Multi_channel_attribution_source_medium.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import subprocess"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "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>MCF Channel Grouping Path</th>\n",
       "      <th>Conversions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Organic Search</td>\n",
       "      <td>1,14,822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Direct</td>\n",
       "      <td>1,09,076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Paid Search</td>\n",
       "      <td>81,375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Display</td>\n",
       "      <td>68,024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Direct &gt; Direct</td>\n",
       "      <td>49,239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct</td>\n",
       "      <td>37,095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct</td>\n",
       "      <td>31,329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Organic Search &gt; Direct</td>\n",
       "      <td>28,251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct</td>\n",
       "      <td>27,809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>24,702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>22,421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>20,622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>18,831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>17,371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>16,297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>15,687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>14,902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>14,137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Organic Search &gt; Direct &gt; Direct</td>\n",
       "      <td>13,523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>13,360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>12,886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>12,530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>11,928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>11,439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>11,266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>10,676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>10,429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>10,102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>10,071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>10,056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34970</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34971</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34972</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34973</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34974</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34975</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34976</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34977</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34978</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34979</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34980</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34981</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34982</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34983</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34984</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34985</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34986</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34987</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34988</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34989</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34990</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34991</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34992</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34993</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34994</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34995</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34996</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34997</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34998</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34999</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>35000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               MCF Channel Grouping Path Conversions\n",
       "0                                         Organic Search    1,14,822\n",
       "1                                                 Direct    1,09,076\n",
       "2                                            Paid Search      81,375\n",
       "3                                                Display      68,024\n",
       "4                                        Direct > Direct      49,239\n",
       "5                               Direct > Direct > Direct      37,095\n",
       "6                      Direct > Direct > Direct > Direct      31,329\n",
       "7                                Organic Search > Direct      28,251\n",
       "8             Direct > Direct > Direct > Direct > Direct      27,809\n",
       "9      Direct > Direct > Direct > Direct > Direct > D...      24,702\n",
       "10     Direct > Direct > Direct > Direct > Direct > D...      22,421\n",
       "11     Direct > Direct > Direct > Direct > Direct > D...      20,622\n",
       "12     Direct > Direct > Direct > Direct > Direct > D...      18,831\n",
       "13     Direct > Direct > Direct > Direct > Direct > D...      17,371\n",
       "14     Direct > Direct > Direct > Direct > Direct > D...      16,297\n",
       "15     Direct > Direct > Direct > Direct > Direct > D...      15,687\n",
       "16     Direct > Direct > Direct > Direct > Direct > D...      14,902\n",
       "17     Direct > Direct > Direct > Direct > Direct > D...      14,137\n",
       "18                      Organic Search > Direct > Direct      13,523\n",
       "19     Direct > Direct > Direct > Direct > Direct > D...      13,360\n",
       "20     Direct > Direct > Direct > Direct > Direct > D...      12,886\n",
       "21     Direct > Direct > Direct > Direct > Direct > D...      12,530\n",
       "22     Direct > Direct > Direct > Direct > Direct > D...      11,928\n",
       "23     Direct > Direct > Direct > Direct > Direct > D...      11,439\n",
       "24     Direct > Direct > Direct > Direct > Direct > D...      11,266\n",
       "25     Direct > Direct > Direct > Direct > Direct > D...      10,676\n",
       "26     Direct > Direct > Direct > Direct > Direct > D...      10,429\n",
       "27     Direct > Direct > Direct > Direct > Direct > D...      10,102\n",
       "28     Direct > Direct > Direct > Direct > Direct > D...      10,071\n",
       "29     Direct > Direct > Direct > Direct > Direct > D...      10,056\n",
       "...                                                  ...         ...\n",
       "34970  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34971  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34972  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34973  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34974  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34975  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34976  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34977  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34978  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34979  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34980  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34981  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34982  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34983  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34984  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34985  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34986  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34987  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34988  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34989  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34990  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34991  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34992  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34993  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34994  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34995  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34996  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34997  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34998  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "34999  Direct > Referral > Direct > Direct > Direct >...           1\n",
       "\n",
       "[35000 rows x 2 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv('MCF_Channel_Grouping_Path_data.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 35000 entries, 0 to 34999\n",
      "Data columns (total 2 columns):\n",
      "MCF Channel Grouping Path    35000 non-null object\n",
      "Conversions                  35000 non-null object\n",
      "dtypes: object(2)\n",
      "memory usage: 547.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns = ['Path', 'Conversion']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "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>Path</th>\n",
       "      <th>Conversion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Organic Search</td>\n",
       "      <td>1,14,822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Direct</td>\n",
       "      <td>1,09,076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Paid Search</td>\n",
       "      <td>81,375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Display</td>\n",
       "      <td>68,024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Direct &gt; Direct</td>\n",
       "      <td>49,239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct</td>\n",
       "      <td>37,095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct</td>\n",
       "      <td>31,329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Organic Search &gt; Direct</td>\n",
       "      <td>28,251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct</td>\n",
