Amazon_Sales_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e9b87355-4ced-42e5-a15b-4921304a0125",
   "metadata": {},
   "source": [
    "## DATA PRE-PROCESSING "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 422,
   "id": "359636c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 424,
   "id": "eaf919a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"Amazon Sale Report.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 426,
   "id": "2324585c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(128976, 21)"
      ]
     },
     "execution_count": 426,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 428,
   "id": "77ea55b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Date</th>\n",
       "      <th>Status</th>\n",
       "      <th>Fulfilment</th>\n",
       "      <th>Sales Channel</th>\n",
       "      <th>ship-service-level</th>\n",
       "      <th>Category</th>\n",
       "      <th>Size</th>\n",
       "      <th>Courier Status</th>\n",
       "      <th>...</th>\n",
       "      <th>currency</th>\n",
       "      <th>Amount</th>\n",
       "      <th>ship-city</th>\n",
       "      <th>ship-state</th>\n",
       "      <th>ship-postal-code</th>\n",
       "      <th>ship-country</th>\n",
       "      <th>B2B</th>\n",
       "      <th>fulfilled-by</th>\n",
       "      <th>New</th>\n",
       "      <th>PendingS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>405-8078784-5731545</td>\n",
       "      <td>04-30-22</td>\n",
       "      <td>Cancelled</td>\n",
       "      <td>Merchant</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Standard</td>\n",
       "      <td>T-shirt</td>\n",
       "      <td>S</td>\n",
       "      <td>On the Way</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>647.62</td>\n",
       "      <td>MUMBAI</td>\n",
       "      <td>MAHARASHTRA</td>\n",
       "      <td>400081.0</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>Easy Ship</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>171-9198151-1101146</td>\n",
       "      <td>04-30-22</td>\n",
       "      <td>Shipped - Delivered to Buyer</td>\n",
       "      <td>Merchant</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>3XL</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>406.00</td>\n",
       "      <td>BENGALURU</td>\n",
       "      <td>KARNATAKA</td>\n",
       "      <td>560085.0</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>Easy Ship</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>404-0687676-7273146</td>\n",
       "      <td>04-30-22</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Expedited</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>XL</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>329.00</td>\n",
       "      <td>NAVI MUMBAI</td>\n",
       "      <td>MAHARASHTRA</td>\n",
       "      <td>410210.0</td>\n",
       "      <td>IN</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>403-9615377-8133951</td>\n",
       "      <td>04-30-22</td>\n",
       "      <td>Cancelled</td>\n",
       "      <td>Merchant</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Blazzer</td>\n",
       "      <td>L</td>\n",
       "      <td>On the Way</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>753.33</td>\n",
       "      <td>PUDUCHERRY</td>\n",
       "      <td>PUDUCHERRY</td>\n",
       "      <td>605008.0</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>Easy Ship</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>407-1069790-7240320</td>\n",
       "      <td>04-30-22</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Expedited</td>\n",
       "      <td>Trousers</td>\n",
       "      <td>3XL</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>574.00</td>\n",
       "      <td>CHENNAI</td>\n",
       "      <td>TAMIL NADU</td>\n",
       "      <td>600073.0</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   index             Order ID      Date                        Status  \\\n",
       "0      0  405-8078784-5731545  04-30-22                     Cancelled   \n",
       "1      1  171-9198151-1101146  04-30-22  Shipped - Delivered to Buyer   \n",
       "2      2  404-0687676-7273146  04-30-22                       Shipped   \n",
       "3      3  403-9615377-8133951  04-30-22                     Cancelled   \n",
       "4      4  407-1069790-7240320  04-30-22                       Shipped   \n",
       "\n",
       "  Fulfilment Sales Channel ship-service-level  Category Size Courier Status  \\\n",
       "0   Merchant     Amazon.in           Standard   T-shirt    S     On the Way   \n",
       "1   Merchant     Amazon.in           Standard     Shirt  3XL        Shipped   \n",
       "2     Amazon     Amazon.in          Expedited     Shirt   XL        Shipped   \n",
       "3   Merchant     Amazon.in           Standard   Blazzer    L     On the Way   \n",
       "4     Amazon     Amazon.in          Expedited  Trousers  3XL        Shipped   \n",
       "\n",
       "   ...  currency  Amount    ship-city   ship-state ship-postal-code  \\\n",
       "0  ...       INR  647.62       MUMBAI  MAHARASHTRA         400081.0   \n",
       "1  ...       INR  406.00    BENGALURU    KARNATAKA         560085.0   \n",
       "2  ...       INR  329.00  NAVI MUMBAI  MAHARASHTRA         410210.0   \n",
       "3  ...       INR  753.33   PUDUCHERRY   PUDUCHERRY         605008.0   \n",
       "4  ...       INR  574.00      CHENNAI   TAMIL NADU         600073.0   \n",
       "\n",
       "   ship-country    B2B  fulfilled-by New  PendingS  \n",
       "0            IN  False     Easy Ship NaN       NaN  \n",
       "1            IN  False     Easy Ship NaN       NaN  \n",
       "2            IN   True           NaN NaN       NaN  \n",
       "3            IN  False     Easy Ship NaN       NaN  \n",
       "4            IN  False           NaN NaN       NaN  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 428,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "id": "e5520ae5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Date</th>\n",
       "      <th>Status</th>\n",
       "      <th>Fulfilment</th>\n",
       "      <th>Sales Channel</th>\n",
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       "      <th>Courier Status</th>\n",
       "      <th>...</th>\n",
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       "      <th>Amount</th>\n",
       "      <th>ship-city</th>\n",
       "      <th>ship-state</th>\n",
       "      <th>ship-postal-code</th>\n",
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       "      <td>Amazon.in</td>\n",
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       "      <td>Shirt</td>\n",
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       "      <td>TELANGANA</td>\n",
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       "      <td>05-31-22</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Expedited</td>\n",
       "      <td>T-shirt</td>\n",
       "      <td>M</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>999.0</td>\n",
       "      <td>GURUGRAM</td>\n",
       "      <td>HARYANA</td>\n",
       "      <td>122004.0</td>\n",
       "      <td>IN</td>\n",
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       "      <td>407-9547469-3152358</td>\n",
       "      <td>05-31-22</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Expedited</td>\n",
       "      <td>Blazzer</td>\n",
       "      <td>XXL</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>690.0</td>\n",
       "      <td>HYDERABAD</td>\n",
       "      <td>TELANGANA</td>\n",
       "      <td>500049.0</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128974</th>\n",
       "      <td>128973</td>\n",
       "      <td>402-6184140-0545956</td>\n",
       "      <td>05-31-22</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Expedited</td>\n",
       "      <td>T-shirt</td>\n",
       "      <td>XS</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>1199.0</td>\n",
       "      <td>Halol</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>389350.0</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>128975</th>\n",
       "      <td>128974</td>\n",
       "      <td>408-7436540-8728312</td>\n",
       "      <td>05-31-22</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Expedited</td>\n",
       "      <td>T-shirt</td>\n",
       "      <td>S</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>696.0</td>\n",
       "      <td>Raipur</td>\n",
       "      <td>CHHATTISGARH</td>\n",
       "      <td>492014.0</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "<p>5 rows × 21 columns</p>\n",
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      ],
      "text/plain": [
       "         index             Order ID      Date   Status Fulfilment  \\\n",
       "128971  128970  406-6001380-7673107  05-31-22  Shipped     Amazon   \n",
       "128972  128971  402-9551604-7544318  05-31-22  Shipped     Amazon   \n",
       "128973  128972  407-9547469-3152358  05-31-22  Shipped     Amazon   \n",
       "128974  128973  402-6184140-0545956  05-31-22  Shipped     Amazon   \n",
       "128975  128974  408-7436540-8728312  05-31-22  Shipped     Amazon   \n",
       "\n",
       "       Sales Channel ship-service-level Category Size Courier Status  ...  \\\n",
       "128971     Amazon.in          Expedited    Shirt   XL        Shipped  ...   \n",
       "128972     Amazon.in          Expedited  T-shirt    M        Shipped  ...   \n",
       "128973     Amazon.in          Expedited  Blazzer  XXL        Shipped  ...   \n",
       "128974     Amazon.in          Expedited  T-shirt   XS        Shipped  ...   \n",
       "128975     Amazon.in          Expedited  T-shirt    S        Shipped  ...   \n",
       "\n",
       "        currency  Amount  ship-city    ship-state ship-postal-code  \\\n",
       "128971       INR   517.0  HYDERABAD     TELANGANA         500013.0   \n",
       "128972       INR   999.0   GURUGRAM       HARYANA         122004.0   \n",
       "128973       INR   690.0  HYDERABAD     TELANGANA         500049.0   \n",
       "128974       INR  1199.0      Halol       Gujarat         389350.0   \n",
       "128975       INR   696.0     Raipur  CHHATTISGARH         492014.0   \n",
       "\n",
       "        ship-country    B2B  fulfilled-by New  PendingS  \n",
       "128971            IN  False           NaN NaN       NaN  \n",
       "128972            IN  False           NaN NaN       NaN  \n",
       "128973            IN  False           NaN NaN       NaN  \n",
       "128974            IN  False           NaN NaN       NaN  \n",
       "128975            IN  False           NaN NaN       NaN  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 430,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 432,
   "id": "1ed8473b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 128976 entries, 0 to 128975\n",
      "Data columns (total 21 columns):\n",
      " #   Column              Non-Null Count   Dtype  \n",
      "---  ------              --------------   -----  \n",
      " 0   index               128976 non-null  int64  \n",
      " 1   Order ID            128976 non-null  object \n",
      " 2   Date                128976 non-null  object \n",
      " 3   Status              128976 non-null  object \n",
      " 4   Fulfilment          128976 non-null  object \n",
      " 5   Sales Channel       128976 non-null  object \n",
      " 6   ship-service-level  128976 non-null  object \n",
      " 7   Category            128976 non-null  object \n",
      " 8   Size                128976 non-null  object \n",
      " 9   Courier Status      128976 non-null  object \n",
      " 10  Qty                 128976 non-null  int64  \n",
      " 11  currency            121176 non-null  object \n",
      " 12  Amount              121176 non-null  float64\n",
      " 13  ship-city           128941 non-null  object \n",
      " 14  ship-state          128941 non-null  object \n",
      " 15  ship-postal-code    128941 non-null  float64\n",
      " 16  ship-country        128941 non-null  object \n",
      " 17  B2B                 128976 non-null  bool   \n",
      " 18  fulfilled-by        39263 non-null   object \n",
      " 19  New                 0 non-null       float64\n",
      " 20  PendingS            0 non-null       float64\n",
      "dtypes: bool(1), float64(4), int64(2), object(14)\n",
      "memory usage: 19.8+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 434,
   "id": "f2799e7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop unrelated/blank columns\n",
    "data.drop(['New','PendingS'],axis=1, inplace=True)\n",
    "\n",
    "# axis =1 means column\n",
    "# inplace=True - permanent change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 436,
   "id": "0b92c1d9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 128976 entries, 0 to 128975\n",
      "Data columns (total 19 columns):\n",
      " #   Column              Non-Null Count   Dtype  \n",
      "---  ------              --------------   -----  \n",
      " 0   index               128976 non-null  int64  \n",
      " 1   Order ID            128976 non-null  object \n",
      " 2   Date                128976 non-null  object \n",
      " 3   Status              128976 non-null  object \n",
      " 4   Fulfilment          128976 non-null  object \n",
      " 5   Sales Channel       128976 non-null  object \n",
      " 6   ship-service-level  128976 non-null  object \n",
      " 7   Category            128976 non-null  object \n",
      " 8   Size                128976 non-null  object \n",
      " 9   Courier Status      128976 non-null  object \n",
      " 10  Qty                 128976 non-null  int64  \n",
      " 11  currency            121176 non-null  object \n",
      " 12  Amount              121176 non-null  float64\n",
      " 13  ship-city           128941 non-null  object \n",
      " 14  ship-state          128941 non-null  object \n",
      " 15  ship-postal-code    128941 non-null  float64\n",
      " 16  ship-country        128941 non-null  object \n",
      " 17  B2B                 128976 non-null  bool   \n",
      " 18  fulfilled-by        39263 non-null   object \n",
      "dtypes: bool(1), float64(2), int64(2), object(14)\n",
      "memory usage: 17.8+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 438,
   "id": "d324974e",
   "metadata": {},
   "outputs": [
    {
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       "<p>128976 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        index  Order ID   Date  Status  Fulfilment  Sales Channel  \\\n",
       "0       False     False  False   False       False          False   \n",
       "1       False     False  False   False       False          False   \n",
       "2       False     False  False   False       False          False   \n",
       "3       False     False  False   False       False          False   \n",
       "4       False     False  False   False       False          False   \n",
       "...       ...       ...    ...     ...         ...            ...   \n",
       "128971  False     False  False   False       False          False   \n",
       "128972  False     False  False   False       False          False   \n",
       "128973  False     False  False   False       False          False   \n",
       "128974  False     False  False   False       False          False   \n",
       "128975  False     False  False   False       False          False   \n",
       "\n",
       "        ship-service-level  Category   Size  Courier Status    Qty  currency  \\\n",
       "0                    False     False  False           False  False     False   \n",
       "1                    False     False  False           False  False     False   \n",
       "2                    False     False  False           False  False     False   \n",
       "3                    False     False  False           False  False     False   \n",
       "4                    False     False  False           False  False     False   \n",
       "...                    ...       ...    ...             ...    ...       ...   \n",
       "128971               False     False  False           False  False     False   \n",
       "128972               False     False  False           False  False     False   \n",
       "128973               False     False  False           False  False     False   \n",
       "128974               False     False  False           False  False     False   \n",
       "128975               False     False  False           False  False     False   \n",
       "\n",
       "        Amount  ship-city  ship-state  ship-postal-code  ship-country    B2B  \\\n",
       "0        False      False       False             False         False  False   \n",
       "1        False      False       False             False         False  False   \n",
       "2        False      False       False             False         False  False   \n",
       "3        False      False       False             False         False  False   \n",
       "4        False      False       False             False         False  False   \n",
       "...        ...        ...         ...               ...           ...    ...   \n",
       "128971   False      False       False             False         False  False   \n",
       "128972   False      False       False             False         False  False   \n",
       "128973   False      False       False             False         False  False   \n",
       "128974   False      False       False             False         False  False   \n",
       "128975   False      False       False             False         False  False   \n",
       "\n",
       "        fulfilled-by  \n",
       "0              False  \n",
       "1              False  \n",
       "2               True  \n",
       "3              False  \n",
       "4               True  \n",
       "...              ...  \n",
       "128971          True  \n",
       "128972          True  \n",
       "128973          True  \n",
       "128974          True  \n",
       "128975          True  \n",
       "\n",
       "[128976 rows x 19 columns]"
      ]
     },
     "execution_count": 438,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking null values\n",
    "pd.isnull(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 440,
   "id": "2a7041ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "index                     0\n",
       "Order ID                  0\n",
       "Date                      0\n",
       "Status                    0\n",
       "Fulfilment                0\n",
       "Sales Channel             0\n",
       "ship-service-level        0\n",
       "Category                  0\n",
       "Size                      0\n",
       "Courier Status            0\n",
       "Qty                       0\n",
       "currency               7800\n",
       "Amount                 7800\n",
       "ship-city                35\n",
       "ship-state               35\n",
       "ship-postal-code         35\n",
       "ship-country             35\n",
       "B2B                       0\n",
       "fulfilled-by          89713\n",
       "dtype: int64"
      ]
     },
     "execution_count": 440,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.isnull(data).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 442,
   "id": "e37c3d0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(128976, 19)"
      ]
     },
     "execution_count": 442,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 444,
   "id": "19b57ddf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop null values\n",
    "data.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 446,
   "id": "5f82aa05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(37514, 19)"
      ]
     },
     "execution_count": 446,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 448,
   "id": "36dae106",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['index', 'Order ID', 'Date', 'Status', 'Fulfilment', 'Sales Channel',\n",
       "       'ship-service-level', 'Category', 'Size', 'Courier Status', 'Qty',\n",
       "       'currency', 'Amount', 'ship-city', 'ship-state', 'ship-postal-code',\n",
       "       'ship-country', 'B2B', 'fulfilled-by'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 448,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 450,
   "id": "08c80882",
   "metadata": {},
   "outputs": [],
   "source": [
    "# change data type\n",
    "data['ship-postal-code'] = data['ship-postal-code'].astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 452,
   "id": "39826212",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('int32')"
      ]
     },
     "execution_count": 452,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking whether the data type change or not\n",
    "data['ship-postal-code'].dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 454,
   "id": "cfe63f91",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\DELL\\AppData\\Local\\Temp\\ipykernel_4040\\1453708669.py:1: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  data['Date'] = pd.to_datetime(data['Date'])\n"
     ]
    }
   ],
   "source": [
    "data['Date'] = pd.to_datetime(data['Date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 456,
   "id": "aea6baf4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 37514 entries, 0 to 128892\n",
      "Data columns (total 19 columns):\n",
      " #   Column              Non-Null Count  Dtype         \n",
      "---  ------              --------------  -----         \n",
      " 0   index               37514 non-null  int64         \n",
      " 1   Order ID            37514 non-null  object        \n",
      " 2   Date                37514 non-null  datetime64[ns]\n",
      " 3   Status              37514 non-null  object        \n",
      " 4   Fulfilment          37514 non-null  object        \n",
      " 5   Sales Channel       37514 non-null  object        \n",
      " 6   ship-service-level  37514 non-null  object        \n",
      " 7   Category            37514 non-null  object        \n",
      " 8   Size                37514 non-null  object        \n",
      " 9   Courier Status      37514 non-null  object        \n",
      " 10  Qty                 37514 non-null  int64         \n",
      " 11  currency            37514 non-null  object        \n",
      " 12  Amount              37514 non-null  float64       \n",
      " 13  ship-city           37514 non-null  object        \n",
      " 14  ship-state          37514 non-null  object        \n",
      " 15  ship-postal-code    37514 non-null  int32         \n",
      " 16  ship-country        37514 non-null  object        \n",
      " 17  B2B                 37514 non-null  bool          \n",
      " 18  fulfilled-by        37514 non-null  object        \n",
      "dtypes: bool(1), datetime64[ns](1), float64(1), int32(1), int64(2), object(13)\n",
      "memory usage: 5.3+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 458,
   "id": "64a90a1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['index', 'Order ID', 'Date', 'Status', 'Fulfilment', 'Sales Channel',\n",
       "       'ship-service-level', 'Category', 'Size', 'Courier Status', 'Qty',\n",
       "       'currency', 'Amount', 'ship-city', 'ship-state', 'ship-postal-code',\n",
       "       'ship-country', 'B2B', 'fulfilled-by'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 458,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 460,
   "id": "46189b0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Date</th>\n",
       "      <th>Qty</th>\n",
       "      <th>Amount</th>\n",
       "      <th>ship-postal-code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>37514.000000</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514.000000</td>\n",
       "      <td>37514.000000</td>\n",
       "      <td>37514.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>60953.809858</td>\n",
       "      <td>2022-05-11 07:56:47.303939840</td>\n",
       "      <td>0.867383</td>\n",
       "      <td>646.553960</td>\n",
       "      <td>463291.552754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>2022-03-31 00:00:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>110001.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>27235.250000</td>\n",
       "      <td>2022-04-20 00:00:00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>458.000000</td>\n",
       "      <td>370465.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>63470.500000</td>\n",
       "      <td>2022-05-09 00:00:00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>629.000000</td>\n",
       "      <td>500019.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>91790.750000</td>\n",
       "      <td>2022-06-01 00:00:00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>771.000000</td>\n",
       "      <td>600042.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>128891.000000</td>\n",
       "      <td>2022-06-29 00:00:00</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5495.000000</td>\n",
       "      <td>989898.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>36844.853039</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.354160</td>\n",
       "      <td>279.952414</td>\n",
       "      <td>194550.425637</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               index                           Date           Qty  \\\n",
       "count   37514.000000                          37514  37514.000000   \n",
       "mean    60953.809858  2022-05-11 07:56:47.303939840      0.867383   \n",
       "min         0.000000            2022-03-31 00:00:00      0.000000   \n",
       "25%     27235.250000            2022-04-20 00:00:00      1.000000   \n",
       "50%     63470.500000            2022-05-09 00:00:00      1.000000   \n",
       "75%     91790.750000            2022-06-01 00:00:00      1.000000   \n",
       "max    128891.000000            2022-06-29 00:00:00      5.000000   \n",
       "std     36844.853039                            NaN      0.354160   \n",
       "\n",
       "             Amount  ship-postal-code  \n",
       "count  37514.000000      37514.000000  \n",
       "mean     646.553960     463291.552754  \n",
       "min        0.000000     110001.000000  \n",
       "25%      458.000000     370465.000000  \n",
       "50%      629.000000     500019.000000  \n",
       "75%      771.000000     600042.000000  \n",
       "max     5495.000000     989898.000000  \n",
       "std      279.952414     194550.425637  "
      ]
     },
     "execution_count": 460,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# describe() method return description of the data in the DataFrame(i.e count, mean,std etc)\n",
    "# we cannot use this for object. only for numbers\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 462,
   "id": "2c61c5dd",
   "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>Order ID</th>\n",
       "      <th>Status</th>\n",
       "      <th>Fulfilment</th>\n",
       "      <th>Sales Channel</th>\n",
       "      <th>ship-service-level</th>\n",
       "      <th>Category</th>\n",
       "      <th>Size</th>\n",
       "      <th>Courier Status</th>\n",
       "      <th>currency</th>\n",
       "      <th>ship-city</th>\n",
       "      <th>ship-state</th>\n",
       "      <th>ship-country</th>\n",
       "      <th>fulfilled-by</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>34664</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4698</td>\n",
       "      <td>58</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>171-5057375-2831560</td>\n",
       "      <td>Shipped - Delivered to Buyer</td>\n",
       "      <td>Merchant</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Standard</td>\n",
       "      <td>T-shirt</td>\n",
       "      <td>M</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>INR</td>\n",
       "      <td>BENGALURU</td>\n",
       "      <td>MAHARASHTRA</td>\n",
       "      <td>IN</td>\n",
       "      <td>Easy Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>12</td>\n",
       "      <td>28741</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "      <td>14062</td>\n",
       "      <td>6806</td>\n",
       "      <td>31859</td>\n",
       "      <td>37514</td>\n",
       "      <td>2839</td>\n",
       "      <td>6236</td>\n",
       "      <td>37514</td>\n",
       "      <td>37514</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Order ID                        Status Fulfilment  \\\n",
       "count                 37514                         37514      37514   \n",
       "unique                34664                            11          1   \n",
       "top     171-5057375-2831560  Shipped - Delivered to Buyer   Merchant   \n",
       "freq                     12                         28741      37514   \n",
       "\n",
       "       Sales Channel ship-service-level Category   Size Courier Status  \\\n",
       "count          37514              37514    37514  37514          37514   \n",
       "unique             1                  1        8     11              3   \n",
       "top        Amazon.in           Standard  T-shirt      M        Shipped   \n",
       "freq           37514              37514    14062   6806          31859   \n",
       "\n",
       "       currency  ship-city   ship-state ship-country fulfilled-by  \n",
       "count     37514      37514        37514        37514        37514  \n",
       "unique        1       4698           58            1            1  \n",
       "top         INR  BENGALURU  MAHARASHTRA           IN    Easy Ship  \n",
       "freq      37514       2839         6236        37514        37514  "
      ]
     },
     "execution_count": 462,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe(include='object')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 464,
   "id": "13ed6ef5",
   "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>Qty</th>\n",
       "      <th>Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>37514.000000</td>\n",
       "      <td>37514.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.867383</td>\n",
       "      <td>646.553960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.354160</td>\n",
       "      <td>279.952414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>458.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>629.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>771.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>5495.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Qty        Amount\n",
       "count  37514.000000  37514.000000\n",
       "mean       0.867383    646.553960\n",
       "std        0.354160    279.952414\n",
       "min        0.000000      0.000000\n",
       "25%        1.000000    458.000000\n",
       "50%        1.000000    629.000000\n",
       "75%        1.000000    771.000000\n",
       "max        5.000000   5495.000000"
      ]
     },
     "execution_count": 464,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# use describe for specific columns\n",
    "data[['Qty','Amount']].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96338fcd",
   "metadata": {},
   "source": [
    "## EXPLORATORY DATA ANALYSIS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 467,
   "id": "d86c1e6e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['index', 'Order ID', 'Date', 'Status', 'Fulfilment', 'Sales Channel',\n",
       "       'ship-service-level', 'Category', 'Size', 'Courier Status', 'Qty',\n",
       "       'currency', 'Amount', 'ship-city', 'ship-state', 'ship-postal-code',\n",
       "       'ship-country', 'B2B', 'fulfilled-by'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 467,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57e23d62",
   "metadata": {},
   "source": [
    "### size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 470,
