jxf/jXT1vuIQDAzPEEIQAAAADMMAlCAAAAAJhhEoQAAAAAMMMkCAEAAABghkkQAgAAAMAMs4sxAAAAsM+97/FPWO4h7LJ/XHVQUpV/3Lz5gBv/E97/vuUeAvsxTxACAAAAwAyTIAQAAACAGSZBCAAAAAAzzDsIAQBgBfrWwfe7yycAwI5IEAIAwAr0lTUnLPcQgCl938638q30fXu5hwJwNxKEAAAAsJd987hvLvcQAHbIOwgBAAAAYIZJEAIAAADADJMgBABgSVTVoVX19qr626q6tqoeV1WHV9WGqrpufB42ylZVva6qNlXVx6vq0VPtrB/lr6uq9VPxx1TVJ0ad11VVjfi8fQAAsDgShAAALJXXJnlXd/9AkkcmuTbJ2Umu7O41Sa4c50lyUpI14++MJOcmk2RfknOSPDbJMUnOmUr4nTvKbq+3bsR31AcALKlDu3N4dw5tm82wskgQAgCwx6rqkCSPT3J+knT3N7r7tiQnJ7lwFLswySnj+OQkF/XEVUkOraqHJjkxyYbu3tbdtybZkGTduHZId3+guzvJRXPamq8PAFhSz77zW3neHXfm2Xd+a7mHAktKghAAgKXwvUm2JnlTVX20qt5YVfdL8uDuvjlJxueDRvkjktwwVX/ziO0svnmeeHbSx11U1RlVtbGqNm7dunX37xQAYIWRIAQAYCmsSvLoJOd296OSfCU7X+pb88R6N+KL1t3ndffa7l67evXqXakKALCiSRACALAUNifZ3N0fHOdvzyRh+PmxPDjj85ap8kdN1T8yyU0LxI+cJ56d9AEAwCJIEAIAsMe6e0uSG6rq+0fo+CTXJLksyfadiNcnuXQcX5bktLGb8bFJbh/Lg69IckJVHTY2JzkhyRXj2per6tixe/Fpc9qarw8AABZh1XIPAACAFeP5Sd5aVQcnuT7JczP5QfqSqjo9yeeSPGOUvTzJU5JsSvLVUTbdva2qXprk6lHuJd29bRz/fJI3J7lPkneOvyR5xQ76gAPeWWedlS1btuQhD3lIXvWqVy33cABYofZagrCqLkjy1CS3dPcjRuzwJG9LcnSSzyR5ZnffOn4Ffm0mk8SvJnlOd39k1Fmf5L+MZl/W3ReO+GPynQni5UleMHa0AwBgGXT3x5KsnefS8fOU7SRn7qCdC5JcME98Y5JHzBP/4nx9wEqwZcuW3Hjjjcs9DABWuL25xPjNSdbNiZ2d5MruXpPkynznxdUnJVkz/s5Icm7y7YTiOUkem+SYJOeMpSYZZc6Yqje3LwAAAABgAXstQdjd70+ybU745CQXjuMLk5wyFb+oJ65Kcuh4wfSJSTZ097buvjXJhiTrxrVDuvsD49fni6baAgAAAAAWaV+/g/DB4wXT6e6bq+pBI35Ekhumym0esZ3FN88Th3l97iU/vNxDmBn/5L9+YrmHAAAAAOyC/WUX45on1rsRn7/xqjOqamNVbdy6detuDhEAAAAAVp59nSD8/FgenPF5y4hvTnLUVLkjk9y0QPzIeeLz6u7zunttd69dvXr1Ht8EAAAAAKwU+zpBeFmS9eN4fZJLp+Kn1cSxSW4fS5GvSHJCVR02Nic5IckV49qXq+rYsQPyaVNtAQAAAACLtNfeQVhVv5/kiUkeWFWbM9mN+BVJLqmq05N8LskzRvHLkzwlyaYkX03y3CTp7m1V9dIkV49yL+nu7Ruf/HwmOyXfJ8k7xx8AAAAAsAv2WoKwu5+1g0vHz1O2k5y5g3YuSHLBPPGNSR6xJ2MEAABmx4G4cd0d2w5Psip3bPvsATd+m9cBHDj2l01KAAAAAIBlIEEIAAAAADNMghAAAAAAZpgEIQAAAADMMAlCAAAAAJhhEoQAAAAAMMMkCAEAAABghkkQAgAAAMAMW7XcAwBg9rzv8U9Y7iHMjCe8/33LPQQA9sAD7/2tJHeMTwDYOyQIAQAA9lO/8iO3LfcQAJgBlhgDAAAAwAyTIAQAAACAGSZBCAAAAAAzTIIQAAAAAGaYBCEAAAAAzDAJQgAAAACYYRKEAAAAADDDJAgBAAAAYIZJEAIAAADADJMgBAAAAIAZJkEIAAAAADNMghAAAAAAZpgEIQAAAADMMAlCAAAAAJhhEoQAAAAAMMMkCAEAAABghkkQAgAAAMAMkyAEAAAAgBkmQQgAAAAAM0yCEAAAAABmmAQhAAAAAMwwCUIAAAAAmGEShAAALJmq+kxVfaKqPlZVG0fs8KraUFXXjc/DRryq6nVVtamqPl5Vj55qZ/0of11VrZ+KP2a0v2nUrZ31AQDAwiQIAQBYav+yu3+0u9eO87OTXNnda5JcOc6T5KQka8bfGUnOTSbJviTnJHlskmOSnDOV8Dt3lN1eb90CfQAAsAAJQgAA9raTk1w4ji9McspU/KKeuCrJoVX10CQnJtnQ3du6+9YkG5KsG9cO6e4PdHcnuWhOW/P1AQDAAiQIAQBYSp3kz6rqw1V1xog9uLtvTpLx+aARPyLJDVN1N4/YzuKb54nvrI9vq6ozqmpjVW3cunXrHtwiAMDKsmq5BwAAwIpyXHffVFUPSrKhqv52J2VrnljvRnxRuvu8JOclydq1axddDwBgpfMEIQAAS6a7bxqftyT5o0zeIfj5sTw44/OWUXxzkqOmqh+Z5KYF4kfOE89O+gAAYAEShAAALImqul9V3X/7cZITkvxNksuSbN+JeH2SS8fxZUlOG7sZH5vk9rE8+IokJ1TVYWNzkhOSXDGufbmqjh27F582p635+gAAYAGWGAMAsFQenOSPJrm7rErye939rqq6OsklVXV6ks8lecYof3mSpyTZlOSrSZ6bJN29rapemuTqUe4l3b1tHP98kjcnuU+Sd46/JHnFDvoAAGABEoQAACyJ7r4+ySPniX8xyfHzxDvJmTto64IkF8wT35jkEYvtAwCAhVliDAAAAAAzTIIQAAAAAGaYBCEAAAAAzDAJQgAAAACYYRKEAAAAADDDJAgBAAAAYIZJEAIAAADADJMgBAAAAIAZtiwJwqr6j1X1yar6m6r6/aq6d1U9rKo+WFXXVdXbqurgUfZe43zTuH70VDsvGvFPVdWJy3EvAAAAAHAg2+cJwqo6Isl/SLK2ux+R5KAkpyZ5ZZJXd/eaJLcmOX1UOT3Jrd39fUlePcqlqh4+6v1QknVJ3lBVB+3LewEAAACAA91yLTFeleQ+VbUqyX2T3JzkSUnePq5fmOSUcXzyOM+4fnxV1Yhf3N1f7+5PJ9mU5Jh9NH4AAAAAWBH2eYKwu29M8j+TfC6TxODtST6c5LbuvmMU25zkiHF8RJIbRt07RvkHTMfnqXMXVXVGVW2sqo1bt25d2hsCAAAAgAPYciwxPiyTp/8eluR7ktwvyUnzFO3tVXZwbUfxuwe7z+vutd29dvXq1bs+aAAAAABYoZZjifGPJ/l0d2/t7m8m+cMkP5bk0LHkOEmOTHLTON6c5KgkGde/O8m26fg8dQAAAACARViOBOHnkhxbVfcd7xI8Psk1Sd6T5OmjzPokl47jy8Z5xvV3d3eP+Kljl+OHJVmT5EP76B4AAAAAYEVYtXCRpdXdH6yqtyf5SJI7knw0yXlJ/jTJxVX1shE7f1Q5P8lbqmpTJk8Onjra+WRVXZJJcvGOJGd295379GYAAAAA4AC3zxOESdLd5yQ5Z074+syzC3F3fy3JM3bQzsuTvHzJBwgAAAAAM2I5lhgDAAAAAPsJCUIAAAAAmGEShAAAAAAwwyQIAQAAAGCGSRACAAAAwAyTIAQAAACAGSZBCAAAAAAzTIIQAAAAAGaYBCEAAAAAzDAJQgAAAACYYRKEAAAAADDDJAgBAAAAYIZJEAIAAADADJMgBAAAAIAZJkEIAAAAADNMghAAAAAAZpgEIQAAAADMMAlCAAAAAJhhEoQAAAAAMMMkCAEAAABghkkQAgAAAMAMkyAEAAAAgBkmQQgAAAAAM0yCEAAAAABmmAQhAABLpqoOqqqPVtWfjPOHVdUHq+q6qnpbVR084vca55vG9aOn2njRiH+qqk6ciq8bsU1VdfZUfN4+AABYHAlCAACW0guSXDt1/sokr+7uNUluTXL6iJ+e5Nbu/r4krx7lUlUPT3Jqkh9Ksi7JG0bS8aAkv5XkpCQPT/KsUXZnfQAAsAgShAAALImqOjLJTyR54zivJE9K8vZR5MIkp4zjk8d5xvXjR/mTk1zc3V/v7k8n2ZTkmPG3qbuv7+5vJLk4yckL9AEAwCJIEAIAsFRek+SsJN8a5w9Iclt33zHONyc5YhwfkeSGJBnXbx/lvx2fU2dH8Z31cRdVdUZVbayqjVu3bt3dewQAWHEkCAEA2GNV9dQkt3T3h6fD8xTtBa4tVfzuwe7zunttd69dvXr1fEUAAGbSquUeAAAAK8JxSX6qqp6S5N5JDsnkicJDq2rVeMLvyCQ3jfKbkxyVZHNVrUry3Um2TcW3m64zX/wLO+kDAIBF8AQhAAB7rLtf1N1HdvfRmWwy8u7u/ukk70ny9FFsfZJLx/Fl4zzj+ru7u0f81LHL8cOSrEnyoSRXJ1kzdiw+ePT4oSiLAAAe0ElEQVRx2aizoz4AAFgECUIAAPamFyb5paralMn7As8f8fOTPGDEfynJ2UnS3Z9MckmSa5K8K8mZ3X3neDrweUmuyGSX5EtG2Z31AQDAIlhiDADAkuru9yZ57zi+PpMdiOeW+VqSZ+yg/suTvHye+OVJLp8nPm8fAAAszqKeIKyqKxcTAwDgwGfuBwAwW3b6BGFV3TvJfZM8sKoOy3d2iTskyffs5bEBALAPmfsBAMymhZYY/1ySX8xkQvjhfGeS+KUkv7UXxwUAwL5n7gcAMIN2miDs7tcmeW1VPb+7X7+PxgQAwDIw9wMAmE2L2qSku19fVT+W5OjpOt190V4aFwAAy8TcDwBgtiwqQVhVb0nyz5J8LMmdI9xJTBIBAFYYcz8AgNmyqARhkrVJHt7dvTcHAwDAfsHcDwBghtxjkeX+JslD9uZAAADYb5j7AQDMkMU+QfjAJNdU1YeSfH17sLt/aq+MCgCA5WTuBwAwQxabIHzx3hwEAHDg+V+//I7lHsJMed5v/OS+7O7F+7IzAACW12J3MX7f3h4IAAD7B3M/AIDZsthdjL+cyc51SXJwknsm+Up3H7K3BgYAwPIw9wMAmC2LfYLw/tPnVXVKkmP2yogAAFhW5n4AALNlsbsY30V3/3GSJy3xWAAA2A+Z+wEArGyLXWL8tKnTeyRZm+8sOwEAYAUx9wMAmC2L3cV4etu8O5J8JsnJSz4aAAD2B+Z+AAAzZLHvIHzuUnZaVYcmeWOSR2Tya/TPJvlUkrclOTqTSegzu/vWqqokr03ylCRfTfKc7v7IaGd9kv8ymn1Zd1+4lOMEAJhFSz33AwBg/7aodxBW1ZFV9UdVdUtVfb6q/qCqjtyDfl+b5F3d/QNJHpnk2iRnJ7myu9ckuXKcJ8lJSdaMvzOSnDvGdHiSc5I8NpOXZp9TVYftwZgAAMhemfsBALAfW+wmJW9KclmS70lyRJJ3jNguq6pDkjw+yflJ0t3f6O7bMlm2sv0JwAuTnDKOT05yUU9cleTQqnpokhOTbOjubd19a5INSdbtzpgAALiLJZv7AQCw/1tsgnB1d7+pu+8Yf29Osno3+/zeJFuTvKmqPlpVb6yq+yV5cHffnCTj80Gj/BFJbpiqv3nEdhS/m6o6o6o2VtXGrVu37uawAQBmxlLO/QAA2M8tNkH4hap6dlUdNP6eneSLu9nnqiSPTnJudz8qyVfyneXE86l5Yr2T+N2D3ed199ruXrt6tbktAMAClnLuBwDAfm6xCcKfTfLMJFuS3Jzk6Ul29+XVm5Ns7u4PjvO3Z5Iw/PxYOpzxectU+aOm6h+Z5KadxAEA2DNLOfcDAGA/t9gE4UuTrO/u1d39oEwmjS/enQ67e0uSG6rq+0fo+CTXZPKem/Ujtj7JpeP4siSn1cSxSW4fS5CvSHJCVR02Nic5YcQAANgzSzb3AwBg/7dqkeV+ZGwEkiTp7m1V9ag96Pf5Sd5aVQcnuT6TX6TvkeSSqjo9yeeSPGOUvTzJU5JsSvLVUXb7GF6a5OpR7iXdvW0PxgQAwMRSz/0AANiPLTZBeI+qOmz7RLGqDt+FunfT3R9LsnaeS8fPU7aTnLmDdi5IcsHujgMAgHkt6dwPAID922Iner+R5P9W1dsz2QjkmUlevtdGBQDAcjL3AwCYIYtKEHb3RVW1McmTMtk9+Gndfc1eHRkAAMvC3A8AYLYseqnImBSaGAIAzABzPwCA2bHYXYwBAAAAgBVIghAAAAAAZpgEIQAAAADMMAlCAAAAAJhhEoQAAAAAMMMkCAEAAABghkkQAgAAAMAMkyAEAAAAgBkmQQgAAAAAM0yCEAAAAABmmAQhAAAAAMwwCUIAAAAAmGEShAAALImqundVfaiq/rqqPllV/23EH1ZVH6yq66rqbVV18Ijfa5xvGtePnmrrRSP+qao6cSq+bsQ2VdXZU/F5+wAAYGEShAAALJWvJ3lSdz8yyY8mWVdVxyZ5ZZJXd/eaJLcmOX2UPz3Jrd39fUlePcqlqh6e5NQkP5RkXZI3VNVBVXVQkt9KclKShyd51iibnfQBAMACJAgBAFgSPfEP4/Se46+TPCnJ20f8wiSnjOOTx3nG9eOrqkb84u7+end/OsmmJMeMv03dfX13fyPJxUlOHnV21AcAAAuQIAQAYMmMJ/0+luSWJBuS/H2S27r7jlFkc5IjxvERSW5IknH99iQPmI7PqbOj+AN20sf02M6oqo1VtXHr1q17eqsAACuGBCEAAEumu+/s7h9NcmQmT/z94HzFxmft4NpSxeeO7bzuXtvda1evXj3f8AEAZpIEIQAAS667b0vy3iTHJjm0qlaNS0cmuWkcb05yVJKM69+dZNt0fE6dHcW/sJM+AABYgAQhAABLoqpWV9Wh4/g+SX48ybVJ3pPk6aPY+iSXjuPLxnnG9Xd3d4/4qWOX44clWZPkQ0muTrJm7Fh8cCYbmVw26uyoDwAAFrBq4SIAALAoD01y4dht+B5JLunuP6mqa5JcXFUvS/LRJOeP8ucneUtVbcrkycFTk6S7P1lVlyS5JskdSc7s7juTpKqel+SKJAcluaC7PznaeuEO+gAAYAEShAAALInu/niSR80Tvz6T9xHOjX8tyTN20NbLk7x8nvjlSS5fbB8AACzMEmMAAAAAmGEShAAAAAAwwyQIAQAAAGCGSRACAAAAwAyTIAQAAACAGSZBCAAAAAAzTIIQAAAAAGaYBCEAAAAAzDAJQgAAAACYYRKEAAAAADDDJAgBAAAAYIZJEAIAAADADJMgBAAAAIAZJkEIAAAAADNMghAAAAAAZpgEIQAAAADMMAlCAAAAAJhhEoQAAAAAMMMkCAEAAABghkkQAgAAAMAMkyAEAAAAgBkmQQgAAAAAM0yCEAAAAABmmAQhAAAAAMywZUsQVtVBVfXRqvqTcf6wqvpgVV1XVW+rqoNH/F7jfNO4fvRUGy8a8U9V1YnLcycAAAAAcOBazicIX5Dk2qnzVyZ5dXevSXJrktNH/PQkt3b39yV59SiXqnp4klOT/FCSdUneUFUH7aOxAwAAAMCKsCwJwqo6MslPJHnjOK8kT0ry9lHkwiSnjOOTx3nG9eNH+ZOTXNzdX+/uTyfZlOSYfXMHAAAAALAyLNcThK9JclaSb43zByS5rbvvGOebkxwxjo9IckOSjOu3j/Lfjs9T5y6q6oyq2lhVG7du3bqU9wEAAAAAB7R9niCsqqcmuaW7PzwdnqdoL3BtZ3XuGuw+r7vXdvfa1atX79J4AQAAAGAlW7UMfR6X5Keq6ilJ7p3kkEyeKDy0qlaNpwSPTHLTKL85yVFJNlfVqiTfnWTbVHy76ToAAAAAwCLs8wRhd78oyYuSpKqemORXuvunq+r/JHl6kouTrE9y6ahy2Tj/wLj+7u7uqrosye9V1W8m+Z4ka5J8aF/eC7BvHff645Z7CDPlr57/V8s9BAAAAPaB5XiCcEdemOTiqnpZko8mOX/Ez0/ylqralMmTg6cmSXd/sqouSXJNkjuSnNndd+77YQMAAADAgWtZE4Td/d4k7x3H12eeXYi7+2tJnrGD+i9P8vK9N0IAAAAAWNmWaxdjAAAAAGA/IEEIAAAAADNMghAAAAAAZpgEIQAAAADMMAlCAAAAAJhhEoQAAAAAMMMkCAEAAABghkkQAgAAAMAMkyAEAGCPVdVRVfWeqrq2qj5ZVS8Y8cOrakNVXTc+DxvxqqrXVdWmqvp4VT16qq31o/x1VbV+Kv6YqvrEqPO6qqqd9QEAwOJIEAIAsBTuSPLL3f2DSY5NcmZVPTzJ2Umu7O41Sa4c50lyUpI14++MJOcmk2RfknOSPDbJMUnOmUr4nTvKbq+3bsR31AcAAIsgQQgAwB7r7pu7+yPj+MtJrk1yRJKTk1w4il2Y5JRxfHKSi3riqiSHVtVDk5yYZEN3b+vuW5NsSLJuXDukuz/Q3Z3kojltzdcHAACLIEEIAMCSqqqjkzwqyQeTPLi7b04mScQkDxrFjkhyw1S1zSO2s/jmeeLZSR9zx3VGVW2sqo1bt27d3dsDAFhxJAgBAFgyVfVdSf4gyS9295d2VnSeWO9GfNG6+7zuXtvda1evXr0rVQEAVjQJQgAAlkRV3TOT5OBbu/sPR/jzY3lwxuctI745yVFT1Y9MctMC8SPnie+sDwAAFkGCEACAPTZ2FD4/ybXd/ZtTly5Lsn0n4vVJLp2KnzZ2Mz42ye1jefAVSU6oqsPG5iQnJLliXPtyVR07+jptTlvz9QEAwCKsWu4BAACwIhyX5GeSfKKqPjZiv5rkFUkuqarTk3wuyTPGtcuTPCXJpiRfTfLcJOnubVX10iRXj3Iv6e5t4/jnk7w5yX2SvHP8ZSd9AACwCBKEAADsse7+y8z/nsAkOX6e8p3kzB20dUGSC+aJb0zyiHniX5yvDwAAFscSYwAAAACYYRKEAAAAADDDJAgBAAAAYIZJEAIAAADADJMgBAAAAIAZJkEIAAAAADNMghAAAAAAZpgEIQAAAADMMAlCAAAAAJhhEoQAAAAAMMMkCAEAAABghkkQAgAAAMAMkyAEAAAAgBkmQQgAAAAAM0yCEAAAAABmmAQhAAAAAMwwCUIAAAAAmGEShAAAAAAwwyQIAQAAAGCGSRACAAAAwAyTIAQAAACAGSZBCAAAAAAzTIIQAAAAAGaYBCEAAAAAzDAJQgAAAACYYRKEAAAAADDDJAgBAAAAYIZJEAIAAADADJMgBAAAAIAZJkEIAAAAADNMghAAAAAAZpgEIQAAAADMsH2eIKyqo6rqPVV1bVV9sqpeMOKHV9WGqrpufB424lVVr6uqTVX18ap69FRb60f566pq/b6+FwAAAAA40C3HE4R3JPnl7v7BJMcmObOqHp7k7CRXdveaJFeO8yQ5Kcma8XdGknOTSUIxyTlJHpvkmCTnbE8qAgAAAACLs88ThN19c3d/ZBx/Ocm1SY5IcnKSC0exC5OcMo5PTnJRT1yV5NCqemiSE5Ns6O5t3X1rkg1J1u3DWwEAAACAA96yvoOwqo5O8qgkH0zy4O6+OZkkEZM8aBQ7IskNU9U2j9iO4vP1c0ZVbayqjVu3bl3KWwAAAACAA9qyJQir6ruS/EGSX+zuL+2s6Dyx3kn87sHu87p7bXevXb169a4PFgAAAABWqGVJEFbVPTNJDr61u/9whD8/lg5nfN4y4puTHDVV/cgkN+0kDgAAAAAs0nLsYlxJzk9ybXf/5tSly5Js34l4fZJLp+Knjd2Mj01y+1iCfEWSE6rqsLE5yQkjBgAAAAAs0qpl6PO4JD+T5BNV9bER+9Ukr0hySVWdnuRzSZ4xrl2e5ClJNiX5apLnJkl3b6uqlya5epR7SXdv2ze3AAAAAAArwz5PEHb3X2b+9wcmyfHzlO8kZ+6grQuSXLB0owMAYHdV1QVJnprklu5+xIgdnuRtSY5O8pkkz+zuW8eqktdm8kPwV5M8p7s/MuqsT/JfRrMv6+4LR/wxSd6c5D6Z/Ij8gu7uHfWxl28XAGDFWNZdjAEAWFHenGTdnNjZSa7s7jVJrhznSXJSkjXj74wk5ybfTiiek+SxSY5Jcs54nUxGmTOm6q1boA8AABZBghAAgCXR3e9PMveVLycnuXAcX5jklKn4RT1xVZJDx0Z1JybZ0N3bxlOAG5KsG9cO6e4PjBUmF81pa74+AABYBAlCAAD2pgePDeYyPh804kckuWGq3OYR21l88zzxnfVxF1V1RlVtrKqNW7du3aObAgBYSSQIAQBYDvO9k7p3I75o3X1ed6/t7rWrV6/elaoAACuaBCEAAHvT58fy4IzPW/7/9u4+aLO6ruP4+xMPSvEgBhq5W8sEooiCsIOkMe5AwIIE1cAAObAQRhJMyMikRBMF04xNPjRGamgIGvKggCBBRBghGg/LtsiTyAaEGwSjELAS1sK3P87vdq9Z733ghvu+9j7n/Zq5Z8/1u37nOr9rv/e5ru/9Pef8TmtfDswd6TcHeHQd7XMmaV/bNiRJkrQeLBBKkiRpOl0FLGrLi4ArR9qPSWcv4Ol2efB1wP5Jtm43J9kfuK4992ySvdodkI9Z7bUm24YkSZLWw8bjHoAkSZL6IclFwAJgmyTL6e5G/BHg0iTHA48Ah7fu1wAHAcuA54DjAKrqySRnA7e3fmdV1cSNT06ku1PyZsC17Ye1bEOSJEnrwQKhJEmSXhFVddQantp3kr4FnLSG1zkPOG+S9sXALpO0/2CybUiSJGn9eImxJEmSJEmSNGAWCCVJkiRJkqQBs0AoSZIkSZIkDZgFQkmSJEmSJGnALBBKkiRJkiRJA2aBUJIkSZIkSRowC4SSJEmSJEnSgFkglCRJkiRJkgbMAqEkSZIkSZI0YBYIJUmSJEmSpAGzQChJkiRJkiQNmAVCSZIkSZIkacAsEEqSJEmSJEkDZoFQkiRJkiRJGjALhJIkSZIkSdKAWSCUJEmSJEmSBswCoSRJkiRJkjRgFgglSZIkSZKkAbNAKEmSJEmSJA2YBUJJkiRJkiRpwCwQSpIkSZIkSQNmgVCSJEmSJEkaMAuEkiRJkiRJ0oBZIJQkSZIkSZIGzAKhJEmSJEmSNGAWCCVJkiRJkqQBs0AoSZIkSZIkDZgFQkmSJEmSJGnALBBKkiRJkiRJA2aBUJIkSZIkSRowC4SSJEmSJEnSgFkglCRJkiRJkgbMAqEkSZIkSZI0YBYIJUmSJEmSpAGzQChJkiRJkiQNmAVCSZIkSZIkacAsEEqSJEmSJEkDZoFQkiRJkiRJGjALhJIkSZIkSdKAWSCUJEmSJEmSBswCoSRJkiRJkjRgs75AmGRhkvuTLEvy4XGPR5IkSeNhXihJkjQ1s7pAmGQj4K+BA4GdgaOS7DzeUUmSJGmmmRdKkiRN3awuEAJ7Asuq6sGq+l/gYuDQMY9JkiRJM8+8UJIkaYpSVeMew5QlOQxYWFXva4+PBt5RVSev1u8E4IT2cCfg/hkd6MzbBvj+uAehV4Sx7Afj2B/Gsh+GEMdfrKptxz2ImbQ+eeEAc0IYxu/7EBjH/jCW/WAc+2MIsVyvvHDjmRjJNMokbT9R8ayqc4Fzp384G4Yki6tq/rjHoZfPWPaDcewPY9kPxrG31pkXDi0nBH/f+8I49oex7Afj2B/GcpXZfonxcmDuyOM5wKNjGoskSZLGx7xQkiRpimZ7gfB2YMck2yfZFDgSuGrMY5IkSdLMMy+UJEmaoll9iXFVrUxyMnAdsBFwXlXdM+ZhbQgGdelMzxnLfjCO/WEs+8E49pB54Rr5+94PxrE/jGU/GMf+MJbNrL5JiSRJkiRJkqSXZ7ZfYixJkiRJkiTpZbBAKEmSJEmSJA2YBcINVJLzkjyR5O6RttcmuT7JA+3frVv7Vkm+luTOJPckOW5knUWt/wNJFo3jvWiVJDslWTry80ySDyT5iyTfSfLtJFckec3IOqcnWZbk/iQHjHP86iSZm+Sfk9zX9rlTVnv+tCSVZJv2OEk+2eL47SS7j2fkWpMkGyX5tyRXt8f7JlnS9tObk+zQ2l+V5JIWy1uTzBvnuNVJ8uokt418D/5pa0+SP0vy3ba//v5Iu/ukZg3zwv4xJ+wP88J+MSec/cwLp84C4YbrfGDham0fBm6oqh2BG9pjgJOAe6tqV2AB8LEkmyZ5LXAm8A5gT+DMieRR41FV91fVblW1G7AH8BxwBXA9sEtVvQ34LnA6QJKd6e7C+Ba634dPJdloLIPXqJXAB6vqzcBewEktViSZC+wHPDLS/0Bgx/ZzAvDpmR2u1sMpwH0jjz8NvLftq18C/qi1Hw88VVU7AJ8A/nxGR6k1+RGwT/se3A1YmGQv4FhgLvCmtr9e3Pq7T2q2OR/zwl4xJ+wV88J+MSec/cwLp8gC4Qaqqm4Cnlyt+VDggrZ8AfDrE92BLZIE2LyttxI4ALi+qp6sqqfoEo6FAElWJPlYOxpyQ5Jtp/cdaRL7Av9eVf9RVf9YVStb+y3AnLZ8KHBxVf2oqh4ClgF7JpnXji5f0I5yfCXJT4/hPQxSVT1WVUva8rN0ScQb2tOfAP6Abr+ccCjwhercArwmyXZJFiS5qZ0hcG+SzyTxc3mGJZkDvAf43EhzAVu25a2AR9vy6OfwV4B921HHY5NcmeQf2pkdZ87E2NVp+9aK9nCT9lPAicBZVfVi6/dE6+M+qVnFvLD3zAlnMfPC/jAn7Afzwqnr9ZvroddX1WPQfREBr2vt5wBvpvuwugs4pf3SvwH43sj6y1n1ZfUzwJKq2h34F7ojyppZRwIXTdL+28C1bXltMdwJOLcdYX4G+L1pGqfWol1O8Hbg1iSHAP9ZVXeu1m1tcdwT+CDwVuCXgN+czvFqUn9Jl7y/ONL2PuCaJMuBo4GPtPYfx7L9Afc08LPtuT2B99IdqTw8yfzpH7ompLskaCnwBF0R5Fa6feqIJIuTXJtkx9bdfVJ9YF7YH+aEPWFeOOuZE/aEeeHUWCDshwOApcDP030InZNkSyCT9J04evUicElb/jvgV6Z7kFolyabAIcCXV2s/g+4o/4UTTZOsPhHD71XVN9uyMRyDJJsDlwEfoIvbGcAfT9Z1kraJON5WVQ9W1Qt0fxwYxxmU5GDgiaq6Y7WnTgUOqqo5wOeBj0+sMsnLTMTy+qr6QVX9D3A5xnJGVdUL7fKfOXRn1ewCvAp4vqrmA58Fzmvd3SfVZ+aFs4g5YX+YF85u5oT9Yl44NRYIZ5fHk2wH0P6dOCX2OODydkrsMuAh4E10le+5I+vPYdUp0aurNbRrehxId6T+8YmGdJOFH0w3x8VEPNYWw9VjZgxnUJJN6JLAC6vqcrojStsDdyZ5mC5WS5L8HMZxQ/Yu4JAWs4uBfZL8PbBrO9II3R/N72zLP45lko3pLjWZuOzPWG4Aquq/gRvpLp1cTrefQje319vasvuk+sC8sB/MCXvAvLAXzAl7yLzwpbFAOLtcBUzccW4RcGVbfoRu7hKSvJ7uMoMHgeuA/ZNsnW4S6v1bG3SxP6wt/xZw87SPXqOOYuRSkiQLgQ8Bh1TVcyP9rgKOTHeXrO3pJk69rT33C0l+eeT1jOEMafM6/S1wX1V9HKCq7qqq11XVvKqaR/dFs3tV/RddHI9p85LsBTw9cVkY3RGt7dt8FkdgHGdUVZ1eVXNazI4Evk43D8lWSd7Yuu3HqsmqRz+HDwO+PvLH237p7iq6Gd1cYBNnc2iaJdk27U6f7f//V4HvAF8F9mnd3k034T+4T6ofzAv7wZxwljMv7Adzwv4wL5y6jcc9AE0uyUV0d57bps13cCbdfAeXJjmeLvk7vHU/Gzg/yV10p8d+qKq+317nbOD21u+sqpo4qvFD4C1J7qCbL+GI6X9XAkg3cfR+wO+ONJ9Dd8rz9V2OwS1V9f6quifJpcC9dJcqnFRVL7Q+9wGLkvwN8AADvtvSGLyLbg6Su9rcFgB/WFXXrKH/NcBBdBOKP0d3dseEf6Xbt98K3ER3NEtjVFUrk/wOcFmSF4Gn6OaBgu4PgC8mWUZ3lPjIkVVvBr4I7AB8qaoWz+Cwh2474IJ0d/T8KeDSqro6yc3AhUlOBVbQzSME7pOaZcwL+8mcsDfMC3vKnHDWMi+coqwqcmtIkqyoqs3HPQ5NTboJkK+uql3GPBS9DEkWAKdV1cHjHoteniTHAvOr6uRxj0VT5z6poTIvnL3MCfvD76B+MCfsjyHuk15iLEmSJEmSJA2YZxBKkiRJkiRJA+YZhJIkSZIkSdKAWSCUJEmSJEmSBswCoSRJkiRJkjRgFgglaQYkmZfk7rY8P8kn2/KCJO8c7+gkSZI0U8wLJW2INh73ACRpaKpqMbC4PVwArAC+NbYBSZIkaSzMCyVtKDyDUJLWIckZSe5P8k9JLkpyWpIbk8xvz2+T5OG2PC/JN5IsaT8/cRS4HR2+Osk84P3AqUmWJtk7yUNJNmn9tkzy8MRjSZIkjZd5oaS+8gxCSVqLJHsARwJvp/vMXALcsZZVngD2q6rnk+wIXATMn6xjVT2c5DPAiqr6aNvejcB7gK+27V5WVf/3Cr0dSZIkTZF5oaQ+8wxCSVq7vYErquq5qnoGuGod/TcBPpvkLuDLwM4vcXufA45ry8cBn3+J60uSJGl6mBdK6i3PIJSkdatJ2lay6iDLq0faTwUeB3Ztzz//kjZU9c12Ocq7gY2q6u4pjFeSJEnTw7xQUi95BqEkrd1NwG8k2SzJFsCvtfaHgT3a8mEj/bcCHquqF4GjgY3W8frPAlus1vYFuktQPEosSZK04TAvlNRbFgglaS2qaglwCbAUuAz4Rnvqo8CJSb4FbDOyyqeARUluAd4I/HAdm/gaXaK5NMnere1CYGu6ZFCSJEkbAPNCSX2WqsnOkJYkTSbJnzAyefQ0beMw4NCqOnq6tiFJkqSXx7xQUp84B6EkbUCS/BVwIHDQuMciSZKk8TEvlDSTPINQkiRJkiRJGjDnIJQkSZIkSZIGzAKhJEmSJEmSNGAWCCVJkiRJkqQBs0AoSZIkSZIkDZgFQkmSJEmSJGnA/h+n8iRSMHdpgwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of quality\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "sns.countplot(x='quality', data=data, ax=ax[0])\n",
    "ax[0].set_title('Count Plot of quality', fontsize=16)\n",
    "\n",
    "sns.barplot(x='quality', y='count', data=data, ax=ax[1])\n",
    "ax[1].set_title('Count vs. quality', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of interval\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "sns.countplot(x='interval', data=data, ax=ax[0])\n",
    "ax[0].set_title('Count Plot of interval', fontsize=16)\n",
    "\n",
    "sns.barplot(x='interval', y='count', data=data, ax=ax[1])\n",
    "ax[1].set_title('Count vs. interval', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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dk5wfH9GfY9sY+L1Jtq6qf5qo/5KmaUushOLm5rZlN7r/Q/wpumkNd9JNM/gi3RSKrQbKPYVuGsDP6O5ungPsNaK+V9Alr35Jd+fvyYy/0tyjhq59C0Mr+rb6rqQbzI27Wm8rexKweiPfdyFDK7C1+IvopiXcTjel4RRg56Ey+9A9GXgbG1lNrpVfQpf8+iXdgOYM4NFDZSa1inErO5+77wLfTHcHe+nw70K3gtxX6V72vJpuoH2PVYYHyr+xnXvsOO1u9G+/kfo/ycBKxS02tsLxeeO0+WLg/Nbez+gSnx8EFgyU2YpuQPud9je5pe2/i+7JwsG/98sHrtua7i76z4FnzPZ/g25ubm5ubnNpYw6NLQeu+VQr+/ER594JfKuNQ35Olyh8zVCZ84CrJtHO1m1seH37vufRLRKywbiTbgbGqXQ3rNfR3fz8PUaMcVv5p7ZzR47T7s50Y9+f0I2FLwZeNFTmHqsYD5x7ZTs3uFLx2ArHtwEPGKdPn2v9v639TU8FnjpU7tl0Ccaftt9kFXAisMdAmauAjw5ddyTdzePXz/Z/E25uc3FLVSFJmlvau3V+VVVOu5UkSZpjkhxDd1P1kdWtFi1Jm8QpxpI0RyS5P/Ak4Jl0d/qXzm6PJEmStDkl2ZNuAZLX0i0eYnJQ0mbhE4SSNEckWQj8kG6q8oeq6k2z2iFJkiRtVkmuonu339nAi2szvsdbUr+ZIJQkSZIkSZJ6bKvZ7oAkSZIkSZKk2TMn30H4sIc9rBYuXDjb3ZAkSdpiLrzwwp9U1fzZ7se9mWNESZLUN5MdI87JBOHChQtZuXLlbHdDkiRpi0nyo1lo89HAJwdCvwW8GTi5xRcCVwF/WFXrkgR4H/Bs4BfAS6rqolbXMuDvWj1vr6rlLf5k4CTggcBZwGurqpLsMKqNifrrGFGSJPXNZMeITjGWJEnStFTV96vqiVX1RODJdEm/zwJHAedU1SLgnHYMcBCwqG1HAMcBtGTf0cBTgL2Ao5Ns3645rpUdu25Ji4/XhiRJkqbIBKEkSZI2h/2BH1TVj4ClwPIWXw4c3PaXAidX53xguyQ7AwcCK6pqbXsKcAWwpJ3btqq+Xt3KeicP1TWqDUmSJE2RCUJJkiRtDocCn2j7O1XVdQDt8+EtvgtwzcA1q1tsovjqEfGJ2thAkiOSrEyycs2aNdP8apIkSXObCUJJkiRtkiTbAM8HPrWxoiNiNY34pFXV8VW1uKoWz5/vGi6SJEmjmCCUJEnSpjoIuKiqbmjHN7TpwbTPG1t8NbDrwHULgGs3El8wIj5RG5IkSZoiE4SSJEnaVH/M3dOLAc4ElrX9ZcAZA/HD0tkbuKVNDz4bOCDJ9m1xkgOAs9u5W5Ps3VZAPmyorlFtSJIkaYrmzXYHJEmSdN+V5EHAs4BXDITfAZyW5HDgauCQFj8LeDawim7F45cCVNXaJG8DLmjl3lpVa9v+K4GTgAcCn2/bRG1IkiRpikwQSpIkadqq6hfAjkOxm+hWNR4uW8CR49RzInDiiPhK4HEj4iPbkCRJ0tQ5xViSJEmSJEnqMROEkiRJkiRJUo+ZIJQkSZIkSZJ6zAShJEmSJEmS1GMmCCVJkiRJkqQeM0EoSZIkSZIk9ZgJQkmSJEmSJKnH5s12ByRJkiRJkiby+te/nuuvv55HPOIRvOtd75rt7khzjglCSXPGl/d92mx34V7haV/58mx3QZIkSdqsrr/+en784x/PdjekOcspxpIkSZIkSVKP+QShJEmSJEkzxKmxku4LTBBKkiRJkjRDnBor6b7AKcaSJEmSJElSj5kglCRJkiRJknrMBKEkSZIkSZLUYyYIJUmSJEmSpB5zkRJJkiRJkqSecGVtjWKCUJIkSZIkqSdcWVujOMVYkiRJkiRJ6rEZfYIwyV8CLwcKuAR4KbAzcCqwA3AR8OKquiPJ/YGTgScDNwF/VFVXtXreCBwO3AW8pqrOnsl+S5IkSZKkDX3wr/991tq++Sc///XnbPbjVe9+3qy1Lc2kGXuCMMkuwGuAxVX1OGBr4FDgncCxVbUIWEeX+KN9rquqRwHHtnIk2aNd91hgCfChJFvPVL8lSZIkSZKkPpnpdxDOAx6Y5E7gQcB1wH7An7Tzy4G3AMcBS9s+wOnAB5OkxU+tqtuBHyZZBewFfH2G+y5JkiRJuo/78r5Pm9X2fzlva0j45erVs9qXp33ly7PWtqR7vxlLEFbVj5P8E3A18Evgi8CFwM1Vtb4VWw3s0vZ3Aa5p165PcguwY4ufP1D14DW/luQI4AiA3XbbbbN/H0mSJEmSJAnm3mrQMznFeHu6p/92Bx4JPBg4aETRGrtknHPjxTcMVB1fVYuravH8+fOn12lJkiRJkiRpI8ZWg77++utnuyubxUyuYvxM4IdVtaaq7gQ+A/w+sF2SsScXFwDXtv3VwK4A7fxDgbWD8RHXSJIkSZIkSdoEM5kgvBrYO8mD2rsE9wcuA84FXtjKLAPOaPtntmPa+S9VVbX4oUnun2R3YBHwzRnstyRJkiRJktQbM/kOwm8kOR24CFgPfAs4HvgP4NQkb2+xE9olJwCntEVI1tKtXExVXZrkNLrk4nrgyKq6a6b6LUmSJEmSJPXJjK5iXFVHA0cPha+kW4V4uOxtwCHj1HMMcMxm76AkSZIkSZLUczOaIJQkSZI0OXNtNURJ0mjHvOiFGy80g9beeEv3ef11s9qXN3309FlrW/dkglCSJEm6FxhbDVGSJGlLm8lFSiRJkiRJkiTdy5kglCRJkiRJknrMKcaSJEmS5hTf56h7k+2qNvjU9Dx4m203+JS0eZkglCRJkjSn+D7HzcNE6+bxort+NdtdmBP2+e0XzHYXpDnNBKEkSZIk6R5MtEpSf5gglCRJkiRJ0n3K5cd8aVbbv2PtL3/9OZt9ecyb9tss9bhIiSRJkiRJktRjJgglSZIkSZKkHjNBKEmSJEmSJPWYCUJJkiRJkiSpx0wQSpIkSZIkST3mKsaSJEkS8OS/OXlW23/IT25la+Dqn9w6q3258B8Pm7W2JUkz7wFbb7XBpwQ+QShJkqRNkGS7JKcn+V6Sy5M8NckOSVYkuaJ9bt/KJsn7k6xKcnGSJw3Us6yVvyLJsoH4k5Nc0q55f5K0+Mg2JEnSxPbc8SE89eEPZc8dHzLbXdG9iAlCSZIkbYr3AV+oqt8BngBcDhwFnFNVi4Bz2jHAQcCith0BHAddsg84GngKsBdw9EDC77hWduy6JS0+XhuSJEmaIhOEkiRJmpYk2wL7AicAVNUdVXUzsBRY3ootBw5u+0uBk6tzPrBdkp2BA4EVVbW2qtYBK4Al7dy2VfX1qirg5KG6RrUhSZKkKfIdhJIkSZqu3wLWAP+a5AnAhcBrgZ2q6jqAqrouycNb+V2AawauX91iE8VXj4gzQRsbSHIE3ROI7LbbbtP8mpqqq9/6u7Pa/vq1OwDzWL/2R7PWl93efMmstCtJ0nT4BKEkSZKmax7wJOC4qtoT+DkTT/XNiFhNIz5pVXV8VS2uqsXz58+fyqWSJEnj2vEBD2X+A3dgxwc8dLa7sln4BKEkSZKmazWwuqq+0Y5Pp0sQ3pBk5/Zk387AjQPldx24fgFwbYs/fSh+XosvGFGeCdqQ5ox9PrDPrLa/zc3bsBVbcc3N18xqX7726q/NWtuSNJ5X7fkns92FzconCCVJkjQtVXU9cE2SR7fQ/sBlwJnA2ErEy4Az2v6ZwGFtNeO9gVvaNOGzgQOSbN8WJzkAOLuduzXJ3m314sOG6hrVhiRJkqbIJwglSZK0KV4NfCzJNsCVwEvpbkKfluRw4GrgkFb2LODZwCrgF60sVbU2yduAC1q5t1bV2rb/SuAk4IHA59sG8I5x2pAkSdIUmSCUJEnStFXVt4HFI07tP6JsAUeOU8+JwIkj4iuBx42I3zSqDUmSJE2dU4wlSZIkSZKkHjNBKEmSJEmSJPWYU4wlSZKke4FfbfPgDT4lSZK2FBOEkiRJ0r3AzxcdMNtdkCRJPeUUY0mSJEmSJKnHTBBKkiRJkiRJPeYUY0mSJElzysMe8CtgffuUJEkbY4JQkiRJ0pzyvx9/82x3QZKk+xSnGEuSJEmSJEk9NmMJwiSPTvLtge2nSV6XZIckK5Jc0T63b+WT5P1JViW5OMmTBupa1spfkWTZTPVZkiRJktSpBxW/evCvqAfVbHdFkjTDZmyKcVV9H3giQJKtgR8DnwWOAs6pqnckOaodvwE4CFjUtqcAxwFPSbIDcDSwGCjgwiRnVtW6meq7JEmSJPXdnfvcOdtdkCRtIVtqivH+wA+q6kfAUmB5iy8HDm77S4GTq3M+sF2SnYEDgRVVtbYlBVcAS7ZQvyVJkiRJkqQ5bUslCA8FPtH2d6qq6wDa58NbfBfgmoFrVrfYePENJDkiycokK9esWbOZuy9JkiRJkiTNTTOeIEyyDfB84FMbKzoiVhPENwxUHV9Vi6tq8fz586feUUmSJEmSJKmHtsQThAcBF1XVDe34hjZ1mPZ5Y4uvBnYduG4BcO0EcUmSJEmSJEmbaEskCP+Yu6cXA5wJjK1EvAw4YyB+WFvNeG/gljYF+WzggCTbtxWPD2gxSZIkSZIkSZtoxlYxBkjyIOBZwCsGwu8ATktyOHA1cEiLnwU8G1gF/AJ4KUBVrU3yNuCCVu6tVbV2JvstSZIkSZIk9cWMJgir6hfAjkOxm+hWNR4uW8CR49RzInDiTPRRkiRJkiRJ6rMttYqxJEmSJEmSpHshE4SSJEmSJElSj5kglCRJkiRJknrMBKEkSZIkSZLUYyYIJUmSJEmSpB4zQShJkiRJkiT1mAlCSZIkSZIkqcdMEEqSJEmSJEk9ZoJQkiRJkiRJ6jEThJIkSZIkSVKPmSCUJEmSJEmSeswEoSRJkiRJktRjJgglSZIkSZKkHjNBKEmSJEmSJPWYCUJJkiRJkiSpx0wQSpIkSZIkST1mglCSJEmSJEnqMROEkiRJkiRJUo+ZIJQkSZIkSZJ6zAShJEmSJEmS1GMmCCVJkiRJkqQeM0EoSZIkSZIk9ZgJQkmSJEmSJKnHTBBKkiRJkiRJPWaCUJIkSdOW5KoklyT5dpKVLbZDkhVJrmif27d4krw/yaokFyd50kA9y1r5K5IsG4g/udW/ql2bidqQJEnS1JkglCRJ0qZ6RlU9saoWt+OjgHOqahFwTjsGOAhY1LYjgOOgS/YBRwNPAfYCjh5I+B3Xyo5dt2QjbUiSJGmKTBBKkiRpc1sKLG/7y4GDB+InV+d8YLskOwMHAiuqam1VrQNWAEvauW2r6utVVcDJQ3WNakOSJElTZIJQkiRJm6KALya5MMkRLbZTVV0H0D4f3uK7ANcMXLu6xSaKrx4Rn6iNDSQ5IsnKJCvXrFkzza8oSZI0t82b7Q5IkiTpPm2fqro2ycOBFUm+N0HZjIjVNOKTVlXHA8cDLF68eErXSpIk9YVPEEqSJGnaqura9nkj8Fm6dwje0KYH0z5vbMVXA7sOXL4AuHYj8QUj4kzQhiRJkqbIBKEkSZKmJcmDkzxkbB84APgucCYwthLxMuCMtn8mcFhbzXhv4JY2Pfhs4IAk27fFSQ4Azm7nbk2yd1u9+LChuka1IUmSpClyirEkSZKmayfgs13ujnnAx6vqC0kuAE5LcjhwNXBIK38W8GxgFfAL4KUAVbU2yduAC1q5t1bV2rb/SuAk4IHA59sG8I5x2pAkSdIUzWiCMMl2wEeAx9G9L+ZlwPeBTwILgauAP6yqde2u8PvoBo2/AF5SVRe1epYBf9eqfXtVLUeSJEmzqqquBJ4wIn4TsP+IeAFHjlPXicCJI+Ir6caSk2pDkiRJUzfTU4zfB3yhqn6HbvB4OXAUcE5VLQLOaccABwGL2nYEcBxAkh2Ao4Gn0L3T5ug29USSJEmSJEnSJpqxBGGSbYF9gRMAquqOqroZWAqMPQG4HDi47S8FTq7O+cB27YXTBwIrqmptVa0DVgBLZqrfkiRJkiRJUp/M5BOEvwWsAf41ybeSfKS9vHqn9sJp2ufDW/ldgGsGrl/dYuPFJUmSJEmSJG2imUwQzgOeBBxXVXsCP+fu6cSjZESsJohveHFyRJKVSVauWbNmOv2VJEmSJEmSemcrYP3GAAAgAElEQVQmE4SrgdVV9Y12fDpdwvCGNnWY9nnjQPldB65fAFw7QXwDVXV8VS2uqsXz58/frF9EkiRJkiRJmqtmLEFYVdcD1yR5dAvtD1wGnAksa7FlwBlt/0zgsHT2Bm5pU5DPBg5Isn1bnOSAFpMkSZIkSZK0iebNcP2vBj6WZBvgSuCldEnJ05IcDlwNHNLKngU8G1gF/KKVparWJnkbcEEr99aqWjvD/ZYkSZIkSZJ6YUYThFX1bWDxiFP7jyhbwJHj1HMicOLm7Z0kSZIkSZKkmXwHoSRJkiRJkqR7OROEkiRJkiRJUo+ZIJQkSZIkSZJ6zAShJEmSJEmS1GMmCCVJkiRJkqQeM0EoSZIkSZIk9ZgJQkmSJEmSJKnHTBBKkiRJkiRJPWaCUJIkSZIkSeoxE4SSJEmSJElSj5kglCRJkiRJknrMBKEkSZIkSZLUY/NmuwOz5cl/c/Jsd2HWXfiPh21yHVe/9Xc3Q0/u+3Z78yWbdP0+H9hnM/Xkvu1rr/7abHdBzQf/+t9nuwuz7lXvft4m13HMi164GXpy3/emj56+SddffsyXNlNP7tse86b9ZrsLkiRJmqN8glCSJEmSJEnqMROEkiRJkiRJUo+ZIJQkSZIkSZJ6zAShJEmSJEmS1GMmCCVJkiRJkqQeM0EoSZIkSZIk9ZgJQkmSJEmSJKnHTBBKkiRJkiRJPWaCUJIkSZIkSeoxE4SSJEmSJElSj5kglCRJkiRJknrMBKEkSZIkSZLUYyYIJUmSJEmSpB4zQShJkiRJkiT1mAlCSZIkSZIkqcdMEEqSJEmSJEk9ZoJQkiRJkiRJ6jEThJIkSZIkSVKPmSCUJEmSJEmSeswEoSRJkiRJktRjM5ogTHJVkkuSfDvJyhbbIcmKJFe0z+1bPEnen2RVkouTPGmgnmWt/BVJls1knyVJkiRJkqQ+2RJPED6jqp5YVYvb8VHAOVW1CDinHQMcBCxq2xHAcdAlFIGjgacAewFHjyUVJUmSNPuSbJ3kW0k+1453T/KNdnP3k0m2afH7t+NV7fzCgTre2OLfT3LgQHxJi61KctRAfGQbkiRJmrrZmGK8FFje9pcDBw/ET67O+cB2SXYGDgRWVNXaqloHrACWbOlOS5IkaVyvBS4fOH4ncGy7IbwOOLzFDwfWVdWjgGNbOZLsARwKPJZunPehlnTcGvhnuhvJewB/3MpO1IYkSZKmaKYThAV8McmFSY5osZ2q6jqA9vnwFt8FuGbg2tUtNl58A0mOSLIyyco1a9Zs5q8hSZKkUZIsAJ4DfKQdB9gPOL0VGb4hPHaj+HRg/1Z+KXBqVd1eVT8EVtHNHNkLWFVVV1bVHcCpwNKNtCFJkqQpmukE4T5V9SS6u75HJtl3grIZEasJ4hsGqo6vqsVVtXj+/PnT660kSZKm6r3A64FfteMdgZuran07Hry5++sbv+38La38VG8UT9TGBryJLEmStHEzmiCsqmvb543AZ+nuAt/Qpg7TPm9sxVcDuw5cvgC4doK4JEmSZlGS5wI3VtWFg+ERRWsj5zZX/J5BbyJLkiRt1IwlCJM8OMlDxvaBA4DvAmcCYysRLwPOaPtnAoe11Yz3Bm5pU5DPBg5Isn1bnOSAFpMkSdLs2gd4fpKr6Kb/7kf3ROF2Sea1MoM3d39947edfyiwlqnfKP7JBG1IkiRpimbyCcKdgK8m+Q7wTeA/quoLwDuAZyW5AnhWOwY4C7iS7p0z/z/wFwBVtRZ4G3BB297aYpIkSZpFVfXGqlpQVQvpFhn5UlX9KXAu8MJWbPiG8NiN4he28tXih7ZVjncHFtGNHy8AFrUVi7dpbZzZrhmvDUmSJE3RvI0XmZ6quhJ4woj4TcD+I+IFHDlOXScCJ27uPkqSJGlGvAE4NcnbgW8BJ7T4CcApSVbRPTl4KEBVXZrkNOAyYD1wZFXdBZDkVXSzR7YGTqyqSzfShiRJkqZoxhKEkiRJ6o+qOg84r+1fSffu6eEytwGHjHP9McAxI+Jn0c00GY6PbEOSJElTN9OrGEuSJEmSJEm6FzNBKEmSJEmSJPWYCUJJkiRJkiSpx0wQSpIkSZIkST1mglCSJEmSJEnqMROEkiRJkiRJUo+ZIJQkSZIkSZJ6bFIJwiTnTCYmSZKk+ybHe5IkSf01b6KTSR4APAh4WJLtgbRT2wKPnOG+SZIkaYY53pMkSdKECULgFcDr6AaHF3L3gPGnwD/PYL8kSZK0ZTjekyRJ6rkJE4RV9T7gfUleXVUf2EJ9kiRJ0hbieE+SJEkbe4IQgKr6QJLfBxYOXlNVJ89QvyRJkrQFOd6TJEnqr0klCJOcAvw28G3grhYuwAGjJEnSHOB4T5Ikqb8mlSAEFgN7VFXNZGckSZI0axzvSZIk9dRWkyz3XeARM9kRSZIkzSrHe5IkST012ScIHwZcluSbwO1jwap6/oz0SpIkSVua4z1JkqSemmyC8C0z2QlJkiTNurfMdgckSZI0Oya7ivGXZ7ojkiRJmj2O9yRJkvprsqsY30q3ih3ANsD9gJ9X1bYz1TFJkiRtOY73JEmS+muyTxA+ZPA4ycHAXjPSI0mSJG1xjvckSZL6a7KrGG+gqv4N2G8z90WSJEn3Eo73JEmS+mOyU4xfMHC4FbCYu6egSJIk6T7O8Z4kSVJ/TXYV4+cN7K8HrgKWbvbeSJIkabY43pMkSeqpyb6D8KUz3RFJkiTNHsd7kiRJ/TWpdxAmWZDks0luTHJDkk8nWTDTnZMkSdKW4XhPkiSpvya7SMm/AmcCjwR2Af69xSRJkjQ3ON6TJEnqqckmCOdX1b9W1fq2nQTMn8F+SZIkactyvCdJktRTk00Q/iTJi5Js3bYXATfNZMckSZK0RTnekyRJ6qnJJghfBvwhcD1wHfBCwBdZS5IkzR2O9yRJknpqUqsYA28DllXVOoAkOwD/RDeQlCRJ0n2f4z1JkqSemuwThI8fGywCVNVaYM+Z6ZIkSZJmgeM9SZKknppsgnCrJNuPHbQ7ypN6+rC9w+ZbST7XjndP8o0kVyT5ZJJtWvz+7XhVO79woI43tvj3kxw42S8nSZKkSZv2eE+SJEn3bZNNEL4b+O8kb0vyVuC/gXdN8trXApcPHL8TOLaqFgHrgMNb/HBgXVU9Cji2lSPJHsChwGOBJcCHkmw9ybYlSZI0OZsy3pMkSdJ92KQShFV1MvC/gBuANcALquqUjV2XZAHwHOAj7TjAfsDprchy4OC2v7Qd087v38ovBU6tqtur6ofAKmCvyfRbkiRJkzPd8Z4kSZLu+yY9baSqLgMum2L97wVeDzykHe8I3FxV69vxamCXtr8LcE1ra32SW1r5XYDzB+ocvObXkhwBHAGw2267TbGbkiRJmuZ4T5IkSfdxk51iPGVJngvcWFUXDoZHFK2NnJvomrsDVcdX1eKqWjx//vwp91eSJEmSJEnqo5l88fQ+wPOTPBt4ALAt3ROF2yWZ154iXABc28qvBnYFVieZBzwUWDsQHzN4jSRJkiRJkqRNMGNPEFbVG6tqQVUtpFtk5EtV9afAucALW7FlwBlt/8x2TDv/paqqFj+0rXK8O7AI+OZM9VuSJEmSJEnqk5l8gnA8bwBOTfJ24FvACS1+AnBKklV0Tw4eClBVlyY5je59OOuBI6vqri3fbUmSJEmSJGnu2SIJwqo6Dziv7V/JiFWIq+o24JBxrj8GOGbmeihJkiRJkiT104xNMZYkSZIkSZJ072eCUJIkSZIkSeoxE4SSJEmaliQPSPLNJN9JcmmSf2jx3ZN8I8kVST6ZZJsWv387XtXOLxyo640t/v0kBw7El7TYqiRHDcRHtiFJkqSpM0EoSZKk6bod2K+qngA8EViSZG/gncCxVbUIWAcc3sofDqyrqkcBx7ZyJNmDboG6xwJLgA8l2TrJ1sA/AwcBewB/3MoyQRuSJEmaIhOEkiRJmpbq/Kwd3q9tBewHnN7iy4GD2/7Sdkw7v3+StPipVXV7Vf0QWEW3qN1ewKqqurKq7gBOBZa2a8ZrQ5IkSVNkglCSJEnT1p70+zZwI7AC+AFwc1Wtb0VWA7u0/V2AawDa+VuAHQfjQ9eMF99xgjYkSZI0RSYIJUmSNG1VdVdVPRFYQPfE32NGFWufGefc5orfQ5IjkqxMsnLNmjWjikiSJPWeCUJJkiRtsqq6GTgP2BvYLsm8dmoBcG3bXw3sCtDOPxRYOxgfuma8+E8maGO4X8dX1eKqWjx//vxN+YqSJElzlglCSZIkTUuS+Um2a/sPBJ4JXA6cC7ywFVsGnNH2z2zHtPNfqqpq8UPbKse7A4uAbwIXAIvaisXb0C1kcma7Zrw2JEmSNEXzNl5EkiRJGmlnYHlbbXgr4LSq+lySy4BTk7wd+BZwQit/AnBKklV0Tw4eClBVlyY5DbgMWA8cWVV3ASR5FXA2sDVwYlVd2up6wzhtSJIkaYpMEEqSJGlaqupiYM8R8Svp3kc4HL8NOGScuo4BjhkRPws4a7JtSJIkaeqcYixJkiRJkiT1mAlCSZIkSZIkqcdMEEqSJEmSJEk9ZoJQkiRJkiRJ6jEThJIkSZIkSVKPmSCUJEmSJEmSeswEoSRJkiRJktRjJgglSZIkSZKkHjNBKEmSJEmSJPWYCUJJkiRJkiSpx0wQSpIkSZIkST1mglCSJEmSJEnqMROEkiRJkiRJUo+ZIJQkSZIkSZJ6zAShJEmSJEmS1GMmCCVJkiRJkqQeM0EoSZIkSZIk9ZgJQkmSJEmSJKnHTBBKkiRJkiRJPWaCUJIkSZIkSeoxE4SSJEmSJElSj81YgjDJA5J8M8l3klya5B9afPck30hyRZJPJtmmxe/fjle18wsH6npji38/yYEz1WdJkiRJkiSpb2byCcLbgf2q6gnAE4ElSfYG3gkcW1WLgHXA4a384cC6qnoUcGwrR5I9gEOBxwJLgA8l2XoG+y1JkiRJkiT1xowlCKvzs3Z4v7YVsB9weosvBw5u+0vbMe38/knS4qdW1e1V9UNgFbDXTPVbkiRJkiRJ6pMZfQdhkq2TfBu4EVgB/AC4uarWtyKrgV3a/i7ANQDt/C3AjoPxEdcMtnVEkpVJVq5Zs2Ymvo4kSZIkSZI058xogrCq7qqqJwIL6J76e8yoYu0z45wbLz7c1vFVtbiqFs+fP3+6XZYkSZIkSZJ6ZYusYlxVNwPnAXsD2yWZ104tAK5t+6uBXQHa+YcCawfjI66RJEmSJEmStAlmchXj+Um2a/sPBJ4JXA6cC7ywFVsGnNH2z2zHtPNfqqpq8UPbKse7A4uAb85UvyVJkiRJkqQ+mbfxItO2M7C8rTi8FXBaVX0uyWXAqUneDnwLOKGVPwE4JckquicHDwWoqkuTnAZcBqwHjqyqu2aw35IkSZIkSVJvzFiCsKouBvYcEb+SEasQV9VtwCHj1HUMcMzm7qMkSZIkSZLUd1vkHYSSJEmSJEmS7p1MEEqSJEmSJEk9ZoJQkiRJkiRJ6jEThJIkSZIkSVKPmSCUJEmSJEmSeswEoSRJkiRJktRjJgglSZIkSZKkHjNBKEmSJEmSJPWYCUJJkiRJkiSpx0wQSpIkSZIkST1mglCSJEmSJEnqMROEkiRJkiRJUo+ZIJQkSdK0JNk1yblJLk9yaZLXtvgOSVYkuaJ9bt/iSfL+JKuSXJzkSQN1LWvlr0iybCD+5CSXtGvenyQTtSFJkqSpM0EoSZKk6VoP/HVVPQbYGzgyyR7AUcA5VbUIOKcdAxwELGrbEcBx0CX7gKOBpwB7AUcPJPyOa2XHrlvS4uO1IUmSpCkyQShJkqRpqarrquqitn8rcDmwC7AUWN6KLQcObvtLgZOrcz6wXZKdgQOBFVW1tqrWASuAJe3ctlX19aoq4OShuka1IUmSpCkyQShJkqRNlmQhsCfwDWCnqroOuiQi8PBWbBfgmoHLVrfYRPHVI+JM0IYkSZKmyAShJEmSNkmS3wA+Dbyuqn46UdERsZpGfCp9OyLJyiQr16xZM5VLJUmSesMEoSRJkqYtyf3okoMfq6rPtPANbXow7fPGFl8N7Dpw+QLg2o3EF4yIT9TGBqrq+KpaXFWL58+fP70vKUmSNMeZIJQkSdK0tBWFTwAur6r3DJw6ExhbiXgZcMZA/LC2mvHewC1tevDZwAFJtm+LkxwAnN3O3Zpk79bWYUN1jWpDkiRJUzRvtjsgSZKk+6x9gBcDlyT5dov9LfAO4LQkhwNXA4e0c2cBzwZWAb8AXgpQVWuTvA24oJV7a1WtbfuvBE4CHgh8vm1M0IYkSZKmyAShJEmSpqWqvsro9wQC7D+ifAFHjlPXicCJI+IrgceNiN80qg1JkiRNnVOMJUmSJEmSpB4zQShJkiRJkiT1mAlCSZIkSZIkqcdMEEqSJEmSJEk9ZoJQkiRJkiRJ6jEThJIkSZIkSVKPmSCUJEmSJEmSeswEoSRJkiRJktRjJgglSZIkSZKkHjNBKEmSJEmSJPWYCUJJkiRJkiSpx2YsQZhk1yTnJrk8yaVJXtviOyRZkeSK9rl9iyfJ+5OsSnJxkicN1LWslb8iybKZ6rMkSZIkSZLUNzP5BOF64K+r6jHA3sCRSfYAjgLOqapFwDntGOAgYFHbjgCOgy6hCBwNPAXYCzh6LKkoSZIkSZIkadPMWIKwqq6rqova/q3A5cAuwFJgeSu2HDi47S8FTq7O+cB2SXYGDgRWVNXaqv/b3t3HWFaXdwD/PrKYqmjBsBLCkmot1VjbCqyIpVotFhe0hTaaSFpAgpI2WDXGWGttaLVNbJpqo2loCaxCpVgUqcTQ0q1v4AuWBXktIltrZAN11671pcSq7dM/5mw6rrOLu3N27t45n08yuXOfe+45z/xCZh++d845/bUkm5Js2F99AwAAAMCUrMg1CKvqiUmOTfLZJEd094PJQoiY5AnDZkcluX/R27YOtd3Vdz3G+VW1uao2b9++fewfAQAAAABWpf0eEFbVIUmuTvLa7v7GnjZdotZ7qH9/ofvi7l7f3evXrl27b80CAAAAwMTs14Cwqg7OQjh4RXd/cCh/ZTh1OMPjtqG+NcnRi96+LskDe6gDAAAAAMu0P+9iXEkuTXJPd7990UvXJtl5J+JzknxoUf3s4W7GJyb5+nAK8vVJTqmqw4abk5wy1AAAAACAZVqzH/d9UpKzktxZVbcNtTcleVuSq6rqvCRfTvLS4bXrkpyWZEuSh5KcmyTdvaOq3prk5mG7t3T3jv3YNwAAAABMxn4LCLv7k1n6+oFJcvIS23eSC3azr41JNo7XHQAAAACQrNBdjAEAAACAA5OAEAAAAAAmTEAIAAAAABMmIAQAAACACRMQAgAAAMCECQgBAAAAYMIEhAAAAAAwYQJCAAAAAJgwASEAAAAATJiAEAAAAAAmTEAIAAAAABMmIAQAAACACRMQAgAAAMCECQgBAAAAYMIEhAAAAAAwYQJCAAAAAJgwASEAAAAATJiAEAAAAAAmTEAIAAAAABMmIAQAAACACRMQAgAAAMCECQgBAAAAYMIEhAAAAAAwYQJCAAD2WVVtrKptVXXXotrjq2pTVd03PB421Kuq3llVW6rqjqo6btF7zhm2v6+qzllUP76q7hze886qqj0dAwCAvScgBABgOd6TZMMutTcm+Uh3H5PkI8PzJDk1yTHD1/lJLkoWwr4kFyZ5VpITkly4KPC7aNh25/s2PMwxAADYSwJCAAD2WXffkGTHLuXTk1w2fH9ZkjMW1S/vBTclObSqjkzywiSbuntHd38tyaYkG4bXHtfdn+nuTnL5Lvta6hgAAOwlASEAAGM7orsfTJLh8QlD/agk9y/abutQ21N96xL1PR3j+1TV+VW1uao2b9++fVk/FADAaiUgBABgpdQStd6H+g+tuy/u7vXdvX7t2rV781YAgMkQEAIAMLavDKcHZ3jcNtS3Jjl60XbrkjzwMPV1S9T3dAwAAPaSgBAAgLFdm2TnnYjPSfKhRfWzh7sZn5jk68PpwdcnOaWqDhtuTnJKkuuH175ZVScOdy8+e5d9LXUMAAD20ppZNwAAwPyqqiuTPC/J4VW1NQt3I35bkquq6rwkX07y0mHz65KclmRLkoeSnJsk3b2jqt6a5OZhu7d0984bn/xWFu6U/Kgkfz98ZQ/HAABgLwkIAQDYZ9195m5eOnmJbTvJBbvZz8YkG5eob07y9CXq/7HUMQAA2Hv77RTjqtpYVduq6q5FtcdX1aaqum94PGyoV1W9s6q2VNUdVXXcovecM2x/X1Wds9SxAAAAAIB9sz+vQfieJBt2qb0xyUe6+5gkHxmeJ8mpSY4Zvs5PclGyEChm4TSVZyU5IcmFO0NFAAAAAGD59ltA2N03JNmxS/n0JJcN31+W5IxF9ct7wU1JDh3uRvfCJJu6e0d3fy3Jpvxg6AgAAAAA7KOVvovxEcPd6DI8PmGoH5Xk/kXbbR1qu6sDAAAAACNY6YBwd2qJWu+h/oM7qDq/qjZX1ebt27eP2hwAAAAArFYrHRB+ZTh1OMPjtqG+NcnRi7Zbl+SBPdR/QHdf3N3ru3v92rVrR28cAAAAAFajlQ4Ir02y807E5yT50KL62cPdjE9M8vXhFOTrk5xSVYcNNyc5ZagBAAAAACNYs792XFVXJnleksOramsW7kb8tiRXVdV5Sb6c5KXD5tclOS3JliQPJTk3Sbp7R1W9NcnNw3Zv6e5db3wCAAAAAOyj/RYQdveZu3np5CW27SQX7GY/G5NsHLE1AAAAAGBwoNykBAAAAACYAQEhAAAAAEyYgBAAAAAAJkxACAAAAAATJiAEAAAAgAkTEAIAAADAhAkIAQAAAGDCBIQAAAAAMGECQgAAAACYMAEhAAAAAEyYgBAAAAAAJkxACAAAAAATJiAEAAAAgAkTEAIAAADAhAkIAQAAAGDCBIQAAAAAMGECQgAAAACYMAEhAAAAAEyYgBAAAAAAJkxACAAAAAATJiAEAAAAgAkTEAIAAADAhAkIAQAAAGDCBIQAAAAAMGECQgAAAACYMAEhAAAAAEyYgBAAAAAAJkxACAAAAAATJiAEAAAAgAkTEAIAAADAhAkIAQAAAGDCBIQAAAAAMGECQgAAAACYsLkJCKtqQ1XdW1VbquqNs+4HAIDZMyMCACzfXASEVXVQkr9IcmqSpyU5s6qeNtuuAACYJTMiAMA45iIgTHJCki3d/cXu/k6S9yU5fcY9AQAwW2ZEAIARVHfPuoeHVVUvSbKhu18xPD8rybO6+1WLtjk/yfnD06ckuXfFG907hyf56qybWCWs5Tis4zis43is5Tis4zjmYR1/rLvXzrqJlWRG5GFYy3FYx3FYx3FYx/FYy3HMwzr+UDPimpXoZAS1RO37ks3uvjjJxSvTzvJV1ebuXj/rPlYDazkO6zgO6zgeazkO6zgO63jAMiOyW9ZyHNZxHNZxHNZxPNZyHKtpHeflFOOtSY5e9Hxdkgdm1AsAAAcGMyIAwAjmJSC8OckxVfWkqnpkkpcluXbGPQEAMFtmRACAEczFKcbd/b2qelWS65MclGRjd98947aWa25OdZkD1nIc1nEc1nE81nIc1nEc1vEAZEbkYVjLcVjHcVjHcVjH8VjLcayadZyLm5QAAAAAAPvHvJxiDAAAAADsBwJCAAAAAJgwAeEMVNWGqrq3qrZU1Rtn3c+8qqqNVbWtqu6adS/zrKqOrqqPVdU9VXV3Vb1m1j3No6r6kar656q6fVjHP5x1T/Osqg6qqs9V1Ydn3cu8qqovVdWdVXVbVW2edT/zrKoOraoPVNXnh9+Vz551T6xOZsRxmBGXz3w4HjPiuMyIy2dGHM9qmxFdg3CFVdVBSb6Q5JeSbM3C3ffO7O5/mWljc6iqnpvkW0ku7+6nz7qfeVVVRyY5srtvrarHJrklyRn+m9w7VVVJHtPd36qqg5N8MslruvumGbc2l6rqdUnWJ3lcd7941v3Mo6r6UpL13f3VWfcy76rqsiQ3dvclw51yH93d/znrvlhdzIjjMSMun/lwPGbEcZkRl8+MOJ7VNiP6C8KVd0KSLd39xe7+TpL3JTl9xj3Npe6+IcmOWfcx77r7we6+dfj+m0nuSXLUbLuaP73gW8PTg4cvn8Dsg6pal+RFSS6ZdS9QVY9L8twklyZJd39nngc/DmhmxJGYEZfPfDgeM+J4zIgcSFbjjCggXHlHJbl/0fOt8Y8tB4iqemKSY5N8dradzKfhlIfbkmxLsqm7reO++fMkb0jyv7NuZM51kn+sqluq6vxZNzPHfjzJ9iTvHk5puqSqHjPrpliVzIgckMyHy2dGHI0ZcRxmxHGsuhlRQLjyaomaT5CYuao6JMnVSV7b3d+YdT/zqLv/p7ufkWRdkhOqymlNe6mqXpxkW3ffMuteVoGTuvu4JKcmuWA45Y69tybJcUku6u5jk/xXEteGY38wI3LAMR+Ow4y4fGbEUZkRx7HqZkQB4crbmuToRc/XJXlgRr1AkmS4HsrVSa7o7g/Oup95N/xp+ceTbJhxK/PopCS/Mlwb5X1JfrGq3jvbluZTdz8wPG5Lck0WTl9k721NsnXRX3t8IAvDIIzNjMgBxXw4PjPispgRR2JGHM2qmxEFhCvv5iTHVNWThotYvizJtTPuiQkbLpx8aZJ7uvvts+5nXlXV2qo6dPj+UUlekOTzs+1q/nT373b3uu5+YhZ+P360u39jxm3Nnap6zHBR+QynOpySxN0890F3/3uS+6vqKUPp5CQu0s/+YEbkgGE+HI8ZcRxmxHGYEcezGmfENbNuYGq6+3tV9aok1yc5KMnG7r57xm3Npaq6MsnzkhxeVVuTXNjdl862q7l0UpKzktw5XBslSd7U3dfNsKd5dGSSy4a7UD4iyVXd/eEZ98R0HZHkmoX/v8uaJH/T3f8w25bm2m8nuWIIbb6Y5NwZ98MqZEYcjxlxFObD8ZgROZCYEce1qmbE6nZpE8HRYbgAAAOvSURBVAAAAACYKqcYAwAAAMCECQgBAAAAYMIEhAAAAAAwYQJCAAAAAJgwASEAAAAATJiAEJikqvqDqnr9iPt7alXdVlWfq6onj7XfRfv/eFWtH3u/AAD8PzMiMFUCQoBxnJHkQ919bHf/66ybAQDggGBGBOaCgBCYjKr6vaq6t6r+KclThtorq+rmqrq9qq6uqkdX1WOr6t+q6uBhm8dV1Zeq6uCqekZV3VRVd1TVNVV1WFWdluS1SV5RVR+rqjdU1auH976jqj46fH9yVb13+P6UqvpMVd1aVe+vqkOG+vFV9YmquqWqrq+qI3f5GR5RVZdV1R+t2MIBAKxiZkQAASEwEVV1fJKXJTk2ya8leebw0ge7+5nd/bNJ7klyXnd/M8nHk7xo2OZlSa7u7u8muTzJ73T3zyS5M8mF3X1dkr9M8o7ufn6SG5I8Z3jv+iSHDIPkzye5saoOT/LmJC/o7uOSbE7yumGbdyV5SXcfn2Rjkj9e9GOsSXJFki9095tHXB4AgEkyIwIsWDPrBgBWyHOSXNPdDyVJVV071J8+fNJ6aJJDklw/1C9J8oYkf5fk3CSvrKofTXJod39i2OayJO9f4li3JDm+qh6b5L+T3JqFIfA5SV6d5MQkT0vyqapKkkcm+UwWPrF+epJNQ/2gJA8u2u9fJbmquxcPhAAA7DszIkAEhMC09BK19yQ5o7tvr6qXJ3leknT3p6rqiVX1C0kO6u67huHv4Q/S/d2q+lIWhsZPJ7kjyfOTPDkLn0A/Ocmm7j5z8fuq6qeT3N3dz97Nrj+d5PlV9Wfd/e0fphcAAB6WGRGYPKcYA1NxQ5JfrapHDZ/a/vJQf2ySB4dTN359l/dcnuTKJO9Oku7+epKvVdXOU0POSvKJLO2GJK8fHm9M8ptJbuvuTnJTkpOq6ieSZLimzU8muTfJ2qp69lA/uKp+atE+L01yXZL3V5UPeAAAls+MCBABITAR3X1rkr9NcluSq7MwkCXJ7yf5bJJNST6/y9uuSHJYFgbAnc5J8qdVdUeSZyR5y24OeWOSI5N8pru/kuTbO4/Z3duTvDzJlcN+bkry1O7+TpKXJPmTqrp96PXndvk53p6F01H+uqr8DgcAWAYzIsCCWvigAoBdVdVLkpze3WfNuhcAAA4MZkRgNfLnxwBLqKp3JTk1yWmz7gUAgAODGRFYrfwFIQAAAABMmGsTAAAAAMCECQgBAAAAYMIEhAAAAAAwYQJCAAAAAJgwASEAAAAATNj/AT+NX0tGM0FAAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of dayofweek\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "sns.countplot(x='dayofweek', data=data, ax=ax[0])\n",
    "ax[0].set_title('Count Plot of dayofweek', fontsize=16)\n",
    "\n",
    "sns.barplot(x='dayofweek', y='count', data=data, ax=ax[1])\n",
    "ax[1].set_title('Count vs. dayofweek', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Questions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>video_id</th>\n",
       "      <th>count</th>\n",
       "      <th>date</th>\n",
       "      <th>length</th>\n",
       "      <th>language</th>\n",
       "      <th>upload_date</th>\n",
       "      <th>quality</th>\n",
       "      <th>interval</th>\n",
       "      <th>dayofweek</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2303</td>\n",
       "      <td>22</td>\n",
       "      <td>2015-01-07</td>\n",
       "      <td>1071</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-10</td>\n",
       "      <td>1080p</td>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1193</td>\n",
       "      <td>54854</td>\n",
       "      <td>2015-01-12</td>\n",
       "      <td>770</td>\n",
       "      <td>Other</td>\n",
       "      <td>2014-12-07</td>\n",
       "      <td>720p</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1219</td>\n",
       "      <td>1788779</td>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>904</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-12</td>\n",
       "      <td>240p</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1472</td>\n",
       "      <td>234</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>157</td>\n",
       "      <td>Other</td>\n",
       "      <td>2014-12-10</td>\n",
       "      <td>240p</td>\n",
       "      <td>25</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2947</td>\n",
       "      <td>14407</td>\n",
       "      <td>2015-01-08</td>\n",
       "      <td>446</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-19</td>\n",
       "      <td>480p</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   video_id    count       date  length language upload_date quality  \\\n",
       "0      2303       22 2015-01-07    1071       Cn  2014-12-10   1080p   \n",
       "1      1193    54854 2015-01-12     770    Other  2014-12-07    720p   \n",
       "2      1219  1788779 2015-01-03     904       Cn  2014-12-12    240p   \n",
       "3      1472      234 2015-01-04     157    Other  2014-12-10    240p   \n",
       "4      2947    14407 2015-01-08     446       Cn  2014-12-19    480p   \n",
       "\n",
       "   interval  dayofweek  \n",
       "0        28          2  \n",
       "1        36          0  \n",
       "2        22          5  \n",
       "3        25          6  \n",
       "4        20          3  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ct_mean</th>\n",
       "      <th>ct_std</th>\n",
       "      <th>ct_min</th>\n",
       "      <th>ct_25%</th>\n",
       "      <th>ct_50%</th>\n",
       "      <th>ct_75%</th>\n",
       "      <th>ct_max</th>\n",
       "      <th>cg_mean</th>\n",
       "      <th>cg_std</th>\n",
       "      <th>cg_min</th>\n",
       "      <th>cg_25%</th>\n",
       "      <th>cg_50%</th>\n",
       "      <th>cg_75%</th>\n",
       "      <th>cg_max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>video_id</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.063560e+04</td>\n",
       "      <td>39200.460092</td>\n",
       "      <td>19382.0</td>\n",
       "      <td>41099.0</td>\n",
       "      <td>65907.0</td>\n",
       "      <td>96335.0</td>\n",
       "      <td>140460.0</td>\n",
       "      <td>-0.127437</td>\n",
       "      <td>0.092392</td>\n",
       "      <td>-0.271522</td>\n",
       "      <td>-0.186381</td>\n",
       "      <td>-0.151384</td>\n",
       "      <td>-0.067977</td>\n",
       "      <td>0.030277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.737141e+06</td>\n",
       "      <td>114254.355156</td>\n",
       "      <td>1550493.0</td>\n",
       "      <td>1673415.5</td>\n",
       "      <td>1718352.0</td>\n",
       "      <td>1782226.5</td>\n",
       "      <td>2011096.0</td>\n",
       "      <td>-0.014184</td>\n",
       "      <td>0.061794</td>\n",
       "      <td>-0.084904</td>\n",
       "      <td>-0.061459</td>\n",
       "      <td>-0.043876</td>\n",
       "      <td>0.030687</td>\n",
       "      <td>0.095038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.292781e+06</td>\n",
       "      <td>218636.897779</td>\n",
       "      <td>2016210.0</td>\n",
       "      <td>2132336.5</td>\n",
       "      <td>2247587.0</td>\n",
       "      <td>2436222.5</td>\n",
       "      <td>2653063.0</td>\n",
       "      <td>0.008923</td>\n",
       "      <td>0.054069</td>\n",
       "      <td>-0.075863</td>\n",
       "      <td>-0.028293</td>\n",
       "      <td>-0.001068</td>\n",
       "      <td>0.056393</td>\n",
       "      <td>0.097053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.740392e+06</td>\n",
       "      <td>169611.440727</td>\n",
       "      <td>2474228.0</td>\n",
       "      <td>2611162.0</td>\n",
       "      <td>2719547.0</td>\n",
       "      <td>2880268.5</td>\n",
       "      <td>2984146.0</td>\n",
       "      <td>0.011310</td>\n",
       "      <td>0.050495</td>\n",
       "      <td>-0.063991</td>\n",
       "      <td>-0.027125</td>\n",
       "      <td>0.001606</td>\n",
       "      <td>0.050860</td>\n",
       "      <td>0.090804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>4.479973e+05</td>\n",
       "      <td>237137.305768</td>\n",
       "      <td>169730.0</td>\n",
       "      <td>255574.5</td>\n",
       "      <td>388594.0</td>\n",
       "      <td>609508.0</td>\n",
       "      <td>983058.0</td>\n",
       "      <td>-0.111811</td>\n",
       "      <td>0.107193</td>\n",
       "      <td>-0.269337</td>\n",
       "      <td>-0.177432</td>\n",
       "      <td>-0.133447</td>\n",
       "      <td>-0.012729</td>\n",
       "      <td>0.031766</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               ct_mean         ct_std     ct_min     ct_25%     ct_50%  \\\n",
       "video_id                                                                 \n",
       "1         7.063560e+04   39200.460092    19382.0    41099.0    65907.0   \n",
       "2         1.737141e+06  114254.355156  1550493.0  1673415.5  1718352.0   \n",
       "3         2.292781e+06  218636.897779  2016210.0  2132336.5  2247587.0   \n",
       "4         2.740392e+06  169611.440727  2474228.0  2611162.0  2719547.0   \n",
       "5         4.479973e+05  237137.305768   169730.0   255574.5   388594.0   \n",
       "\n",
       "             ct_75%     ct_max   cg_mean    cg_std    cg_min    cg_25%  \\\n",
       "video_id                                                                 \n",
       "1           96335.0   140460.0 -0.127437  0.092392 -0.271522 -0.186381   \n",
       "2         1782226.5  2011096.0 -0.014184  0.061794 -0.084904 -0.061459   \n",
       "3         2436222.5  2653063.0  0.008923  0.054069 -0.075863 -0.028293   \n",
       "4         2880268.5  2984146.0  0.011310  0.050495 -0.063991 -0.027125   \n",
       "5          609508.0   983058.0 -0.111811  0.107193 -0.269337 -0.177432   \n",
       "\n",
       "            cg_50%    cg_75%    cg_max  \n",
       "video_id                                \n",
       "1        -0.151384 -0.067977  0.030277  \n",
       "2        -0.043876  0.030687  0.095038  \n",
       "3        -0.001068  0.056393  0.097053  \n",