       "      <td>27,809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>24,702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>22,421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>20,622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>18,831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>17,371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>16,297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>15,687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>14,902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>14,137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Organic Search &gt; Direct &gt; Direct</td>\n",
       "      <td>13,523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>13,360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>12,886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>12,530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>11,928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>11,439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>11,266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>10,676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>10,429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>10,102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>10,071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Direct &gt; Direct &gt; Direct &gt; Direct &gt; Direct &gt; D...</td>\n",
       "      <td>10,056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34970</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34971</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34972</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34973</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34974</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34975</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34976</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34977</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34978</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34979</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34980</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34981</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34982</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34983</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34984</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34985</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34986</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34987</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34988</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34989</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34990</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34991</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34992</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34993</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34994</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34995</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34996</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34997</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34998</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34999</th>\n",
       "      <td>Direct &gt; Referral &gt; Direct &gt; Direct &gt; Direct &gt;...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>35000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Path Conversion\n",
       "0                                         Organic Search   1,14,822\n",
       "1                                                 Direct   1,09,076\n",
       "2                                            Paid Search     81,375\n",
       "3                                                Display     68,024\n",
       "4                                        Direct > Direct     49,239\n",
       "5                               Direct > Direct > Direct     37,095\n",
       "6                      Direct > Direct > Direct > Direct     31,329\n",
       "7                                Organic Search > Direct     28,251\n",
       "8             Direct > Direct > Direct > Direct > Direct     27,809\n",
       "9      Direct > Direct > Direct > Direct > Direct > D...     24,702\n",
       "10     Direct > Direct > Direct > Direct > Direct > D...     22,421\n",
       "11     Direct > Direct > Direct > Direct > Direct > D...     20,622\n",
       "12     Direct > Direct > Direct > Direct > Direct > D...     18,831\n",
       "13     Direct > Direct > Direct > Direct > Direct > D...     17,371\n",
       "14     Direct > Direct > Direct > Direct > Direct > D...     16,297\n",
       "15     Direct > Direct > Direct > Direct > Direct > D...     15,687\n",
       "16     Direct > Direct > Direct > Direct > Direct > D...     14,902\n",
       "17     Direct > Direct > Direct > Direct > Direct > D...     14,137\n",
       "18                      Organic Search > Direct > Direct     13,523\n",
       "19     Direct > Direct > Direct > Direct > Direct > D...     13,360\n",
       "20     Direct > Direct > Direct > Direct > Direct > D...     12,886\n",
       "21     Direct > Direct > Direct > Direct > Direct > D...     12,530\n",
       "22     Direct > Direct > Direct > Direct > Direct > D...     11,928\n",
       "23     Direct > Direct > Direct > Direct > Direct > D...     11,439\n",
       "24     Direct > Direct > Direct > Direct > Direct > D...     11,266\n",
       "25     Direct > Direct > Direct > Direct > Direct > D...     10,676\n",
       "26     Direct > Direct > Direct > Direct > Direct > D...     10,429\n",
       "27     Direct > Direct > Direct > Direct > Direct > D...     10,102\n",
       "28     Direct > Direct > Direct > Direct > Direct > D...     10,071\n",
       "29     Direct > Direct > Direct > Direct > Direct > D...     10,056\n",
       "...                                                  ...        ...\n",
       "34970  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34971  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34972  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34973  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34974  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34975  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34976  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34977  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34978  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34979  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34980  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34981  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34982  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34983  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34984  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34985  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34986  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34987  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34988  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34989  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34990  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34991  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34992  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34993  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34994  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34995  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34996  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34997  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34998  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "34999  Direct > Referral > Direct > Direct > Direct >...          1\n",
       "\n",
       "[35000 rows x 2 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "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>Path</th>\n",
       "      <th>Conversion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(unavailable)</td>\n",
       "      <td>2,077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(unavailable) &gt; (unavailable)</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(unavailable) &gt; (unavailable) &gt; (unavailable)</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(unavailable) &gt; (unavailable) &gt; (unavailable) ...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(unavailable) &gt; (unavailable) &gt; (unavailable) ...</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>(unavailable) &gt; (unavailable) &gt; Direct</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(unavailable) &gt; (unavailable) &gt; Direct &gt; Direct</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>(unavailable) &gt; (unavailable) &gt; Direct &gt; Direc...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(unavailable) &gt; (unavailable) &gt; Organic Search</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>(unavailable) &gt; Direct</td>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; (unavailable) &gt; (unav...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; (unavailable...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; (unavailable...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; (un...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Direct</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Dir...</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Dir...</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Dir...</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Dir...</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Dir...</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Dir...</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Dir...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Dir...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Dir...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Dir...</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Dir...</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Dir...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>(unavailable) &gt; Direct &gt; Direct &gt; Direct &gt; Dir...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34970</th>\n",
       "      <td>Social Network &gt; Direct &gt; Direct &gt; Direct &gt; Di...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34971</th>\n",
       "      <td>Social Network &gt; Direct &gt; Direct &gt; Direct &gt; Di...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34972</th>\n",
       "      <td>Social Network &gt; Direct &gt; Direct &gt; Direct &gt; Di...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34973</th>\n",
       "      <td>Social Network &gt; Direct &gt; Direct &gt; Paid Search</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34974</th>\n",