   "id": "09e9f350",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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EfH19ER0djeDgYBw+fBjr16/H+vXrAQCVlZV47733MGbMGDg6OuLq1av45JNPcPHiRUycOBHAnZmhgIAA3Lx5E4mJiSgvL0d5eTkAwM7ODgYGBrCyssKsWbOwbNkyODs7w8XFBR988AEASPshamkMRERE1CRPP/00kpOTERkZiXfeeQeurq5Ys2YNJk+eDAAwMDDAzz//jISEBPz++++wsbHB008/jX379qFXr14AgNzcXOlGjU8++aTW/gsLC9G1a1cAwAcffABDQ0OEhISgqqoK3t7eSE9PR6dOndpuwCQrvA9RE/E+RLqjb/dsAXgfIno4+vab5u+ZHmW8DxERERFREzEQERERkezxHCIiInogHuajRx1niIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPZ0HoguXbqEl156CTY2NjAzM0Pfvn2Rm5srbRdCICoqCk5OTjA1NYW/vz/y8/O19lFdXY25c+fC1tYW5ubmGDNmDC5evKhVU1ZWhpCQEKhUKqhUKoSEhOD69ettMUQiIiLSczoNRGVlZRg4cCCMjIzw3Xff4eTJk1i1ahU6duwo1axcuRKrV69GbGwscnJyoFarMXz4cNy4cUOqCQ8PR3JyMpKSkrB//35UVFRg1KhRuH37tlQzadIk5OXlITU1FampqcjLy0NISEhbDpeIiIj0lKEuP3zFihVwdnZGfHy8tK5r167Sn4UQWLNmDZYuXYrx48cDABISEuDg4IBt27Zh5syZ0Gg02LhxI7Zs2YJhw4YBABITE+Hs7Iy9e/dixIgROHXqFFJTU5GdnQ1vb28AwIYNG+Dj44OCggJ07969Xm/V1dWorq6WXpeXl7fGV0BERER6QKczRCkpKfDy8sLEiRNhb2+Pfv36YcOGDdL2wsJClJSUICAgQFqnVCrh5+eHgwcPAgByc3NRW1urVePk5AR3d3epJisrCyqVSgpDADBgwACoVCqp5l7Lly+XDq+pVCo4Ozu36NiJiIhIf+g0EJ07dw5xcXFwc3PD7t27MWvWLMybNw+bN28GAJSUlAAAHBwctN7n4OAgbSspKYGxsTE6derUaI29vX29z7e3t5dq7hUZGQmNRiMtRUVFDzdYIiIi0ls6PWRWV1cHLy8vREdHAwD69euH/Px8xMXF4eWXX5bqFAqF1vuEEPXW3evemobqG9uPUqmEUqls8liIiIio/dLpDJGjoyN69uypta5Hjx64cOECAECtVgNAvVmc0tJSadZIrVajpqYGZWVljdZcvny53udfuXKl3uwTERERyY9OA9HAgQNRUFCgte706dNwcXEBALi6ukKtViMtLU3aXlNTg8zMTPj6+gIAPD09YWRkpFVTXFyMEydOSDU+Pj7QaDQ4fPiwVHPo0CFoNBqphoiIiORLp4fMIiIi4Ovri+joaAQHB+Pw4cNYv3491q9fD+DOYa7w8HBER0fDzc0Nbm5uiI6OhpmZGSZNmgQAUKlUmDZtGhYsWAAbGxtYW1tj4cKF8PDwkK4669GjBwIDAxEWFoZ169YBAGbMmIFRo0Y1eIUZERERyYtOA9HTTz+N5ORkREZG4p133oGrqyvWrFmDyZMnSzWLFi1CVVUVZs+ejbKyMnh7e2PPnj2wtLSUamJiYmBoaIjg4GBUVVVh6NCh2LRpEwwMDKSarVu3Yt68edLVaGPGjEFsbGzbDZaIiIj0lkIIIXTdRHtQXl4OlUoFjUYDKysrXbcjK56vb9Z1C/XkfvDyg4uI7kPfftNN+T23x56JgKb/+63zR3cQERER6RoDEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMREbV7UVFRUCgUWotarZa2CyEQFRUFJycnmJqawt/fH/n5+Vr7OHv2LJ577jnY2dnBysoKwcHBuHz5slZNWVkZQkJCoFKpoFKpEBISguvXr7fFEImolTEQEdEjoVevXiguLpaW48ePS9tWrlyJ1atXIzY2Fjk5OVCr1Rg+fDhu3LgBAKisrERAQAAUCgXS09Nx4MAB1NTUYPTo0airq5P2M2nSJOTl5SE1NRWpqanIy8tDSEhIm4+ViFqeoa4bICJqCYaGhlqzQncJIbBmzRosXboU48ePBwAkJCTAwcEB27Ztw8yZM3HgwAGcP38ex44dg5WVFQAgPj4e1tbWSE9Px7Bhw3Dq1CmkpqYiOzsb3t7eAIANGzbAx8cHBQUF6N69e9sNlohaHGeIiOiRcObMGTg5OcHV1RUvvPACzp07BwAoLCxESUkJAgICpFqlUgk/Pz8cPHgQAFBdXQ2FQgGlUinVmJiYoEOHDti/fz8AICsrCyqVSgpDADBgwACoVCppP0TUfjEQEVG75+3tjc2bN2P37t3YsGEDSkpK4Ovri6tXr6KkpAQA4ODgoPUeBwcHaduAAQNgbm6ON954Azdv3kRlZSVef/111NXVobi4GABQUlICe3v7ep9tb28v7YeI2i8GIiJq94KCgjBhwgR4eHhg2LBh2LVrF4A7h8buUigUWu8RQkjr7Ozs8MUXX+Drr7+GhYUFVCoVNBoN+vfvDwMDg/vu4979EFH7xXOIiOiRY25uDg8PD5w5cwbjxo0DcGeGx9HRUaopLS3VmjUKCAjA2bNn8fvvv8PQ0BAdO3aEWq2Gq6srAECtVte76gwArly5Um/2iYjaH84QEdEjp7q6GqdOnYKjoyNcXV2hVquRlpYmba+pqUFmZiZ8fX3rvdfW1hYdO3ZEeno6SktLMWbMGACAj48PNBoNDh8+LNUeOnQIGo2mwf0QUfvCGSIiavcWLlyI0aNHo0uXLigtLcW7776L8vJyhIaGQqFQIDw8HNHR0XBzc4Obmxuio6NhZmaGSZMmSfuIj49Hjx49YGdnh6ysLMyfPx8RERHS1WM9evRAYGAgwsLCsG7dOgDAjBkzMGrUKF5hRvQIYCAionbv4sWLePHFF/H777/Dzs4OAwYMQHZ2NlxcXAAAixYtQlVVFWbPno2ysjJ4e3tjz549sLS0lPZRUFCAyMhIXLt2DV27dsXSpUsRERGh9Tlbt27FvHnzpCvWxowZg9jY2LYbKBG1GoUQQui6ifagvLxcOtHy7n1KqG14vr5Z1y3Uk/vBy7pugdoxfftNN+X33B57JgKa/u83zyEiIiIi2eMhMyJq1zhzQUQtgTNEREREJHs6DUQt8YTq6upqzJ07F7a2tjA3N8eYMWNw8eJFrRo+oZqIiIgao/MZood5QjUAhIeHIzk5GUlJSdi/fz8qKiowatQo3L59W6rhE6qJiIioMTo/h+hhnlCt0WiwceNGbNmyBcOGDQMAJCYmwtnZGXv37sWIESOa/YTq6upqVFdXS6/Ly8tbeuhERESkJ3Q+Q/QwT6jOzc1FbW2tVo2TkxPc3d2lmuY+oXr58uXSITaVSgVnZ+cWHTcRERHpD50Good9QnVJSQmMjY3RqVOnRmua84TqyMhIaDQaaSkqKnqosRIREZH+0ukhs6CgIOnPHh4e8PHxwRNPPIGEhAQMGDAAQONPqL6fe2ua84RqpVIJpVLZpHEQERFR+6bzQ2Z/9ucnVN89r+jeWZw/P6FarVajpqYGZWVljdbwCdVERETUGL0KRH/1CdWenp4wMjLSqikuLsaJEyekGj6hmoiIiB5Ep4fMHvYJ1SqVCtOmTcOCBQtgY2MDa2trLFy4EB4eHtJVZ3xCNRERET2ITgNRSzyhOiYmBoaGhggODkZVVRWGDh2KTZs2wcDAQKrhE6qJiIioMToNRElJSY1uVygUiIqKQlRU1H1rTExMsHbtWqxdu/a+NdbW1khMTGxum0RERPSI06tziIiIiIh0gYGIiIiIZI+BiIiIiGSPgaiFLV++XLpC7q4pU6ZAoVBoLXdvPHmXv79/vZoXXnhBq+b06dMYO3YsbG1tYWVlhYEDB+L7779vi2ERERE90hiIWlBOTg7Wr1+P3r1719sWGBiI4uJiafn222/r1YSFhWnV3L1NwF0jR47ErVu3kJ6ejtzcXPTt2xejRo1q9BEkTdHcEDdz5kw88cQTMDU1hZ2dHcaOHYuff/5Zq6Zr16719rN48eKH6peIiKil6fxp94+KiooKTJ48GRs2bMC7775bb7tSqZTuvn0/ZmZm9635/fff8csvv+Dzzz+XAtf777+PTz75BPn5+Q/c9/08KMTFx8dLr42NjbW2e3p6YvLkyejSpQuuXbuGqKgoBAQEoLCwUOu2B++88w7CwsKk1xYWFs3qlYiIqLVwhqiFzJkzByNHjpRuCHmvjIwM2Nvbo1u3bggLC0NpaWm9mq1bt8LW1ha9evXCwoULcePGDWmbjY0NevTogc2bN6OyshK3bt3CunXr4ODgAE9Pz2b1/OcQd+8DcoH/C3F3F2tra63tM2bMwDPPPIOuXbuif//+ePfdd1FUVITz589r1VlaWmrth4GIiIj0DQNRC0hKSsLRo0exfPnyBrcHBQVh69atSE9Px6pVq5CTk4MhQ4agurpaqpk8eTL+/e9/IyMjA2+99RZ27NiB8ePHS9sVCgXS0tJw7NgxWFpawsTEBDExMUhNTUXHjh2b1XdLhLi7KisrER8fD1dXVzg7O2ttW7FiBWxsbNC3b1+89957qKmpaVa/RERErYWHzB5SUVER5s+fjz179sDExKTBmueff176s7u7O7y8vODi4oJdu3ZJoefPh5Tc3d3h5uYGLy8vHD16FP3794cQArNnz4a9vT327dsHU1NTfPbZZxg1ahRycnLg6Oj4l/q+G+JycnIa3B4UFISJEyfCxcUFhYWFeOuttzBkyBDk5uZCqVRKdZ988gkWLVqEyspKPPXUU0hLS9M6tDZ//nz0798fnTp1wuHDhxEZGYnCwkJ89tlnf6lfIiKi1sRA9JByc3NRWlqqddjq9u3b+OGHHxAbG4vq6mqt82kAwNHRES4uLjhz5sx999u/f38YGRnhzJkz6N+/P9LT0/HNN9+grKwMVlZWAO6EkbS0NCQkJPylE5VbKsQBd2a2hg8fjuLiYnz44YcIDg7GgQMHpP1GRERItb1790anTp3wj3/8Q5o1IiIi0gcMRA9p6NChOH78uNa6V155BU899RTeeOONemEIAK5evYqioqJGZ3Xy8/NRW1sr1dy8eRMA0KGD9lHODh06oK6u7i/13JIhTqVSQaVSwc3NDQMGDECnTp2QnJyMF198scHPvnul2i+//MJAREREeoOB6CFZWlrC3d1da525uTlsbGzg7u6OiooKREVFYcKECXB0dMT58+exZMkS2Nra4rnnngMAnD17Flu3bsWzzz4LW1tbnDx5EgsWLEC/fv0wcOBAAICPjw86deqE0NBQ/Otf/4KpqSk2bNiAwsJCjBw58i/13FohDgCEEFrnRt3r2LFjAPCXD/ERERG1JgaiVmZgYIDjx49j8+bNuH79OhwdHTF48GBs374dlpaWAO5czv7f//4XH330ESoqKuDs7IyRI0di2bJlUjixtbVFamoqli5diiFDhqC2tha9evXCV199hT59+vylnloixJ07dw7bt29HQEAA7OzscOnSJaxYsQKmpqZ49tlnAQBZWVnIzs7G4MGDoVKpkJOTg4iICIwZMwZdunR52K+WiIioxTAQtYKMjAzpz6ampti9e3ej9c7OzsjMzHzgfr28vB64r5bQlBBnYmKCffv2Yc2aNSgrK4ODgwOeeeYZHDx4EPb29gDuXLa/fft2vP3226iuroaLiwvCwsKwaNGiVh8DERHRX8FARAD+eohzcnJq8G7bf9a/f39kZ2e3RHtEREStioHoIXi+vlnXLWjJ/eBlXbdARETULjEQyQxDHBERUX28UzURERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyZ7eBKLly5dDoVAgPDxcWieEQFRUFJycnGBqagp/f3/k5+drva+6uhpz586Fra0tzM3NMWbMGFy8eFGrpqysDCEhIVCpVFCpVAgJCcH169fbYFRERETUHuhFIMrJycH69evRu3dvrfUrV67E6tWrERsbi5ycHKjVagwfPhw3btyQasLDw5GcnIykpCTs378fFRUVGDVqFG7fvi3VTJo0CXl5eUhNTUVqairy8vIQEhLSZuMjIiIi/abzQFRRUYHJkydjw4YN6NSpk7ReCIE1a9Zg6dKlGD9+PNzd3ZGQkICbN29i27ZtAACNRoONGzdi1apVGDZsGPr164fExEQcP34ce/fuBQCcOnUKqamp+Oyzz+Dj4wMfHx9s2LAB33zzDQoKCnQyZiIiItIvOg9Ec+bMwciRIzFs2DCt9YWFhSgpKUFAQIC0TqlUws/PDwcPHgQA5Obmora2VqvGyckJ7u7uUk1WVhZUKhW8vb2lmgEDBkClUkk1DamurkZ5ebnWQkRERI8mQ11+eFJSEo4ePYqcnJx620pKSgAADg4OWusdHBzw66+/SjXGxsZaM0t3a+6+v6SkBPb29vX2b29vL9U0ZPny5Xj77bf/2oCIiIioXdLZDFFRURHmz5+PxMREmJiY3LdOoVBovRZC1Ft3r3trGqp/0H4iIyOh0WikpaioqNHPJCIiovZLZ4EoNzcXpaWl8PT0hKGhIQwNDZGZmYmPP/4YhoaG0szQvbM4paWl0ja1Wo2amhqUlZU1WnP58uV6n3/lypV6s09/plQqYWVlpbUQERHRo0lngWjo0KE4fvw48vLypMXLywuTJ09GXl4eHn/8cajVaqSlpUnvqampQWZmJnx9fQEAnp6eMDIy0qopLi7GiRMnpBofHx9oNBocPnxYqjl06BA0Go1UQ0RERPKms3OILC0t4e7urrXO3NwcNjY20vrw8HBER0fDzc0Nbm5uiI6OhpmZGSZNmgQAUKlUmDZtGhYsWAAbGxtYW1tj4cKF8PDwkE7S7tGjBwIDAxEWFoZ169YBAGbMmIFRo0ahe/fubThiIiIi0lfNmiEaMmRIgzc2LC8vx5AhQx62J8miRYsQHh6O2bNnw8vLC5cuXcKePXtgaWkp1cTExGDcuHEIDg7GwIEDYWZmhq+//hoGBgZSzdatW+Hh4YGAgAAEBASgd+/e2LJlS4v1SURERO1bs2aIMjIyUFNTU2/9H3/8gX379jW7mYyMDK3XCoUCUVFRiIqKuu97TExMsHbtWqxdu/a+NdbW1khMTGx2X0RERPRo+0uB6KeffpL+fPLkSa0Tnm/fvo3U1FQ89thjLdcdERERURv4S4Gob9++UCgUUCgUDR4aMzU1bXSmhoiIiEgf/aVAVFhYCCEEHn/8cRw+fBh2dnbSNmNjY9jb22udu0NERETUHvylQOTi4gIAqKura5VmiIiIiHSh2Zfdnz59GhkZGSgtLa0XkP71r389dGNEREREbaVZgWjDhg345z//CVtbW6jV6nqPyWAgIiIiovakWYHo3XffxXvvvYc33nijpfshIiIianPNujFjWVkZJk6c2NK9EBEREelEswLRxIkTsWfPnpbuhYiIiEgnmnXI7Mknn8Rbb72F7OxseHh4wMjISGv7vHnzWqQ5IiIiorbQrEC0fv16WFhYIDMzE5mZmVrbFAoFAxERERG1K80KRIWFhS3dBxEREZHONOscIiIiIqJHSbNmiKZOndro9s8//7xZzRARERHpQrMCUVlZmdbr2tpanDhxAtevX2/woa9ERERE+qxZgSg5Obneurq6OsyePRuPP/74QzdFRERE1JZa7ByiDh06ICIiAjExMS21SyIiIqI20aInVZ89exa3bt1qyV0SERERtbpmHTJ77bXXtF4LIVBcXIxdu3YhNDS0RRojIiIiaivNCkTHjh3Tet2hQwfY2dlh1apVD7wCjYiIiEjfNCsQff/99y3dBxEREZHONCsQ3XXlyhUUFBRAoVCgW7dusLOza6m+iIiIiNpMs06qrqysxNSpU+Ho6IhnnnkGf//73+Hk5IRp06bh5s2bLd0jERERUatqViB67bXXkJmZia+//hrXr1/H9evX8dVXXyEzMxMLFixo6R6JiIiIWlWzDpnt2LEDX375Jfz9/aV1zz77LExNTREcHIy4uLiW6o+IiIio1TVrhujmzZtwcHCot97e3p6HzIiIiKjdaVYg8vHxwbJly/DHH39I66qqqvD222/Dx8enxZojIiIiagvNOmS2Zs0aBAUFoXPnzujTpw8UCgXy8vKgVCqxZ8+elu6RiIiIqFU1KxB5eHjgzJkzSExMxM8//wwhBF544QVMnjwZpqamLd0jERERUatqViBavnw5HBwcEBYWprX+888/x5UrV/DGG2+0SHNEREREbaFZ5xCtW7cOTz31VL31vXr1wqeffvrQTRERERG1pWYFopKSEjg6OtZbb2dnh+Li4oduioiIiKgtNSsQOTs748CBA/XWHzhwAE5OTg/dFBEREVFbatY5RNOnT0d4eDhqa2sxZMgQAMB///tfLFq0iHeqJiIionanWYFo0aJFuHbtGmbPno2amhoAgImJCd544w1ERka2aINEREREra1ZgUihUGDFihV46623cOrUKZiamsLNzQ1KpbKl+yMiIiJqdc0KRHdZWFjg6aefbqleiIiIiHSiWSdVExERET1KGIiIiIhI9hiIiIiISPYYiIiIiEj2dBqI4uLi0Lt3b1hZWcHKygo+Pj747rvvpO1CCERFRcHJyQmmpqbw9/dHfn6+1j6qq6sxd+5c2NrawtzcHGPGjMHFixe1asrKyhASEgKVSgWVSoWQkBBcv369LYZIRERE7YBOA1Hnzp3x/vvv48iRIzhy5AiGDBmCsWPHSqFn5cqVWL16NWJjY5GTkwO1Wo3hw4fjxo0b0j7Cw8ORnJyMpKQk7N+/HxUVFRg1ahRu374t1UyaNAl5eXlITU1Famoq8vLyEBIS0ubjJSIiIv30UJfdP6zRo0drvX7vvfcQFxeH7Oxs9OzZE2vWrMHSpUsxfvx4AEBCQgIcHBywbds2zJw5ExqNBhs3bsSWLVswbNgwAEBiYiKcnZ2xd+9ejBgxAqdOnUJqaiqys7Ph7e0NANiwYQN8fHxQUFCA7t27t+2giYiISO/ozTlEt2/fRlJSEiorK+Hj44PCwkKUlJQgICBAqlEqlfDz88PBgwcBALm5uaitrdWqcXJygru7u1STlZUFlUolhSEAGDBgAFQqlVTTkOrqapSXl2stRERE9GjSeSA6fvw4LCwsoFQqMWvWLCQnJ6Nnz54oKSkBADg4OGjVOzg4SNtKSkpgbGyMTp06NVpjb29f73Pt7e2lmoYsX75cOudIpVLB2dn5ocZJRERE+kvngah79+7Iy8tDdnY2/vnPfyI0NBQnT56UtisUCq16IUS9dfe6t6ah+gftJzIyEhqNRlqKioqaOiQiIiJqZ3QeiIyNjfHkk0/Cy8sLy5cvR58+ffDRRx9BrVYDQL1ZnNLSUmnWSK1Wo6amBmVlZY3WXL58ud7nXrlypd7s058plUrp6re7CxERET2adB6I7iWEQHV1NVxdXaFWq5GWliZtq6mpQWZmJnx9fQEAnp6eMDIy0qopLi7GiRMnpBofHx9oNBocPnxYqjl06BA0Go1UQ0RERPKm06vMlixZgqCgIDg7O+PGjRtISkpCRkYGUlNToVAoEB4ejujoaLi5ucHNzQ3R0dEwMzPDpEmTAAAqlQrTpk3DggULYGNjA2trayxcuBAeHh7SVWc9evRAYGAgwsLCsG7dOgDAjBkzMGrUKF5hRkRERAB0HIguX76MkJAQFBcXQ6VSoXfv3khNTcXw4cMBAIsWLUJVVRVmz56NsrIyeHt7Y8+ePbC0tJT2ERMTA0NDQwQHB6OqqgpDhw7Fpk2bYGBgINVs3boV8+bNk65GGzNmDGJjY9t2sERERKS3dBqINm7c2Oh2hUKBqKgoREVF3bfGxMQEa9euxdq1a+9bY21tjcTExOa2SURERI84vTuHiIiIiKitMRARERGR7DEQEbWi5cuX4+mnn4alpSXs7e0xbtw4FBQUaNVMmTIFCoVCaxkwYIBWTUlJCUJCQqBWq2Fubo7+/fvjyy+/lLZnZGTU28fdJScnp03GSkTUnjEQEbWizMxMzJkzB9nZ2UhLS8OtW7cQEBCAyspKrbrAwEAUFxdLy7fffqu1PSQkBAUFBUhJScHx48cxfvx4PP/88zh27BgAwNfXV+v9xcXFmD59Orp27QovL682Gy8RUXul05OqiR51qampWq/j4+Nhb2+P3NxcPPPMM9J6pVIp3Yy0IVlZWYiLi8Pf/vY3AMCbb76JmJgYHD16FP369YOxsbHW+2tra5GSkoJXX331gXd2JyIizhARtSmNRgPgzpWPf5aRkQF7e3t069YNYWFhKC0t1do+aNAgbN++HdeuXUNdXR2SkpJQXV0Nf3//Bj8nJSUFv//+O6ZMmdIawyAieuRwhoiojQgh8Nprr2HQoEFwd3eX1gcFBWHixIlwcXFBYWEh3nrrLQwZMgS5ublQKpUAgO3bt+P555+HjY0NDA0NYWZmhuTkZDzxxBMNftbGjRsxYsQIPpSYiKiJGIiI2sirr76Kn376Cfv379da//zzz0t/dnd3h5eXF1xcXLBr1y6MHz8ewJ1DZGVlZdi7dy9sbW2xc+dOTJw4Efv27YOHh4fW/i5evIjdu3fj//2//9f6gyIiekQwEBG1gblz5yIlJQU//PADOnfu3Gito6MjXFxccObMGQDA2bNnERsbixMnTqBXr14AgD59+mDfvn343//9X3z66ada74+Pj4eNjQ3GjBnTOoMhInoEMRARtSIhBObOnYvk5GRkZGTA1dX1ge+5evUqioqK4OjoCAC4efMmAKBDB+1T/gwMDFBXV1fv8+Lj4/Hyyy/DyMiohUZBRPTo40nVRK1ozpw5SExMxLZt22BpaYmSkhKUlJSgqqoKAFBRUYGFCxciKysL58+fR0ZGBkaPHg1bW1s899xzAICnnnoKTz75JGbOnInDhw/j7NmzWLVqFdLS0jBu3Ditz0tPT0dhYSGmTZvW1kMlImrXGIiIWlFcXBw0Gg38/f3h6OgoLdu3bwdwZ5bn+PHjGDt2LLp164bQ0FB069YNWVlZ0kOMjYyM8O2338LOzg6jR49G7969sXnzZiQkJODZZ5/V+ryNGzfC19cXPXr0aPOxEhG1ZzxkRtSKhBCNbjc1NcXu3bsfuB83Nzfs2LHjgXXbtm1rcm9ERPR/OENEREREsscZIqJW4vn6Zl23oCX3g5d13QIRkd7iDBERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyZ5OA9Hy5cvx9NNPw9LSEvb29hg3bhwKCgq0aoQQiIqKgpOTE0xNTeHv74/8/HytmurqasydOxe2trYwNzfHmDFjcPHiRa2asrIyhISEQKVSQaVSISQkBNevX2/tIRIREVE7oNNAlJmZiTlz5iA7OxtpaWm4desWAgICUFlZKdWsXLkSq1evRmxsLHJycqBWqzF8+HDcuHFDqgkPD0dycjKSkpKwf/9+VFRUYNSoUbh9+7ZUM2nSJOTl5SE1NRWpqanIy8tDSEhIm46XiIiI9JOhLj88NTVV63V8fDzs7e2Rm5uLZ555BkIIrFmzBkuXLsX48eMBAAkJCXBwcMC2bdswc+ZMaDQabNy4EVu2bMGwYcMAAImJiXB2dsbevXsxYsQInDp1CqmpqcjOzoa3tzcAYMOGDfDx8UFBQQG6d+9er7fq6mpUV1dLr8vLy1vrayAiIiId06tziDQaDQDA2toaAFBYWIiSkhIEBARINUqlEn5+fjh48CAAIDc3F7W1tVo1Tk5OcHd3l2qysrKgUqmkMAQAAwYMgEqlkmrutXz5cunwmkqlgrOzc8sOloiIiPSG3gQiIQRee+01DBo0CO7u7gCAkpISAICDg4NWrYODg7StpKQExsbG6NSpU6M19vb29T7T3t5eqrlXZGQkNBqNtBQVFT3cAImIiEhv6fSQ2Z+9+uqr+Omnn7B///562xQKhdZrIUS9dfe6t6ah+sb2o1QqoVQqm9I6ERERtXN6MUM0d+5cpKSk4Pvvv0fnzp2l9Wq1GgDqzeKUlpZKs0ZqtRo1NTUoKytrtOby5cv1PvfKlSv1Zp+IiIhIfnQaiIQQePXVV/Gf//wH6enpcHV11dru6uoKtVqNtLQ0aV1NTQ0yMzPh6+sLAPD09ISRkZFWTXFxMU6cOCHV+Pj4QKPR4PDhw1LNoUOHoNFopBoiIiKSL50eMpszZw62bduGr776CpaWltJMkEqlgqmpKRQKBcLDwxEdHQ03Nze4ubkhOjoaZmZmmDRpklQ7bdo0LFiwADY2NrC2tsbChQvh4eEhXXXWo0cPBAYGIiwsDOvWrQMAzJgxA6NGjWrwCjMiIiKSF50Gori4OACAv7+/1vr4+HhMmTIFALBo0SJUVVVh9uzZKCsrg7e3N/bs2QNLS0upPiYmBoaGhggODkZVVRWGDh2KTZs2wcDAQKrZunUr5s2bJ12NNmbMGMTGxrbuAImIiKhd0GkgEkI8sEahUCAqKgpRUVH3rTExMcHatWuxdu3a+9ZYW1sjMTGxOW0SERHRI04vTqomIiIi0iUGIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj2dBqIffvgBo0ePhpOTExQKBXbu3Km1XQiBqKgoODk5wdTUFP7+/sjPz9eqqa6uxty5c2Frawtzc3OMGTMGFy9e1KopKytDSEgIVCoVVCoVQkJCcP369VYeHREREbUXOg1ElZWV6NOnD2JjYxvcvnLlSqxevRqxsbHIycmBWq3G8OHDcePGDakmPDwcycnJSEpKwv79+1FRUYFRo0bh9u3bUs2kSZOQl5eH1NRUpKamIi8vDyEhIa0+PiIiImofDHX54UFBQQgKCmpwmxACa9aswdKlSzF+/HgAQEJCAhwcHLBt2zbMnDkTGo0GGzduxJYtWzBs2DAAQGJiIpydnbF3716MGDECp06dQmpqKrKzs+Ht7Q0A2LBhA3x8fFBQUIDu3bu3zWCJiIhIb+ntOUSFhYUoKSlBQECAtE6pVMLPzw8HDx4EAOTm5qK2tlarxsnJCe7u7lJNVlYWVCqVFIYAYMCAAVCpVFJNQ6qrq1FeXq61EBER0aNJbwNRSUkJAMDBwUFrvYODg7StpKQExsbG6NSpU6M19vb29fZvb28v1TRk+fLl0jlHKpUKzs7ODzUeIiIi0l96G4juUigUWq+FEPXW3evemobqH7SfyMhIaDQaaSkqKvqLnRMREVF7obeBSK1WA0C9WZzS0lJp1kitVqOmpgZlZWWN1ly+fLne/q9cuVJv9unPlEolrKystBYiIiJ6NOltIHJ1dYVarUZaWpq0rqamBpmZmfD19QUAeHp6wsjISKumuLgYJ06ckGp8fHyg0Whw+PBhqebQoUPQaDRSDREREcmbTq8yq6iowC+//CK9LiwsRF5eHqytrdGlSxeEh4cjOjoabm5ucHNzQ3R0NMzMzDBp0iQAgEqlwrRp07BgwQLY2NjA2toaCxcuhIeHh3TVWY8ePRAYGIiwsDCsW7cOADBjxgyMGjWKV5gRERERAB0HoiNHjmDw4MHS69deew0AEBoaik2bNmHRokWoqqrC7NmzUVZWBm9vb+zZsweWlpbSe2JiYmBoaIjg4GBUVVVh6NCh2LRpEwwMDKSarVu3Yt68edLVaGPGjLnvvY+IiIhIfnQaiPz9/SGEuO92hUKBqKgoREVF3bfGxMQEa9euxdq1a+9bY21tjcTExIdplYiIiB5hensOEREREVFbYSAiIiIi2WMgIiIiItljICIiIiLZYyAiIiJZiYqKgkKh0Fru3gwYAKZMmVJv+4ABAxrclxACQUFBUCgU2LlzZxuNgFqDTq8yIyIi0oVevXph79690us/36oFAAIDAxEfHy+9NjY2bnA/a9aseeDjpKh9YCAiIiLZMTQ01JoVupdSqWx0OwD8+OOPWL16NXJycuDo6NjSLVIb4yEzIiKSnTNnzsDJyQmurq544YUXcO7cOa3tGRkZsLe3R7du3RAWFobS0lKt7Tdv3sSLL76I2NjYBwYnah8YiIiISFa8vb2xefNm7N69Gxs2bEBJSQl8fX1x9epVAEBQUBC2bt2K9PR0rFq1Cjk5ORgyZAiqq6ulfURERMDX1xdjx47V1TCohfGQGRERyUpQUJD0Zw8PD/j4+OCJJ55AQkICXnvtNTz//PPSdnd3d3h5ecHFxQW7du3C+PHjkZKSgvT0dBw7dkwX7VMr4QwRERHJmrm5OTw8PHDmzJkGtzs6OsLFxUXanp6ejrNnz6Jjx44wNDSEoeGduYUJEybA39+/rdqmFsYZIiIikrXq6mqcOnUKf//73xvcfvXqVRQVFUknTi9evBjTp0/XqvHw8EBMTAxGjx7d6v1S62AgIiIiWVm4cCFGjx6NLl26oLS0FO+++y7Ky8sRGhqKiooKREVFYcKECXB0dMT58+exZMkS2Nra4rnnngMAqNXqBk+k7tKlC1xdXdt6ONRCGIiIiEhWLl68iBdffBG///477OzsMGDAAGRnZ8PFxQVVVVU4fvw4Nm/ejOvXr8PR0RGDBw/G9u3bYWlpqevWqRUxEBERkawkJSXdd5upqSl27979l/cphHiYlkgP8KRqIiIikj3OEBER0SPJ8/XNum5BS+4HL+u6BWoEZ4iIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiI6IF++OEHjB49Gk5OTlAoFNi5c6fW9oqKCrz66qvo3LkzTE1N0aNHD8TFxWnVnD17Fs899xzs7OxgZWWF4OBgXL58uQ1HQUR0fwxERPRAlZWV6NOnD2JjYxvcHhERgdTUVCQmJuLUqVOIiIjA3Llz8dVXX0nvDwgIgEKhQHp6Og4cOICamhqMHj0adXV1bTkUIqIG8caMRPRAQUFBCAoKuu/2rKwshIaGwt/fHwAwY8YMrFu3DkeOHMHYsWNx4MABnD9/HseOHYOVlRUAID4+HtbW1khPT8ewYcPaYhhERPfFGSIiemiDBg1CSkoKLl26BCEEvv/+e5w+fRojRowAAFRXV0OhUECpVErvMTExQYcOHbB//35dtU3UbjzosPV//vMfjBgxAra2tlAoFMjLy6u3Dx62bhwDERE9tI8//hg9e/ZE586dYWxsjMDAQHzyyScYNGgQAGDAgAEwNzfHG2+8gZs3b6KyshKvv/466urqUFxcrOPuifTfgw5bV1ZWYuDAgXj//ffvu72tD1s/KMQJIRAVFQUnJyeYmprC398f+fn5De5LCIGgoKAG99NSeMiMiB7axx9/jOzsbKSkpMDFxQU//PADZs+eDUdHRwwbNgx2dnb44osv8M9//hMff/wxOnTogBdffBH9+/eHgYGBrtsn0nsPOmwdEhICADh//nyD23Vx2PpuiHvllVcwYcKEettXrlyJ1atXY9OmTejWrRveffddDB8+HAUFBbC0tNSqXbNmDRQKRYv3+GcMRET0UKqqqrBkyRIkJydj5MiRAIDevXsjLy8PH374ofR/tAEBATh79ix+//13GBoaomPHjlCr1XB1ddVl+0Sy8KDD1q0RiBoLcUIIrFmzBkuXLsX48eMBAAkJCXBwcMC2bdswc+ZMqfbHH3/E6tWrkZOTA0dHxxbv8y4eMiOih1JbW4va2lp06KD9fycGBgYNTsXb2tqiY8eOSE9PR2lpKcaMGdNWrRLJlr4dti4sLERJSQkCAgKkdUqlEn5+fjh48KC07ubNm3jxxRcRGxsLtVrdqj0xEBHRA1VUVCAvL086UbOwsBB5eXm4cOECrKys4Ofnh9dffx0ZGRkoLCzEpk2bsHnzZjz33HPSPuLj45GdnY2zZ88iMTEREydOREREBLp3766jURHJx93D1l9//TUsLCygUqmg0Wh0dti6pKQEAODg4KC13sHBQdoG3Lmlh6+vL8aOHdvqPfGQGRE90JEjRzB48GDp9WuvvQYACA0NxaZNm5CUlITIyEhMnjwZ165dg4uLC9577z3MmjVLek9BQQEiIyNx7do1dO3aFUuXLkVERESbj4VIrvTxsPW95wUJIaR1KSkpSE9Px7Fjx9qkFwYiInogf39/CCHuu12tViM+Pr7Rfbz//vv3vQKGiNqOra0tAOj0sPXdw18lJSVa5wWVlpZKs0bp6ek4e/YsOnbsqPXeCRMm4O9//zsyMjJatCcGIiIiIj1XUVGBX375RXp997C1tbU1unTpgmvXruHChQv47bffANyZkQXuBI+74SM+Ph49evSAnZ0dsrKyMH/+fJ0dtnZ1dYVarUZaWhr69esHAKipqUFmZiZWrFgBAFi8eDGmT5+u9T4PDw/ExMRg9OjRLd4TAxERSTxf36zrFrTkfvCyrlsg0gsPOmydkpKCV155Rdr+wgsvAACWLVuGqKgoAG1/2PpBIS48PBzR0dFwc3ODm5sboqOjYWZmhkmTJgHQDnN/1qVLl1Y5zMdAREREpOcedNh6ypQpmDJlSqP7aOvD1g8KcYsWLUJVVRVmz56NsrIyeHt7Y8+ePfXuQdRWGIiIiIioxT0oxCkUCkRFRUkzWE3R2P4eFi+7JyIiItnjDBEREZGeaI/n8bXHnhvCGSIiIiKSPVkFok8++QSurq4wMTGBp6cn9u3bp+uWiIiISA/IJhBt374d4eHhWLp0KY4dO4a///3vCAoKwoULF3TdGhEREemYbALR6tWrMW3aNEyfPh09evTAmjVr4OzsjLi4OF23RkRERDomi5Oqa2pqkJubi8WLF2utDwgI0Hqq7p9VV1ejurpaeq3RaAAA5eXl0rrb1VWt0G3z/bm3+2HPLaM99s2e2wZ7bhvsuW08Cj3fff3AS/aFDFy6dEkAEAcOHNBa/95774lu3bo1+J5ly5YJAFy4cOHChQuXR2ApKipqNCvIYoborsaeqnuvyMhI6a6aAFBXV4dr167Bxsbmvu9pjvLycjg7O6OoqAhWVlYttt/W1B57Btpn3+y5bbDntsGe2wZ71iaEwI0bN+Dk5NRonSwCka2tLQwMDFBSUqK1/s9P1b2XUqmEUqnUWnfvE3dbkpWVVbv54d7VHnsG2mff7LltsOe2wZ7bBnv+PyqV6oE1sjip2tjYGJ6enkhLS9Nan5aWBl9fXx11RURERPpCFjNEwJ2HyoWEhMDLyws+Pj5Yv349Lly4gFmzZum6NSIiItIx2QSi559/HlevXsU777yD4uJiuLu749tvv4WLi4tO+1IqlVi2bFm9w3P6rD32DLTPvtlz22DPbYM9tw323DwKIVrx0bFERERE7YAsziEiIiIiagwDEREREckeAxERERHJHgMRERERyR4DkQ6VlpZi5syZ6NKlC5RKJdRqNUaMGIGsrKw27yUuLg69e/eWborl4+OD7777DgBQUVGBJ554QuvO3QBw/vx5WFlZ4bPPPgMAZGRkQKFQ4Pr1623dfqOmTJmCcePG6bqNBt2+fRu+vr6YMGGC1nqNRgNnZ2e8+eabAIAdO3bA29sbKpUKlpaW6NWrFxYsWNCmvV66dAkvvfQSbGxsYGZmhr59+yI3NxeA/v1GmvK9fvvttzA2NsbRo0e1aj788EPY2tpKN3LVl9/PlClToFAoGrxVyOzZs6FQKDBlypS2b+weTfnuz58/D4VCgby8vDbv7+73eO/yyy+/tHkvf0VUVFS9ntVqNQD9+/t3P8uXL4dCoUB4eDgAPey7RR4WRs0yaNAg4e3tLdLT08X58+fFoUOHRHR0tPjmm2/avJeUlBSxa9cuUVBQIAoKCsSSJUuEkZGROHHihBBCiMzMTGFoaCh++OEHIYQQdXV1wt/fXwQGBkr7+P777wUAUVZW1ub9NyY0NFSMHTtW123c1+nTp4WZmZlITEyU1oWEhIjevXuL6upqkZaWJgwNDcXKlSvFzz//LAoKCkRycrJ49dVX26zHa9euCRcXFzFlyhRx6NAhUVhYKPbu3St++eUXqUbffiMP+l6FEGLatGmiV69e4o8//hBCCHHy5ElhYmIikpKSpPfoy+8nNDRUODs7C5VKJW7evCmtr6qqEh07dhRdunQRoaGhumvwTx703RcWFgoA4tixY23eW2hoqAgMDBTFxcVay61bt7Tq7v5G9MWyZctEr169tHouLS2Vtuvb3797HT58WHTt2lX07t1bzJ8/X1qvT30zEOlIWVmZACAyMjJ03cp9derUSXz22WfS64iICPHEE0+IiooKERMTIzp27CguXrwobWcgar6PPvpIdOrUSVy6dEns3LlTGBkZSf9YzJ8/X/j7++u0vzfeeEMMGjTogXX69htp7HsVQojy8nLh4uIi3njjDVFbWyu8vLzExIkTtfahL7+fu314eHhoBY2tW7cKDw8PMXbsWL0JREI0/t3rOhA19L+nn5+fmDNnjoiIiBA2NjbimWeeEUIIkZ+fL4KCgoS5ubmwt7cXL730krhy5Yr0vrq6OrFixQrh6uoqTExMRO/evcUXX3zR4n0vW7ZM9OnTp9Eaffv7d9eNGzeEm5ubSEtLE35+flqBSJ/65iEzHbGwsICFhQV27tyJ6upqXbej5fbt20hKSkJlZSV8fHyk9dHR0TAyMsJLL72EJUuWYO3atXjsscd02OmjY+7cuejTpw9efvllzJgxA//617/Qt29fAIBarUZ+fj5OnDihs/5SUlLg5eWFiRMnwt7eHv369cOGDRvq1enbb6Sx7xUALC0t8fnnn2PVqlWYPHkyioqK8Mknn+is36Z45ZVXEB8fL73+/PPPMXXqVB121LAHfff6KCEhAYaGhjhw4ADWrVuH4uJi+Pn5oW/fvjhy5AhSU1Nx+fJlBAcHS+958803ER8fj7i4OOTn5yMiIgIvvfQSMjMzW7y/M2fOwMnJCa6urnjhhRdw7tw5re369vfvrjlz5mDkyJEYNmxYg9v1pu9WjVvUqC+//FJ06tRJmJiYCF9fXxEZGSl+/PFHnfXz008/CXNzc2FgYCBUKpXYtWtXvZrU1FQBQAQFBdXbxhmih3Pq1CkBQHh4eIja2lppfUVFhXj22WcFAOHi4iKef/55sXHjRukwT1tQKpVCqVSKyMhIcfToUfHpp58KExMTkZCQUK9W334j9/te/+yFF14QAMT27dvrbdOX38/dPq5cuSKUSqUoLCwU58+fFyYmJuLKlSt6N0MkxP2/e13PEBkYGAhzc3Np+cc//iH8/PxE3759tWrfeustERAQoLWuqKhIABAFBQWioqJCmJiYiIMHD2rVTJs2Tbz44ost2ve3334rvvzyS/HTTz9JMy0ODg7i999/16rTt79///73v4W7u7uoqqoSQogGZ4iE0I++OUOkQxMmTMBvv/2GlJQUjBgxAhkZGejfvz82bdqkk366d++OvLw8ZGdn45///CdCQ0Nx8uRJrZqNGzfCzMwMx48fh0aj0Umfj6rPP/8cZmZmKCwsxMWLF6X15ubm2LVrF3755Re8+eabsLCwwIIFC/C3v/0NN2/ebJPe6urq0L9/f0RHR6Nfv36YOXMmwsLCEBcXV69W334j9/te7/rtt9+QmpoKMzMz7Nu3Twcd/jW2trYYOXIkEhISEB8fj5EjR8LW1lbXbTXoQd+9rgwePBh5eXnS8vHHHwMAvLy8tOpyc3Px/fffSzP6FhYWeOqppwAAZ8+excmTJ/HHH39g+PDhWjWbN2/G2bNnW7TnoKAgTJgwAR4eHhg2bBh27doF4M6s1p/p09+/oqIizJ8/H4mJiTAxMWm0Vh/6ZiDSMRMTEwwfPhz/+te/cPDgQUyZMgXLli3TSS/GxsZ48skn4eXlheXLl6NPnz746KOPpO3bt29HSkoK9u/fD5VKhYiICJ30+SjKyspCTEwMvvrqK/j4+GDatGkQ9zxV54knnsD06dPx2Wef4ejRozh58iS2b9/eJv05OjqiZ8+eWut69OiBCxcuaK3Tt99IU77X6dOno0+fPvj2228RFxfXKoc6WtrUqVOxadMmJCQk6OXhMqBp372umJub48knn5QWR0dHaf2f1dXVYfTo0VrhKS8vD2fOnMEzzzyDuro6AMCuXbu0tp88eRJffvllq4/Bw8MDZ86ckdbp29+/3NxclJaWwtPTE4aGhjA0NERmZiY+/vhjGBoa4vbt23rVNwORnunZsycqKyt13QYAQAghnd90+fJlzJkzB++++y769euHTZs2YcuWLdKl+dR8VVVVCA0NxcyZMzFs2DB89tlnyMnJwbp16+77nq5du8LMzKzNfisDBw5EQUGB1rrTp09rPRxZ334jTfleP/vsM+zbtw/x8fHw8/PDq6++iqlTp+rN38H7CQwMRE1NDWpqajBixAhdt1NPc37T+qh///7Iz89H165dtQLUk08+CXNzc/Ts2RNKpRIXLlyot93Z2blVe6uursapU6ekMKdvf/8AYOjQoTh+/LhWWPTy8sLkyZORl5cHAwMDvepbNk+71zdXr17FxIkTMXXqVPTu3RuWlpY4cuQIVq5cibFjx7Z5P0uWLEFQUBCcnZ1x48YNJCUlISMjA6mpqQCAmTNnonv37tL9Iry8vLBo0SLMmDEDJ06cgEqlkvZ1/PhxWFpaau1f1ydTajSaevc8sba2RpcuXXTT0J8sXrwYdXV1WLFiBQCgS5cuWLVqFV577TUEBgZi06ZNuHnzJp599lm4uLjg+vXr+Pjjj1FbW4vhw4e3SY8RERHw9fVFdHQ0goODcfjwYaxfvx7r16+XavTtN/Kg77VDhw5YsGABPvzwQ7i6ugK4c3Lnrl27sHjxYqxdu1bal779fgwMDHDq1Cnpz/rmQd/9XfeGbODOfxQaGxu3Wa+NmTNnDjZs2IAXX3wRr7/+OmxtbfHLL78gKSkJGzZsgKWlJRYuXIiIiAjU1dVh0KBBKC8vx8GDB2FhYYHQ0NAW62XhwoUYPXo0unTpgtLSUrz77rsoLy+XPkPf/v4Bdy5acHd311pnbm4OGxsbab1e9d2qZyjRff3xxx9i8eLFon///kKlUgkzMzPRvXt38eabb2rdY6StTJ06Vbi4uAhjY2NhZ2cnhg4dKvbs2SOEECIhIUGYmZmJ06dPa72nurpauLu7i1deeUUI8X8nvjW06FJoaGiDPenDCagZGRnCwMBA7Nu3r962gIAAMWTIEJGeni4mTJggnJ2dhbGxsXBwcBCBgYENvqc1ff3118Ld3V0olUrx1FNPifXr10vb9O030pTvdciQIfVOmBVCiH379gkDAwPplhj68vt50Mnd+nJSdVO++3Pnzt33d1BYWNiq/TV22X1DJ/uePn1aPPfcc6Jjx47C1NRUPPXUUyI8PFzU1dUJIe5cdv/RRx+J7t27CyMjI2FnZydGjBghMjMzW7Tv559/Xjg6OgojIyPh5OQkxo8fL/Lz84UQ+vf3rzF//p71rW+FEHpyUJeIiIhIR3gOEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMREcmOQqHAzp07dd0GEekRBiIieuSUlpZi5syZ6NKlC5RKJdRqNUaMGIGsrCwAQHFxMYKCgnTcJRHpEz7clYgeORMmTEBtbS0SEhLw+OOP4/Lly/jvf/+La9euAQDUarWOOyQifcMZIiJ6pFy/fh379+/HihUrMHjwYLi4uOBvf/sbIiMjMXLkSADah8yioqKgUCjqLZs2bQIACCGwcuVKPP744zA1NUWfPn3w5Zdf6mh0RNRaGIiI6JFiYWEBCwsL7Ny5E9XV1Q+sX7hwIYqLi6Xlww8/hJmZGby8vAAAb775JuLj4xEXF4f8/HxERETgpZdeQmZmZmsPhYjaEJ92T0SPnB07diAsLAxVVVXo378//Pz88MILL6B3794A7swQJScnY9y4cVrvy87OxuDBg5GQkIDg4GBUVlbC1tYW6enp8PHxkeqmT5+OmzdvYtu2bW05LCJqRZwhIqJHzoQJE/Dbb78hJSUFI0aMQEZGBvr37y8dBmvIhQsXMG7cOCxcuBDBwcEAgJMnT+KPP/7A8OHDpZknCwsLbN68GWfPnm2j0RBRW+AMERHJwvTp05GWloZff/213gxRZWUlBg4cCFdXV/znP/+BQqEAABw6dAgDBgxARkYGHnvsMa39KZVKODs7t/UwiKiV8CozIpKFnj17NnjvISEEXnrpJdTV1WHLli1SGLr7HqVSiQsXLsDPz68NuyWitsZARESPlKtXr2LixImYOnUqevfuDUtLSxw5cgQrV67E2LFj69VHRUVh79692LNnDyoqKlBRUQEAUKlUsLS0xMKFCxEREYG6ujoMGjQI5eXlOHjwICwsLBAaGtrWwyOiVsJARESPFAsLC3h7eyMmJgZnz55FbW0tnJ2dERYWhiVLltSrz8zMREVFBXx9fbXWx8fHY8qUKfif//kf2NvbY/ny5Th37hw6duyI/v37N7gvImq/eA4RERERyR6vMiMiIiLZYyAiIiIi2WMgIiIiItljICIiIiLZYyAiIiIi2WMgIiIiItljICIiIiLZYyAiIiIi2WMgIiIiItljICIiIiLZYyAiIiIi2fv/kqoyUoIT33wAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sns.countplot(x='Size',data=data)\n",
    "for bars in ax.containers:\n",
    "    ax.bar_label(bars)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9878a8b1",
   "metadata": {},
   "source": [
    "From above graph we can see most of the people buy M-size"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6db48b0",
   "metadata": {},
   "source": [
    "### Groupby"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "198f0b93",
   "metadata": {},
   "source": [
    "The groupby() function in pandas is used to group data based on one or more columns in a DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 475,
   "id": "167730ab",
   "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>Size</th>\n",
       "      <th>Qty</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>M</td>\n",
       "      <td>5905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>L</td>\n",
       "      <td>5795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>XL</td>\n",
       "      <td>5481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>XXL</td>\n",
       "      <td>4465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3XL</td>\n",
       "      <td>3972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>S</td>\n",
       "      <td>3896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>XS</td>\n",
       "      <td>2191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Free</td>\n",
       "      <td>467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6XL</td>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5XL</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4XL</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Size   Qty\n",
       "6      M  5905\n",
       "5      L  5795\n",
       "8     XL  5481\n",
       "10   XXL  4465\n",
       "0    3XL  3972\n",
       "7      S  3896\n",
       "9     XS  2191\n",
       "4   Free   467\n",
       "3    6XL   170\n",
       "2    5XL   104\n",
       "1    4XL    93"
      ]
     },
     "execution_count": 475,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby(['Size'], as_index=False)['Qty'].sum().sort_values(by='Qty',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 477,
   "id": "feb8dc60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Size', ylabel='Qty'>"
      ]
     },
     "execution_count": 477,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "quant = data.groupby(['Size'], as_index=False)['Qty'].sum().sort_values(by='Qty',ascending=False)\n",
    "sns.barplot(x='Size',y='Qty',data=quant)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "996903bb",
   "metadata": {},
   "source": [
    "From above graph you can see that most of the Qty buys M-size in sales"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45050de0",
   "metadata": {},
   "source": [
    "### Courier status"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 481,
   "id": "3304732a",
   "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>index</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Date</th>\n",
       "      <th>Status</th>\n",
       "      <th>Fulfilment</th>\n",
       "      <th>Sales Channel</th>\n",
       "      <th>ship-service-level</th>\n",
       "      <th>Category</th>\n",
       "      <th>Size</th>\n",
       "      <th>Courier Status</th>\n",
       "      <th>Qty</th>\n",
       "      <th>currency</th>\n",
       "      <th>Amount</th>\n",
       "      <th>ship-city</th>\n",
       "      <th>ship-state</th>\n",
       "      <th>ship-postal-code</th>\n",
       "      <th>ship-country</th>\n",
       "      <th>B2B</th>\n",
       "      <th>fulfilled-by</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>405-8078784-5731545</td>\n",
       "      <td>2022-04-30</td>\n",
       "      <td>Cancelled</td>\n",
       "      <td>Merchant</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Standard</td>\n",
       "      <td>T-shirt</td>\n",
       "      <td>S</td>\n",
       "      <td>On the Way</td>\n",
       "      <td>0</td>\n",
       "      <td>INR</td>\n",
       "      <td>647.62</td>\n",
       "      <td>MUMBAI</td>\n",
       "      <td>MAHARASHTRA</td>\n",
       "      <td>400081</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>Easy Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>171-9198151-1101146</td>\n",
       "      <td>2022-04-30</td>\n",
       "      <td>Shipped - Delivered to Buyer</td>\n",
       "      <td>Merchant</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>3XL</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>1</td>\n",
       "      <td>INR</td>\n",
       "      <td>406.00</td>\n",
       "      <td>BENGALURU</td>\n",
       "      <td>KARNATAKA</td>\n",
       "      <td>560085</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>Easy Ship</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index             Order ID       Date                        Status  \\\n",
       "0      0  405-8078784-5731545 2022-04-30                     Cancelled   \n",
       "1      1  171-9198151-1101146 2022-04-30  Shipped - Delivered to Buyer   \n",
       "\n",
       "  Fulfilment Sales Channel ship-service-level Category Size Courier Status  \\\n",
       "0   Merchant     Amazon.in           Standard  T-shirt    S     On the Way   \n",
       "1   Merchant     Amazon.in           Standard    Shirt  3XL        Shipped   \n",
       "\n",
       "   Qty currency  Amount  ship-city   ship-state  ship-postal-code  \\\n",
       "0    0      INR  647.62     MUMBAI  MAHARASHTRA            400081   \n",
       "1    1      INR  406.00  BENGALURU    KARNATAKA            560085   \n",
       "\n",
       "  ship-country    B2B fulfilled-by  \n",
       "0           IN  False    Easy Ship  \n",
       "1           IN  False    Easy Ship  "
      ]
     },
     "execution_count": 481,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 483,
   "id": "6987aa46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Courier Status', ylabel='count'>"
      ]
     },
     "execution_count": 483,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=data, x='Courier Status', hue='Status')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 484,
   "id": "4f7bc79a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# to get figure size, we're using matplotlib(plt)\n",
    "plt.figure(figsize=(10,5))\n",
    "ax=sns.countplot(data=data, x='Courier Status', hue='Status')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25c700ce",
   "metadata": {},
   "source": [
    "From above graph the majority of the orders are shipped through the courier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 488,
   "id": "2023b79a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 488,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# we're making histogram of Size\n",
    "data['Size'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 490,
   "id": "b6614a34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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S0tKUlpam7OxsxcXFGdvLy8s1aNAgFRUVKTMzU6mpqXrvvfeUkJBg9pAAAAAA4Jp5mX3BwIEDNXDgwEtuczqdSk5O1tSpUzV48GBJ0pIlSxQaGqoVK1Zo9OjRcjgcWrRokZYuXao+ffpIkpYtW6aIiAitXbtW/fv31969e5WWlqaNGzeqS5cukqSFCxcqOjpa+/btU6tWrZSenq49e/YoNzdX4eHhkqTZs2dr+PDhmjFjhgICAn7VLwQAAAAArqRK74k6ePCg8vLy1K9fP2PM19dXPXr00Pr16yVJWVlZKisrc6kJDw9X27ZtjZoNGzbIbrcbAUqSunbtKrvd7lLTtm1bI0BJUv/+/VVSUqKsrKxL9ldSUqJTp065PAAAAADAjCoNUXl5eZKk0NBQl/HQ0FBjW15ennx8fNS4ceMr1oSEhFTaf0hIiEvNxT+ncePG8vHxMWouNnPmTOMeK7vdroiIiF9xlAAAAADcWbXMzmez2VyeO53OSmMXu7jmUvW/puZCU6ZMkcPhMB65ublX7AkAAAAALlalISosLEySKp0Jys/PN84ahYWFqbS0VIWFhVesOXr0aKX9Hzt2zKXm4p9TWFiosrKySmeozvP19VVAQIDLAwAAAADMqNIQ1aJFC4WFhWnNmjXGWGlpqTIyMtStWzdJUseOHeXt7e1Sc+TIEe3atcuoiY6OlsPh0ObNm42aTZs2yeFwuNTs2rVLR44cMWrS09Pl6+urjh07VuVhAQAAAIDB9Ox8Z86c0YEDB4znBw8eVHZ2tgIDA9W0aVONGzdOSUlJioyMVGRkpJKSklS/fn0NHTpUkmS32zVixAglJCQoKChIgYGBmjhxoqKioozZ+lq3bq0BAwZo5MiRWrBggSRp1KhRiomJUatWrSRJ/fr1U5s2bRQXF6dZs2bpxIkTmjhxokaOHMkZJgAAAADVxnSI2rp1q3r16mU8nzBhgiRp2LBhWrx4sSZNmqTi4mKNGTNGhYWF6tKli9LT0+Xv72+8Zu7cufLy8tKQIUNUXFys3r17a/HixfL09DRqli9frvj4eGMWv9jYWJe1qTw9PfXpp59qzJgx6t69u/z8/DR06FC98sor5n8LAAAAAHCNTIeonj17yul0Xna7zWZTYmKiEhMTL1tTr149zZs3T/PmzbtsTWBgoJYtW3bFXpo2bapPPvnkqj0DAAAAQFWpltn5AAAAAOC3ihAFAAAAACYQogAAAADABEIUAAAAAJhAiAIAAAAAEwhRAAAAAGACIQoAAAAATCBEAQAAAIAJhCgAAAAAMIEQBQAAAAAmEKIAAAAAwARCFAAAAACYQIgCAAAAABMIUQAAAABgAiEKAAAAAEwgRAEAAACACYQoAAAAADCBEAUAAAAAJhCiAAAAAMAEQhQAAAAAmECIAgAAAAATCFEAAAAAYAIhCgAAAABMIEQBAAAAgAmEKAAAAAAwgRAFAAAAACYQogAAAADABEIUAAAAAJhAiAIAAAAAEwhRAAAAAGACIQoAAAAATCBEAQAAAIAJhCgAAAAAMIEQBQAAAAAmEKIAAAAAwARCFAAAAACYQIgCAAAAABMIUQAAAABgAiEKAAAAAEwgRAEAAACACYQoAAAAADChykPUzz//rGeeeUYtWrSQn5+fWrZsqeeff14VFRVGjdPpVGJiosLDw+Xn56eePXtq9+7dLvspKSnR2LFjFRwcrAYNGig2NlaHDh1yqSksLFRcXJzsdrvsdrvi4uJ08uTJqj4kAAAAADBUeYh66aWX9PrrryslJUV79+7Vyy+/rFmzZmnevHlGzcsvv6w5c+YoJSVFW7ZsUVhYmPr27avTp08bNePGjdMHH3yg1NRUZWZm6syZM4qJiVF5eblRM3ToUGVnZystLU1paWnKzs5WXFxcVR8SAAAAABi8qnqHGzZs0O9+9zsNGjRIktS8eXO988472rp1q6RfzkIlJydr6tSpGjx4sCRpyZIlCg0N1YoVKzR69Gg5HA4tWrRIS5cuVZ8+fSRJy5YtU0REhNauXav+/ftr7969SktL08aNG9WlSxdJ0sKFCxUdHa19+/apVatWVX1oAAAAAFD1Z6LuvPNOffbZZ9q/f78k6ZtvvlFmZqbuvfdeSdLBgweVl5enfv36Ga/x9fVVjx49tH79eklSVlaWysrKXGrCw8PVtm1bo2bDhg2y2+1GgJKkrl27ym63GzUXKykp0alTp1weAAAAAGBGlZ+J+vOf/yyHw6FbbrlFnp6eKi8v14wZM/Twww9LkvLy8iRJoaGhLq8LDQ3Vjz/+aNT4+PiocePGlWrOvz4vL08hISGVfn5ISIhRc7GZM2dq+vTp/94BAgAAAHBrVX4m6m9/+5uWLVumFStWaNu2bVqyZIleeeUVLVmyxKXOZrO5PHc6nZXGLnZxzaXqr7SfKVOmyOFwGI/c3NxrPSwAAAAAkFQNZ6KefvppTZ48WQ899JAkKSoqSj/++KNmzpypYcOGKSwsTNIvZ5KaNGlivC4/P984OxUWFqbS0lIVFha6nI3Kz89Xt27djJqjR49W+vnHjh2rdJbrPF9fX/n6+lbNgQIAAABwS1V+Jurs2bPy8HDdraenpzHFeYsWLRQWFqY1a9YY20tLS5WRkWEEpI4dO8rb29ul5siRI9q1a5dREx0dLYfDoc2bNxs1mzZtksPhMGoAAAAAoKpV+Zmo++67TzNmzFDTpk116623avv27ZozZ46eeOIJSb9cgjdu3DglJSUpMjJSkZGRSkpKUv369TV06FBJkt1u14gRI5SQkKCgoCAFBgZq4sSJioqKMmbra926tQYMGKCRI0dqwYIFkqRRo0YpJiaGmfkAAAAAVJsqD1Hz5s3Ts88+qzFjxig/P1/h4eEaPXq0nnvuOaNm0qRJKi4u1pgxY1RYWKguXbooPT1d/v7+Rs3cuXPl5eWlIUOGqLi4WL1799bixYvl6elp1Cxfvlzx8fHGLH6xsbFKSUmp6kMCAAAAAEOVhyh/f38lJycrOTn5sjU2m02JiYlKTEy8bE29evU0b948l0V6LxYYGKhly5b9G90CAAAAgDlVfk8UAAAAAPyWEaIAAAAAwARCFAAAAACYQIgCAAAAABMIUQAAAABgAiEKAAAAAEwgRAEAAACACYQoAAAAADCBEAUAAAAAJhCiAAAAAMAEQhQAAAAAmECIAgAAAAATCFEAAAAAYAIhCgAAAABMIEQBAAAAgAmEKAAAAAAwgRAFAAAAACYQogAAAADABEIUAAAAAJhAiAIAAAAAEwhRAAAAAGACIQoAAAAATCBEAQAAAIAJhCgAAAAAMIEQBQAAAAAmEKIAAAAAwARCFAAAAACY4GV1AwDcU05OjgoKCqpt/8HBwWratGm17R8AALgvQhSAGpeTk6NWt7TWueKz1fYz6vnV175v9xKkAABAlSNEAahxBQUFOld8VkExCfIOiqjy/Zcdz9XxT2aroKCAEAUAAKocIQqAZbyDIuQbdpPVbQAAAJjCxBIAAAAAYAIhCgAAAABMIEQBAAAAgAmEKAAAAAAwgRAFAAAAACYQogAAAADABEIUAAAAAJhAiAIAAAAAEwhRAAAAAGACIQoAAAAATKiWEPXTTz/p0UcfVVBQkOrXr6/bbrtNWVlZxnan06nExESFh4fLz89PPXv21O7du132UVJSorFjxyo4OFgNGjRQbGysDh065FJTWFiouLg42e122e12xcXF6eTJk9VxSAAAAAAgqRpCVGFhobp37y5vb2/985//1J49ezR79mw1atTIqHn55Zc1Z84cpaSkaMuWLQoLC1Pfvn11+vRpo2bcuHH64IMPlJqaqszMTJ05c0YxMTEqLy83aoYOHars7GylpaUpLS1N2dnZiouLq+pDAgAAAACDV1Xv8KWXXlJERITeeustY6x58+bGn51Op5KTkzV16lQNHjxYkrRkyRKFhoZqxYoVGj16tBwOhxYtWqSlS5eqT58+kqRly5YpIiJCa9euVf/+/bV3716lpaVp48aN6tKliyRp4cKFio6O1r59+9SqVauqPjQAAAAAqPozUR999JE6deqkBx54QCEhIerQoYMWLlxobD948KDy8vLUr18/Y8zX11c9evTQ+vXrJUlZWVkqKytzqQkPD1fbtm2Nmg0bNshutxsBSpK6du0qu91u1FyspKREp06dcnkAAAAAgBlVHqJ++OEHzZ8/X5GRkVq9erWefPJJxcfH6+2335Yk5eXlSZJCQ0NdXhcaGmpsy8vLk4+Pjxo3bnzFmpCQkEo/PyQkxKi52MyZM437p+x2uyIiIv69gwUAAADgdqo8RFVUVOj2229XUlKSOnTooNGjR2vkyJGaP3++S53NZnN57nQ6K41d7OKaS9VfaT9TpkyRw+EwHrm5udd6WAAAAAAgqRpCVJMmTdSmTRuXsdatWysnJ0eSFBYWJkmVzhbl5+cbZ6fCwsJUWlqqwsLCK9YcPXq00s8/duxYpbNc5/n6+iogIMDlAQAAAABmVHmI6t69u/bt2+cytn//fjVr1kyS1KJFC4WFhWnNmjXG9tLSUmVkZKhbt26SpI4dO8rb29ul5siRI9q1a5dREx0dLYfDoc2bNxs1mzZtksPhMGoAAAAAoKpV+ex848ePV7du3ZSUlKQhQ4Zo8+bNeuONN/TGG29I+uUSvHHjxikpKUmRkZGKjIxUUlKS6tevr6FDh0qS7Ha7RowYoYSEBAUFBSkwMFATJ05UVFSUMVtf69atNWDAAI0cOVILFiyQJI0aNUoxMTHMzAcAAACg2lR5iLrjjjv0wQcfaMqUKXr++efVokULJScn65FHHjFqJk2apOLiYo0ZM0aFhYXq0qWL0tPT5e/vb9TMnTtXXl5eGjJkiIqLi9W7d28tXrxYnp6eRs3y5csVHx9vzOIXGxurlJSUqj4kAAAAADBUeYiSpJiYGMXExFx2u81mU2JiohITEy9bU69ePc2bN0/z5s27bE1gYKCWLVv277QKAAAAAKZU+T1RAAAAAPBbRogCAAAAABMIUQAAAABgAiEKAAAAAEwgRAEAAACACYQoAAAAADCBEAUAAAAAJhCiAAAAAMAEQhQAAAAAmECIAgAAAAATCFEAAAAAYAIhCgAAAABMIEQBAAAAgAmEKAAAAAAwgRAFAAAAACYQogAAAADABEIUAAAAAJhAiAIAAAAAEwhRAAAAAGACIQoAAAAATCBEAQAAAIAJhCgAAAAAMIEQBQAAAAAmEKIAAAAAwARCFAAAAACYQIgCAAAAABMIUQAAAABgAiEKAAAAAEwgRAEAAACACYQoAAAAADCBEAUAAAAAJhCiAAAAAMAEQhQAAAAAmECIAgAAAAATCFEAAAAAYAIhCgAAAABMIEQBAAAAgAmEKAAAAAAwgRAFAAAAACYQogAAAADABEIUAAAAAJhQ7SFq5syZstlsGjdunDHmdDqVmJio8PBw+fn5qWfPntq9e7fL60pKSjR27FgFBwerQYMGio2N1aFDh1xqCgsLFRcXJ7vdLrvdrri4OJ08ebK6DwkAAACAG6vWELVlyxa98cYbateuncv4yy+/rDlz5iglJUVbtmxRWFiY+vbtq9OnTxs148aN0wcffKDU1FRlZmbqzJkziomJUXl5uVEzdOhQZWdnKy0tTWlpacrOzlZcXFx1HhIAAAAAN1dtIerMmTN65JFHtHDhQjVu3NgYdzqdSk5O1tSpUzV48GC1bdtWS5Ys0dmzZ7VixQpJksPh0KJFizR79mz16dNHHTp00LJly7Rz506tXbtWkrR3716lpaXpzTffVHR0tKKjo7Vw4UJ98skn2rdvX3UdFgAAAAA3V20h6o9//KMGDRqkPn36uIwfPHhQeXl56tevnzHm6+urHj16aP369ZKkrKwslZWVudSEh4erbdu2Rs2GDRtkt9vVpUsXo6Zr166y2+1GzcVKSkp06tQplwcAAAAAmOFVHTtNTU3Vtm3btGXLlkrb8vLyJEmhoaEu46Ghofrxxx+NGh8fH5czWOdrzr8+Ly9PISEhlfYfEhJi1Fxs5syZmj59uvkDAgAAAID/U+VnonJzc/XUU09p2bJlqlev3mXrbDaby3On01lp7GIX11yq/kr7mTJlihwOh/HIzc294s8DAAAAgItVeYjKyspSfn6+OnbsKC8vL3l5eSkjI0OvvvqqvLy8jDNQF58tys/PN7aFhYWptLRUhYWFV6w5evRopZ9/7NixSme5zvP19VVAQIDLAwAAAADMqPIQ1bt3b+3cuVPZ2dnGo1OnTnrkkUeUnZ2tli1bKiwsTGvWrDFeU1paqoyMDHXr1k2S1LFjR3l7e7vUHDlyRLt27TJqoqOj5XA4tHnzZqNm06ZNcjgcRg0AAAAAVLUqvyfK399fbdu2dRlr0KCBgoKCjPFx48YpKSlJkZGRioyMVFJSkurXr6+hQ4dKkux2u0aMGKGEhAQFBQUpMDBQEydOVFRUlDFRRevWrTVgwACNHDlSCxYskCSNGjVKMTExatWqVVUfFgAAAABIqqaJJa5m0qRJKi4u1pgxY1RYWKguXbooPT1d/v7+Rs3cuXPl5eWlIUOGqLi4WL1799bixYvl6elp1Cxfvlzx8fHGLH6xsbFKSUmp8eMBAAAA4D5qJEStW7fO5bnNZlNiYqISExMv+5p69epp3rx5mjdv3mVrAgMDtWzZsirqEgAAAACurtrWiQIAAACA3yJCFAAAAACYQIgCAAAAABMIUQAAAABgAiEKAAAAAEwgRAEAAACACYQoAAAAADCBEAUAAAAAJhCiAAAAAMAEQhQAAAAAmECIAgAAAAATCFEAAAAAYAIhCgAAAABMIEQBAAAAgAmEKAAAAAAwgRAFAAAAACYQogAAAADABEIUAAAAAJhAiAIAAAAAEwhRAAAAAGACIQoAAAAATCBEAQAAAIAJhCgAAAAAMIEQBQAAAAAmEKIAAAAAwARCFAAAAACYQIgCAAAAABMIUQAAAABgAiEKAAAAAEwgRAEAAACACYQoAAAAADCBEAUAAAAAJnhZ3QAAAPj35OTkqKCgoFr2HRwcrKZNm1bLvgGgriJEAQBQh+Xk5KjVLa11rvhstey/nl997ft2L0EKAC5AiAIAoA4rKCjQueKzCopJkHdQRJXuu+x4ro5/MlsFBQWEKAC4ACEKAIDfAO+gCPmG3WR1GwDgFphYAgAAAABMIEQBAAAAgAmEKAAAAAAwgRAFAAAAACYQogAAAADAhCoPUTNnztQdd9whf39/hYSE6P7779e+fftcapxOpxITExUeHi4/Pz/17NlTu3fvdqkpKSnR2LFjFRwcrAYNGig2NlaHDh1yqSksLFRcXJzsdrvsdrvi4uJ08uTJqj4kAAAAADBUeYjKyMjQH//4R23cuFFr1qzRzz//rH79+qmoqMioefnllzVnzhylpKRoy5YtCgsLU9++fXX69GmjZty4cfrggw+UmpqqzMxMnTlzRjExMSovLzdqhg4dquzsbKWlpSktLU3Z2dmKi4ur6kMCAAAAAEOVrxOVlpbm8vytt95SSEiIsrKydPfdd8vpdCo5OVlTp07V4MGDJUlLlixRaGioVqxYodGjR8vhcGjRokVaunSp+vTpI0latmyZIiIitHbtWvXv31979+5VWlqaNm7cqC5dukiSFi5cqOjoaO3bt0+tWrWq6kMDAAAAgOq/J8rhcEiSAgMDJUkHDx5UXl6e+vXrZ9T4+vqqR48eWr9+vSQpKytLZWVlLjXh4eFq27atUbNhwwbZ7XYjQElS165dZbfbjZqLlZSU6NSpUy4PAAAAADCjWkOU0+nUhAkTdOedd6pt27aSpLy8PElSaGioS21oaKixLS8vTz4+PmrcuPEVa0JCQir9zJCQEKPmYjNnzjTun7Lb7YqIiPj3DhAAAACA26nWEPWnP/1JO3bs0DvvvFNpm81mc3nudDorjV3s4ppL1V9pP1OmTJHD4TAeubm513IYAAAAAGCothA1duxYffTRR/riiy90ww03GONhYWGSVOlsUX5+vnF2KiwsTKWlpSosLLxizdGjRyv93GPHjlU6y3Wer6+vAgICXB4AAAAAYEaVhyin06k//elPev/99/X555+rRYsWLttbtGihsLAwrVmzxhgrLS1VRkaGunXrJknq2LGjvL29XWqOHDmiXbt2GTXR0dFyOBzavHmzUbNp0yY5HA6jBgAAAACqWpXPzvfHP/5RK1as0Icffih/f3/jjJPdbpefn59sNpvGjRunpKQkRUZGKjIyUklJSapfv76GDh1q1I4YMUIJCQkKCgpSYGCgJk6cqKioKGO2vtatW2vAgAEaOXKkFixYIEkaNWqUYmJimJkPAAAAQLWp8hA1f/58SVLPnj1dxt966y0NHz5ckjRp0iQVFxdrzJgxKiwsVJcuXZSeni5/f3+jfu7cufLy8tKQIUNUXFys3r17a/HixfL09DRqli9frvj4eGMWv9jYWKWkpFT1IQEAAACAocpDlNPpvGqNzWZTYmKiEhMTL1tTr149zZs3T/PmzbtsTWBgoJYtW/Zr2gQAAACAX6Xa14kCAAAAgN8SQhQAAAAAmECIAgAAAAATCFEAAAAAYAIhCgAAAABMIEQBAAAAgAmEKAAAAAAwgRAFAAAAACYQogAAAADABEIUAAAAAJhAiAIAAAAAEwhRAAAAAGACIQoAAAAATCBEAQAAAIAJhCgAAAAAMIEQBQAAAAAmEKIAAAAAwARCFAAAAACYQIgCAAAAABMIUQAAAABgAiEKAAAAAEwgRAEAAACACYQoAAAAADCBEAUAAAAAJhCiAAAAAMAEQhQAAAAAmECIAgAAAAATCFEAAAAAYAIhCgAAAABMIEQBAAAAgAmEKAAAAAAwgRAFAAAAACYQogAAAADABEIUAAAAAJhAiAIAAAAAEwhRAAAAAGACIQoAAAAATPCyugEAAADgWuTk5KigoKDa9h8cHKymTZtW2/7x20GIAgAA+BWq8wM9H+Yry8nJUatbWutc8dlq+xn1/Opr37d7+d3jqghRAAAAJlX3B3o+zFdWUFCgc8VnFRSTIO+giCrff9nxXB3/ZLYKCgr4veOqCFEA4Ea4FAaoGtX5gZ4P81fmHRQh37CbrG4Dbq7Oh6jXXntNs2bN0pEjR3TrrbcqOTlZd911l9VtAUCtw6UwQNXjAz3gnup0iPrb3/6mcePG6bXXXlP37t21YMECDRw4UHv27OEfcAC4CJfCAABQNep0iJozZ45GjBihP/zhD5Kk5ORkrV69WvPnz9fMmTMt7g4Aaie+OQcAmMGl4JXV2RBVWlqqrKwsTZ482WW8X79+Wr9+/SVfU1JSopKSEuO5w+GQJJ06dar6Gr1GZ86ckSSV5B1QRem5Kt9/2YlDkqSsrCzjZ1UlDw8PVVRUVPl+q3v/+/btk8Tvvab3z+/dmv3ze7du/9W57+p8X6v7PZX4vV8K/y9dGn+HWbP/o0eP6tG4x1RaUvW/8/N86/kpa+sWRURU/VUSZpzPBE6n86q1Nue1VNVChw8f1vXXX6+vv/5a3bp1M8aTkpK0ZMkS43+0CyUmJmr69Ok12SYAAACAOiQ3N1c33HDDFWvq7Jmo82w2m8tzp9NZaey8KVOmaMKECcbziooKnThxQkFBQZd9TU05deqUIiIilJubq4CAAEt7wS94T2of3pPahfej9uE9qX14T2oX3o/apza9J06nU6dPn1Z4ePhVa+tsiAoODpanp6fy8vJcxvPz8xUaGnrJ1/j6+srX19dlrFGjRtXV4q8SEBBg+X9AcMV7UvvwntQuvB+1D+9J7cN7UrvwftQ+teU9sdvt11TnUc19VBsfHx917NhRa9ascRlfs2aNy+V9AAAAAFCV6uyZKEmaMGGC4uLi1KlTJ0VHR+uNN95QTk6OnnzySatbAwAAAPAbVadD1IMPPqjjx4/r+eef15EjR9S2bVv94x//ULNmzaxuzTRfX19Nmzat0uWGsA7vSe3De1K78H7UPrwntQ/vSe3C+1H71NX3pM7OzgcAAAAAVqiz90QBAAAAgBUIUQAAAABgAiEKAAAAAEwgRAEAAACACYQoAAAAADCBEGWRli1b6vjx45XGT548qZYtW1rQESTpyy+/1M8//1xp/Oeff9aXX35pQUcAcO3Ky8uVnZ2twsJCq1sBgN80QpRF/vWvf6m8vLzSeElJiX766ScLOoIk9erVSydOnKg07nA41KtXLws6cm9Op1M//vijiouLrW4F/6e4uFhnz541nv/4449KTk5Wenq6hV25r3HjxmnRokWSfglQPXr00O23366IiAitW7fO2ubcFF+SAle3ZMkSffrpp8bzSZMmqVGjRurWrZt+/PFHCzu7dnV6sd266KOPPjL+vHr1atntduN5eXm5PvvsMzVv3tyCziD98qHdZrNVGj9+/LgaNGhgQUfuzel0KjIyUrt371ZkZKTV7UDS7373Ow0ePFhPPvmkTp48qS5dusjb21sFBQWaM2eO/uu//svqFt3KypUr9eijj0qSPv74Yx08eFDffvut3n77bU2dOlVff/21xR26H74krd0OHDig77//Xnfffbf8/Pwu++8+qldSUpLmz58vSdqwYYNSUlKUnJysTz75ROPHj9f7779vcYdXR4iqYffff7/x52HDhrls8/b2VvPmzTV79uwa7gqDBw+WJNlsNg0fPtxl1ezy8nLt2LFD3bp1s6o9t+Xh4aHIyEgdP36cEFVLbNu2TXPnzpX0ywf40NBQbd++Xe+9956ee+45QlQNKygoUFhYmCTpH//4hx544AHdfPPNGjFihF599VWLu3MvfElaux0/flwPPvigPv/8c9lsNn333Xdq2bKl/vCHP6hRo0Z89qphubm5uummmyRJq1at0u9//3uNGjVK3bt3V8+ePa1t7hoRompYRUWFJKlFixbaunWrgoKCLO4Ikox/7JxOp/z9/eXn52ds8/HxUdeuXTVy5Eir2nNrL7/8sp5++mnNnz9fbdu2tbodt3f27Fn5+/tLktLT0zV48GB5eHioa9eudeYSjN+S0NBQ7dmzR02aNFFaWppee+01Sb+8T56enhZ3517Of0lqs9n4krQWGj9+vLy8vJSTk6PWrVsb4w8++KDGjx/Pe1PDGjZsqOPHj6tp06ZKT0/X+PHjJUn16tWrM5fwE6IsUFZWpubNm+v48eOEqFrirbfektPplNPp1Lx584wPibDeo48+qrNnz6p9+/by8fFxCbiSLnkPG6rPTTfdpFWrVuk//uM/tHr1auMfvvz8fAUEBFjcnft5/PHHNWTIEDVp0kQ2m019+/aVJG3atEm33HKLxd25lwu/JN2yZYuCg4Mt7ggXSk9P1+rVq3XDDTe4jEdGRvIFkAX69u2rP/zhD+rQoYP279+vQYMGSZJ2795dZ87YEqIs4O3trV27dnENbi3jdDq1YsUKTZ06lRBViyQnJ1vdAi7w3HPPaejQoRo/frx69+6t6OhoSb98QOnQoYPF3bmfxMRERUVFKScnRw888IBxKbKnp6cmT55scXfu6eDBg8afz507p3r16lnYDc4rKipS/fr1K40XFBS4XMKPmvGXv/xFzzzzjHJzc/Xee+8ZJxWysrL08MMPW9zdtbE5nU6n1U24o4SEBHl7e+t//ud/rG4FF7j11lu1aNEide3a1epWgForLy9PR44cUfv27eXh8cskr5s3b1ZAQABnP2pQWVmZ+vXrpwULFujmm2+2uh38n4qKCs2YMUOvv/66jh49qv3796tly5Z69tln1bx5c40YMcLqFt3SoEGDdPvtt+uFF16Qv7+/duzYoWbNmumhhx5SRUWFVq5caXWLqGOY4twipaWlmj9/vjp27KjRo0drwoQJLg9Y4/z9N7t27bK6FVzg+++/1zPPPKOHH35Y+fn5kqS0tDTt3r3b4s7cz2effaawsDB16NDBCFCS1LlzZ61du9bCztwPVzXUTi+++KIWL16sl19+WT4+PsZ4VFSU3nzzTQs7c2+zZs3SggULNHDgQJWWlmrSpElq27atvvzyS7300ktWt+eWvvrqKz366KPq1q2bMXPl0qVLlZmZaXFn14YQZZFdu3bp9ttvV0BAgPbv36/t27cbj+zsbKvbc1uPPvqoNm/erPbt28vPz0+BgYEuD9S8jIwMRUVFadOmTXr//fd15swZSdKOHTs0bdo0i7tzP//5n/+pLVu2VBpPTk7Wf//3f1vQkXt77LHHjHWiUDu8/fbbeuONN/TII4+4TO7Rrl07ffvttxZ25t7atGmjHTt2qHPnzurbt6+Kioo0ePBgbd++XTfeeKPV7bmd9957T/3795efn5+2bdumkpISSdLp06eVlJRkcXfXhnuiLPLFF19Y3QIugftvap/JkyfrxRdf1IQJE1zuVevVq5f+93//18LO3NPcuXN17733KiMjQ23atJEkvfLKK3rhhRdcFk5EzSgtLdWbb76pNWvWqFOnTpXWs5szZ45Fnbmvn376yZi6+UIVFRUqKyuzoCOcFxYWpunTp1vdBvTLGdvXX39djz32mFJTU43xbt266fnnn7ews2tHiAIucPG0tLDezp07tWLFikrj1113nY4fP25BR+7t8ccf1/Hjx9WvXz9lZmbqb3/7m5KSkvTPf/6TtdQscP6qBknav3+/yzYu87PGrbfeqq+++krNmjVzGX/33XeZfMVi586d044dO5Sfn2/MpnhebGysRV25p3379unuu++uNB4QEKCTJ0/WfEO/AiGqBg0ePFiLFy9WQECAsbjr5dSFlZp/K06dOmVMzXzq1Kkr1jKFc81r1KiRjhw5ohYtWriMb9++Xddff71FXbm3iRMn6vjx4+rUqZPKy8uVnp6uLl26WN2WW+Kqhtpn2rRpiouL008//aSKigq9//772rdvn95++2198sknVrfnttLS0vTYY4+poKCg0jabzaby8nILunJfTZo00YEDBypNZ56ZmamWLVta05RJhKgaZLfbjW8GL1zJHNZq3Lixjhw5opCQEDVq1OiS3946nU7+krXI0KFD9ec//1nvvvuubDabKioq9PXXX2vixIl67LHHrG7PLbz66quVxpo0aaL69evr7rvv1qZNm7Rp0yZJUnx8fE23B0kHDhzQ999/r7vvvlt+fn7G31moeffdd59xhtZms+m5557T7bffro8//thYxws1709/+pMeeOABPffccwoNDbW