       "4         0.001606  0.050860  0.090804  \n",
       "5        -0.133447 -0.012729  0.031766  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def parse_data(df):\n",
    "    \"\"\" function to calculate the statistics for \"\"\"\n",
    "    counts = df.sort_values(by='date')['count'].values\n",
    "    change = (counts[1:] - counts[:-1]) / counts[:-1]\n",
    "    \n",
    "    index = ['ct_mean', 'ct_std', 'ct_min', 'ct_25%', 'ct_50%', 'ct_75%', 'ct_max', \n",
    "             'cg_mean', 'cg_std', 'cg_min', 'cg_25%', 'cg_50%', 'cg_75%', 'cg_max']\n",
    "    \n",
    "    ct_vals = pd.Series(counts).describe()\n",
    "    cg_vals = pd.Series(change).describe()\n",
    "    \n",
    "    ct_values = [ct_vals['mean'], ct_vals['std'], ct_vals['min'], ct_vals['25%'], \n",
    "                 ct_vals['50%'], ct_vals['75%'], ct_vals['max']]\n",
    "    cg_values = [cg_vals['mean'], cg_vals['std'], cg_vals['min'], cg_vals['25%'], \n",
    "                 cg_vals['50%'], cg_vals['75%'], cg_vals['max']]\n",
    "    \n",
    "    return pd.Series(ct_values + cg_values, index=index)\n",
    "\n",
    "data_stats = data.groupby('video_id').apply(parse_data)\n",
    "data_stats.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Popularity\n",
    "fig, ax = plt.subplots(figsize=(8, 4))\n",
    "sns.distplot(data_stats['ct_mean'], ax=ax, hist_kws=hist_kws)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. For `Stable and Popular` videos, based on above figure, we can manually set some threshold, for example, set `ct_mean` cutoff threshold to be $1,500,000$, we can define the popular `Stable and Popular` videos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ct_mean</th>\n",
       "      <th>ct_std</th>\n",
       "      <th>ct_min</th>\n",
       "      <th>ct_25%</th>\n",
       "      <th>ct_50%</th>\n",
       "      <th>ct_75%</th>\n",
       "      <th>ct_max</th>\n",
       "      <th>cg_mean</th>\n",
       "      <th>cg_std</th>\n",
       "      <th>cg_min</th>\n",
       "      <th>cg_25%</th>\n",
       "      <th>cg_50%</th>\n",
       "      <th>cg_75%</th>\n",
       "      <th>cg_max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>video_id</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.737141e+06</td>\n",
       "      <td>114254.355156</td>\n",
       "      <td>1550493.0</td>\n",
       "      <td>1673415.5</td>\n",
       "      <td>1718352.0</td>\n",
       "      <td>1782226.5</td>\n",
       "      <td>2011096.0</td>\n",
       "      <td>-0.014184</td>\n",
       "      <td>0.061794</td>\n",
       "      <td>-0.084904</td>\n",
       "      <td>-0.061459</td>\n",
       "      <td>-0.043876</td>\n",
       "      <td>0.030687</td>\n",
       "      <td>0.095038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.292781e+06</td>\n",
       "      <td>218636.897779</td>\n",
       "      <td>2016210.0</td>\n",
       "      <td>2132336.5</td>\n",
       "      <td>2247587.0</td>\n",
       "      <td>2436222.5</td>\n",
       "      <td>2653063.0</td>\n",
       "      <td>0.008923</td>\n",
       "      <td>0.054069</td>\n",
       "      <td>-0.075863</td>\n",
       "      <td>-0.028293</td>\n",
       "      <td>-0.001068</td>\n",
       "      <td>0.056393</td>\n",
       "      <td>0.097053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.740392e+06</td>\n",
       "      <td>169611.440727</td>\n",
       "      <td>2474228.0</td>\n",
       "      <td>2611162.0</td>\n",
       "      <td>2719547.0</td>\n",
       "      <td>2880268.5</td>\n",
       "      <td>2984146.0</td>\n",
       "      <td>0.011310</td>\n",
       "      <td>0.050495</td>\n",
       "      <td>-0.063991</td>\n",
       "      <td>-0.027125</td>\n",
       "      <td>0.001606</td>\n",
       "      <td>0.050860</td>\n",
       "      <td>0.090804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2.049360e+06</td>\n",
       "      <td>157190.210173</td>\n",
       "      <td>1776574.0</td>\n",
       "      <td>1950028.5</td>\n",
       "      <td>2042499.0</td>\n",
       "      <td>2154066.5</td>\n",
       "      <td>2328022.0</td>\n",
       "      <td>0.004013</td>\n",
       "      <td>0.055904</td>\n",
       "      <td>-0.090772</td>\n",
       "      <td>-0.034195</td>\n",
       "      <td>0.009304</td>\n",
       "      <td>0.046501</td>\n",
       "      <td>0.081409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1.593414e+06</td>\n",
       "      <td>249941.247042</td>\n",
       "      <td>1301816.0</td>\n",
       "      <td>1380598.0</td>\n",
       "      <td>1502636.0</td>\n",
       "      <td>1793568.0</td>\n",
       "      <td>2056101.0</td>\n",
       "      <td>-0.011086</td>\n",
       "      <td>0.063787</td>\n",
       "      <td>-0.095199</td>\n",
       "      <td>-0.074206</td>\n",
       "      <td>-0.005127</td>\n",
       "      <td>0.049045</td>\n",
       "      <td>0.092254</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               ct_mean         ct_std     ct_min     ct_25%     ct_50%  \\\n",
       "video_id                                                                 \n",
       "2         1.737141e+06  114254.355156  1550493.0  1673415.5  1718352.0   \n",
       "3         2.292781e+06  218636.897779  2016210.0  2132336.5  2247587.0   \n",
       "4         2.740392e+06  169611.440727  2474228.0  2611162.0  2719547.0   \n",
       "8         2.049360e+06  157190.210173  1776574.0  1950028.5  2042499.0   \n",
       "14        1.593414e+06  249941.247042  1301816.0  1380598.0  1502636.0   \n",
       "\n",
       "             ct_75%     ct_max   cg_mean    cg_std    cg_min    cg_25%  \\\n",
       "video_id                                                                 \n",
       "2         1782226.5  2011096.0 -0.014184  0.061794 -0.084904 -0.061459   \n",
       "3         2436222.5  2653063.0  0.008923  0.054069 -0.075863 -0.028293   \n",
       "4         2880268.5  2984146.0  0.011310  0.050495 -0.063991 -0.027125   \n",
       "8         2154066.5  2328022.0  0.004013  0.055904 -0.090772 -0.034195   \n",
       "14        1793568.0  2056101.0 -0.011086  0.063787 -0.095199 -0.074206   \n",
       "\n",
       "            cg_50%    cg_75%    cg_max  \n",
       "video_id                                \n",
       "2        -0.043876  0.030687  0.095038  \n",
       "3        -0.001068  0.056393  0.097053  \n",
       "4         0.001606  0.050860  0.090804  \n",
       "8         0.009304  0.046501  0.081409  \n",
       "14       -0.005127  0.049045  0.092254  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popular_video = data_stats[data_stats['ct_mean'] > 1500000]\n",
    "popular_video.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. For `Hot` videos, we can use the video's daily change rate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Popularity\n",
    "fig, ax = plt.subplots(figsize=(8, 4))\n",
    "sns.distplot(data_stats['cg_mean'], ax=ax, hist_kws=hist_kws)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From above figure, it's clear that if we set the cutoff threshold for change rate, we can separate a group of videos that the mean daily change rate is above $20\\%$, which can be defined a `Hot` videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ct_mean</th>\n",
       "      <th>ct_std</th>\n",
       "      <th>ct_min</th>\n",
       "      <th>ct_25%</th>\n",
       "      <th>ct_50%</th>\n",
       "      <th>ct_75%</th>\n",
       "      <th>ct_max</th>\n",
       "      <th>cg_mean</th>\n",
       "      <th>cg_std</th>\n",
       "      <th>cg_min</th>\n",
       "      <th>cg_25%</th>\n",
       "      <th>cg_50%</th>\n",
       "      <th>cg_75%</th>\n",
       "      <th>cg_max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>video_id</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8903.133333</td>\n",
       "      <td>10248.629782</td>\n",
       "      <td>591.0</td>\n",
       "      <td>1882.5</td>\n",
       "      <td>5483.0</td>\n",
       "      <td>11318.5</td>\n",
       "      <td>34789.0</td>\n",
       "      <td>0.353819</td>\n",
       "      <td>0.220112</td>\n",
       "      <td>0.006865</td>\n",
       "      <td>0.238332</td>\n",
       "      <td>0.324975</td>\n",
       "      <td>0.416434</td>\n",
       "      <td>0.780195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>91228.200000</td>\n",
       "      <td>91574.506421</td>\n",
       "      <td>4746.0</td>\n",
       "      <td>16688.0</td>\n",
       "      <td>45930.0</td>\n",
       "      <td>153985.5</td>\n",
       "      <td>264570.0</td>\n",
       "      <td>0.350798</td>\n",
       "      <td>0.223287</td>\n",
       "      <td>-0.000643</td>\n",
       "      <td>0.171082</td>\n",
       "      <td>0.373361</td>\n",
       "      <td>0.514471</td>\n",
       "      <td>0.629066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>6184.400000</td>\n",
       "      <td>9384.882059</td>\n",
       "      <td>494.0</td>\n",
       "      <td>1190.0</td>\n",
       "      <td>1705.0</td>\n",
       "      <td>6231.5</td>\n",
       "      <td>33208.0</td>\n",
       "      <td>0.381382</td>\n",
       "      <td>0.313682</td>\n",
       "      <td>-0.048170</td>\n",
       "      <td>0.026856</td>\n",
       "      <td>0.471749</td>\n",
       "      <td>0.656678</td>\n",
       "      <td>0.740953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>105011.600000</td>\n",
       "      <td>132346.803029</td>\n",
       "      <td>6152.0</td>\n",
       "      <td>14399.0</td>\n",
       "      <td>30084.0</td>\n",
       "      <td>152599.5</td>\n",
       "      <td>405278.0</td>\n",
       "      <td>0.367767</td>\n",
       "      <td>0.239208</td>\n",
       "      <td>-0.045739</td>\n",
       "      <td>0.206640</td>\n",
       "      <td>0.300966</td>\n",
       "      <td>0.502638</td>\n",
       "      <td>0.778389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>78372.866667</td>\n",
       "      <td>70559.053747</td>\n",
       "      <td>9118.0</td>\n",
       "      <td>16789.5</td>\n",
       "      <td>45226.0</td>\n",
       "      <td>131717.0</td>\n",
       "      <td>212419.0</td>\n",
       "      <td>0.271285</td>\n",
       "      <td>0.228626</td>\n",
       "      <td>-0.028478</td>\n",
       "      <td>0.046231</td>\n",
       "      <td>0.293353</td>\n",
       "      <td>0.455947</td>\n",
       "      <td>0.665369</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                ct_mean         ct_std  ct_min   ct_25%   ct_50%    ct_75%  \\\n",
       "video_id                                                                     \n",
       "10          8903.133333   10248.629782   591.0   1882.5   5483.0   11318.5   \n",
       "13         91228.200000   91574.506421  4746.0  16688.0  45930.0  153985.5   \n",
       "15          6184.400000    9384.882059   494.0   1190.0   1705.0    6231.5   \n",
       "28        105011.600000  132346.803029  6152.0  14399.0  30084.0  152599.5   \n",
       "29         78372.866667   70559.053747  9118.0  16789.5  45226.0  131717.0   \n",
       "\n",
       "            ct_max   cg_mean    cg_std    cg_min    cg_25%    cg_50%  \\\n",
       "video_id                                                               \n",
       "10         34789.0  0.353819  0.220112  0.006865  0.238332  0.324975   \n",
       "13        264570.0  0.350798  0.223287 -0.000643  0.171082  0.373361   \n",
       "15         33208.0  0.381382  0.313682 -0.048170  0.026856  0.471749   \n",
       "28        405278.0  0.367767  0.239208 -0.045739  0.206640  0.300966   \n",
       "29        212419.0  0.271285  0.228626 -0.028478  0.046231  0.293353   \n",
       "\n",
       "            cg_75%    cg_max  \n",
       "video_id                      \n",
       "10        0.416434  0.780195  \n",
       "13        0.514471  0.629066  \n",
       "15        0.656678  0.740953  \n",
       "28        0.502638  0.778389  \n",
       "29        0.455947  0.665369  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hot_video = data_stats[data_stats['cg_mean'] > 0.2]\n",
    "hot_video.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. For `Everything else`, the rest videos are selected."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>video_id</th>\n",
       "      <th>count</th>\n",
       "      <th>date</th>\n",
       "      <th>length</th>\n",
       "      <th>language</th>\n",
       "      <th>upload_date</th>\n",
       "      <th>quality</th>\n",
       "      <th>interval</th>\n",
       "      <th>dayofweek</th>\n",
       "      <th>hot</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2303</td>\n",
       "      <td>22</td>\n",
       "      <td>2015-01-07</td>\n",
       "      <td>1071</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-10</td>\n",
       "      <td>1080p</td>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1193</td>\n",
       "      <td>54854</td>\n",
       "      <td>2015-01-12</td>\n",
       "      <td>770</td>\n",
       "      <td>Other</td>\n",
       "      <td>2014-12-07</td>\n",
       "      <td>720p</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1219</td>\n",
       "      <td>1788779</td>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>904</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-12</td>\n",
       "      <td>240p</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1472</td>\n",
       "      <td>234</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>157</td>\n",
       "      <td>Other</td>\n",
       "      <td>2014-12-10</td>\n",
       "      <td>240p</td>\n",
       "      <td>25</td>\n",
       "      <td>6</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2947</td>\n",
       "      <td>14407</td>\n",
       "      <td>2015-01-08</td>\n",
       "      <td>446</td>\n",
       "      <td>Cn</td>\n",
       "      <td>2014-12-19</td>\n",
       "      <td>480p</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   video_id    count       date  length language upload_date quality  \\\n",
       "0      2303       22 2015-01-07    1071       Cn  2014-12-10   1080p   \n",
       "1      1193    54854 2015-01-12     770    Other  2014-12-07    720p   \n",
       "2      1219  1788779 2015-01-03     904       Cn  2014-12-12    240p   \n",
       "3      1472      234 2015-01-04     157    Other  2014-12-10    240p   \n",
       "4      2947    14407 2015-01-08     446       Cn  2014-12-19    480p   \n",
       "\n",
       "   interval  dayofweek    hot  \n",
       "0        28          2  False  \n",
       "1        36          0  False  \n",
       "2        22          5  False  \n",
       "3        25          6  False  \n",
       "4        20          3   True  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['hot'] = False\n",
    "data.loc[data['video_id'].isin(hot_video.index), 'hot'] = True\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of length\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "sns.distplot(data[data['hot']==True]['length'], label='Hot', ax=ax, hist_kws=hist_kws)\n",
    "sns.distplot(data[data['hot']==False]['length'], label='Not Hot', ax=ax, hist_kws=hist_kws)\n",
    "ax.legend(fontsize=12)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of language\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "tmp = data.groupby('hot')['language'].apply(lambda x: x.value_counts(normalize=True)).unstack()\n",
    "tmp.plot(kind='bar', ax=ax[0])\n",
    "\n",
    "sns.barplot(x='language', y='count', data=data, hue='hot', ax=ax[1])\n",
    "ax[1].set_title('Count vs. language', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of quality\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "tmp = data.groupby('hot')['quality'].apply(lambda x: x.value_counts(normalize=True)).unstack()\n",
    "tmp.plot(kind='bar', ax=ax[0])\n",
    "\n",
    "sns.barplot(x='quality', y='count', hue='hot', data=data, ax=ax[1])\n",
    "ax[1].set_title('Count vs. quality', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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yC7vtthuf/vSnOeSQQ5gzZw4XX3wxixcvZosttmh16JIkSWoC80VJY40FQklaTzNnzmT27NkAdHZ2cs899/D444/ztre9DYD58+dzww03tDJESZIktZD5oqSxxgKhJK2nzTbbbO3niRMn8vjjj7cwGkmSJI025ouSxhoLhJK0kV75yleyzTbb8D//8z8AXHjhhWu/Hd5yyy1ZtWpVK8OTJElSi5kvShrtNml1AJI0HlxwwQUcffTRPP300+y8886cd955ABxxxBEcffTRbLHFFtx4442uKyNJUqmrq4tKpUJHRwfd3d2tDkdqOPNFSaNZZGarY2iIOXPm5MKFC1sdhqQmu/POO3n961/f6jAa5o4Hl9dsjyeXjev3llRbRCzKzDmtjmMsMldsvXnz5tHX18fUqVPp6elpdThqI+M9XxxMu7631O5Gmi86xViSJEmSJElqYxYIJUmSJEmSpDbmGoSS1CY6F9SevrXojHlNjkSSJEmSNJo4glCSJEmSJElqYxYIJUmSJEmSpDZmgVCSJEmSJElqY65BKGlcG2zdvQ01kvX6Jk6cyG677bb2+Nvf/jYzZsyo2ff+++/nPe95D7fddlu9QpQkSdJ6MF+UJAuEklR3W2yxBYsXL251GHXnJieS+kXEucB7gEczc9ey7Qzgz4DngXuAD2fm4+W5E4EjgReB4zLzmrJ9P+DLwETg65n5+bJ9JnApsC3wS+BDmfl8RGwG9ACdwArg0My8f6hnSNJoNF7zRUljV8OmGEfEThHx44i4MyJuj4hPlu3bRsS1EXF3+Xubsj0i4qyIWBIRt0TE7lX3ml/2vzsi5jcqZklqlPvvv5+3vOUt7L777uy+++787Gc/e1mf22+/nT322IPZs2fzxje+kbvvvhuAiy66aG37KSf8DS+++GKzw5ekgc4H9hvQdi2wa2a+EfgtcCJAROwCHAa8obzmKxExMSImAmcD+wO7AIeXfQFOB87MzFnAYxSFP8rfj2Xm64Azy36DPqPeLy1JjVSvfPHjH/+4+aKk9dbINQhXA3+Tma8H9gKOKZO3E4DryoTvuvIYiuRwVvlzFPBVKAqKwMnAnsAewMn9RUVJGo2eeeYZZs+ezezZsznooIMA2GGHHbj22mv55S9/yWWXXcZxxx33suu+9rWv8clPfpLFixezcOFCpk2bxp133slll13GT3/6UxYvXsyEiRP57reuaPYrSdI6MvMGYOWAtv/OzNXl4U3AtPLzgcClmflcZt4HLKHI6fYAlmTmvZn5PMWIwQMjIoB3AP3/sbsAeG/VvS4oP18B7Fv2H+wZkjQqNTJfnDhxIhdffHGzX0nSGNewKcaZ+TDwcPl5VUTcCUylSOD2KbtdAFwPHF+292RmAjdFxNYRsWPZ99rMXAkQEddSfDN8SaNil6SNUWvKyAsvvMCxxx67Nmn77W9/+7Lr9t57b0477TR6e3s5+OCDmTVrFtdddx2LFi3izW9+MwBPrHqS7bbbvinvIUkb4SPAZeXnqRQFw369ZRvAgwPa9wS2Ax6vKjZW95/af01mro6IJ8r+Qz1DkkadRuaLzzzzDDvssENT3kPS+NGUNQgjYgbwh8DPgVeVxUMy8+GI6P8v19qEr9Sf2A3WLkljxplnnsmrXvUqfv3rX7NmzRo233zzl/V5//vfz5577sn3vvc93vWud/H1r3+dzGT+/Pl87nOfA+COB5c3O3RJWi8R8fcUM0n6h69EjW5J7ZksOUT/oe411DXVsR1FMVOF6dOn17hEY0VXVxeVSoWOjg66u7tbHY5UF/XKFyVpQzRyijEAEfEK4ErgrzPzd0N1rdE24oSvfNZREbEwIhYuW7Zs/YOVpAZ54okn2HHHHZkwYQIXXnhhzXVh7r33XnbeeWeOO+44DjjgAG655Rb23XdfrrjiCh599FEAHn/8MR7qffBl10rSaFCuFf0e4APlrBAovtzdqarbNOChIdqXA1tHxCYD2te5V3n+lRRTnQe71zoy85zMnJOZc6ZMmbKhr6lRoFKp0NfXR6VSaXUoUt3UK19cuXIlDzzwQLPDlzTGNXQEYURsSlEcvDgz/7NsfiQidixHD+4IPFq2D5U87jOg/fpaz8vMc4BzAObMmVOziCipvYyWHXb/8i//kj//8z/nm9/8Jm9/+9uZPHnyy/pcdtllXHTRRWy66aZ0dHRw0kknse222/LZz36WuXPnsmbNGl7M4B8+ezqvnrZTjadIUuuUOxIfD7wtM5+uOnUV8B8R8UXg1RTrTd9M8SXwrHLH4j6KTUben5kZET8GDqFYl3A+8J2qe80HbizP/6jsP9gzJGlY4y1f3HTTTTn77LN5zWte04K3kDRWNaxAWC4Y/Q3gzsz8YtWp/sTu87w84Ts2Ii6lWH/mibKIeA3wT1Ubk8yl3BVPkkajJ5988mVts2bN4pZbbll73D8FZMaMGdx2220AnHjiiZx44sv/83booYdy6KGHAk4xljQ6RMQlFF/gbh8RvRQbyp0IbAZcW6SB3JSZR2fm7RFxOXAHxdTjYzLzxfI+xwLXABOBczPz9vIRxwOXRsRngV9R5JSUvy+MiCUUIwcPAxjqGZI0GjUyX5SkDdHIEYR/DHwIuDUi+ldf/TuKwuDlEXEksBR4X3nuauDdFLvOPQ18GCAzV0bEZ4BflP1O7d+wRJIkSc2XmYfXaP5Gjbb+/qcBp9Vov5oiBxzYfi81diHOzGd5KXcc0TMkSZI0vEbuYvy/1F4/EGDfGv0TOGaQe50LnFu/6CSpNQYbAbjLTu5MLElSs7jJiSRJ62rKLsaSJEmSNFr0b3IiSZIKDd/FWJIkSZIkSdLoZYFQkiRJkiRJamNOMZYkSZKkEXL9QknSeGSBUNK4tvTU3ep6v+kn3Trk+RUrVrDvvsU+TJVKhYkTJzJlyhQAbr755rrGIkmSms/1C8ef0ZYvTpo0qa7xSNJIWCCUpDrabrvtWLx4MQCnnHIKr3jFK/jbv/3bdfpkJpnJhAmu8iBJktRuzBcljUb+10aSmmDJkiXsuuuufPrEv+WQd7+DykN97LXra9eev/TSS/noRz8KwCOPPMLBBx/MnDlz2GOPPbjppptaFbYkSaqzrq4u5s2bR1dXV6tD0SjTny8effTR7L777jz44INsvfXWa8+bL0pqJAuEktQkd9xxBwcf9gGu/P6P2aFjx0H7HXfccXR1dbFw4UIuv/zytYmgJEka+/qnKFcqlVaHolHojjvu4Mgjj+RXv/oVU6dOHbSf+aKkenOKsSQ1yWtf+1p2e9MfDtvvhz/8IXfdddfa48cee4xnnnmGLbbYopHhSZIkqcVe+9rX8uY3v3nYfuaLkurNAqEkNcnkyZPXfp4wYQKZufb42WefXfs5M12gWpIkvYw7KI9/5ouSWsUpxpLUAhMmTGCrV27NA/fdw5o1a/jWt7619tw73/lOzj777LXH/YtYj2WdC3pq/kiSpJFzenJ7mTBhAttssw133313W+SLklrLEYSSxrXpJ93a6hAG9akT/pGPf+gwOqZO5c1/+Caee+45AM4++2w+8YlPcN5557F69Wre/va3r5MASpIkqX5Gc754+umns99++zF9+nR22WUX80VJDWOBUJIa5JRTTln7+XWvex2LFy/mjgeXr23b/4CD2P+AgwDYZaft17ZPmTKFK664omlxSpIkqTVq5YvVDj30UA499NCXXWe+KKnenGIsSZIkSZIktTELhJIkSZIkSVIbc4qxpHEnM4mIVofRNJlJ+7ytJEnaUO6C/JJ2zBclaSiOIJQ0rmy++easWLGibZKgzOT5p1ex+eabtzoUSZI0yrkLcqEd88UVK1aYL0oakiMIJY0r06ZNo7e3l2XLljXsGQ8/9mTN9h23ecWw11YGuTaeHFm8A6/PhN7Hn+X9c/ca0fWSJEntrhn54miz+eabM23atFaHIWkUs0AoaVzZdNNNmTlzZkOf8cEFPTXbF50xr6HXDnX9/D99y4iulyRJanfNyBclaaxxirEkSZIkSZLUxiwQSpIkSZIkSW3MAqEkSZIkSZLUxiwQSpIkSZIkSW3MTUokSZIkSUPq6uqiUqnQ0dFBd3d3q8ORJNWZBUJJkiRJ0pAqlQp9fX2tDkOS1CBOMZYkSZIkSZLamAVCSZIkSZIkqY1ZIJQkSZIkSZLamGsQSpIkSdIwOhf0ALDl8lVMBJYuX7W2bdEZ81oYmSRJG88CoSRJkqS2MFiRrxkFvlY+W5Kk4VgglNR2+hP0gUzQJUka3RzFJ0lSY1gglCRJkqRRzNGHkqRGs0AoSRr1HPUpSZIkSY3TsF2MI+LciHg0Im6rarssIhaXP/dHxOKyfUZEPFN17mtV13RGxK0RsSQizoqIaFTMkiRJkiRJUrtp5AjC84F/BdYO+8jMQ/s/R8QXgCeq+t+TmbNr3OerwFHATcDVwH7A9xsQryRJkiRJktR2GlYgzMwbImJGrXPlKMC/AN4x1D0iYkdgq8y8sTzuAd6LBUJJkiRpTHI9veYbDX/zrq4uKpUKHR0ddHd3N+25kqSRadgU42G8BXgkM++uapsZEb+KiJ9ExFvKtqlAb1Wf3rKtpog4KiIWRsTCZcuW1T9qSZIkSdJ6q1Qq9PX1UalUWh2KJKmGVhUIDwcuqTp+GJiemX8IfAr4j4jYCqi13mAOdtPMPCcz52TmnClTptQ1YEmSJEmSJGk8avouxhGxCXAw0NnflpnPAc+VnxdFxD3A71OMGJxWdfk04KHmRStJkiRJkiSNb60YQfhO4DeZuXbqcERMiYiJ5eedgVnAvZn5MLAqIvYq1y2cB3ynBTFLkiRJkiRJ41LDCoQRcQlwI/AHEdEbEUeWpw5j3enFAG8FbomIXwNXAEdn5sry3CeArwNLgHtwgxJJkiRJkiSpbhq5i/Hhg7QfUaPtSuDKQfovBHata3CSJEmSpGG5A7IktYemr0EoSZIkSdJI9e+ALElqnFbtYixJkiRJkiRpFLBAKEmSJEmSJLUxC4SSJEmSJElSG7NAKEmSpPUSEedGxKMRcVtV27YRcW1E3F3+3qZsj4g4KyKWRMQtEbF71TXzy/53R8T8qvbOiLi1vOasiIgNfYYkSZKG5yYlksak/h31BmrmjnqS1MbOB/4VqP6P8QnAdZn5+Yg4oTw+HtgfmFX+7Al8FdgzIrYFTgbmAAksioirMvOxss9RwE3A1cB+wPfX9xkNe3tJkqRxxhGEkiRJWi+ZeQOwckDzgcAF5ecLgPdWtfdk4SZg64jYEXgXcG1mriyLgtcC+5XntsrMGzMzKYqQ793AZ0iSJGkEHEEoSZKkenhVZj4MkJkPR8QOZftU4MGqfr1l21DtvTXaN+QZD1cHGBFHUYxMZPr06RvwipLGoq6uLiqVCh0dHXR3d7c6HEkalRxBKEmSpEaKGm25Ae0b8ox1GzLPycw5mTlnypQpw9xS0nhRqVTo6+ujUqm0OhRJGrUsEEqSJKkeHumf1lv+frRs7wV2quo3DXhomPZpNdo35BmSWqxzQQ+dC3pYunwVAEuXrxp0LWlJUutYIJQkSVI9XAX070Q8H/hOVfu8cqfhvYAnymnC1wBzI2KbcjfiucA15blVEbFXuXvxvAH3Wp9nSJIkaQRcg1CSNK6547VUfxFxCbAPsH1E9FLsRvx54PKIOBJYCryv7H418G5gCfA08GGAzFwZEZ8BflH2OzUz+zc++QTFTslbUOxe/P2yfb2eITXCmkmT1/ndzOs39tmSJA3GAqEkSZLWS2YePsipfWv0TeCYQe5zLnBujfaFwK412les7zOkentq1tyWXb+xz5YkaTBOMZYkSZIkSZLamCMIJUmSJKkNjLUpyv3LhGy5fBUTeWmDE5cJkaT6s0AoSZIkSW3AKcqSpMFYIJQkSZIkDWmsjT6sl66uLiqVCh0dHXR3d7c6HElqGAuEkiRJkqQhtevow0qlQl9fX6vDkKSGc5MSSZIkSZIkqY05glCSJElSW2nX6bKSJA3GAqEkSZKkttKu02UlSRqMBUJJLdG5oKdm+6Iz5jU5EkmSJI1H/fnmlstXMRFYunwVnQt6zDclqQbXIJQkSZIkSZLamAVCSZIkSZIkqY05xViSJEnSmOImIxorurq6qFTrHmg+AAAgAElEQVQqdHR00N3d3epwJGlQFgglSZIkjSluMjL2tGtRt1Kp0NfX1+owJGlYFgglSZIkSQ1lUVeSRjfXIJQkSZIkSZLamAVCSZIkSZIkqY05xViSJEmSNGq16/qFktRMFgglSZIkSaNWK9Yv7FzQA8CWy1cxEVi6fBWdC3pYdMa8psXgDsiSmskCoSRJkiRJo4w7IEtqpoYVCCPiXOA9wKOZuWvZdgrwMWBZ2e3vMvPq8tyJwJHAi8BxmXlN2b4f8GVgIvD1zPx8o2KWJKla/+iBWpo5gkCSJEmSGqmRm5ScD+xXo/3MzJxd/vQXB3cBDgPeUF7zlYiYGBETgbOB/YFdgMPLvpIkSZIkSZLqoGEjCDPzhoiYMcLuBwKXZuZzwH0RsQTYozy3JDPvBYiIS8u+d9Q5XEmSJEnSOOQmJ5I0vFasQXhsRMwDFgJ/k5mPAVOBm6r69JZtAA8OaN9zsBtHxFHAUQDTp0+vZ8ySJEmSpDGoFZucSNJY08gpxrV8FXgtMBt4GPhC2R41+uYQ7TVl5jmZOScz50yZMmVjY5UkSZIkSZLGvaaOIMzMR/o/R8S/A98tD3uBnaq6TgMeKj8P1i5JkiRJkiRpIzV1BGFE7Fh1eBBwW/n5KuCwiNgsImYCs4CbgV8AsyJiZkRMotjI5KpmxixJkiRJ0vroXNBD54Ieli5fBcDS5avoXNDT4qgkaXANG0EYEZcA+wDbR0QvcDKwT0TMppgmfD/wcYDMvD0iLqfYfGQ1cExmvlje51jgGmAicG5m3t6omCVJkiRJGg+6urqoVCp0dHTQ3d3d6nAkjXKN3MX48BrN3xii/2nAaTXarwaurmNokiRJkiSNa5VKhb6+vlaHIWmMaPYmJZIkSZIkSZJGEQuEkiRJkiRJUhuzQChJkiRJkiS1sYatQShJkiRJg1kzafI6v6XRqBX/O+3f7XjL5auYyEs7IC86Y17TYpDUfiwQSpIkSWq6p2bNbXUI0rD836mkduEUY0mSJEmSJKmNWSCUJEmSJEmS2pgFQkmSJEmSJKmNWSCUJEmSJEmS2pgFQkmSJEmSJKmNuYuxJEmSJEkNsGbS5HV+N0Pngh4Atly+ionA0uWr6FzQw6Iz5o34Hl1dXVQqFTo6Ouju7m5QpJJGEwuEkiRJkiQ1wFOz5rY6hA1SqVTo6+trdRiSmsgpxpIkSZIkSVIbs0AoSZIkSZIktTELhJIkSZIkSVIbcw1CSZIapH+R8IHWZ5FwSZLUnlqxwYmk9mWBUJIkSZKkUWasbnAiaWyyQChpgzk6SpIkSZKksc81CCVJklQ3EfH/IuL2iLgtIi6JiM0jYmZE/Dwi7o6IyyJiUtl3s/J4SXl+RtV9Tizb74qId1W171e2LYmIE6raaz5DkiRJw7NAKEmSpLqIiKnAccCczNwVmAgcBpwOnJmZs4DHgCPLS44EHsvM1wFnlv2IiF3K694A7Ad8JSImRsRE4Gxgf2AX4PCyL0M8Q5IkScOwQChJkqR62gTYIiI2AX4PeBh4B3BFef4C4L3l5wPLY8rz+0ZElO2XZuZzmXkfsATYo/xZkpn3ZubzwKXAgeU1gz1DkiRJw7BAKEmSpLrIzD7gn4GlFIXBJ4BFwOOZubrs1gtMLT9PBR4sr11d9t+uun3ANYO1bzfEM9aKiKMiYmFELFy2bNnGvawkSdI4YoFQkiRJdRER21CM/psJvBqYTDEdeKDsv2SQc/VqX7ch85zMnJOZc6ZMmVLjEkkaP9ZMmsyLm23FmkmTR3xN54IeOhf0sHT5KgCWLl816MaEksYXdzGWJElSvbwTuC8zlwFExH8CfwRsHRGblCP8pgEPlf17gZ2A3nJK8iuBlVXt/aqvqdW+fIhnSFJbemrW3JY9u6uri0qlQkdHB93d3S2LQ9LIOYJQkiRJ9bIU2Csifq9cF3Bf4A7gx8AhZZ/5wHfKz1eVx5Tnf5SZWbYfVu5yPBOYBdwM/AKYVe5YPIliI5OrymsGe4YkqckqlQp9fX1UKpVWhyJphCwQSpIkqS4y8+cUG4X8EriVItc8Bzge+FRELKFYL/Ab5SXfALYr2z8FnFDe53bgcori4g+AYzLzxXJ04LHANcCdwOVlX4Z4hiRJkobhFGNJkiTVTWaeDJw8oPleih2IB/Z9FnjfIPc5DTitRvvVwNU12ms+Q5IkScNzBKEkSZIkSZLUxiwQSpIkSZIkSW3MAqEkSZIkSZLUxiwQSpIkSZIkSW3MAqEkSZIkSZLUxiwQSpIkSZIkSW2sYQXCiDg3Ih6NiNuq2s6IiN9ExC0R8a2I2LpsnxERz0TE4vLna1XXdEbErRGxJCLOiohoVMySJEmSJElSu2nkCMLzgf0GtF0L7JqZbwR+C5xYde6ezJxd/hxd1f5V4ChgVvkz8J6SJEmSJEmSNlDDCoSZeQOwckDbf2fm6vLwJmDaUPeIiB2BrTLzxsxMoAd4byPilSRJkiRJsGbSZF7cbCvWTJq8Xtd1Luihc0EPS5evAmDp8lV0LuhpRIiS6myTFj77I8BlVcczI+JXwO+Af8jM/wGmAr1VfXrLtpoi4iiK0YZMnz697gFLkiRJkjTePTVrbqtDkNRkLSkQRsTfA6uBi8umh4HpmbkiIjqBb0fEG4Ba6w3mYPfNzHOAcwDmzJkzaD9JkiRJkjT6dHV1UalU6OjooLu7u9XhSG2j6QXCiJgPvAfYt5w2TGY+BzxXfl4UEfcAv08xYrB6GvI04KHmRixJkiRJkpqhUqnQ19fX6jCkttPITUpeJiL2A44HDsjMp6vap0TExPLzzhSbkdybmQ8DqyJir3L34nnAd5oZsyRJkiRJkjSeNWwEYURcAuwDbB8RvcDJFLsWbwZcW9T7uKncsfitwKkRsRp4ETg6M/s3OPkExY7IWwDfL38kSZIkSZIk1UHDCoSZeXiN5m8M0vdK4MpBzi0Edq1jaJIkSZIkSZJKTZ1iLEmSJEmSJGl0ackuxpIkSZIkSSPl7sZSY1kglCRJkiRJo5q7G0uN5RRjSZIkSZIkqY05glCSJEmSJNXNmkmT1/ktafSzQChJkiRJkurmqVlzWx2CpPVkgVCSJEmSJLVU54IeALZcvoqJwNLlq+hc0MOiM+a1NjCpTbgGoSRJkiRJktTGHEEoSdIo1P8tei1+ky5JkiSpnkY0gjAirhtJmyRJksYOczxJ0njT1dXFvHnz6OrqanUo0pgy5AjCiNgc+D1g+4jYBojy1FbAqxscmyRJkhrAHE+SNF5VKhX6+vpaHYY05gw3xfjjwF9TJIqLeCl5/B1wdgPjkiRJUuOY40mSJGmtIQuEmfll4MsR8VeZ+S9NikmSJEkNZI4nSZKkaiPapCQz/yUi/giYUX1NZg6+grokSZJGNXM8SZIkwQgLhBFxIfBaYDHwYtmcgMmjJEnSGGWOJ0mSJBhhgRCYA+ySmdnIYCQ1V+eCwf//36Iz5jUxEklSi5jjSZIkiQkj7Hcb0NHIQCRJktR05niSJEka8QjC7YE7IuJm4Ln+xsw8oCFRSZIkqRnM8SRJkjTiAuEpjQxCkiRJLXFKqwOQJKnamkmT1/ktqTlGuovxTxodiCRJkprLHE+SNNo8NWtuq0OQ2tJIdzFeRbGjHcAkYFPgqczcqlGBSZIkqbHM8SRJkgQjH0G4ZfVxRLwX2KMhEUmSJKkpzPEkSeNB54KetZ+3XL6KicDS5avoXNDDojPmtS4waQwZ6RqE68jMb0fECfUORpIkSa1jjidJaqSuri4qlQodHR10d3e3OhxJVUY6xfjgqsMJwBxemo4iSZKkMcgcT5LUTJVKhb6+vlaHIamGkY4g/LOqz6uB+4ED6x6NJEmSmskcT5IkSSNeg/DDjQ5EkiRJzWWOJ0mSJCimkgwrIqZFxLci4tGIeCQiroyIaY0OTpIkSY1jjidJ0ku6urqYN28eXV1drQ5FaroRFQiB84CrgFcDU4H/KtskSZI0dpnjSZJU6l8jsVKptDoUqelGWiCckpnnZebq8ud8YEoD45IkSVLjmeNJkiRpxAXC5RHxwYiYWP58EFjRyMAkSZLUcOZ4kiRJGnGB8CPAXwAV4GHgEMBFrSVJksY2czxJkiSNbBdj4DPA/Mx8DCAitgX+mSKplCRJ0thkjidJkqQRjyB8Y3/iCJCZK4E/HO6iiDi33BXvtqq2bSPi2oi4u/y9TdkeEXFWRCyJiFsiYveqa+aX/e+OiPkjfz1JkiQNYYNyvKFExNYRcUVE/CYi7oyIveuZ/0VEZ0TcWl5zVkRE2V7zGZIkSRreSAuEE6qTrPLb5ZGMPjwf2G9A2wnAdZk5C7iuPAbYH5hV/hwFfLXqWScDewJ7ACeb8EmSJNXFhuZ4Q/ky8IPM/D/Am4A7qW/+99Wyb/91/bnmYM+QJLWRNZMm8+JmW7Fm0uRWhyKNKSNNAL8A/CwirgCSYq2a04a7KDNviIgZA5oPBPYpP18AXA8cX7b3ZGYCN5XfPu9Y9r22/EabiLiWIhG8ZISxS5IkqbYNyvEGExFbAW8FjgDIzOeB5yOiLvlfRFwPbJWZN5btPcB7ge8zeI4pSWojT82a2+oQpDFpRAXCzOyJiIXAO4AADs7MOzbwma/KzIfL+z4cETuU7VOBB6v69ZZtg7W/TEQcRfGNMtOnT9/A8CRJktpDnXM8gJ2BZcB5EfEmYBHwSeqX/00tPw9sZ4hnrGWuKEmSVNuIp5CUyeLGJIzDiVqPHaL95Y2Z5wDnAMyZM6dmH0mSJL2kzjneJsDuwF9l5s8j4ssMPdV3ffO/EeeFtZgrSpIk1TbSNQjr6ZFy6gjl70fL9l5gp6p+04CHhmiXJEnS6NIL9Gbmz8vjKygKhvXK/3rLzwPbGeIZkiRJGkYrCoRXAf070c0HvlPVPq/czW4v4Ilymsg1wNyI2KZcnHpu2SZJkqRRJDMrwIMR8Qdl074UoxPrkv+V51ZFxF7l7sXzBtyr1jMkSRpS54IeOhf0sHT5KgCWLl9F54KeFkclNdfG7lI3pIi4hGKx6O0jopdiN7rPA5dHxJHAUuB9ZfergXcDS4CngQ8DZObKiPgM8Iuy36n9C1ZLkiRp1Pkr4OKImATcS5HTTaB++d8ngPOBLSg2J/l+2T5YjilJkqRhNLRAmJmHD3Jq3xp9EzhmkPucC5xbx9AkSZLUAJm5GJhT41Rd8r/MXAjsWqN9Ra1nSJIkaXitmGIsSZIkSZIkaZSwQChJkiRJkiS1sYZOMZYkSZIkSWoHXV1dVCoVOjo66O7ubnU40nqxQChJkiRJkrSRKpUKfX19rQ5D2iBOMZYkSZIkSZLamAVCSZIkSZIkqY1ZIJQkSZIkSZLamGsQSpI0DnUu6KnZvuiMeU2ORJIkSdJo5whCSZIkSZIkqY05glAa4xwlJEmSJEkbb82kyev8ltqJBUJJkiRJktT2npo1t9UhSC3jFGNJkiRJkiSpjVkglCRJkiRJktqYBUJJkiRJkiSpjbkGoSRJkiRJ0gao3jRyy+WrmAgsXb6KzgU9bhypMcURhJIkSZIkSVIbs0AoSZIkSZIktTELhJIkSZIkSVIbs0AoSZIkSZIktTELhJIkSZIkSVIbcxdjSZIkSZKkFurq6qJSqdDR0UF3d3erw1EbskAoSZIkSZLUQpVKhb6+vlaHoTbmFGNJkiRJkiSpjVkglCRJkiRJktqYU4wlSZIkSdKwXCdPGr8sEEqSJEmSpGG5Tp40flkglCRJkiRJ2khrJk1e57c0llgglCRJkiRJ2khPzZrb6hCkDeYmJZIkSZIkSVIbs0AoSZIkSZIktTELhJIkSZIkSVIbs0AoSZIkSZIktbGmFwgj4g8iYnHVz+8i4q8j4pSI6Ktqf3fVNSdGxJKIuCsi3tXsmCVJkiRJkuqtc0EPnQt6WLp8FQBLl6+ic0FPi6NSO2r6LsaZeRcwGyAiJgJ9wLeADwNnZuY/V/ePiF2Aw4A3AK8GfhgRv5+ZLzY1cKlBhvqP/6Iz5jUxEkmSJEmS1I5aPcV4X+CezHxgiD4HApdm5nOZeR+wBNijKdFJkiRJkiRJ41yrC4SHAZdUHR8bEbdExLkRsU3ZNhV4sKpPb9kmSZIkSZIkaSO1rEAYEZOAA4Bvlk1fBV5LMf34YeAL/V1rXJ6D3POoiFgYEQuXLVtW54glSZIkSZKk8afpaxBW2R/4ZWY+AtD/GyAi/h34bnnYC+xUdd004KFaN8zMc4BzAObMmVOziChJkiRJkjRedHV1UalU6OjooLu7u9XhaIxq5RTjw6maXhwRO1adOwi4rfx8FXBYRGwWETOBWcDNTYtSkiRJkiRplKpUKvT19VGpVFodisawlowgjIjfA/4E+HhVc3dEzKaYPnx//7nMvD0iLgfuAFYDx7iDsSRJkiRJklQfLSkQZubTwHYD2j40RP/TgNMaHZckSZIkSZLUblq9i7EkSZIkSZKkFrJAKEmSJEmSJLUxC4SSJEmSJElSG2vJGoSSJEmSJEkqrJk0eZ3fUrNZIJQkSevoXNAz6LlFZ8xrYiSSJEnt4alZc1sdgtqcU4wlSZJUNxExMSJ+FRHfLY9nRsTPI+LuiLgsIiaV7ZuVx0vK8zOq7nFi2X5XRLyrqn2/sm1JRJxQ1V7zGZKk0WHpqbux9NTdWL3yAQBWr3yApafu1uKoJFWzQChJkqR6+iRwZ9Xx6cCZmTkLeAw4smw/EngsM18HnFn2IyJ2AQ4D3gDsB3ylLDpOBM4G9gd2AQ4v+w71DEmSJI2ABUJJkiTVRURMA/4U+Hp5HMA7gCvKLhcA7y0/H1geU57ft+x/IHBpZj6XmfcBS4A9yp8lmXlvZj4PXAocOMwzJEmSNAKuQShJkqR6+RLQBWxZHm8HPJ6Zq8vjXmBq+Xkq8CBAZq6OiCfK/lOBm6ruWX3NgwPa9xzmGeuIiKOAowCmT5++Aa8nSWNfV1cXlUqFjo4Ouru7Wx2ONkL/utFbLl/FRGDp8lVr21w3WuvLEYSSJEnaaBHxHuDRzFxU3Vyjaw5zrl7tL2/MPCcz52TmnClTptTqIknjXqVSoa+vj0ql0upQJI0ijiCUJElSPfwxcEBEvBvYHNiKYkTh1hGxSTnCbxrwUNm/F9gJ6I2ITYBXAiur2vtVX1OrffkQz5AkSdIIOIJQkiRJGy0zT8zMaZk5g2KTkR9l5geAHwOHlN3mA98pP19VHlOe/1FmZtl+WLnL8UxgFnAz8AtgVrlj8aTyGVeV1wz2DEmSJI2ABUJJkiQ10vHApyJiCcV6gd8o278BbFe2fwo4ASAzbwcuB+4AfgAck5kvlqMDjwWuodgl+fKy71DPkCRJ0gg4xViqg/6FYAdyYVhJUjvKzOuB68vP91LsQDywz7PA+wa5/jTgtBrtVwNX12iv+QxJkiSNjCMIJUmSJEmSpDZmgVCSJEmSJElqYxYIJUmSJEmSpDZmgVCSJEmSJElqY25SIkmSJEmSRqWlp+4GwOqV2wKbsHrlAyw9dTemn3RrawOTxhkLhJIkqa7c2V2SJKl51kyavM7v9dXV1UWlUqGjo4Pu7u56hqYxxAKhJEmSJEnSGPXUrLkbdX2lUqGvr69O0Wiscg1CSZIkSZIkqY1ZIJQkSZIkSZLamAVCSZIkSZIkqY1ZIJQkSZIkSZLamJuUSJIkSZKkQS09dTcAVq/cFtiE1SsfYOmpuzH9pFtbG5ikunEEoSRJkiRJktTGLBBKkiRJkiRJbcwCoaT/396dh0tWlwce/77soBhtARuFFk3AcWlEaZEJRkETgkxGdMb1ydC4DTNGRtHAjdugaR8npHEZdUYzqAQ6LgEXlDi4ECJRM2yCSLe2IMam7aYvDLZoK6Mzl37nj/O7WH2pc+pU3aVu3fp+nqeee+rUeev93aq36779q7NIkiRJkqQx5gShJEmSJEmSNMacIJQkSZIkSZLGmFcxliRJkiRJGjNHn70OgP3v3sHuwOa7d3D02eu44bzVwx2YhsI9CCVJkiRJkqQxNrQ9CCNiE7ADuA+YysxVEbEMuBg4DNgEvDgzfxoRAbwfOBm4F3h5Zt44jHFLkiRJkjQsExMTTE5Osnz5ctauXTvs4UhaIoZ9iPEJmXl3x/03AVdm5rkR8aZy/8+A5wKHl9vTgQ+Xn9KcmN61uht3r5YkSZK0WExOTrJ169a+4zavWQnA1PZlwB5Mbb+dzWtWsuKc9XM8QkmjaLEdYnwKcFFZvgh4fsf6dVm5BnhoRBw8jAFKkiRJkiRJS8kw9yBM4KsRkcD/yMzzgUdk5jaAzNwWEQeVbR8F/LgjdktZt63zCSPidOB0gBUrVszz8DUupr9pm6nNN22ziR3n3JLGl3t0S5IkSQtvmBOEx2XmHWUS8IqI+H7DttFlXT5gRTXJeD7AqlWrHvC4JEmSJEmSpF0N7RDjzLyj/LwLuBQ4Brhz+tDh8vOusvkW4NCO8EOAOxZutJIkSZIkSdLSNJQJwoh4UETsP70MnAhsAC4DTiubnQZ8oSxfBqyOyrHAz6YPRZYkSZIkSZI0uGEdYvwI4NKImB7DJzPzyxFxPXBJRLwK2Ay8qGx/OXAycBtwL/CKhR+yJEmSJEmStPQMZYIwM/8ZeHKX9T8BntNlfQKvXYChSZIkSZIkSWNlmBcpkSRJkiRJ0hDt3OtBu/zUeHKCUEve5jUru65fcc76BR6JJEmSJEmLyy8PP3HYQ9AiMLSrGEuSJEmSJEkaPvcglLSo1O3xCe71KUmSJEnSfHAPQkmSJEmSJGmMOUEoSZIkSZIkjTEnCCVJkiRJkqQx5jkINRK8ErEkSZIkSdL8cIJQkiQtGUefva7r+hvOW73AI5Ekqd7ExASTk5MsX76ctWvXDns4kuQEoSRJkiRJC2lycpKtW7cOexiSdD/PQShJkiRJkiSNMfcglCRJkiRpkZs+L/vU9mXAHkxtv53Na1Z6XnZJc8IJQkmSJEmS+uA5BCUtNU4QSlpSvOK1JEmS5pvnEJS01DhBqAWxEJM2dVeuvHT/OUshSZIkSRrQAfvsBKbKT0mLiROEkiRJkiSpp9lO8J115D1zOyBJc8YJQkmSJEmS1JMTfNLS5QShJEmSJEljwsN8JXWz27AHIEmSpKUhIg6NiK9FxMaI+G5EvL