       "      <td>Social Network &gt; Direct &gt; Organic Search &gt; Direct</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34975</th>\n",
       "      <td>Social Network &gt; Direct &gt; Organic Search &gt; Dir...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34976</th>\n",
       "      <td>Social Network &gt; Direct &gt; Organic Search &gt; Dir...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34977</th>\n",
       "      <td>Social Network &gt; Direct &gt; Organic Search &gt; Dir...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34978</th>\n",
       "      <td>Social Network &gt; Direct &gt; Organic Search &gt; Pai...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34979</th>\n",
       "      <td>Social Network &gt; Direct &gt; Paid Search &gt; Social...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34980</th>\n",
       "      <td>Social Network &gt; Display</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34981</th>\n",
       "      <td>Social Network &gt; Display &gt; Display</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34982</th>\n",
       "      <td>Social Network &gt; Organic Search</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34983</th>\n",
       "      <td>Social Network &gt; Organic Search &gt; Direct</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34984</th>\n",
       "      <td>Social Network &gt; Organic Search &gt; Direct &gt; Direct</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34985</th>\n",
       "      <td>Social Network &gt; Organic Search &gt; Direct &gt; Org...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34986</th>\n",
       "      <td>Social Network &gt; Organic Search &gt; Referral &gt; D...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34987</th>\n",
       "      <td>Social Network &gt; Paid Search</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34988</th>\n",
       "      <td>Social Network &gt; Paid Search &gt; Direct &gt; Direct...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34989</th>\n",
       "      <td>Social Network &gt; Paid Search &gt; Direct &gt; Direct...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34990</th>\n",
       "      <td>Social Network &gt; Paid Search &gt; Direct &gt; Direct...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34991</th>\n",
       "      <td>Social Network &gt; Paid Search &gt; Paid Search</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34992</th>\n",
       "      <td>Social Network &gt; Paid Search &gt; Paid Search &gt; P...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34993</th>\n",
       "      <td>Social Network &gt; Paid Search &gt; Paid Search &gt; P...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34994</th>\n",
       "      <td>Social Network &gt; Referral</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34995</th>\n",
       "      <td>Social Network &gt; Referral &gt; Direct</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34996</th>\n",
       "      <td>Social Network &gt; Social Network</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34997</th>\n",
       "      <td>Social Network &gt; Social Network &gt; Direct</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34998</th>\n",
       "      <td>Social Network &gt; Social Network &gt; Display</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34999</th>\n",
       "      <td>Social Network &gt; Social Network &gt; Organic Search</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>35000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Path Conversion\n",
       "0                                          (unavailable)      2,077\n",
       "1                          (unavailable) > (unavailable)         23\n",
       "2          (unavailable) > (unavailable) > (unavailable)         10\n",
       "3      (unavailable) > (unavailable) > (unavailable) ...          2\n",
       "4      (unavailable) > (unavailable) > (unavailable) ...          5\n",
       "5                 (unavailable) > (unavailable) > Direct          3\n",
       "6        (unavailable) > (unavailable) > Direct > Direct          3\n",
       "7      (unavailable) > (unavailable) > Direct > Direc...          2\n",
       "8         (unavailable) > (unavailable) > Organic Search          2\n",
       "9                                 (unavailable) > Direct        151\n",
       "10     (unavailable) > Direct > (unavailable) > (unav...          2\n",
       "11                       (unavailable) > Direct > Direct         34\n",
       "12     (unavailable) > Direct > Direct > (unavailable...          2\n",
       "13     (unavailable) > Direct > Direct > (unavailable...          2\n",
       "14              (unavailable) > Direct > Direct > Direct         22\n",
       "15     (unavailable) > Direct > Direct > Direct > (un...          2\n",
       "16     (unavailable) > Direct > Direct > Direct > Direct         16\n",
       "17     (unavailable) > Direct > Direct > Direct > Dir...         18\n",
       "18     (unavailable) > Direct > Direct > Direct > Dir...         15\n",
       "19     (unavailable) > Direct > Direct > Direct > Dir...         12\n",
       "20     (unavailable) > Direct > Direct > Direct > Dir...          9\n",
       "21     (unavailable) > Direct > Direct > Direct > Dir...          7\n",
       "22     (unavailable) > Direct > Direct > Direct > Dir...          6\n",
       "23     (unavailable) > Direct > Direct > Direct > Dir...          3\n",
       "24     (unavailable) > Direct > Direct > Direct > Dir...          4\n",
       "25     (unavailable) > Direct > Direct > Direct > Dir...          4\n",
       "26     (unavailable) > Direct > Direct > Direct > Dir...          8\n",
       "27     (unavailable) > Direct > Direct > Direct > Dir...          9\n",
       "28     (unavailable) > Direct > Direct > Direct > Dir...          3\n",
       "29     (unavailable) > Direct > Direct > Direct > Dir...          4\n",
       "...                                                  ...        ...\n",
       "34970  Social Network > Direct > Direct > Direct > Di...          2\n",
       "34971  Social Network > Direct > Direct > Direct > Di...          2\n",
       "34972  Social Network > Direct > Direct > Direct > Di...          2\n",
       "34973     Social Network > Direct > Direct > Paid Search          2\n",
       "34974  Social Network > Direct > Organic Search > Direct          4\n",
       "34975  Social Network > Direct > Organic Search > Dir...          2\n",
       "34976  Social Network > Direct > Organic Search > Dir...          2\n",
       "34977  Social Network > Direct > Organic Search > Dir...          2\n",
       "34978  Social Network > Direct > Organic Search > Pai...          2\n",
       "34979  Social Network > Direct > Paid Search > Social...          2\n",
       "34980                           Social Network > Display          3\n",
       "34981                 Social Network > Display > Display          2\n",
       "34982                    Social Network > Organic Search         14\n",
       "34983           Social Network > Organic Search > Direct          5\n",
       "34984  Social Network > Organic Search > Direct > Direct          3\n",
       "34985  Social Network > Organic Search > Direct > Org...          2\n",
       "34986  Social Network > Organic Search > Referral > D...          2\n",
       "34987                       Social Network > Paid Search          5\n",
       "34988  Social Network > Paid Search > Direct > Direct...          2\n",
       "34989  Social Network > Paid Search > Direct > Direct...          2\n",
       "34990  Social Network > Paid Search > Direct > Direct...          2\n",
       "34991         Social Network > Paid Search > Paid Search          9\n",
       "34992  Social Network > Paid Search > Paid Search > P...          2\n",
       "34993  Social Network > Paid Search > Paid Search > P...          4\n",
       "34994                          Social Network > Referral          5\n",
       "34995                 Social Network > Referral > Direct          2\n",
       "34996                    Social Network > Social Network         10\n",
       "34997           Social Network > Social Network > Direct          2\n",
       "34998          Social Network > Social Network > Display          3\n",
       "34999   Social Network > Social Network > Organic Search          2\n",
       "\n",
       "[35000 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.groupby('Path').sum().reset_index()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('Paths.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the path to the R script that will run the Markov Model\n",
    "path2script = 'C:/Users/Krishna.Priya/Desktop/Channel_attribution/MCF-attribution/Markov.r'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Call the R script\n",
    "subprocess.call(['Rscript', '--vanilla', path2script], shell=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load in the CSV file with the model output from R\n",
    "markov = pd.read_csv('Markov - Output - Conversion values.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Select only the necessary columns and rename them\n",
    "markov = markov[['channel_name', 'total_conversions']]\n",
    "markov.columns = ['Channel', 'Conversion']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# First Touch Attribution\n",
    "df['First Touch'] = df['Path'].map(lambda x: x.split(' > ')[0])\n",
    "df_ft = pd.DataFrame()\n",
    "df_ft['Channel'] = df['First Touch']\n",
    "df_ft['Attribution'] = 'First Touch'\n",
    "df_ft['Conversion'] = 1\n",
    "df_ft = df_ft.groupby(['Channel', 'Attribution']).sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>Channel</th>\n",
       "      <th>Attribution</th>\n",
       "      <th>Conversion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Direct</td>\n",
       "      <td>First Touch</td>\n",
       "      <td>21347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Paid Search</td>\n",
       "      <td>First Touch</td>\n",
       "      <td>10416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Organic Search</td>\n",
       "      <td>First Touch</td>\n",
       "      <td>2144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Display</td>\n",
       "      <td>First Touch</td>\n",
       "      <td>601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Referral</td>\n",
       "      <td>First Touch</td>\n",
       "      <td>306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(unavailable)</td>\n",
       "      <td>First Touch</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Social Network</td>\n",
       "      <td>First Touch</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Email</td>\n",
       "      <td>First Touch</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Channel  Attribution  Conversion\n",
       "1          Direct  First Touch       21347\n",
       "5     Paid Search  First Touch       10416\n",
       "4  Organic Search  First Touch        2144\n",
       "2         Display  First Touch         601\n",
       "6        Referral  First Touch         306\n",
       "0   (unavailable)  First Touch          76\n",
       "7  Social Network  First Touch          70\n",
       "3           Email  First Touch          40"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ft = df_ft.sort_values('Conversion', ascending=False)\n",
    "df_ft"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Last Touch Attribution\n",
    "df['Last Touch'] = df['Path'].map(lambda x: x.split(' > ')[-1])\n",
    "df_lt = pd.DataFrame()\n",
    "df_lt['Channel'] = df['Last Touch']\n",
    "df_lt['Attribution'] = 'Last Touch'\n",
    "df_lt['Conversion'] = 1\n",
    "df_lt = df_lt.groupby(['Channel', 'Attribution']).sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>Channel</th>\n",
       "      <th>Attribution</th>\n",
       "      <th>Conversion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Direct</td>\n",
       "      <td>Last Touch</td>\n",
       "      <td>25079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Paid Search</td>\n",
       "      <td>Last Touch</td>\n",
       "      <td>7098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Organic Search</td>\n",
       "      <td>Last Touch</td>\n",
       "      <td>1783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Referral</td>\n",
       "      <td>Last Touch</td>\n",
       "      <td>543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Display</td>\n",
       "      <td>Last Touch</td>\n",
       "      <td>322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(unavailable)</td>\n",
       "      <td>Last Touch</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Social Network</td>\n",
       "      <td>Last Touch</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Email</td>\n",
       "      <td>Last Touch</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Channel Attribution  Conversion\n",
       "1          Direct  Last Touch       25079\n",
       "5     Paid Search  Last Touch        7098\n",
       "4  Organic Search  Last Touch        1783\n",
       "6        Referral  Last Touch         543\n",
       "2         Display  Last Touch         322\n",
       "0   (unavailable)  Last Touch         119\n",
       "7  Social Network  Last Touch          33\n",
       "3           Email  Last Touch          23"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lt = df_lt.sort_values('Conversion', ascending=False)\n",
    "df_lt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Linear Attribution\n",
    "channel = []\n",
    "conversion = []\n",
    "for i in df.index:\n",
    "    for j in df.at[i, 'Path'].split(' > '):\n",
    "        channel.append(j)\n",
    "        conversion.append(1/len(df.at[i, 'Path'].split(' > ')))\n",
    "lin_att_df = pd.DataFrame()\n",
    "lin_att_df['Channel'] = channel\n",
    "lin_att_df['Attribution'] = 'Linear'\n",
    "lin_att_df['Conversion'] = conversion\n",
    "lin_att_df = lin_att_df.groupby(['Channel', 'Attribution']).sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>Channel</th>\n",
       "      <th>Attribution</th>\n",
       "      <th>Conversion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Direct</td>\n",
       "      <td>Linear</td>\n",
       "      <td>24176.387022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Paid Search</td>\n",
       "      <td>Linear</td>\n",
       "      <td>7835.961433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Organic Search</td>\n",
       "      <td>Linear</td>\n",
       "      <td>1854.935938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Referral</td>\n",
       "      <td>Linear</td>\n",
       "      <td>498.325999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Display</td>\n",
       "      <td>Linear</td>\n",
       "      <td>427.791682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(unavailable)</td>\n",
       "      <td>Linear</td>\n",
       "      <td>133.451185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Social Network</td>\n",
       "      <td>Linear</td>\n",
       "      <td>41.519578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Email</td>\n",
       "      <td>Linear</td>\n",
       "      <td>31.627164</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Channel Attribution    Conversion\n",
       "1          Direct      Linear  24176.387022\n",
       "5     Paid Search      Linear   7835.961433\n",
       "4  Organic Search      Linear   1854.935938\n",
       "6        Referral      Linear    498.325999\n",
       "2         Display      Linear    427.791682\n",
       "0   (unavailable)      Linear    133.451185\n",
       "7  Social Network      Linear     41.519578\n",
       "3           Email      Linear     31.627164"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lin_att_df = lin_att_df.sort_values('Conversion', ascending=False)\n",
    "lin_att_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "markov['Attribution'] = 'Markov'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>Channel</th>\n",
       "      <th>Conversion</th>\n",
       "      <th>Attribution</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Direct</td>\n",
       "      <td>1.097036e+06</td>\n",
       "      <td>Markov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Paid Search</td>\n",
       "      <td>7.645427e+05</td>\n",
       "      <td>Markov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Organic Search</td>\n",
       "      <td>6.295376e+05</td>\n",
       "      <td>Markov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Referral</td>\n",
       "      <td>3.034706e+05</td>\n",
       "      <td>Markov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Display</td>\n",
       "      <td>1.243626e+05</td>\n",
       "      <td>Markov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>(unavailable)</td>\n",
       "      <td>7.388884e+04</td>\n",
       "      <td>Markov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Email</td>\n",
       "      <td>1.634612e+04</td>\n",
       "      <td>Markov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Social Network</td>\n",
       "      <td>1.509906e+04</td>\n",
       "      <td>Markov</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Channel    Conversion Attribution\n",
       "1          Direct  1.097036e+06      Markov\n",
       "2     Paid Search  7.645427e+05      Markov\n",
       "0  Organic Search  6.295376e+05      Markov\n",
       "4        Referral  3.034706e+05      Markov\n",
       "3         Display  1.243626e+05      Markov\n",
       "5   (unavailable)  7.388884e+04      Markov\n",
       "7           Email  1.634612e+04      Markov\n",
       "6  Social Network  1.509906e+04      Markov"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "markov = markov.sort_values('Conversion', ascending=False)\n",
    "markov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Krishna.Priya\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:2: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n",
      "of pandas will change to not sort by default.\n",
      "\n",
      "To accept the future behavior, pass 'sort=False'.\n",
      "\n",
      "To retain the current behavior and silence the warning, pass 'sort=True'.\n",
      "\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "# Concatenate the four data frames to a single data frame\n",
    "df_total_attr = pd.concat([df_ft, df_lt, lin_att_df, markov])\n",
    "df_total_attr['Channel'] = df_total_attr['Channel'].astype(str)\n",
    "# df_total_attr.sort_values(by='Channel', ascending=True, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the attributions\n",
    "sns.set_style(\"whitegrid\")\n",
    "plt.rc('legend', fontsize=15)\n",
    "fig, ax = plt.subplots(figsize=(16, 10))\n",
    "sns.barplot(x='Channel', y='Conversion', hue='Attribution', data=df_total_attr)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read in transition matrix CSV\n",
    "trans_prob = pd.read_csv('Markov - Output - Transition matrix.csv')\n",
    "\n",
    "# Convert data to floats\n",
    "trans_prob ['transition_probability'] = trans_prob ['transition_probability'].astype(float)\n",
    "\n",
    "# Convert start and conversion event to numeric values so we can sort and iterate through\n",
    "trans_prob .replace('(start)', '0', inplace=True)\n",
    "trans_prob .replace('(conversion)', '9', inplace=True)\n",
    "trans_prob .replace('(unavailable)', '1', inplace=True)\n",
    "trans_prob .replace('Direct', '2', inplace=True)\n",
    "trans_prob .replace('Display', '3', inplace=True)\n",
    "trans_prob .replace('Email', '4', inplace=True)\n",
    "trans_prob .replace('Organic Search', '5', inplace=True)\n",
    "trans_prob .replace('Paid Search', '6', inplace=True)\n",
    "trans_prob .replace('Referral', '7', inplace=True)\n",
    "trans_prob .replace('Social Network', '8', inplace=True)\n",
    "\n",
    "# Get unique origin channels\n",
    "channel_from_unique = trans_prob ['channel_from'].unique().tolist()\n",
    "channel_from_unique.sort(key=float)\n",
    "\n",
    "# Get unique destination channels\n",
    "channel_to_unique = trans_prob ['channel_to'].unique().tolist()\n",
    "channel_to_unique.sort(key=float)\n",
    "\n",
    "# Create new matrix with origin and destination channels as columns and index\n",
    "trans_matrix = pd.DataFrame(columns=channel_to_unique, index=channel_from_unique)\n",
    "\n",
    "# Assign the probabilities to the corresponding cells in our transition matrix\n",
    "for f in channel_from_unique:\n",
    "    for t in channel_to_unique:\n",
    "        x = trans_prob [(trans_prob ['channel_from'] == f) & (trans_prob ['channel_to'] == t)]\n",
    "        prob = x['transition_probability'].values\n",
    "        if prob.size > 0:\n",
    "            trans_matrix[t][f] = prob[0]\n",
    "        else:\n",