6sXxYRV0TED8rPh5X1EREfiIjbIuLmiHhqx3OdVrb/QUSc1rH+6IhYX2I+EBHRlEOStKuzjryHc4/Z7t6AknbhBKEkSZLmyhTwp5n5eOBY4LUR8QTgTcCVmXk4cGW5D/Bc4PByOx34MFSTfcDbgacDxwBv75jw+3DZdjrupLK+LockdTUxMcHq1auZmJgY9lAkaeicIJQkSdKcyMxtmXljWd4BbAQeBZwCXFQ2uwh4flk+BViXlWuAh0bEwcAfAldk5vbM/ClwBXBSeewhmXl1ZiawbsZzdcshSV1NTk6ydetWJicnhz0USRo6z0EoScXmNStrH1txzvoFHIkkjb6IOAx4CnAt8IjM3AbVJGJEHFQ2exTw446wLWVd0/otXdbTkKNzTKdT7X3IihUrZvHbSZIkLS3uQShJkqQ5FREPBj4LnJmZP2/atMu6HGB9K5l5fmauysxVBx54YNswSZKkJc89CNVa3d5V7lklSZKmRcSeVJODn8jMz5XVd0bEwWXPvoOBu8r6LcChHeGHAHeU9cfPWH9VWX9Il+2bckjSojH9f6qp7cuAPZjafjub16z0/1SShs49CCVJkjQnyhWFPwZszMz3djx0GTB9JeLTgC90rF9drmZ8LPCzcpjwV4ATI+Jh5eIkJwJfKY/tiIhjS67VM56rWw5JkiT14B6EkiRJwNFnr+u6/obzVi/wSEbaccCpwPqIuKmsewtwLnBJRLwK2Ay8qDx2OXAycBtwL/AKgMzcHhHvBK4v263JzO1l+TXAhcC+wJfKjYYckiRpnkxMTDA5Ocny5ctZu3btsIejWXCCUJIkSXMiM79J9/MEAjyny/YJvLbmuS4ALuiy/lvAk7qs/0m3HJIkaf5MXw1co88JQkmSJEmSWqg7hyB4bnZJo80JQkmSJEmSRsQB++wEpspPSZobThBKkiRJkjQizjrynmEPQZoznsNw8XCCUJIkSZIkSa1NX9xt/7t3sDuw+e4d96/r5wJvnsNw8XCCUJIkSZIkSSPFvQ/n1oJPEEbEocA6YDmwEzg/M98fEe8A/j3wv8umb8nMy0vMm4FXAfcBr8vMryz0uJeC6ZPnzuTJdKW54b8xSZIkSVoY7n04t4axB+EU8KeZeWNE7A/cEBFXlMfel5nv7tw4Ip4AvBR4IvBI4O8j4ojMvG9BRy1JkiRJWjTce0gaXXWHKPdzeLLm1oJPEGbmNmBbWd4RERuBRzWEnAL8bWb+GvhRRNwGHANcPe+D1YKa/oDo5tL9F3AgkiRJkha9Qfcemj7qY2r7MmAPprbfzuY1Kz3qQxrAzr0etMvPUeKXDLsa6jkII+Iw4CnAtcBxwBkRsRr4FtVehj+lmjy8piNsCzUTihFxOnA6wIoVK+Zt3JIkSZIkSePul4efOOwhDMxDlHe127ASR8SDgc8CZ2bmz4EPA78NHEW1h+F7pjftEp7dnjMzz8/MVZm56sADD5yHUUuSJEmSJGlYjj57HUefvY7Nd+8Adr2CsgY3lD0II2JPqsnBT2Tm5wAy886Oxz8CfLHc3QIc2hF+CHDHAg1VkiRJkqQ5dcA+O4Gp8lPSqFmKhycP4yrGAXwM2JiZ7+1Yf3A5PyHAC4ANZfky4JMR8V6qi5QcDly3gEOWJEmSJGnOnHXkPcMegrQoDOMchnNxgZTZHp68GCcYh7EH4XHAqcD6iLiprHsL8LKIOIrq8OFNwH8AyMzvRsQlwPeoroD82nG+gvH0CXVn8oS60mir+7cN/vuWJElabNwDUJobo3wOw9mYzQTjfE0uDuMqxt+k+3kFL2+IeRfwrnkblCRJkiRpwS3GvWjacA9Aaencvj4AABOJSURBVPhG+QrKszFfF1cZ6lWMJUmSJEnjy6uIShrUMPY+nIvDkxcrJwglSZIkSSNj+tQsU9uXAXswtf32+9d5ahZJGowThJIkSXNg+hvlmZbCN8qSJElLzbgeolzHCUJJkiRJkrSoeWEYzTUPUd6VE4SSJEmSJGlR88Iw0vxyglCSJEmSNHbcI03SoIZxePJ8733oBKEkSZIkaUHVXWhkIS8y4h5pkgY1jMOT55sThJK0BEw32TN5JT9JkiRJUi9OEEqSJEmSJEkLZDFeQdkJwgXmXj6SJEmSlpKJiQkmJydZvnw5a9euXbC8nkNQ0qhajIcoO0EoSZIkSRrY5OQkW7duXfC8nkNQkuaOE4SSJEmSJEnSCJivw5OdIJQkSZIkSZJGwHwdnuwEoSRJkiRpKDyPoCQtDk4Qak4dffa6rusv3X+BByJJkiRp0fM8gpK0ODhBKEmSJEnqy+Y1K+9fntq+DNiDqe23s3nNSlacs354A5MkDcQJwgF0/jHs5B9CSaPIzzRJkiRJGm+7DXsAkiRJkiRJkobHPQglSZIkaYxNTEwwOTnJ8uXLWbt27bCHI0kaAicIJUmSJGmMTU5OsnXr1mEPQ5I0RE4QSpIkSZIGdsA+O4Gp8lOSNIqcIJQkSRqyo89e13X9DeetXuCRSFL/zjrynmEPQZI0S04QSpIkSdKIG+Q8gpvXrARgavsyYA+mtt/O5jUrWXHO+nkcqSRpMXKCUJI0K9P/uZjJ/1xIkrRwPI+gJGk2dhv2ACRJkiRJkiQNj3sQSpIkSdII6tyLfzaHCXuREUmSE4SSJEmSNGSDnENwrniREUnSWE4Q1p0vCzxnliRJkqSF5zkEJUnDNJYThJIkSZI014Z5JWEPE5YkzYYThJKkofEKyJKkpWSYewF6mLAkaTacIJQkSZIkBj8P4FztBShJ0rA4QShJkiRpyZjNxT6GuQeghwhLkobJCUJJkiRJc2o2k3SzvZrvIJN8i+E8gB4iLEkappGZIIyIk4D3A7sDH83Mc4c8JEmSJC0i9ou7GtVJui3fW8ad/6f/Sbq5mOSb7V58TvJJkkbVSEwQRsTuwH8H/gDYAlwfEZdl5veGOzJJkiQtBvaLDzSqk3Sz5V58kiT1byQmCIFjgNsy858BIuJvgVOAsW34JEmStIs57Rdne5X12cTPVe5RnaRzLz5JkhZeZOawx9BTRLwQOCkzX13unwo8PTPPmLHd6cDp5e7jgFtqnvIA4O5ZDGk28eY2t7nnL9bc5ja3uRdb7HznfnRmHjjgcy8pbfrFPnpFWNzvu7nNPRex5ja3uc291HKP6rjnO3e7fjEzF/0NeBHVeWSm758KfHAWz/etWY5n4Hhzm9vcS3Pc5ja3uZdu7lEd97jd7BfNPY65R3Xc5ja3uc292GLHOff0bTdGwxbg0I77hwB3DGkskiRJWnzsFyVJkgY0KhOE1wOHR8RjImIv4KXAZUMekyRJkhYP+0VJkqQBjcRFSjJzKiLOAL4C7A5ckJnfncVTnj/LIc0m3tzmNvf8xZrb3OY292KLHXbusWG/aO4xzT2q4za3uc1t7sUWO865gRG5SIkkSZIkSZKk+TEqhxhLkiRJkiRJmgdOEEqSJEmSJEljbOwmCCPiDRHx3YjYEBGfioh9+oh9fYn7bkSc2WL7CyLirojY0LFuWURcERE/KD8f1kfsi0runRGxaoDc50XE9yPi5oi4NCIe2mf8O0vsTRHx1Yh4ZNvYjsfOioiMiAP6yPuOiNha8t4UESf3M+6y/j9FxC3l9VvbR+6LO/Juioib+skdEUdFxDUl/lsRcUwfsU+OiKsjYn1E/F1EPKQm9tCI+FpEbCy/3+vL+ra1Vhffs94aYlvVWkN8z1qri+14vFet1eXuWW9NuVvWWl3unvXWENu21urie9ZbROwTEddFxHdK7J+X9Y+JiGtLrV0c1cUBuuWuiz8jIm7r8X7VxX6ivN4bovp3tGef8R8r626OiM9ExIPbxnY8/sGI+EW3vD1yXxgRP+p4z4/qIzYi4l0RcWt5L1/XZ+5vdOS9IyI+30fscyLixhL7zYj4nT5in11iN0TERRHReC7kiNg9Ir4dEV8s91vVWk1szzrrEd+q1mpie9ZZU3zH+sZa09wJ+8U2f8MH7hXr4jses19sH2u/aL9ov9g7dlH3iw15e/aKPeIjevSLDbE9e8Ue8faLo9gvZubY3IBHAT8C9i33LwFe3jL2ScAGYD+qi7v8PXB4j5hnAk8FNnSsWwu8qSy/CfjLPmIfDzwOuApYNUDuE4E9yvJf1uVuiH9Ix/LrgL9qG1vWH0p14vDbgQP6yPsO4KyW71O3+BPK+7V3uX9QP+PuePw9wDl95v4q8NyyfDJwVR+x1wPPKsuvBN5ZE3sw8NSyvD9wK/CEPmqtLr5nvTXEtqq1hvietVYX20et1eXuWW8NsW1rrXbsveqtIXfbWquL71lvQAAPLst7AtcCx1J9lr60rP8r4DU1uevinwIcBmxqeL/qYk8ujwXwqQFyd9baeyn/ZtrElvurgL8BftFQL3W5LwRe2KPW6mJfAawDdutRa7Vj79jms8DqPnLfCjy+rP8T4MKWsb8L/Bg4oqxfA7yqx+//RuCTwBfL/Va1VhPbs856xLeqtZrYnnXWFN+21rzNzQ37xbZ/wwfuFeviy3r7RfvFtvH2i/aLbWMXdb/YkPdCevSKPeJ79otN4+7Ypmuv2CO3/eII9otjtwchVbO2b5mF3g+4o2Xc44FrMvPezJwC/hF4QVNAZn4d2D5j9SnARWX5IuD5bWMzc2Nm3tJmsDXxXy1jB7gGOKTP+J933H0QkG1ji/cBE3VxPWJbqYl/DXBuZv66bHNXv7kjIoAXU/0j7yd3AtPfrP0WNfVWE/s44Otl+Qrg39bEbsvMG8vyDmAj1X9u2tZa1/g29dYQ26rWGuJ71lrD7w3taq0pvlFDbNtaa8zdVG8NsW1rrS6+Z71lZfrbqD3LLYFnA58p65tqrWt8Zn47Mzd1i2kRe3l5LIHrqK+1uvifw/2v+b50r7WusRGxO3AeVa31PfammBaxrwHWZObOsl1drTXmjoj9qd6/B3wr3BDbs9ZqYu8Dfp2Zt5b1tZ9rZWyHAP8K+Gi5H7SstZmxZUw966xHfKtaq4ntWWdN8W1rTXPKfrHS9Dd84F6xLr6wX7RfbBtvv2i/2DZ2UfeLvfq1Xhrie/aLvXI39Yo94u0XR7BfHKsJwszcCrwb2AxsA36WmV9tGb4BeGZEPDwi9qOaGT50gGE8IjO3lfFsAw4a4DnmwiuBL/UbVHZR/jHwx8A5fcQ9D9iamd/pN2dxRtnV9oKoOfShwRHA75XdjP8xIp42QP7fA+7MzB/0GXcmcF55zd4NvLmP2A3A88ryi2hRbxFxGNW3HtcyQK3NiO9LQ2yrWpsZ30+tdcYOUmtdxt663mbE9l1rNa9bq3qbEdt3rc2Ib1VvZVf2m4C7qP5g/xC4p6PB30JD4zwzPjNb11pTbNl9/1Tgy/3GR8RfA5PAvwA+2EfsGcBl0//OBhz7u0qtvS8i9u4j9reBl0R1eNCXIuLwAXJDNXFx5Yz/ZPWKfTVweURsoXrNz20TS9Uk7Rm/OQTthTR/rv1XqgZnZ7n/cNrX2szYftXGt6i1rrFt6qwhvnWtafbsF3fRd784aK9YYu0X7Rf7irdftF/sJ3Yx94uz6RUb4lv1i7PpFRvi7RdHsF8cqwnC8sF9CvAY4JHAgyLi37WJzcyNVLu+X0H1Jn8HmGoMWqQi4q1UY/9Ev7GZ+dbMPLTEntEy337AW+mzSezwYaoPt6OoGvX39Bm/B/Awql2dzwYuiYjo8zleRsO3wQ1eA7yhvGZvAD7WR+wrgddGxA1Uu/b/36aNozpHwWeBM5s+wOcjvi62ba11i29ba52xJVdftdYld+t66xLbV601vOY9661LbF+11iW+Vb1l5n2ZeRTVt2HHUO0t84DN6vLOjI+IJzWNs4/YDwFfz8xv9Bufma+g+puwEXhJy9hnUjXGTX+4e+V+M9Uf/6cBy4A/6yN2b+BXmbkK+AhwQb+/d9FYazWxbwBOzsxDgL+mOgSiZyzwROClwPsi4jpgBzV/RyPij4C7MvOGztXd0rSMba1FfG2tNcW2qbNu8VGdU6t1rWn27Bcrg/aLg/SKJZ/9ov2i/WK7+Gn2i/3HLtp+cTa9YkN8q35xNr1iQ7z94ij2iznAccmjeisv2Mc67q8GPjTgc/0X4E9abHcYu54n5Bbg4LJ8MHBL29iO9VfR45wydfHAacDVwH6DxHc89ui6x2bGAiupvhHYVG5TVN/KLx8gb+1jDa/5l4HjO+7/EDiwj9dsD+BO4JAB3u+fAVGWA/j5gK/3EcB1DbF7Up1D5Y0D1toD4tvWW11s21pryt2r1mbGDlBrvXI3vSfdXvN+aq3udetZbzW5+6m1Xr93Y711bPd2qsb2bn5zDqF/CXylV2xH/Fkd9zfR4lwfM2PL8ucp51cZJHdZ9yw6zuHRI/btVN/uTdfaTuC2WeQ+vo/cZwHfBw7reL9/NsDr9nDgJ8A+fcSeDfywY90K4HsD/s4nApfUbP8XVN/4biqv871U//nrWWs1sR9vW2dN8b1qrVfuXnVWE//TQWvN22A37Beh/d/wrrnLY4294sx47BftF5tfM/vFPuutJrf94gj0izV5j2+TtzOeAfpFZtErzni/7RdHsF8cqz0IqT74j42I/cq3NM+hmpltJSIOKj9XAP+Gwb4hvIzqDyHl5xcGeI6BRMRJVN86PC8z7x0gvnOX5OdRfeD0lJnrM/OgzDwsMw+jKuanZuZky7wHd9x9AdWu7f34PNV5CIiII4C9qD402vp94PuZuaXPvFCda+FZZfnZQOtDTjrqbTfgbVQnWO22XVB9+7cxMzu/mWlVaw3xbcbYNbZtrTXE96y1brH91FpD7p711vCataq1Hq95Y701xLaqtYbfu2e9RcSBUa4wGBH7lrFuBL5Gtfs/NNdat/hWnyN1sRHxauAPgZdlOb9KH/G3RLmiWnld/nW38dTE3pCZyztq7d7MfMDV2XqM/eCO3M+ne63VvWb31xrV+37rzNge8VBNgnwxM3/VR+xG4LdKfQP8AV3+jjb8ztN1tjfVZ0TXz7XMfHNmHlJe25cC/5CZf0yLWquJbbX3V1N8m1rrFguc2qbOGnI/rG2tac7YLw7YLw7aK4L9IvaL9ovt48F+satR7Rdn0ys2xdOiX5xNr9gQb784qv1ivzOKo34D/ry80Buoru6ydx+x3wC+R3W4yHNabP8pql3O/x/VH55XUc3CX0n1YXwlsKyP2BeU5V9TfWNU+61LTfxtVFcEuqncmq4s1y3+s+V1uxn4O6qTA7eKnfH4JuqvPNUt798A60veyyjfcvYRvxfw8TL2G4Fn9zNuqqtH/ccB3+9nADeUmrkWOLqP2NdTfYjfSnXOhqiJfQbVbtM3d7y3J/dRa3XxPeutIbZVrTXE96y1utg+aq0ud896a4htW2u1Y+9Vbw2529ZaXXzPegOOBL5dYjdQrpoHPJbqfCG3AZ+m5nO1If51pdamqBrXj/YRO0X1zfv079L1ypHd4qlOs/FP5f3eQPWN40Pa5p6xTdNVjOvG/g8duT9OuYpby9iHAv+zxF8NPLmf3OWxq4CTBhj3C0re75TneGwfsedRNYi3UB2u1Pi5WmKO5zdXd2tVazWxPeusR3yrWpsZ27bOmnK3rTVvc3fDfrHN3/CBe8W6+BmPb8J+sU2s/aL9Yj/jtl9chP1iw7h79oo94nv2i03jpkev2CO3/eII9ovTuxdLkiRJkiRJGkPjdoixJEmSJEmSpA5OEEqSJEmSJEljzAlCSZIkSZIkaYw5QShJkiRJkiSNMScIJUmSJEmSpDHmBKGksRcR/6vFNmdGxH4LMJYLI+KF851HkiRJ7dkvSlrqnCCUNPYy83dbbHYm0FfDFxG7DzYiSZIkLSb2i5KWOicIJY29iPhF+Xl8RFwVEZ+JiO9HxCei8jrgkcDXIuJrZdsTI+LqiLgxIj4dEQ8u6zdFxDkR8U1gIiKu68hzWETcXJbPiYjrI2JDRJwfEbHgv7gkSZJasV+UtNQ5QShJu3oK1be/TwAeCxyXmR8A7gBOyMwTIuIA4G3A72fmU4FvAW/seI5fZeYzMvMvgL0i4rFl/UuAS8ryf8vMp2Xmk4B9gT+a999MkiRJc8F+UdKS4wShJO3quszckpk7gZuAw7pscyxVQ/hPEXETcBrw6I7HL+5YvgR4cVl+ScdjJ0TEtRGxHng28MS5+xUkSZI0j+wXJS05ewx7AJK0yPy6Y/k+un9OBnBFZr6s5jl+2bF8MfDpiPgckJn5g4jYB/gQsCozfxwR7wD2mf3QJUmStADsFyUtOe5BKEnt7AD2L8vXAMdFxO8ARMR+EXFEt6DM/CFV4/if+c23wdPN3d3lXDRehU6SJGn02S9KGlnuQShJ7ZwPfCkitpXzyrwc+FRE7F0efxtwa03sxcB5wGMAMvOeiPgIsB7YBFw/nwOXJEnSgrBflDSyIjOHPQZJkiRJkiRJQ+IhxpIkSZIkSdIYc4JQkiRJkiRJGmNOEEqSJEmSJEljzAlCSZIkSZIkaYw5QShJkiRJkiSNMScIJUmSJEmSpDHmBKEkSZIkSZI0xv4/gfNDgAIKp/kAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of interval\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "sns.countplot(x='interval', hue='hot', data=data, ax=ax[0])\n",
    "ax[0].set_title('Count Plot of interval', fontsize=16)\n",
    "\n",
    "sns.barplot(x='interval', y='count', hue='hot', data=data, ax=ax[1])\n",
    "ax[1].set_title('Count vs. interval', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of dayofweek\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "tmp = data.groupby('hot')['dayofweek'].apply(lambda x: x.value_counts(normalize=True)).unstack()\n",
    "tmp.plot(kind='bar', ax=ax[0])\n",
    "\n",
    "sns.barplot(x='dayofweek', y='count', hue='hot', data=data, ax=ax[1])\n",
    "ax[1].set_title('Count vs. dayofweek', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Reference](https://github.com/stasi009/TakeHomeDataChallenges/blob/master/18.OnlineVideo/online_videos.ipynb)\n",
    "\n",
    "* we can build a model to predict whether the video will be Hot (trending up) or not. The videos which are predicted to be Hot will be shown on the Home page and attract users to click.\n",
    "* study the reason why videos uploaded on Sunday/Monday are much more likely to be Hot than videos uploaded on Thursday.\n",
    "    - if the reason is like my guess, is because Sunday/Monday allow the video have longer \"offline propagation time\"\n",
    "    - then the problem is why \"online propagation\" doesn't work well?\n",
    "    - Is it because our website doesn't have a \"Share...\" buttion?\n",
    "    - or is it because we didn't include the most popular social network in our \"Share with\" list?\n",
    "* study the reason why English videos are more likely to be Hot.\n",
    "    - is is because the translation issue?\n",
    "    - or maybe we didn't include local social network (such as weibo in China) in our 'Share with' list."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}