    "            trans_matrix[t][f] = 0\n",
    "\n",
    "# Convert all probabilities to floats\n",
    "trans_matrix = trans_matrix.apply(pd.to_numeric)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.004802</td>\n",
       "      <td>0.601816</td>\n",
       "      <td>0.037240</td>\n",
       "      <td>0.002598</td>\n",
       "      <td>0.133745</td>\n",
       "      <td>0.195992</td>\n",
       "      <td>0.019150</td>\n",
       "      <td>0.004657</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.552134</td>\n",
       "      <td>0.152032</td>\n",
       "      <td>0.006286</td>\n",
       "      <td>0.101529</td>\n",
       "      <td>0.028989</td>\n",
       "      <td>0.052016</td>\n",
       "      <td>0.010258</td>\n",
       "      <td>0.096757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.015534</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.024076</td>\n",
       "      <td>0.002984</td>\n",
       "      <td>0.165852</td>\n",
       "      <td>0.400501</td>\n",
       "      <td>0.082016</td>\n",
       "      <td>0.002013</td>\n",
       "      <td>0.307024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.099942</td>\n",
       "      <td>0.642004</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.037086</td>\n",
       "      <td>0.069322</td>\n",
       "      <td>0.002122</td>\n",
       "      <td>0.000653</td>\n",
       "      <td>0.148871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.102704</td>\n",
       "      <td>0.658098</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.095927</td>\n",
       "      <td>0.055636</td>\n",
       "      <td>0.003170</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.084465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.004737</td>\n",
       "      <td>0.701324</td>\n",
       "      <td>0.001235</td>\n",
       "      <td>0.001002</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.195474</td>\n",
       "      <td>0.035829</td>\n",
       "      <td>0.001198</td>\n",
       "      <td>0.059201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.002713</td>\n",
       "      <td>0.564420</td>\n",
       "      <td>0.004814</td>\n",
       "      <td>0.001756</td>\n",
       "      <td>0.280201</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.056515</td>\n",
       "      <td>0.000714</td>\n",
       "      <td>0.088867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.007136</td>\n",
       "      <td>0.713698</td>\n",
       "      <td>0.002198</td>\n",
       "      <td>0.001070</td>\n",
       "      <td>0.078965</td>\n",
       "      <td>0.141532</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001790</td>\n",
       "      <td>0.053611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.054024</td>\n",
       "      <td>0.549603</td>\n",
       "      <td>0.022802</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.126577</td>\n",
       "      <td>0.087928</td>\n",
       "      <td>0.020790</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.138276</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          1         2         3         4         5         6         7  \\\n",
       "0  0.004802  0.601816  0.037240  0.002598  0.133745  0.195992  0.019150   \n",
       "1  0.000000  0.552134  0.152032  0.006286  0.101529  0.028989  0.052016   \n",
       "2  0.015534  0.000000  0.024076  0.002984  0.165852  0.400501  0.082016   \n",
       "3  0.099942  0.642004  0.000000  0.000000  0.037086  0.069322  0.002122   \n",
       "4  0.102704  0.658098  0.000000  0.000000  0.095927  0.055636  0.003170   \n",
       "5  0.004737  0.701324  0.001235  0.001002  0.000000  0.195474  0.035829   \n",
       "6  0.002713  0.564420  0.004814  0.001756  0.280201  0.000000  0.056515   \n",
       "7  0.007136  0.713698  0.002198  0.001070  0.078965  0.141532  0.000000   \n",
       "8  0.054024  0.549603  0.022802  0.000000  0.126577  0.087928  0.020790   \n",
       "\n",
       "          8         9  \n",
       "0  0.004657  0.000000  \n",
       "1  0.010258  0.096757  \n",
       "2  0.002013  0.307024  \n",
       "3  0.000653  0.148871  \n",
       "4  0.000000  0.084465  \n",
       "5  0.001198  0.059201  \n",
       "6  0.000714  0.088867  \n",
       "7  0.001790  0.053611  \n",
       "8  0.000000  0.138276  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trans_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>unavailable</th>\n",
       "      <th>Direct</th>\n",
       "      <th>Display</th>\n",
       "      <th>Email</th>\n",
       "      <th>Organic Search</th>\n",
       "      <th>Paid Search</th>\n",
       "      <th>Referral</th>\n",
       "      <th>Social Network</th>\n",
       "      <th>Conversion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Start</th>\n",
       "      <td>0.004802</td>\n",
       "      <td>0.601816</td>\n",
       "      <td>0.037240</td>\n",
       "      <td>0.002598</td>\n",
       "      <td>0.133745</td>\n",
       "      <td>0.195992</td>\n",
       "      <td>0.019150</td>\n",
       "      <td>0.004657</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unavailable</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.552134</td>\n",
       "      <td>0.152032</td>\n",
       "      <td>0.006286</td>\n",
       "      <td>0.101529</td>\n",
       "      <td>0.028989</td>\n",
       "      <td>0.052016</td>\n",
       "      <td>0.010258</td>\n",
       "      <td>0.096757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Direct</th>\n",
       "      <td>0.015534</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.024076</td>\n",
       "      <td>0.002984</td>\n",
       "      <td>0.165852</td>\n",
       "      <td>0.400501</td>\n",
       "      <td>0.082016</td>\n",
       "      <td>0.002013</td>\n",
       "      <td>0.307024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Display</th>\n",
       "      <td>0.099942</td>\n",
       "      <td>0.642004</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.037086</td>\n",
       "      <td>0.069322</td>\n",
       "      <td>0.002122</td>\n",
       "      <td>0.000653</td>\n",
       "      <td>0.148871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Email</th>\n",
       "      <td>0.102704</td>\n",
       "      <td>0.658098</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.095927</td>\n",
       "      <td>0.055636</td>\n",
       "      <td>0.003170</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.084465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Organic Search</th>\n",
       "      <td>0.004737</td>\n",
       "      <td>0.701324</td>\n",
       "      <td>0.001235</td>\n",
       "      <td>0.001002</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.195474</td>\n",
       "      <td>0.035829</td>\n",
       "      <td>0.001198</td>\n",
       "      <td>0.059201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paid Search</th>\n",
       "      <td>0.002713</td>\n",
       "      <td>0.564420</td>\n",
       "      <td>0.004814</td>\n",
       "      <td>0.001756</td>\n",
       "      <td>0.280201</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.056515</td>\n",
       "      <td>0.000714</td>\n",
       "      <td>0.088867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Referral</th>\n",
       "      <td>0.007136</td>\n",
       "      <td>0.713698</td>\n",
       "      <td>0.002198</td>\n",
       "      <td>0.001070</td>\n",
       "      <td>0.078965</td>\n",
       "      <td>0.141532</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001790</td>\n",
       "      <td>0.053611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Social Network</th>\n",
       "      <td>0.054024</td>\n",
       "      <td>0.549603</td>\n",
       "      <td>0.022802</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.126577</td>\n",
       "      <td>0.087928</td>\n",
       "      <td>0.020790</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.138276</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                unavailable    Direct   Display     Email  Organic Search  \\\n",
       "Start              0.004802  0.601816  0.037240  0.002598        0.133745   \n",
       "unavailable        0.000000  0.552134  0.152032  0.006286        0.101529   \n",
       "Direct             0.015534  0.000000  0.024076  0.002984        0.165852   \n",
       "Display            0.099942  0.642004  0.000000  0.000000        0.037086   \n",
       "Email              0.102704  0.658098  0.000000  0.000000        0.095927   \n",
       "Organic Search     0.004737  0.701324  0.001235  0.001002        0.000000   \n",
       "Paid Search        0.002713  0.564420  0.004814  0.001756        0.280201   \n",
       "Referral           0.007136  0.713698  0.002198  0.001070        0.078965   \n",
       "Social Network     0.054024  0.549603  0.022802  0.000000        0.126577   \n",
       "\n",
       "                Paid Search  Referral  Social Network  Conversion  \n",
       "Start              0.195992  0.019150        0.004657    0.000000  \n",
       "unavailable        0.028989  0.052016        0.010258    0.096757  \n",
       "Direct             0.400501  0.082016        0.002013    0.307024  \n",
       "Display            0.069322  0.002122        0.000653    0.148871  \n",
       "Email              0.055636  0.003170        0.000000    0.084465  \n",
       "Organic Search     0.195474  0.035829        0.001198    0.059201  \n",
       "Paid Search        0.000000  0.056515        0.000714    0.088867  \n",
       "Referral           0.141532  0.000000        0.001790    0.053611  \n",
       "Social Network     0.087928  0.020790        0.000000    0.138276  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Rename our start and conversion events\n",
    "trans_matrix.rename(index={'0': 'Start'}, inplace=True)\n",
    "trans_matrix.rename(index={'1': 'unavailable'}, inplace=True)\n",
    "trans_matrix.rename(index={'2': 'Direct'}, inplace=True)\n",
    "trans_matrix.rename(index={'3': 'Display'}, inplace=True)\n",
    "trans_matrix.rename(index={'4': 'Email'}, inplace=True)\n",
    "trans_matrix.rename(index={'5': 'Organic Search'}, inplace=True)\n",
    "trans_matrix.rename(index={'6': 'Paid Search'}, inplace=True)\n",
    "trans_matrix.rename(index={'7': 'Referral'}, inplace=True)\n",
    "trans_matrix.rename(index={'8': 'Social Network'}, inplace=True)\n",
    "\n",
    "trans_matrix.rename(columns={'1': 'unavailable'}, inplace=True)\n",
    "trans_matrix.rename(columns={'2': 'Direct'}, inplace=True)\n",
    "trans_matrix.rename(columns={'3': 'Display'}, inplace=True)\n",
    "trans_matrix.rename(columns={'4': 'Email'}, inplace=True)\n",
    "trans_matrix.rename(columns={'5': 'Organic Search'}, inplace=True)\n",
    "trans_matrix.rename(columns={'6': 'Paid Search'}, inplace=True)\n",
    "trans_matrix.rename(columns={'7': 'Referral'}, inplace=True)\n",
    "trans_matrix.rename(columns={'8': 'Social Network'}, inplace=True)\n",
    "trans_matrix.rename(columns={'9': 'Conversion'}, inplace=True)\n",
    "\n",
    "trans_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABGwAAAK5CAYAAADq07j6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzs3X2Y1XWdP/7nmWFABRTQrLxB8YZI09AU1wJMyUuy3QJNQcttq03zrozRSHe3JSTUWtBN866foWLclWYlpptmol62V7qxqQUmylregAiijMQwzPn9UTvfZZOZM7XnnM/ueTyu61yd8zkzc56e68rL63m9Xu9PqVwulwMAAABAYTTVOwAAAAAAW1PYAAAAABSMwgYAAACgYBQ2AAAAAAWjsAEAAAAoGIUNAAAAQMEobAAAAAAKRmEDAAAAUDAKGwAAAICC6VPNP97vXZ+q5p+nCn6y05P1jkAv/VX/99c7Ar306m/9/+x/myM/+tf1jkAvvfcdb6l3BHpp9pf/v3pH4E/Q3ra+3hHopXLnlnpHoJfaf/7Nekeoi0+X9q7r519bXlnXz09M2AAAAAAUjsIGAAAAoGCquhIFAAAA0FvNpXonqD8TNgAAAAAFo7ABAAAAKBgrUQAAAEChNJfsRJmwAQAAACgYEzYAAABAoTh02IQNAAAAQOEobAAAAAAKxkoUAAAAUCgOHTZhAwAAAFA4JmwAAACAQnHosAkbAAAAgMJR2AAAAAAUjJUoAAAAoFAcOmzCBgAAAKBwFDYAAAAABWMlCgAAACgUd4kyYQMAAABQOCZsAAAAgEJx6LAJGwAAAIDCUdgAAAAAFIyVKAAAAKBQTJf4DgAAAAAKx4QNAAAAUCgOHTZhAwAAAFA4ChsAAACAgrESBQAAABRKs40oEzYAAAAARWPCBgAAACgUhw6bsAEAAAAoHIUNAAAAQMFYiQIAAAAKxaHDFU7YvPjii1u9fvrpp6sSBgAAAIAeJmyefPLJrFq1Kv/0T/+UCy64IEmyZcuWzJ49O9/73vdqEhAAAABoLA4d7qGwefXVV3PnnXfm5ZdfzuLFi5MkpVIpp556ak3CAQAAADSibgubww47LIcddliuuuqqnHPOObXKBAAAANDQKjrD5qc//Wm1cwAAAAAk+f2hw/V8FEFFd4lqb2/PhAkTMmzYsDQ1/b7jmTVrVlWDAQAAADSqigqb888/v9o5AAAAAJI4dDipcCVq+PDhWb16dZ5//vk899xz+fnPf17tXAAAAAANq6IJm8985jPZe++98+STT6Zfv37Zfvvtq50LAAAAoGFVNGGTJNOnT8+wYcMyZ86crF+/vpqZAAAAgAbm0OFeFDabNm3Kxo0bUyqV8vrrr1czEwAAAEBDq6iw+chHPpKbbrop73nPe3LUUUdln332qXYuAAAAgIZV0Rk2u+22W4477rgkyfvf//788pe/rGooAAAAoHEVZS2pnrotbB555JE89dRTufHGG/Pxj388SbJly5bMmzcvd9xxR00CAgAAADSabgubHXfcMWvWrEl7e3teeumlrF+/PoMGDcoFF1xQq3wAAABAg2kuGbHp9gybzZs350c/+lFuueWWDB8+PIsXL873v//9dHR01CofAAAAQMPptrC5/PLLc9lll2W33XbLFVdckW984xu59dZb841vfKNW+QAAAAAaTrcrUeVyOSNGjMiqVauycePGHHjggUmSpqaK7wYOAAAA0CsOHe5hwqazszNJ8sADD+TII49MkrS3t6etra36yQAAAAAaVLcTNkceeWQmT56cF198Mddcc02effbZTJs2Lccff3yt8gEAAAANxqHDPRQ2p59+esaNG5chQ4Zk8ODBefbZZ3PKKafk2GOPrVU+AAAAgIbTbWGTJPvuu2/X86FDh2bo0KFVDQQAAADQ6HosbAAAAABqyaHDPRw6DAAAAEDtmbABAAAACsWhwyZsAAAAAApHYQMAAABQMFaiAAAAgEJx6LAJGwAAAIDCMWEDAAAAFIpDh03YAAAAABSOwgYAAACgYKxEAQAAAIXSZCXKhA0AAABA0ShsAAAAAArGShQAAABQKKVmK1EmbAAAAAAKpqoTNuXOLdX881TBm9+5e70j0EtHvv2oekegl370jZX1jkAvrX/59XpHoJe+Nmt+vSPQSwPfum+9I/AnWLfy8XpHoJf2O+r4ekeAijSZsDFhAwAAAFA0ChsAAACAgnHoMAAAAFAopWbzJb4BAAAAgIIxYQMAAAAUitt6m7ABAAAAKByFDQAAAEDBWIkCAAAACqXJSpQJGwAAAICiMWEDAAAAFEqpyXyJbwAAAACgYBQ2AAAAAAVjJQoAAAAoFIcOm7ABAAAAKBwTNgAAAEChlEzYmLABAAAAKBqFDQAAAEDBWIkCAAAACqXUbL7ENwAAAABQMCZsAAAAgEJxW28TNgAAAACFo7ABAAAAKBgrUQAAAEChlJqsRJmwAQAAACgYhQ0AAABAwViJAgAAAAqlqdl8iW8AAAAAoGBM2AAAAACFUmp26LDCBgAAAKAXOjs7M23atCxfvjx9+/bNjBkzstdee3W9f//99+frX/96kuSAAw7IP/7jP2bTpk254IIL8vLLL6d///657LLLMmTIkG1+hpUoAAAAgF6455570t7enoULF6a1tTWXXnpp13sbNmzIV7/61Vx77bVZtGhRdt9996xbty7z58/P8OHDM2/evEyYMCFXX311t5+hsAEAAAAKpdRcquujJ48++mjGjBmTJBk5cmQef/zxrvd+/vOfZ/jw4bnsssty6qmnZpdddsmQIUO2+p2xY8fm4Ycf7vYzrEQBAAAA/BcLFy7MwoULu15PmjQpkyZN6nq9YcOGDBgwoOt1c3NzOjo60qdPn6xbty7/+q//mttvvz077LBDPvKRj2TkyJHZsGFDBg4cmCTp379/XnvttW4zKGwAAACAQqn3bb3/e0Hz3w0YMCBtbW1drzs7O9Onz+8rlkGDBuWggw7Km970piTJYYcdll/96ldb/U5bW1t23HHHbjNYiQIAAADohUMPPTRLlixJkixdujTDhw/veu8d73hHnnzyyaxduzYdHR3593//9+y333459NBDc//99ydJlixZkne9613dfoYJGwAAAIBeOPbYY/PQQw9l8uTJKZfLmTlzZubMmZOhQ4dm3LhxaW1tzd/+7d8mScaPH5/hw4dnzz33zNSpU3PKKaekpaUls2bN6vYzKi5sHn744fzmN7/JwQcfnGHDhqVfv35/3j8dAAAAwBuo5ODfempqasr06dO3urbvvvt2Pf/ABz6QD3zgA1u9v/322+drX/taxZ9RUWEze/bsvPjii1mxYkVaWlpy/fXXZ/bs2RV/CAAAAACVq+gMm0cffTRf+cpXssMOO2TixIn57W9/W+1cAAAAQINqairV9VEEFRU2W7ZsyaZNm1IqlbJly5Y0NTmrGAAAAKBaKlqJ+tjHPpYTTjgha9euzUknnZS/+Zu/qXIsAAAAgMZVUWHz/ve/P+9+97vzH//xH9ljjz0yZMiQaucCAAAAGlSp2WZPt4XNlClTUiq98e5WT7efAgAAAOBP021hM3ny5FrlAAAAAEiSNBX8tt610G1hM2rUqCTJunXrct1112XlypXZf//9c/rpp9ckHAAAAEAjqmgpbOrUqRk6dGjOO++8vPnNb87UqVOrnQsAAACgYVV06PCmTZty6qmnJklGjBiRu+++u6qhAAAAgMZVshLVfWHzzDPPJEkGDx6cH/7whznssMPyi1/8InvssUdNwgEAAAA0om4Lmy9+8Ytdz+fNm5d58+YlyTbvHAUAAADw53Jb7x4Km7lz577h9c2bN1clDAAAAAAVnmGzYMGCzJkzJx0dHSmXy2lpaXGODQAAAECVVFTYLFq0KHPnzs0111yT8ePH56abbqp2LgAAAKBBNTl0uLLbeg8ePDi77rpr2tracsQRR2T9+vXVzgUAAADQsCoqbAYOHJh77rknpVIpCxYsyNq1a6udCwAAAKBhVVTYzJgxI7vttltaW1uzcuXKTJs2rcqxAAAAgEZVairV9VEE3Z5h8+CDD271eu3atRk9erS7RAEAAABUUbeFzeLFi7f53ujRo//HwwAAAAA0NVe0EPR/WreFzcUXX5w+ffqkvb29VnkAAAAAGl63hc3UqVMza9asjB8/PqXS73e4yuVySqVS7r333poEBAAAAGg03RY2s2bNSpL8+Mc/rkkYAAAAgFJzMQ7+raduC5v/dO+992bevHnZvHlzyuVyXnnllfzgBz+odjYAAACAhlTRKT5f//rXc8455+Stb31rJk6cmOHDh1c7FwAAANCgSs1NdX0UQUUpBg8enEMOOSRJcsIJJ2TVqlVVDQUAAADQyCoqbFpaWvKzn/0sHR0deeCBB/LSSy9VOxcAAABAw6qosPnSl76Ujo6OnHnmmVm0aFE+85nPVDsXAAAA0KBKTU11fRRBRYcO33DDDTn55JOz33775corr6x2JgAAAICGVlFhc+ihh+arX/1q2tracsIJJ+T444/PdtttV+1sAAAAQANqKsjBv/VU0Tcwfvz4XHfddZk9e3YeeOCBjB49utq5AAAAABpWRRM2zz//fG6//fbcfffdOeCAA/KNb3yj2rkAAAAAGlZFhc25556bk046Kd/61rcyYMCAamcCAAAAGljJSlRlhc2tt96a1atX59VXX8369euzevXqHHLIIdXOBgAAANCQKipsLrrooixdujQbN27Mxo0bM3To0CxatKja2QAAAIAGZMKmwkOHn3766SxevDijR4/OnXfemX79+lU7FwAAAEDDqmjCpn///imVSnn99dczZMiQbN68uaI/3tJ/pz8rHLU34if1TkBvbf/vP6h3BHqp3Lml3hHopYMO2LXeEeilR879aL0j0EsHznyi3hH4E6x58mf1jkAvfe/zY+sdAahQRYXNgQcemBtuuCG77rprPve5z6Wjo6PauQAAAIAGVWqyElVRYTNlypRs2LAh2223XZYsWZJ3vvOd1c4FAAAA0LAqKmxeeOGF3HHHHdm0aVOS5Je//GXOOeecqgYDAAAAaFQVFTaf/exnc+SRR+atb31rtfMAAAAADa7U3FzvCHVX8aHDn/vc56qdBQAAAIBUWNjsv//+Wbx4cd7+9renVColSYYNG1bVYAAAAEBjKjU7dLiiwuZXv/pVli1bttW1m2++uSqBAAAAABpdRYXNc889t9XrgQMHViUMAAAAABUWNnfddVeSpFwu5/HHH8/dd99d1VAAAABA42pqshJV0TfQt2/f9O3bN/369cu73vWuPPHEE9XOBQAAANCwKpqwmTVrVtdhwy+99JKmCwAAAKgahw5XWNjss88+Xc9HjBiRMWPGVC0QAAAAQKOrqLCZOHFitXMAAAAA8AcVFTYAAAAAtWIlqsJDhwEAAACoHRM2AAAAQKGU3OzIhA0AAABA0ShsAAAAAArGShQAAABQKA4dNmEDAAAAUDgmbAAAAIBCMWFjwgYAAACgcBQ2AAAAAAVjJQoAAAAolCYrUSZsAAAAAIrGhA0AAABQKKUm8yW+AQAAAICCUdgAAAAAFIyVKAAAAKBQSg4dNmEDAAAAUDQKGwAAAICCsRIFAAAAFIqVKBM2AAAAAIVjwgYAAAAolFKT+RLfAAAAAEDBdFvYbNmyJe3t7TnnnHOyefPmtLe3Z9OmTfnrv/7rWuUDAAAAaDjdrkTdeuutufbaa7NmzZqMHz8+5XI5TU1NOeyww2qVDwAAAGgwTc3N9Y5Qd90WNieffHJOPvnkfOc738mHP/zhJEl7e3v69u1bk3AAAAAAjaiiM2y2bNmSmTNnJkk+/elP5/bbb69qKAAAAKBxlZqb6voogopSLFiwIK2trUmS6667LvPnz69qKAAAAIBGVlFh09TUlH79+iVJWlpaUiqVqhoKAAAAoJF1e4bNfxo3blxOPfXUHHzwwXniiSdyzDHHVDsXAAAA0KCKspZUTxUVNmeddVaOPvroPPPMM5kwYUJGjBhR7VwAAAAADauiwmbVqlW54YYbsm7duhx33HHZtGlT3vnOd1Y7GwAAANCASk0mbCr6Bv7hH/4hJ554Ytrb23PYYYfly1/+crVzAQAAADSsigqbTZs25cgjj0ypVMo+++zTdQAxAAAAAP/zKlqJ6tu3bx544IF0dnZm6dKl6du3b7VzAQAAAA3KocMVTthcfPHFue2227Ju3bp885vfzLRp06ocCwAAAKBxVTRhM2fOnFx++eXVzgIAAABgwiYVTtisWLEir776arWzAAAAAJAKJ2xWrFiRI444IkOGDEmpVEqSPPjgg1UNBgAAANCoKips7rvvvmrnAAAAAEiSlJqsRHVb2Fx99dU566yz0tra+kfvzZo1q2qhAAAAABpZt4XNMccck2XLluWFF17IunXr8qEPfShDhgzJ3nvvXaN4AAAAQKMpNTXXO0LddTtj9Mwzz+Siiy7KhAkTcv7556d///6ZO3euA4gBAAAAqqjbCZubb745t9xyS3bYYYeuaxMnTsyZZ56Z973vfVUPBwAAANCIui1s+vTps1VZkyQDBgxIc7PRJAAAAKBKrER1vxL1n7fw/u86OzurEgYAAACAHiZsnnrqqT+6Q1S5XM6KFSuqGgoAAACgkXVb2FxxxRVveH3y5MlVCQMAAACQpm4XghpCt4XNqFGjapUDAAAAgD/otrABAAAAqLWSmx11f+gwAAAAALWnsAEAAAAoGCtRAAAAQLE0WYkyYQMAAABQMCZsAAAAgGIxYWPCBgAAAKBoFDYAAAAABWMlCgAAACiUUpP5Et8AAAAAQMFUdcJmv9HHVvPPUwUX3/T5ekeglz6cUfWOAP/n/XDhPfWOQC/t95Nh9Y5ALz3/6N31jgAN4ZzvPFbvCPTSnZ9+d70j1IdDh03YAAAAABSNwgYAAACgYBw6DAAAABSLlSgTNgAAAABFY8IGAAAAKBS39TZhAwAAAFA4ChsAAACAgrESBQAAABSLQ4dN2AAAAAAUjcIGAAAAoGCsRAEAAADFYiXKhA0AAABA0ZiwAQAAAAql1GzCxoQNAAAAQMEobAAAAAAKxkoUAAAAUCxN5kt8AwAAAAAFY8IGAAAAKBa39TZhAwAAAFA0ChsAAACAgrESBQAAABRKqeArUZ2dnZk2bVqWL1+evn37ZsaMGdlrr73+6GdOP/30jBs3LqecckrK5XLGjh2bvffeO0kycuTItLa2bvMzFDYAAAAAvXDPPfekvb09CxcuzNKlS3PppZfmmmuu2epnrrjiiqxfv77r9bPPPpsDDzww1157bUWfobABAAAAiqXgt/V+9NFHM2bMmCS/n5R5/PHHt3r/rrvuSqlUytixY7uuPfHEE1m1alVOO+20bLfddrnwwguzzz77bPMziv0NAAAAANTYwoULc8IJJ3Q9Fi5cuNX7GzZsyIABA7peNzc3p6OjI0ny5JNP5o477shnP/vZrX7nTW96U04//fTMnTs3Z5xxRi644IJuM5iwAQAAAPgvJk2alEmTJm3z/QEDBqStra3rdWdnZ/r0+X3Fcvvtt2fVqlX52Mc+lueeey4tLS3Zfffdc/jhh6e5+fdn8xx22GFZtWpVyuVySqXSG36GwgYAAAAolKIfOnzooYfmvvvuy/HHH5+lS5dm+PDhXe99/vOf73p+5ZVXZpdddsnYsWPz1a9+NYMGDcqnPvWpLFu2LLvttts2y5pEYQMAAADQK8cee2weeuihTJ48OeVyOTNnzsycOXMydOjQjBs37g1/5/TTT88FF1yQ+++/P83Nzbnkkku6/QyFDQAAAFAsBZ+waWpqyvTp07e6tu+++/7Rz5177rldz3faaadcf/31lX/Gnx4PAAAAgGpQ2AAAAAAUjJUoAAAAoFiazJf4BgAAAAAKxoQNAAAAUCil5mIfOlwLJmwAAAAACkZhAwAAAFAwFRU2F198cX71q19VOwsAAABA0tRc30cBVFTYHHXUUbn22mszefLkzJs3Lxs2bKh2LgAAAICGVVFhM3bs2PzzP/9zrr766jz66KMZPXp0vvCFL+S5556rdj4AAACAhlPRXaJWrFiR2267Lffdd19GjRqVefPmpaOjI+eee25uu+22amcEAAAAGklB1pLqqaLC5u/+7u8yadKknHvuudluu+26rp944olVCwYAAADQqCoqbBYsWJDVq1dn7dq1KZfLWb16dQ455JB85CMfqXY+AAAAoMGUmtzUuqLC5qKLLsrSpUuzcePGbNy4MUOHDs2iRYuqnQ0AAACgIVVUWT399NNZvHhxRo8enTvvvDP9+vWrdi4AAACAhlXRhE3//v1TKpXy+uuvZ8iQIdm8eXO1cwEAAACNyqHDlU3YHHjggbnhhhuy66675nOf+1w6OjqqnQsAAACgYVU0YTNlypS0tbWlX79+WbJkSd75zndWOxcAAADQqEoOHe62sJk1a1ZKpdIfXV+6dGmmTJlStVAAAAAAjazbwmafffapVQ4AAAAA/qDbwmbixIlJko0bN2bhwoV55plnsv/++2fSpEk1CQcAAAA0ICtRlR063NramjVr1mTMmDF5/vnnc+GFF1Y7FwAAAEDDqujQ4VdeeSXnn39+kuR973tfTj311KqGAgAAABpX2YRNZRM2++23Xx599NEkyfLly7Pbbrtl8+bNaW9vr2o4AAAAgEZU0YTNo48+mgcffDAtLS3ZvHlzkuS4445LqVTKvffeW9WAAAAAAI2mosJm8eLFXc+3bNmS5ubmqgUCAAAAGpyVqMpWon74wx9m8eLF+e53v5sxY8bkhhtuqHYuAAAAgIZVUWHzzW9+M+9+97vz/e9/Pz/5yU9y3333VTsXAAAA0KhKpfo+CqCiwqZfv35Jkv79+6dv375pa2uraigAAACARlZRYbPHHnvkxBNPzIknnpirrroqBx98cLVzAQAAADSsig4dvvTSS9PW1pb+/fvnoIMOyi677FLtXAAAAECjanLocLeFzdVXX52zzjorra2tf/TerFmzqhYKAAAAoJF1W9gcc8wxWbZsWV544YWsW7cuH/rQhzJkyJDsvffeNYoHAAAANJqy23p3f4bNM888k4suuigTJkzI+eefn/79+2fu3Ll59dVXa5UPAAAAoOF0O2Fz880355ZbbskOO+zQdW3ixIk588wz8773va/q4QAAAAAaUbeFTZ8+fbYqa5JkwIABaW5urmooAAAAoIFZiep+JapUKr3h9c7OzqqEAQAAAKCHCZunnnrqj+4QVS6Xs2LFiqqGAgAAAGhk3RY2V1xxxRtenzx5clXCAAAAAFiJ6qGwGTVqVK1yAAAAAPAH3RY2AAAAADVnwqb7Q4cBAAAAqD2FDQAAAEDBWIkCAAAACqVsJaq6hY3v93+fte1b6h0BoHDe+vaD6h2BXlr7m+fqHYFeKjU11zsCf4Jyp/92/N/m6V+9VO8IQIVM2AAAAADFYgLEGTYAAAAARaOwAQAAACgYK1EAAABAsZRK9U5QdyZsAAAAAArGhA0AAABQLA4dNmEDAAAAUDQKGwAAAICCsRIFAAAAFErZSpQJGwAAAICiMWEDAAAAFEuT+RLfAAAAAEDBKGwAAAAACsZKFAAAAFAsDh02YQMAAABQNCZsAAAAgGIxYWPCBgAAAKBoFDYAAAAABWMlCgAAACgWK1EmbAAAAACKRmEDAAAAUDBWogAAAIBCKVuJMmEDAAAAUDQmbAAAAIBiMWFjwgYAAACgaBQ2AAAAAAVjJQoAAAAollKp3gnqzoQNAAAAQMGYsAEAAACKxaHDJmwAAAAAikZhAwAAAFAwVqIAAACAQilbiTJhAwAAAFA0JmwAAACAYjFh031hs3Dhwm2+N2nSpP/xMAAAAAD0UNi89NJLtcoBAAAAwB90W9h8+MMfzlve8pY888wztcoDAAAANLhyqVTvCHXXbWEzZ86cXHjhhfniF7+41fVSqZSbb765qsEAAAAAGlW3hc2FF16YJJk7d+5W19vb26uXCAAAAGho5XK9E9RfRXeJWrBgQebMmZOOjo6Uy+W0tLTk7rvvrnY2AAAAgIZU0X2yFi1alLlz52bs2LG55JJLsu+++1Y7FwAAAEDDqqiwGTx4cHbddde0tbXliCOOyPr166udCwAAAGhQneVyXR9FUFFhM3DgwNxzzz0plUpZsGBB1q5dW+1cAAAAAA2rosJmxowZ2W233dLa2pqVK1fmS1/6UrVzAQAAADSsig4dLpfLeeGFF7Jy5cocfPDBWbNmTbVzAQAAAA2qGEtJ9VVRYfOJT3wi++67b3bcccckSalUyvHHH1/VYAAAAACNqqLCZuDAgbn00kurnQUAAAAgnUZsKitsRo8enfnz52e//fbrunb44YdXLRQAAABAI6uosHnkkUfS3t6en/3sZ0l+vxKlsAEAAACojooKm9dffz033nhjlaMAAAAA/P7mR42uosJm//33zx133JEDDjggpVIpSTJs2LCqBgMAAABoVBUVNsuWLcvy5cu7Gq729vYsXLiwqsEAAACAxuTQ4aSpuzfPO++8JMncuXNz1FFHZe7cuZk7d2769u1bk3AAAAAAjajbwubll1/uen7//fd3Pf/PtSgAAAAA/udVtBKVOPAHAAAAqA0NRA8TNv91ksZUDQAAAEBtdDth89RTT6W1tTXlcnmr5ytWrKhVPgAAAKDBOHS4h8Lmiiuu6Ho+efLkN3wOAAAAwP+sbgubUaNG1SoHAAAAAH9Q8aHDAAAAALXgxkc9HDoMAAAAQO2ZsAEAAAAKpbPeAQrAhA0AAABAwShsAAAAAArGShQAAABQKM4cNmEDAAAAUDgmbAAAAIBC6TRhY8IGAAAAoGgUNgAAAAAFYyUKAAAAKJSyU4dN2AAAAAAUTVUnbH5193er+eepgsdf3VTvCACFs/xHt9Y7Ar104aWfr3cEeumqf36p3hH4E7z2wop6R6CX2tauq3cEoEJWogAAAIBC6ax3gAKwEgUAAABQMCZsAAAAgEJx5rAJGwAAAIDCUdgAAAAAFIyVKAAAAKBQOu1EmbABAAAAKBoTNgAAAEChmK8xYQMAAABQOAobAAAAgIKxEgUAAAAUSqedKBMo5MGRAAAgAElEQVQ2AAAAAEVjwgYAAAAolKLf1buzszPTpk3L8uXL07dv38yYMSN77bVX1/vf+ta3ctttt6VUKuXss8/O0Ucfnd/97ne54IIL8vLLL6d///657LLLMmTIkG1+hgkbAAAAgF6455570t7enoULF6a1tTWXXnpp13tr167NvHnzsmDBgtx4442ZNm1ayuVy5s+fn+HDh2fevHmZMGFCrr766m4/Q2EDAAAA0AuPPvpoxowZkyQZOXJkHn/88a73hgwZku9973tpaWnJmjVrsuOOO6ZUKm31O2PHjs3DDz/c7WdYiQIAAAAKpTP13YlauHBhFi5c2PV60qRJmTRpUtfrDRs2ZMCAAV2vm5ub09HRkT59fl+z9OnTJ7fcckuuvPLKnHbaaV2/M3DgwCRJ//7989prr3WbQWEDAAAA8F/894LmvxswYEDa2tq6Xnd2dnaVNf/pox/9aE4++eR86lOfyk9/+tOtfqetrS077rhjtxmsRAEAAACFUi7X99GTQw89NEuWLEmSLF26NMOHD+967+mnn84555yTcrmclpaW9O3bN01NTTn00ENz//33J0mWLFmSd73rXd1+hgkbAAAAgF449thj89BDD2Xy5Mkpl8uZOXNm5syZk6FDh2bcuHEZMWJEJk2alFKplDFjxmTUqFE56KCDMnXq1JxyyilpaWnJrFmzuv0MhQ0AAABALzQ1NWX69OlbXdt33327np9zzjk555xztnp/++23z9e+9rWKP0NhAwAAABRKZ33PHC4EZ9gAAAAAFIwJGwAAAKBQKjn49/86EzYAAAAABaOwAQAAACgYK1EAAABAoXTGTpQJGwAAAICCUdgAAAAAFIyVKAAAAKBQ3CXKhA0AAABA4ZiwAQAAAAql04iNCRsAAACAolHYAAAAABSMlSgAAACgULZ01jtB/fVY2Fx11VW55ZZb0qfP//vRBx98sKqhAAAAABpZj4XNfffdl5/85CfZbrvtapEHAAAAaHAOHa7gDJudd955q+kaAAAAAKprm03MlClTUiqVsmbNmkycODH7779/kqRUKmXWrFk1CwgAAADQaLZZ2EyePLmWOQAAAACSJFusRG17JWrUqFEZNWpUNmzYkIcffjijRo3Kddddl02bNtUyHwAAAEDD6fEMmyuvvDIf/ehHkyRXXHFFvv71r1c9FAAAANC4Osvluj6KoMfCpk+fPtl5552TJAMHDkxTU4+/AgAAAMCfocfbPx188MFpbW3NyJEj89hjj+WAAw6oRS4AAACAhtVjYXPuuefmkUceydNPP53jjjsu48aNq0UuAAAAoEFt6ax3gvrrsbA588wzM3/+/FpkAQAAACAVFDY77bRTbrrppgwbNqzr/JrRo0dXPRgAAADQmIpy8G899VjYDB48OMuWLcuyZcu6rilsAAAAAKqnx8Lmkksu2er16tWrqxYGAAAAgAoKm6997WuZN29eNm/enN/97nfZe++9s3jx4lpkAwAAABrQFitRaerpB5YsWZIlS5bkr/7qr3LnnXfmzW9+cy1yAQAAADSsHgubQYMGpW/fvmlra8tee+2VjRs31iIXAAAAQMPqcSXqLW95S77zne9k++23z6xZs7Jhw4Za5AIAAAAaVKeNqJ4Lm+nTp+fFF1/M+PHj893vfjeXX355LXIBAAAANKweC5vXX389CxcuzEsvvZT3vve9aWlpqUUuAAAAoEFtMWLT8xk2F110Ufbcc8+sXLkyu+yyS/7u7/6uFrkAAAAAGlaPhc0rr7ySD3/4w+nTp08OPfTQlN1aCwAAAKCqelyJSpIVK1YkSV588cU0NfXY8QAAAAD8yToNi/Q8YfP3f//3ueiii/LLX/4yn/nMZ/KFL3yhFrkAAAAAGlaPEzbDhw/PwoULs379+jQ3N2fAgAG1yAUAAAA0qC0GbLY9YfPEE09kwoQJ2bx5c370ox/l/e9/f0488cT8+Mc/rmU+AAAAgIazzcLm8ssvz6WXXpqWlpZcfvnluf7663Prrbfm+uuvr2U+AAAAgIazzZWocrmcESNGZNWqVdm4cWPe8Y53JIlDhwEAAICqcuhwNxM2nZ2dSZIHHnggRx55ZJKkvb09bW1ttUkGAAAA0KC2OWFz5JFHZvLkyXnxxRdzzTXX5Nlnn820adNy/PHH1zIfAAAA0GC2dJqw2WZhc/rpp2fcuHEZMmRIBg8enGeffTannHJKjj322FrmAwAAAGg43d7We9999+16PnTo0AwdOrTqgQAAAAAaXbeFDQAAAECtOXS4m0OH38jmzZurlQMAAACAP+ixsFm0aFFmzpyZJDnjjDNy++23Vz0UAAAA0Li2lOv7KIIeC5v58+entbU1SXLddddl/vz5VQ8FAAAA0Mh6LGyamprSr1+/JElLS0tKpVLVQwEAAAA0sh4PHR43blxOPfXUHHzwwXniiSdyzDHH1CIXAAAA0KAcOlxBYXPWWWfl6KOPzjPPPJMJEyZkxIgRFf/xcueWPysctfepj4+sdwR66cpHm+sdgV7y78b/fR7+/ux6R6CXjvzglHpHoJd2PeA99Y7An+C1F1bUOwK9NGCXIfWOAFRom4XNt7/97Zx00kmZNWtW1xrUsmXLcuedd2bKFP8RBAAAAFRHZ6cJm20WNm95y1uSJPvss0/NwgAAAADQTWEzZsyYJMmECRPy2GOPZdOmTTULBQAAANDIejzD5txzz83atWu7Jm5KpVIOP/zwqgcDAAAAGtMWG1E9FzZr1qzJggULapEFAAAAgCRNPf3AsGHDsmrVqlpkAQAAACAVTNj827/9W44++ugMGfL/bv/24IMPVjUUAAAA0Lg6y3aieixs7r777lrkAAAAAOAPeixsli5dmttuuy2bN29OkqxevTo33HBD1YMBAAAAjWmLCZuez7CZMWNGRo0alQ0bNmS33XbLoEGDapELAAAAoGH1WNjsuOOO+cu//MsMGDAg5557rgOIAQAAAKqsx5WoUqmUX//619m4cWOefvrpvPTSS7XIBQAAADSozk4rUT1O2HzhC1/Ir3/965x22mk5//zzc8opp9QiFwAAAEDD6nHCpn///hk5cmSS5KqrrkqfPn2yefPmtLS0VD0cAAAA0Hi2GLDpubA544wzsmrVqgwbNiwrV67M9ttvn46OjlxwwQX50Ic+VIuMAAAAAA2lx5WoPfbYI3fddVcWLlyYf/mXf8lBBx2UO+64I7fcckst8gEAAAA0nB4nbF5++eUMGTIkSbLTTjtlzZo1GTRoUJqaeux6AAAAAHqts2wnqsfC5oADDsiUKVMycuTILF26NG9/+9tz5513Zuedd65FPgAAAICG02NhM2XKlPzsZz/LihUr8sEPfjDvfe978/TTT+foo4+uRT4AAACgwWwxYVPZocPz58/PuHHjuq7ts88+VQ0FAAAA0Mh6LGx22mmn3HTTTRk2bFjXuTWjR4+uejAAAACARtVjYTN48OAsW7Ysy5Yt67qmsAEAAACqZUunlageC5uzzz47L7zwQt761rdmjz32qEUmAAAAgIa2zcKmra0tra2teeWVV7L77rtn5cqV2XnnnTN79uwMGDCglhkBAACABmLCppvCZtasWRk/fnwmTJjQde3b3/52vvKVr2T69Ok1CQcAAADQiJq29cayZcu2KmuS5KSTTsry5curHgoAAACgkW1zwqZPnzd+q7m5uWphAAAAAKxEdTNhM2jQoDz22GNbXXvsscey0047VT0UAAAAQCPb5oTN5z//+Zx55pk54ogjsueee+a3v/1tHn744VxzzTW1zAcAAAA0GBM23UzY7LHHHvnOd76Tww8/PJs3b87BBx+cRYsWZc8996xlPgAAAICGs80JmyTp169fjjvuuFplAQAAACA9FDYAAAAAtWYlqpuVKAAAAADqQ2EDAAAAUDA9rkQtWrQoN910U373u9+lXC6nVCrl3nvvrUU2AAAAoAFZiaqgsFmwYEGuv/76vOlNb6pFHgAAAICG12NhM3jw4Oy+++61yAIAAABgwibdFDazZ89OkrS3t+eTn/xkDjjggJRKpSTJlClTapMOAAAAoAFts7AZNmzYVv8LAAAAQG1s8y5REydOzMSJEzNs2LC89tprmThxYh588MEMHz68lvkAAACABrOls1zXRxH0eFvvGTNm5N3vfneS5LzzzsvMmTOrHgoAAACgkfV46HCfPn2y3377JUn23HPPNDX12PEAAAAA/MmKMuVSTz0WNrvttltmz56dkSNH5he/+EV23XXXWuQCAAAAaFg9jst8+ctfzpAhQ3L//fdnyJAhueSSS2qRCwAAAKBh9Thhc/bZZ+eb3/xmLbIAAAAAWIlKBYXNwIEDc++992bvvffuOr/Grb4BAAAAqqfHwmbt2rW58cYbu16XSqXcfPPN1cwEAAAANLAOEzY9FzZz587d6nV7e3vVwgAAAABQQWGzYMGCzJkzJx0dHSmXy2lpacndd99di2wAAAAADanHwmbRokWZO3durrnmmowfPz433XRTLXIBAAAADcqhwxXc1nvw4MHZdddd09bWliOOOCLr16+vRS4AAACAhlXRXaLuueeelEqlLFiwIGvXrq1FLgAAAKBBmbCpYMJmxowZ2X333dPa2pqVK1dm2rRpNYgFAAAA0Lh6nLDZfvvt8/jjj+eFF17I0Ucfnf33378WuQAAAAAaVo8TNl/84hfz/PPP56GHHkpbW1umTp1ai1wAAABAg9pSLtf1UQQ9FjbPPvtsPvvZz6Zfv3455phj8tprr9UiFwAAAEDD6rGw2bJlS9dBwxs2bEhTU4+/AgAAAMCfocczbM4777yccsopeemllzJp0qRcdNFFtcgFAAAANCh3iaqgsBk1alTuvvvuvPzyy9l5551rkQkAAACgoW1zv+k3v/lNzj777HR0dOSRRx7JBz/4wRx77LFZunRpLfMBAAAADWZLZ7mujyLYZmEzc+bMnHDCCenTp08uueSSfOUrX8ktt9ySWbNm1TIfAAAAQMPZ5kpUe3t7xo0bl3Xr1uXFF1/Me97zniRJZ2dnzcIBAAAANKIez7B5+OGH8xd/8RdJfl/WuK03AAAAUE1FWUuqp20WNvvvv39aW1vz+OOP5+KLL87q1asze/bsrvIGAAAAgOrYZmEzderULFmyJGeccUaGDx+e5cuXZ8SIETnttNNqmQ8AAABoMFscx7LtwqZUKuWoo47qev22t70tb3vb22oSCgAAAKCRbfMuUQAAAADUR4+HDgMAAADUkkOHuylsbr/99m3+0oQJE6oSBgAAAIBuCpsVK1YkSZYuXZrtt98+hxxySB577LF0dHQobAAAAICqMWHTTWHT2tqaJPnkJz+Z66+/vuv6Jz7xieqnAgAAAGhgPZ5hs3bt2rz66qvZcccds27durzyyisV//GmPn3/rHDU3uXf+Ld6R6CXyiOPqXcE+D9v8qX31TsCvTTm4x+vdwR66YE5c+odARrCqy++WO8IQIV6LGw+/elP58QTT8yAAQOyYcOGzJw5sxa5AAAAgAbVYSWq58LmuOOOy3HHHZeXX345gwYNSnNzcy1yAQAAADSsbRY206dPzxe/+MVMmjQppVJpq/cWLFhQ9WAAAABAY3LocDeFzVlnnZUkmT17ds3CAAAAANBNYbPLLrskSTo6OnLXXXdl8+bNSZLVq1dn+vTptUkHAAAAUDCdnZ2ZNm1ali9fnr59+2bGjBnZa6+9tvqZtWvXZvLkyfnBD36Qfv36pVwuZ+zYsdl7772TJCNHjuy6Q/cb6fEMm6lTp+boo4/+/9u78/iY7v2P4+9JJGQRSQixVqK0qtdVl8ZyUbUvtbWRRJtWqeUqbQWlJOoiEUukpRLSWxT3R5C4bd0utym1VbWUqyiCtqKWhNiSVJbJ/P7wMz8pk6Qlk2Fez8cjDzNnjnM+c858z5z5nM/3e/Tdd9+pevXqysnJubN3BQAAAAAAUAxb7xKVkpKivLw8JSYmat++fYqOjlZ8fLz59W3btikmJkbnz583Tzt58qSaNGmixYsXl2odDiXNUKlSJY0YMUI1atRQdHR0kZUBAAAAAADYmz179qhdu3aSrlfKHDhwoMjrDg4OWrZsmTw9Pc3TDh48qHPnzik0NFTDhg3TiRMnil1HiRU2JpNJGRkZysnJUU5Oji5fvvxH3gsAAAAAAECplHeFTWJiohITE83Pg4KCFBQUZH6elZUld3d383NHR0cVFBSoQoXraZa2bdveskwfHx8NHz5cPXr00O7duzVhwgQlJSVZjKHEhM3o0aP1+eefq0+fPurUqZP69etXuncHAAAAAABwD/ptgua33N3dlZ2dbX5eWFhoTtZY8uijj8rR0VGS1KJFC507d04mk+mWO3PfUOzSsrKy9Oijj6ply5aSpE6dOhW7cgAAAAAAgPtd8+bNtXnzZvXs2VP79u1To0aNSvw/77zzjjw9PTVs2DAdPnxYtWrVspiskYpJ2KxatUpLly5VhQoVFBERYe6bBQAAAAAAUJbKu0tUSbp06aIdO3YoODhYJpNJUVFRWrZsmerVq2ex2GX48OGaMGGCtmzZIkdHR82aNavYdVhM2GzcuFGffvqpsrKy9Prrr5OwAQAAAAAA0PVBhadPn15kWoMGDW6Zb9OmTebHVapUUUJCQunXYekFZ2dnOTs7y9vbW/n5+aVeIAAAAAAAAO5MiYMOS9fvFAUAAAAAAGANtt4lyhosJmyOHTumcePGyWQymR/fEBMTY5XgAAAAAAAA7JHFhM1bb71lfhwcHGyVYAAAAAAAAExU2FhO2Dz++OPWjAMAAAAAAAD/x+KgwwAAAAAAACgfpRp0GAAAAAAAwFoK6RJFhQ0AAAAAAICtocIGAAAAAADYFJOJChsqbAAAAAAAAGwMCRsAAAAAAAAbQ5coAAAAAABgU0wMOkyFDQAAAAAAgK2hwgYAAAAAANgUbutNhQ0AAAAAAIDNIWEDAAAAAABgY+gSBQAAAAAAbIqpsLwjKH9U2AAAAAAAANgYKmwAAAAAAIBNMZkYdJgKGwAAAAAAABtDwgYAAAAAAMDG0CUKAAAAAADYlMJCukRRYQMAAAAAAGBjiq2w+etf/2rxte3bt9/1YAAAAAAAAExU2BSfsCEpAwAAAAAAYH2lGsNm3759Sk5OVn5+viQpPT1d7733XpkGBgAAAAAAYK9KNYbNzJkz9fjjjysrK0u1atWSp6dnWccFAAAAAADslKnQVK5/tqBUCRsPDw/17t1b7u7uGjNmjM6dO1fWcQEAAAAAANitUiVsDAaDUlNT9euvv+rEiRPKyMgo67gAAAAAAADsVqnGsJk0aZJSU1MVGhqq8ePHKyQkpKzjAgAAAAAAdqrQZBvdkspTqRI269ev1xtvvCFJSk5OLtOAAAAAAAAA7F2pEjbHjx/XlStX5OHhUdbxAAAAAAAAO2crA/+Wp1IlbE6cOKFWrVrJy8tLBoNBkrR9+/YyDQwAAAAAAMBelSphExkZqdatW5d1LAAAAAAAAFAp7xL1zjvvlHUcAAAAAAAAkq53iSrPP1tQqgobg8Ggl19+WX5+fnJwuJ7jCQsLK9PAAAAAAAAA7FWpEjZPP/10WccBAAAAAAAgSSq0kSqX8lSqLlFPPfWUCgoKlJaWplq1aqlDhw5lHRcAAAAAAIDdKlXC5s0339Tp06e1Y8cOZWdna+LEiWUdFwAAAAAAgN0qVcLm5MmTevXVV+Xs7Kwnn3xSV69eLeu4AAAAAACAnTKZTOX6ZwtKlbAxGo3KzMyUwWBQVlaWeeBhAAAAAAAA3H2lGnR47NixCgkJUUZGhoKCgjR58uSyjgsAAAAAANgpU2F5R1D+ik3YxMbGauzYsbp8+bI+++wzZWZmysvLSwaDwVrxAQAAAAAA2J1iEzZffPGFqlevrpUrV+rChQtFXgsKCirTwAAAAAAAAOxVsQmbqKgo7dixQ3l5ecrIyLBWTAAAAAAAwI4VFtrGwL/lqdiETdOmTdW0aVO1bdtW/v7++uWXX1S3bl25urpaKz4AAAAAAAC7U6pBh0+fPq2pU6fKaDSqe/fuMhgMGjVqVFnHBgAAAAAA7JCJCpvS3dZ7+fLlWrt2rTw9PTVq1CilpKSUdVwAAAAAAAB2q1QJG4PBIGdnZxkMBhkMBrm4uJR1XAAAAAAAAHarVF2iWrZsqbCwMJ07d05Tp05V06ZNyzouAAAAAABgp+gSVULCpqCgQJs2bVKbNm2Ul5enRx55RNWqVdOXX35ppfAAAAAAAADsT7EJm/Hjx8vR0VHnz59Xly5d1KBBA4WHh+v555+3VnwAAAAAAMDOFJqosCk2YXPy5EklJycrLy9PTz/9tJycnLRixQo1aNDAWvEBAAAAAADYnWITNu7u7pIkZ2dnFRYWaunSpfL09LRKYAAAAAAAAPaqVIMOS1LVqlVJ1gAAAAAAgDLHoMMlJGyOHTumcePGyWQymR/fEBMTU+bBAQAAAAAA2KNiEzZvvfWW+XFwcHCZBwMAAAAAAIASEjaPP/64teIAAAAAAACQRJcoSXIo7wAAAAAAAABQVKkHHQYAAAAAALCGQipsyjZhU/XB5mW5eJSBiR2yyzsE/E6rv/Mt7xDwO/168Wx5h4DfqUY97pJ4rzn948XyDgG/U6UqPuUdAv6Aa5czyjsE/E6NAh4u7xAAlBJdogAAAAAAAGwMXaIAAAAAAIBNMZnoEkWFDQAAAAAAgI2hwgYAAAAAANgUbutNhQ0AAAAAAIDNIWEDAAAAAABgY+gSBQAAAAAAbEohXaKosAEAAAAAALA1VNgAAAAAAACbYio0lncI5Y4KGwAAAAAAABtDwgYAAAAAAMDG0CUKAAAAAADYFLpEUWEDAAAAAABgc6iwAQAAAAAANoUKGypsAAAAAAAAbA4JGwAAAAAAABtDlygAAAAAAGBTTEa6RFFhAwAAAAAAYGNI2AAAAAAAANgYukQBAAAAAACbwl2iqLABAAAAAACwOVTYAAAAAAAAm0KFDRU2AAAAAAAANoeEDQAAAAAAgI2hSxQAAAAAALApdImiwgYAAAAAAMDmUGEDAAAAAABsChU2VNgAAAAAAADYHBI2AAAAAAAANoYuUQAAAAAAwKbQJYoKGwAAAAAAAJtDhQ0AAAAAALAphVTYUGEDAAAAAABga0pM2Hz99dfmx9euXdPUqVPLNCAAAAAAAAB7V2KXqLfffltubm4yGo0KDw9Xnz59rBEXAAAAAACwUww6XIqEzaJFizRq1Cjl5eXp7bffVoMGDawRFwAAAAAAgN2ymLCJiYmRwWCQJPn5+Wnbtm364IMPJElhYWHWiQ4AAAAAANgdKmyKSdj4+/tLkgoLC+Xn56fHH3/cakEBAAAAAADYM4sJm/79+0uShgwZoqVLl1otIAAAAAAAAHtX4hg2lStX1hdffKH69evLweH6TaX8/PzKPDAAAAAAAGCfTEa6RJWYsMnMzNTy5cvNzw0Gg1asWFGWMQEAAAAAANi1EhM2K1eu1MWLF5WWlqY6derI29vbGnEBAAAAAAA7xaDDkkNJM3zyyScKDg7W4sWLFRQUZL5TFAAAAAAAAMpGiRU2y5cvV3Jystzc3JSVlaUXXnhBffv2tUZsAAAAAAAAdqnEhI3BYJCbm5skyd3dXRUrVizzoAAAAAAAgP2iS1QpEjb16tVTdHS0WrRood27d6tevXrWiAsAAAAAAMBulTiGTVRUlOrWrauvvvpKdevW1YwZM6wRFwAAAAAAgN0qscJmxIgR6tq1q15++WVVrVrVGjEBAAAAAAA7RpeoUlbYGI1GTZkyRUOGDNGKFSusERcAAAAAAIDdKjFhU716df3pT39Ss2bNdOXKFX388cfWiAsAAAAAANgpU2Fhuf7ZghK7RLVq1Uo1a9bUsGHDtGzZMlWuXNkacQEAAAAAANitEhM2ixcv1vbt25WUlKTPPvtMbdq0UXBwsDViAwAAAAAAsEslJmwee+wx1apVS9WrV9fGjRu1YcMGEjYAAAAAAKDMMOhwKRI2/fr1k5eXlzp37qx58+apRo0a1ogLAAAAAADAbpWYsOnVq5eGDRtmfr5ixQo9//zzZRoUAAAAAACwX1TYFJOw2bhxozZt2qRdu3bp8OHDkiSj0ajU1FQSNgAAAAAAAGXIYsKmXbt28vHx0aVLlxQUFCRJcnBwUN26da0WHAAAAAAAgD2ymLCpUqWKAgICFBAQoJ07dyotLU1NmzaVp6enNeMDAAAAAAB2ppAuUSWPYTN//nydPXtWx48fl5OTkxISEjR//nxrxAYAAAAAAGCXHEqaYc+ePZozZ45cXV3Vv39/nTp1yhpxAQAAAAAAO2UyGsv1zxaUmLAxGo3Kzc2VwWCQ0WiUg0OJ/wUAAAAAAAB3oMQuUS+88IIGDBigzMxMBQYGavDgwVYICwAAAAAAwH6VmLDp0aOH2rRpo59//ll16tSRt7e3NeICAAAAAAB2ysSgw5YTNu+8847F/zR69OgyCQYAAAAAAADFJGyqVatW5Pmvv/6qd999V7Vr1yZhAwAAAAAAygwVNsUkbIKDg82Pd+/erYiICD377LMaOXKkVQIDAAAAAACwV8WOYZOfn6/58+dr586diomJ0SOPPGKtuAAAAAAAAOyWxYTNoUOH9MYbb6hdu3Zat26dnJycrBkXAAAAAACwU3SJKiZhM3DgQLm5uenbb79VaGioJMlkMslgMGjNmjVWCxAAAAAAAMDeWEzYfPbZZ9aMAwAAAAAAQJLtV9gUFhZq2rRpOnLkiJydnTVz5kw98MAD5tfXrl2rNWvWqEKFCvrb3/6mjh07KjMzU+PHj9e1a9dUvXp1zZo1Sy4uLhbXYTFhU7t27bv7bgAAAAAAAO4DKSkpysvLU2Jiovbt26fo6GjFx8dLkjIyMrRy5UolJSUpNzdXgwYNUtu2bRUXF6fevXtrwIABSkhIUGJiolfMF8cAABkpSURBVAYPHmxxHQ5Wei8AAAAAAAD3hT179qhdu3aSpGbNmunAgQPm1/bv36/HHntMzs7Oqly5surVq6fDhw8X+T/t27fXV199Vew6ir1L1J36ZfXwslw8ygT77F5zubwDAADgruhT3gEAAGxI3t6l5br+xMREJSYmmp8HBQUpKCjI/DwrK0vu7u7m546OjiooKFCFChWUlZWlypUrm19zc3NTVlZWkelubm66evVqsTFYTNiEhYXJYDDc9rWYmJgS3hoAAAAAAMC96bcJmt9yd3dXdna2+XlhYaEqVKhw29eys7NVuXJl8/RKlSopOztbHh4excZgMWETHBxc6jcCAAAAAABgL5o3b67NmzerZ8+e2rdvnxo1amR+rWnTpnrrrbeUm5urvLw8HT9+XI0aNVLz5s21ZcsWDRgwQFu3btVf/vKXYtdhMJlMpuJmuHTpkrZv366CggKZTCalp6drxIgRd+cdAgAAAAAA3GNu3CXq6NGjMplMioqK0tatW1WvXj116tRJa9euVWJiokwmk0aMGKFu3brp/PnzmjhxorKzs+Xl5aWYmBi5urpaXEeJCZvnn39e9evX19GjR1WxYkW5uLho8eLFd/3NAgAAAAAA4LpS3SVq+vTp8vPz07Jly3T5MkOcAgAAAAAAlKVSJWxyc3P166+/ymAwKCcnp6xjAgAAAAAAsGslJmyeffZZLV++XG3btlWHDh3k7+9vjbjuGWPHjlVeXp4mTZqkrVu3WpwvNDRUx48fLzJt165dGjt2bFmHeN/atWuXWrdurdDQUD333HMKDg7Wxx9/rB9++EHvvPPOHS07MTFR+fn5dylS+3U391FycrLmzZtXRpHCkpv34Y2/V1555Q8vLzIyUqdPn9bChQu1evXquxjpvSctLU1jxoxRaGiogoODNW3aNGVlZZXJurZu3VrktpTFSUhI0ODBgzVkyBANHTpUBw4cuOvx3I/ff79tKwMHDtTKlSstzp+RkaFp06bdMn3evHlKTk4uMq2wsFCzZs3Siy++qKFDh2rkyJFKS0u722+B46wFv923AwYM0CuvvKK8vLzbzr9//3716tXrrt5VtW3btndtWfeKOz0WWWpjN9zuOHTq1Ck1adKkyLpWr16thQsXWlzOpUuX9NFHH/2u2CyxhzaYmpqq4cOHKzQ0VE8//bQWLFigEkboKFOjR48ut3UDpWHxLlE3dOvWzfy4R48eRe4zDik2Nra8Q7BrrVq1Mu+D7OxshYaGKjIy8o4PvkuWLFG/fv3uRoh2r6z2Eazn5n14p6ZMmXJXlnOvu3btmkaNGqWZM2fqz3/+syRpw4YNGjdunJYsWXLX19e+fftSzXfs2DFt2rRJq1evlsFg0A8//KCJEyfqww8/vOsx3Y9ubit5eXnq3r27+vbte9tbdvr4+BT7Y/Jm27ZtU3p6upYtWyZJSklJUVRUlOLj4+9a7Cjeb4+D48aN06ZNm9S9e/db5t2+fbuCg4MVGhpqzRDvK3fjWPR72tjN3N3d9cYbbygpKUnOzs4lzn/kyBFt2rRJTz311O9el725cuWKwsLCtHDhQtWvX19Go1Gvvvqq1qxZo5CQkHKJ6U4v8gJlzWLCZvr06Zo6daqCgoJkMBiKvLZmzZoyD+xOJCcn68SJExo/frxyc3PVo0cP1a5dWw8//LBSU1OVlZWlt99+W7Vr11ZMTIwOHDig7OxsNWjQQLNmzdKAAQO0YMEC1alTR5988on27Nmjl156SdOmTVNubq4uXbqkl19+WZ07d9aTTz6pTz75xLzurKwsTZkyRVevXtXFixcVGBioQYMGSZIWLFigixcvytnZWXPmzCkS8yeffKLly5fLwcFBf/nLXzR+/HirbrP7gZubm4KCgjR9+nT5+voqNjZWHTt2lL+/v/z9/TVkyBBFREQoNzdXFStW1IwZM1SzZk3FxcUpJSVFRqNRISEhcnR0VEZGhsaOHau4uLjyflv3ldvto0mTJunkyZPKzc3V0KFD1bNnT/Xs2VMtWrRQamqqqlSpovnz5xdZzu3abXBwsGbMmKGGDRtqy5Yt+vLLL/Xmm2+W0zu9/4WGhuqhhx5SamqqXF1d1aJFC23fvl1XrlzR0qVL5ejoeNtjYWho6B86gb7ffPnll2rZsqU5WSNJ/fv31+rVq5WWlqZFixbp0qVLunTpkpYsWaLY2FgdOHBA1apV0y+//KL4+Hjl5OQoOjpahYWFunLlisLDw9W8eXN17dpVzZs3148//qiqVatq4cKF+uCDD8zfi7895gUHB5tj8Pb21unTp7V+/Xq1b99ejRs31vr16yVd/1Eyc+ZMSZKnp6eioqLk6uqqqVOn6uzZs7p48aLat2+v1157TZMmTTLHHx8fr4ULF2r//v3Kz8/XmDFjVLlyZf3888966aWXlJmZqY4dO2rMmDHW3QllLCsrSw4ODnJ0dNQ333xj/lFw7do1zZ49W05OTgoLC9PatWv12WefKT4+Xt7e3srPz7+lmtnX11cHDhzQxx9/rFatWqlTp07mJNw333yj2NhYOTo6qm7dupo+fbpyc3Mttj8vLy9duXJFcXFxmjJlik6fPq38/HxFRERIkv773/9qyJAhyszMVEhIiIKCgqy74e4BeXl5Sk9PV5UqVRQTE6Nvv/1WJpNJgwcPVu3atbV+/Xo5OTnJ19dXVapUuWX/fPTRR0pKSlJhYaFeeeUVTZ482XyuEhgYeNt2bW+KOxYdOnRIM2bMkKOjo/l8rlatWrcc2/7617+a29inn36qf/7zn+blv/322xbX/cADD6hFixaKjY3VxIkTi7x2u/P1xYsX6/Dhw0pISNC///1vffDBB9q7d69GjBihnTt3KiMjQ1OmTNHixYs1efJkpaWlyWg06sUXX1TPnj2LtMtevXpJkjIzMzVq1Ci9+uqrat26dRls4fLxxRdfKCAgQPXr15ckOTo6mo+H0dHR2rNnjySpd+/eeuGFFzRp0iQ5Ozvrl19+UXp6uqKjo3X27FmlpKRo1qxZkqR+/frpvffe0zfffHPLvlm4cKH27t2rnJwcRUZGau7cucrKytK1a9c0YcIEBQQEqG3bttqxY8dtP1eFhYUaN26cfH19lZaWpj/96U/6+9//Xl6bD3bKYsJm1KhRkqT58+fLZDLJYDAoLy+vVJlmW9W0aVNNmTJFsbGx+ve//61BgwbJw8NDy5YtU2FhoXr16qVz587pmWee0b/+9S+NHj1aGzZs0Pjx43XixAm9+OKLCggI0HfffaeFCxeqc+fOt6zj559/Vq9evdS1a1edO3dOoaGh5oRN165d1atXL/3zn//UkiVL9OSTT0q6Xkq5cOFCJSUlycXFRRMmTNCOHTvssvz1TlWtWlUXL16Ur6+vJOnMmTNKTk6Wl5eXXnvtNYWGhqpDhw7auXOn5s2bp6FDh2rr1q1at26d8vLyFBMToylTpig+Pp7qqTJy8z7KysrSrl27lJSUJEnasWOHpOs/aJ566im1bNlSc+bMUWJioqpUqSLp+o+g27XbwMBAbdiwQa+//rqSkpI0YsSIcnuP95uvv/66yJXiDh06SLp+TA0PD9fQoUNVqVIlLVu2TBMnTtS3336rmjVrWjwW4np3qHr16t0yvU6dOjp9+rSk61f0Bw8erJSUFF26dEnr169XZmamunbtKun6FeiJEyfqoYce0kcffaTk5GQ1b95caWlpev/991WzZk0FBwfr+++/Ny//0KFDtxzzbnzHS9d/JMXHx2vVqlVatGiRKlWqpLFjx6pbt26KiIhQVFSUHnzwQa1bt07/+Mc/FBgYqGbNmikwMFC5ubnmhM3N8X/++ee6ePGi1q9fr4yMDK1atUpt2rRRbm6u4uLiZDQa9cQTT9wXCZsbbcVgMMjJyUkRERFyc3NTamqq5s6dqxo1amjx4sX69NNPi1yNnzt3rtatWydPT08NHz78luU+9NBDmjFjhtauXauZM2fK19dXkyZNUsuWLRUREaH/+Z//UdWqVfXWW29pw4YNatKkicX299RTT6lLly5avny5ateurdjYWB09elRfffWVPDw8VKFCBb333nv65ZdfNHz4cBI2/+fGvr1w4YIcHBw0cOBA5eXl6dSpU1qzZo1yc3PN3eD69++vatWqqXPnzurevfst+6dChQry8PAwV0jdfK7y8ccf37Zd25vijkXh4eGKjIxU48aNlZKSoujoaI0cOfKWY9vN59E//fSTEhIS5OLioqlTp2r79u2qUaOGxfW/9tpreuaZZ7R7927zNEvn6yNHjtSaNWs0fPhw7dixQ2fOnNG2bdvk6+urgwcP6vvvv1fnzp2VmJgoLy8vc9JgwIABatWqlaT/b5fJycm6cOGC/va3v2ny5MlFkvr3g/T0dNWtW7fINDc3N23evFmnTp3S2rVrVVBQoEGDBpm3Ta1atTR9+nTz7ZHffPNNzZ07Vzk5OTp27Jjq1asnR0fH2+4bSfL391d4eLhSU1N1/vx5LV++XBcuXNBPP/1UJI7bfa5ef/11/fTTT3rvvffk4uKizp07KyMjQz4+PlbZXoBUTMKmWrVqkq7/gDp27JgmT56sIUOGqE+fPqpdu7bVArxTN/eJfOSRRyRdv1J1/vx5VaxYUZmZmQoLC5Orq6tycnKUn5+vPn36KCQkRIGBgcrKylKjRo1kMBgUHx+v9evXy2AwqKCg4Lbrq1atmt5//3395z//kbu7e5H5WrRoIUlq3ry5tmzZYp5+8uRJZWZmmk/SsrOzy6Rvuj04ffq0+vTpo9TUVEmSl5eXvLy8JElHjx7VkiVL9I9//EMmk0lOTk768ccf1bRpUzk6OsrFxUXh4eHlGb5duHkfubu7KyIiQhEREcrKylKfPn0kSRUqVFDLli0lXW8vW7duVbNmzSTJYrvt2bOn+vfvr6FDh+rs2bNq0qRJub3H+83tukRt2bLFvI09PDz04IMPmh/n5uYWeyyEVKNGDe3fv/+W6T/99JNq1aolSfLz85MknThxwvz59/b2NldfVK9eXXFxcapUqZKys7PNXZa9vLxUs2ZNSVLNmjWVm5trXn5Jx7yff/5Z7u7u5iuX33//vYYPH66AgAAdP37cfGUxPz9ffn5+8vT01Pfff6+vv/5a7u7uRcb0uBH/jz/+aI7fx8dHY8eO1a5du9SwYUPzRaAKFUrsoX1PsNR9sEaNGoqMjJSrq6vOnTtX5Af4+fPn5e7ubv6ueuyxx275/4cPH5afn5/5ItqOHTv02muv6cMPP1R6ero5SXbt2jXzmIOW2t/Nn6sbVTqNGjVSo0aNlJycrEceeUQGg0E+Pj66du3a3ds497gb+/bixYsaMmSI6tSpo6NHj+rgwYPmhHZBQYE54Spdr5K43f6pV6+eeT9IRc9VLLVre1PcsSg9PV2NGzeWJLVs2VIxMTG3PbadOnXKvLyqVatq4sSJcnNzK3JMtcTZ2VmzZs3SuHHjNHDgQEmWz9dv3pddunTRli1btHfvXg0bNkw7duzQ3r17FRkZqbi4OLVp00bS9W5XDRo0MJ/v37yMbdu2ycfHR4WFhXe6GW1OrVq1dOjQoSLT0tLSdPDgQbVo0cKc7P7zn/9sHvvzxr729fXVd999J0dHR3Xr1k3/+c9/tG/fPgUGBhb7W+rGtm3YsKGeffZZhYWFqaCg4JYui7f7XElSvXr1zO3Qx8enyHcqYA0lDjq8evVqjRs3TtL1cT3uhUEiK1asqIyMDEnSwYMHLc63detWnTlzRvPnz1dYWJiuXbsmk8kkd3d3Pfroo+buUdL10sm+fftq7ty5CggIsDg41tKlS9WsWTPNmzdP3bt3LzLfjaucu3fvVsOGDc3T69Spo5o1a2rp0qVauXKlnnvuufsuo24NWVlZWrdunby9vc3THBz+/yPu7++v8ePHa+XKlfr73/+ubt26yd/fX4cOHVJhYaHy8/P14osvKi8vTwaD4b78oixvv91H6enpOnjwoBYtWqSEhATNnTtXBQUFKigo0OHDhyVJe/bsMScDJMvt1sXFRQEBAYqMjFTfvn3L5f3h/xV3LITUqVMnffXVV0WSNjfaxo2rjzeqXho2bKh9+/ZJki5fvmy+KhgZGalXXnlFs2fPVqNGjczb+LfdmG9m6Zh3w5EjR8zdf6XrJ7qVK1eWo6Oj/Pz8NHv2bK1cuVITJkxQhw4dlJycrMqVKysmJkZDhgwxt8eb4/D39zd//129elVDhw4tMc77TXh4uKKiohQdHa3q1asXaQ+enp66evWqMjMzJalIRdQNO3fu1Pz582U0GmUwGNSwYUO5uLjI29tbvr6+iouL08qVKzVy5EgFBAQU2/5ubPcGDRqY15WWlmY+17On/fJH3KiQCA8PV7Vq1RQQEKCVK1fq/fffV48ePVSnTp0i895u/0hFz09ufmypXdub4o5F1atXN58jfPvtt6pfv36xx7arV69qwYIFio2N1cyZM1WxYsVSbdcmTZqod+/eevfddyVZPl93cHAwnzN27txZGzdulLu7u9q3b6+UlBTl5eXJx8dHDRo0MFfsZGVl6ejRo+bPy83trl+/fubP2P12d96OHTtq27ZtOnnypKTryf/o6Gh5eHiYu0Pl5+dr7969euCBByTd/pj0zDPP6MMPP9R///tftW3bttjfUjfa15EjR5Sdna2EhARFR0drxowZRZZ5u8+VpfUD1lTiJS0HBwdVrFhRkuTk5HRPfGjbtWun1atXKyQkRE2aNJGbm9tt52vatKni4uI0cOBAOTs7q27duuZSvcDAQL300kuKioqSJHXv3l2RkZFasmSJatasqYsXL952mR07dtS0adP00UcfydPTU46OjuYvjJSUFL3//vtyc3PT7NmzzQcFb29vDR48WKGhoTIajapdu7Z69OhRBlvm/nOjRNnBwUFGo1FjxoxRlSpVtGvXrlvmnThxovnL/9q1a5oyZYoaN26sdu3aKSQkRIWFhQoJCZGzs7NatGih4cOHa8WKFffEZ96WFbePfHx8lJGRoX79+snV1VVDhgwxX2l/9913dfr0adWqVUtjx47Vxo0bJRXfbgcOHKiQkBDGSLnLftslSlKJV96LOxbiegn44sWLFRUVpUuXLsloNOqhhx66ZbwmSXriiSe0detWBQcHq1q1aqpUqZKcnJzUp08fjRo1SlWrVpWvr6/F76WbWTrm3dC1a1cdP35cgYGBcnV1lclk0uuvv67KlStr2rRpmjhxooxGo6TrPywbNGigsLAw7dmzRy4uLnrggQeUnp5eZJ2dOnXSzp07FRISIqPRqJdffvkOt969p2/fvho4cKA8PDxUrVq1ItuoQoUKmjVrloYOHaoqVarcttooNDRUs2fPVr9+/eTu7i4HBwfNmTNHDg4OmjJlioYPHy6TySQ3NzfNmTNHBoOhxPYXHBysyZMn67nnnpPRaNTkyZPN1ako3oMPPqjQ0FBt3rxZNWvW1KBBg5STk6POnTsXqYixtH/OnDljcdl/pF3fj4o7Fs2cOVMzZsyQyWSSo6OjoqKiVLduXYvHNnd3dzVv3lz9+/eXq6urPDw8lJ6eXiS5ZsnIkSO1efNmSZbP169cuaKjR49q+fLlGjx4sHJzc9WqVStze37iiSckSQMHDlRERIRCQkKUm5ur0aNHq2rVqrdd74MPPqg+ffpo1qxZtyQW7mXu7u6Kjo5WeHi4TCaTsrOz1bFjR4WGhurMmTMKCgpSfn6+unfvXmyl9I0LG506dZKDg0OpfkvVr19fixYt0r/+9S85OTndcsfL232uAFtgMJWQYo6Li9P27dvVtGlTHTx4UO3atbtt/2oAuFtuDOZ9I1lcWvv379eqVatuGdQbuJcdP35chw8fVq9evXTx4kX17t1bmzdvvqfHlAMAAEDJSkzYSNIPP/ygH3/8Uf7+/nr44YetERcAO/ZHEjarVq1SUlKSFixYcMuAdsC9LCcnR+PGjdOFCxdkNBr13HPPqX///uUdFgAAAMpYiQmbs2fPKioqSseOHZOfn5/eeOONUpUQAgAAAAAA4I8pMWHz0ksvKSQkRC1bttQ333xjHlgNAAAAAAAAZaPEu0Tl5uaqU6dO8vDwUOfOnc2DDQIAAAAAAKBslJiwMRqNOnLkiCSZ/wUAAAAAAEDZKbFL1A8//KDw8HClp6erRo0amjFjhho3bmyt+AAAAAAAAOxOqe4SJUmXL1+Wo6Oj3N3dyzomAAAAAAAAu2axS9TBgwfVr18/5efn6/PPP1ePHj309NNPa9OmTdaMDwAAAAAAwO5YTNjExsYqOjpaTk5Oio2NVUJCgpKSkpSQkGDN+AAAAAAAAOxOBUsvmEwmPfzwwzp37px+/fVXPfroo5IkB4cSxykGAAAAAADAHbCYfSksLJQkbdu2Ta1bt5Yk5eXlKTs72zqRAQAAAAAA2CmLFTatW7dWcHCwzp49q/j4eJ08eVLTpk1Tz549rRkfAAAAAACA3Sn2LlHHjx+Xt7e3vLy8dPLkSR05ckRdunSxZnwAAAAAAAB2p9S39QYAAAAAAIB1MIIwAAAAAACAjSFhAwAAAAAAYGNI2AAAAAAAANgYEjYAAAAAAAA2hoQNAAAAAACAjflfZ3cQVLXFOowAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1584x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize this transition matrix in a heatmap\n",
    "sns.set_style(\"whitegrid\")\n",
    "fig, ax = plt.subplots(figsize=(22, 12))\n",
    "sns.heatmap(trans_matrix, cmap=\"RdBu_r\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "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": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}