6Hbc3evRoPfXUU/rrX/8qm82mw4cPa8OGDZo4caKee+45q9u7JkxxDreXkZGh7t27y8vLSxkZGVes7dGjRw11hfPKyso0fPhwpaamyul0ysvLS+Xl5Ro6dKgWL17scuM2qsfFZwEvx2az6YcffqjmbnCh48ePa8iQIfriiy9ks9n03XffqWXLlhoxYoQaNWqk2bNnW90iUCsEBAQwiUQtM3XqVM2dO1fnzp2TJPn6+mrixIl64YUXLO7s2hCiANQJ33//vbZv366Kigp16NBBkZGRVrcEWO6xxx5Tfn6+3nzzTbVu3VrffPONWrZsqfT0dI0fP55lAID/88QTT6h79+6s01XLnD17Vnv27FFFRYXatGmjhg0bWt3SNSNEWeTo0aOaOHGiPvvsM+Xn5+vit4HLxqxz8uRJbd68+ZI3nnL5WM378ssvdcsttygkJMRlvKysTBs2bLjkjamAuwgLC9Pq1avVvn17+fv7GyHq4MGDioqKMpYEQPVq3LjxNV8+eeLEiWruBpdy9uxZPfDAA7ruuusUFRUlb29vl+1cimydQ4cOyWaz1bn7nLknyiLDhw9XTk6Onn32WTVp0oRr12uJjz/+WI888oiKiork7+/v8r7YbDZClAV69uyp0NBQvf/++4qOjjbGT5w4oV69evGFQw37/e9/r06dOmny5Mku47NmzdLmzZv17rvvWtSZeyoqKlL9+vUrjRcUFMjX19eCjtwTy2PUfitWrNDq1avl5+endevWVfr3nRBVsyoqKvTiiy9q9uzZxpc9/v7+SkhI0NSpU10Wc6+tOBNlEX9/f3311Ve67bbbrG4FF7j55pt17733Kikp6ZIfTFDzPDw89NRTT2nBggV67bXXNHz4cEm/nM1t0qRJpbOFqF7XXXedPv/8c0VFRbmM79y5U3369NHRo0ct6sw9DRo0SLfffrteeOEF+fv7a8eOHWrWrJkeeughVVRUaOXKlVa3CNQKYWFhio+P1+TJk+vEB/TfuilTpmjRokWaPn26unfvLqfTqa+//lqJiYkaOXKkZsyYYXWLV8WZKItERERUuoQP1vvpp58UHx9PgKpFbDabpkyZorvuukvDhg3Tjh07jJvlOYNb886cOSMfH59K497e3lddIgBVb9asWerZs6e2bt2q0tJSTZo0Sbt379aJEyf09ddfW92e2zDz3z5LZVijtLRUDz74IAGqlliyZInefPNNl/W52rdvr+uvv15jxoypEyGK/5IskpycrMmTJ+tf//qX1a3gAv3799fWrVutbgMXOP9lw+DBg/Xll19q5cqVGjhwYJ1ZjO+3pm3btvrb3/5WaTw1NVVt2rSxoCP31qZNG+3YsUOdO3dW3759VVRUpMGDBzMLWQ1r1KiRGjdufMXH+RpYY9iwYZf8uwvWOHHihG655ZZK47fcckuduW+QM1E16OIbT4uKinTjjTeqfv36lW5wrCv/Af0WfPTRR8afBw0apKefflp79uy55I2nrGhurQ4dOmjz5s26//771bt3b6vbcUvPPvus/vM//1Pff/+97rnnHknSZ599pnfeeYf7oSwSFham6dOnW92GW2PR49qvvLxcL7/8slavXq127dpV+vd9zpw5FnXmntq3b6+UlJRK6xCmpKSoffv2FnVlDvdE1aAlS5Zcc+2wYcOqsRNc6FpP7bPYrjUef/xxvfrqq/L39zfGSkpKNGrUKH355Zc6ePCghd25p08//VRJSUnKzs6Wn5+f2rVrp2nTprGOmgXS0tLUsGFD3XnnnZKkv/zlL1q4cKHatGmjv/zlL5z5AP5Pr169LrvNZrPp888/r8FukJGRoUGDBqlp06aKjo6WzWbT+vXrlZubq3/84x+66667rG7xqghRAADUUVFRUXrppZd07733aufOnerUqZMSEhL0+eefq3Xr1nrrrbesbtFtnT17Vjk5OSotLXUZb9eunUUdAbXL4cOH9Ze//EXffvutnE6n2rRpozFjxig8PNzq1q4JIcoi27Ztk7e3tzHD1Ycffqi33npLbdq0UWJi4iVv3Eb12bRpk06cOKGBAwcaY2+//bamTZumoqIi3X///Zo3bx5TBlugZcuW6tGjh15//XWX339BQYE6d+6sH374wcLu3FdWVpb27t0rm82mNm3aqEOHDla35JYaNmyoXbt2qXnz5kpMTNSuXbu0cuVKbdu2Tffee6/y8vKsbtHtHDt2TI8//rj++c9/XnI7VzQAvw3cE2WR0aNHa/LkyYqKitIPP/ygBx98UIMHD9a7776rs2fPsuZEDZs2bZp69eplhKidO3dqxIgRGj58uFq3bq1Zs2YpPDxciYmJ1jbqhv71r3/Jy8tLd911lz788EM1adJE0i8fRJiYpebl5+froYce0rp169SoUSM5nU45HA716tVLqampuu6666xu0a34+Pjo7NmzkqS1a9caa9kFBgYyW6JFxo0bp8LCQm3cuFG9evXSBx98oKNHjxpr4sAavXr1uuKMrlzOV/NOnjypzZs3Kz8/v9JyJXVhXU5ClEX2799vrBH17rvvqkePHlqxYoW+/vprPfTQQ4SoGvbNN9/oxRdfNJ6npqaqS5cuWrhwoaRfpqSfNm0aIcoCNptNaWlpmjhxojp16qRVq1bpjjvuMLahZo0dO1anTp3S7t271bp1a0nSnj17NGzYMMXHx+udd96xuEP3cuedd2rChAnq3r27Nm/ebMw+tn//ft1www0Wd+eePv/8c3344Ye644475OHhoWbNmqlv374KCAjQzJkzNWjQIKtbdEsXr8tZVlam7Oxs7dq1i/vQLfDxxx/rkUceUVFRkfz9/SstfkyIwmU5nU4jda9du1YxMTGSfvmwXlBQYGVrbqmwsFChoaHG84yMDA0YMMB4fscddyg3N9eK1tye0+lUw4YN9f7772vKlCnq0aOH3njjDfXt29fq1txSWlqa1q5dawQoScYkBv369bOwM/eUkpKiMWPGaOXKlZo/f76uv/56SdI///lPl7/DUHOKiooUEhIi6ZczgseOHdPNN9+sqKgobdu2zeLu3NfcuXMvOZ6YmKgzZ87UcDdISEjQE088oaSkpDq7NichyiKdOnXSiy++qD59+igjI0Pz58+XJB08eNDlwzxqRmhoqA4ePKiIiAiVlpZq27ZtLlMGnz59utJ0qKgZF347NXPmTN16660aOXKkHn74YQu7cl8VFRWX/H/B29u70uUYqH5NmzbVJ598Umn8ch8YUf1atWqlffv2qXnz5rrtttu0YMECNW/eXK+//rpxOTJqj0cffVSdO3fWK6+8YnUrbuWnn35SfHx8nQ1QEiHKMsnJyXrkkUe0atUqTZ06VTfddJMkaeXKlerWrZvF3bmfAQMGaPLkyXrppZe0atUq1a9f32V6zR07drBwpUUunvvm0Ucf1Y033qj/+I//sKgj93bPPffoqaee0jvvvGPMoPTTTz9p/PjxrN1lgZycnCtub9q0aQ11ggMHDuimm27SuHHjdOTIEUm/3G/bv39/LV++XD4+Plq8eLG1TaKSDRs2qF69ela34Xb69++vrVu3qmXLlla38qsxO18tc+7cOXl6enLWo4YdO3ZMgwcP1tdff62GDRtqyZIlLh/Se/fura5du2rGjBkWdokLHT16VN9++y1rE9Ww3Nxc/e53v9OuXbsUEREhm82mH3/8Ue3atdOHH37IfTg1zMPD44r3BjITXM3x8PDQ9ddfr169ehmP5s2b6+zZs/r222/VtGlTBQcHW92m2xo8eLDLc6fTqSNHjmjr1q169tlnNW3aNIs6cx8fffSR8edjx47p+eef1+OPP66oqKhKn3tjY2Nruj3TCFG1wJgxY/T888/zl2st4HA41LBhQ3l6erqMnzhxQg0bNmTqeeD/rFmzxljb49Zbb+UslEW++eYbl+dlZWXavn275syZoxkzZlT64Ijq89VXXykjI0Pr1q3Thg0bdO7cOTVt2lT33HOPEarO37OGmvf444+7PPfw8NB1112ne+65h/s5a4iHh8c11dlstjrxBRAhqhYICAhQdnZ2nT6lCVSnlStX6u9///slF67kRu2acam11JYsWaJp06bp7NmzrKVWy3z66aeaNWuW1q1bZ3UrbqmsrEwbNmzQunXrtG7dOm3cuFElJSW66aabtG/fPqvbcxuvvvqqRo0apXr16iknJ0c33HDDNX+QB66G/5JqAXIscHmvvvqqHn/8cYWEhGj79u3q3LmzgoKC9MMPP7h8oEf1SkxM1I4dO4znO3fu1MiRI9W3b19NnjxZH3/8sWbOnGlhh7jQzTffrC1btljdhtvy9vbW3XffraefflpTpkzRmDFj1LBhQx04cMDq1tzKhAkTjPXSWrRowezHtcCmTZsqLUT99ttvq0WLFgoJCdGoUaNUUlJiUXfmEKJq2BNPPKHTp09b3QZQZ7z22mt64403lJKSIh8fH02aNElr1qxRfHy8HA6H1e25jezsbJdL9lJTU9W5c2ctXLhQEyZM0Kuvvqq///3vFnbonk6dOuXycDgc+vbbb/Xss88qMjLS6vbczrlz5/T555/r2Wef1V133aXGjRsrPj5eZ86c0fz58686EQiqVnh4uN577z39+OOPcjqdOnTokHJyci75QM2YNm1apS/kRowYoT59+tS5L+S4nK+GeXp66siRI8YaEgCurH79+tq7d6+aNWumkJAQrVmzRu3bt9d3332nrl276vjx41a36Bbq1aun7777ThEREZJ+WeR1wIABeuaZZyRJ//rXvxQVFcWXRDXsUhNLOJ1ORUREKDU1VdHR0RZ15n569OihLVu26MYbb9Tdd9+tHj16qEePHixbYqE33nhDY8eO1c8//3zZGqfTWWfuwfktaNKkiT7++GN16tRJkjR16lRlZGQoMzNTkvTuu+9q2rRp2rNnj5VtXhOmOK9hZFbAnLCwMB0/flzNmjVTs2bNtHHjRrVv314HDx7k/6caxFpqtdMXX3zh8vz8zfI33XSTvLz4J74mrV+/Xk2aNFGvXr3Us2dP3X333UwYZbFRo0bp4YcfNmYQXbt2rYKCgqxuy60VFha6fLGQkZHhsjD4HXfcodzcXCtaM42/YS1wpeloAbi655579PHHH+v222/XiBEjNH78eK1cuVJbt25l5rEaxFpqtRNT/NceJ0+e1FdffaV169bppZde0sMPP6ybb75ZPXr0UM+ePdWjRw9dd911Vrfpdvz9/dW6dWv99a9/VevWrVnw2GK/pS/kuJyvhnl4eMhut181SJ04caKGOgJqt4qKClVUVBjfqv/9739XZmambrrpJj355JNMO19DWEut9vr++++VnJysvXv3ymazqXXr1nrqqacItRY7ffq0MjMz9cUXX2jdunX65ptvFBkZqV27dlndmluqV6+e9u7dqxYtWljdilsbPXq0du7caXwht2TJEh0+fNj4t3z58uVKTk6uExPjcCbKAtOnT5fdbre6DaBO8PDwcJmSdsiQIRoyZIiFHbmn6667Tl999dVl11J799131bBhQ4u6c1+rV69WbGysbrvtNnXv3l1Op1Pr16/Xrbfeqo8//lh9+/a1ukW31aBBAwUGBiowMFCNGzeWl5eX9u7da3VbbisqKko//PADIcpiL774ogYPHqwePXoYX8hd+GXoX//61zqzbhdnomqYh4eH8vLymFgCuIILZ+65mnbt2lVjJ0Dt1qFDB/Xv31//8z//4zI+efJkpaens45aDaqoqNDWrVu1bt06ffHFF/r6669VVFSk66+/3lhst1evXmrWrJnVrbql9PR0/fnPf9YLL7ygjh07qkGDBi7bAwICLOrMPV3uC7kTJ06oYcOGdeIqE0JUDWN2PuDqzs84drW/nphRCe6uXr162rlzZ6XpzPfv36927drp3LlzFnXmfgICAlRUVKQmTZqoZ8+e6tmzp3r16sVllbXEhVc0XHhLBbPz4dficr4aRmYFru7gwYNWtwDUCdddd52ys7Mrhajs7Gy+rKths2bNUq9evXTzzTdb3Qou4eKZLIF/FyGqhlVUVFjdAlDrXXi5y/Hjx40paXNzc7Vw4UIVFxcrNjbWZXY4wB2NHDlSo0aN0g8//KBu3brJZrMpMzNTL730khISEqxuz62MHj3a6hZwBcxkiarG5XwAaqWdO3fqvvvuU25uriIjI5WamqoBAwaoqKhIHh4eKioq0sqVK3X//fdb3SpgGafTqeTkZM2ePVuHDx+WJIWHh+vpp59WfHw8S2oAF/jqq6+0YMEC/fDDD3r33Xd1/fXXa+nSpWrRooXuvPNOq9tDHeNx9RIAqHmTJk1SVFSUMjIy1LNnT8XExOjee++Vw+FQYWGhRo8eXelmesCd/Pzzz3r77bf18MMP69ChQ3I4HHI4HDp06JCeeuopAhRwgffee0/9+/eXn5+ftm3bppKSEkm/TEWflJRkcXeoizgTBaBWCg4O1ueff6527drpzJkzCggI0ObNm9WpUydJ0rfffquuXbvq5MmT1jYKWKh+/frau3cvM74BV9GhQweNHz9ejz32mPz9/fXNN9+oZcuWys7O1oABA5SXl2d1i6hjOBMFoFY6ceKEwsLCJEkNGzY01lw5r3Hjxjp9+rRV7QG1QpcuXbR9+3ar2wBqvX379unuu++uNB4QEMCXcfhVmFgCQK118eVIXJ4EuBozZowSEhJ06NChS659wzpqwC+aNGmiAwcOqHnz5i7jmZmZatmypTVNoU4jRAGotYYPHy5fX19J0rlz5/Tkk08aHxLPX88OuKMnnnhCycnJevDBByVJ8fHxxrbza6yx9g3w/40ePVpPPfWU/vrXv8pms+nw4cPasGGDJk6cqOeee87q9lAHcU8UgFrp8ccfv6a6t956q5o7AWqf8wu3FxcXX7GOe6WA/++ZZ57RnDlzjEWofX19NXHiRL3wwgsWd4a6iBAFAEAd4+Hhoby8PBbUBa7i7Nmzevrpp7Vq1SqVlZWpV69exhpqbdq0UcOGDS3uEHUVl/MBAFAHcY8gcHXTpk3T4sWL9cgjj8jPz08rVqxQRUWF3n33XatbQx3HmSgAAOoYDw8P2e32qwapEydO1FBHQO104403asaMGXrooYckSZs3b1b37t117tw5eXp6Wtwd6jLORAEAUAdNnz5ddrvd6jaAWi03N1d33XWX8bxz587y8vLS4cOHFRERYWFnqOsIUQAA1EEPPfQQ90QBV1FeXi4fHx+XMS8vL/38888WdYTfCkIUAAB1DPdDAdfG6XS6LJchVV4yQ5Lef/99K9pDHUaIAgCgjuF2ZuDaDBs2rNLYo48+akEn+K1hYgkAAAAAMMHD6gYAAAAAoC4hRAEAAACACYQoAAAAADCBEAUAAAAAJhCiAAAAAMAEQhQAAAAAmECIAgAAAAAT/h840OcvczCowwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# we convert Category to string\n",
    "# we made a variable called column_data\n",
    "# \"bins\" is used for distance between bars\n",
    "data['Category'] = data['Category'].astype(str)\n",
    "column_data = data['Category']\n",
    "plt.figure(figsize=(10,5))\n",
    "plt.hist(column_data,bins=30,edgecolor='Black')\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd6bfdbd",
   "metadata": {},
   "source": [
    "From above graph you can see that most of the buyers are T-shirt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 493,
   "id": "dd1086a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# checking B2B Data using pie chart\n",
    "B2B_Check = data['B2B'].value_counts()\n",
    "\n",
    "# plot the pie chart\n",
    "plt.pie(B2B_Check, labels=B2B_Check.index, autopct='%1.1f%%')\n",
    "# plt.axis('equal')\n",
    "plt.show()\n",
    "\n",
    "# plt is used for matplotlib\n",
    "# .index - to get label name displayed"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1f590bf",
   "metadata": {},
   "source": [
    "From the above chart we can see that, maximum i.e 99.2% buyers are retailers and 0.8% are B2B buyers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 496,
   "id": "fc6d8722",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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4ceOGroyjoyMWL16MLVu2oHv37hg+fLjR283NzYVWq9WbTOFI+s0SR3oeJwBkax7gSPpNk2zPGv1p4nJERETGsprg07dvXwwePBh+fn548cUXsX170VGAxMREvXJr1qyBs7MzUlNTodFojN5ubGws1Gq1bvLw8DB6nQBw/U7Zoacq5YiIiMh4VhN8inNxcYGfnx/OnTunm7dhwwZs27YNBw4cgFqtRkREhNHbiYqKgkaj0U2ZmZlGrxMA6rs6mrQcERERGc9qg09ubi7S0tLQsGHRnU/Xrl1DWFgY5s6dC39/fyQkJGDdunXYuXOnUdtRKpVwc3PTm0yhs1dtNFQ7QlHGcgWK7u7q7FXbJNuzRoZefWWdV2kREVFNZDXBZ9q0adi3bx/S09Nx+PBhvPbaa9BqtRg1ahQAYNy4cWjZsqXuWT4dO3bEjBkz8M4775Q45ZWamoqUlBS9ydxsbRSIGeALACXCz6PXMQN8YWtTVjR68v1q4K3qhpYjIiIyltUEnytXrmDo0KFo2bIlXn31VTg4OOC3335Ds2bNsHbtWvz4449ISEiAjc1/qxwTE4NatWqVOOXVrVs3+Pv7602W0OfZhlg+vD3c1fqns9zVjlg+vL0Uz/Gp6Dk9fI4PERGZk0IIUXPvp64CrVYLtVoNjUZjstNeBYUCR9Jv4vqdB6jvWnR6qyYf6SlNUOR2vbu3GoNHeoiIyHQM/f5m8CmmOoIPERERVS9Dv7+t5lQXERERUXVj8CEiIiJpMPgQERGRNBh8iIiISBoMPkRERCQNBh8iIiKSBoMPERERSYPBh4iIiKTB4ENERETSYPAhIiIiaTD4EBERkTQYfIiIiEgaDD5EREQkDQYfIiIikgaDDxEREUmDwYeIiIikweBDRERE0mDwISIiImkw+BAREZE0GHyIiIhIGgw+REREJA07S1eAiIhqPs/I7SXmZczvb4GaWI7sfbDl0CVM2XpK93rxwGfxSkAzs9fDokd8QkNDoVAoSkznz5+3ZLWIiMiESvvCL29+TSR7H3hGbtcLPQAwZespi7Tf4qe6+vTpg+zsbL3Jy8tLr0xeXp6FakdERMao6ItNhi9+2fvA2tpv8eCjVCrh7u6uN/Xs2ROTJk3C1KlTUbduXfTq1QsAcObMGfTr1w8qlQoNGjTAiBEj8Pfff+vWJYTAggUL0Lx5czg5OaFt27b49ttvLdU0IiKpGfqFVpO/+GXvgy2HLpm0nClYPPiUJTExEXZ2dvj111+xcuVKZGdnIzg4GO3atcPRo0exa9cuXLt2Da+//rruPbNmzUJ8fDyWL1+O06dPIyIiAsOHD8e+ffvK3E5ubi60Wq3eRERERMYrfnrL2HKmYPGLm7///nuoVCrd6759+wIAvL29sWDBAt386OhotG/fHvPmzdPNi4uLg4eHB/744w80btwYn376KX7++WcEBAQAAJo3b44DBw5g5cqVCA4OLnX7sbGxmDNnTnU0jYiIiKyMxYNPjx49sHz5ct1rFxcXDB06FB07dtQrd+zYMezdu1cvJD1y4cIFaDQaPHjwQHda7JG8vDz4+/uXuf2oqChMnTpV91qr1cLDw6OqzSEiIiIrZvHg4+LiAm9v71LnP66wsBADBgzAxx9/XKJsw4YNcepU0WGy7du3o3HjxnrLlUplmdtXKpXlLiciIqKqWTzwWYNOYy0e+KwZalPEaq/xKa59+/Y4ffo0PD094e3trTe5uLjA19cXSqUSly9fLrGcR3CIiMzP0GfU1ORn2cjeB4Y+p8ecz/N5YoJPWFgYbt68iaFDh+LIkSO4ePEifvjhB4wZMwYFBQVwdXXFtGnTEBERgcTERFy4cAHHjx/HsmXLkJiYaOnqExFJqaIv9Jr6hf842fvA2tr/xASfRo0a4ddff0VBQQFCQkLw7LPPYvLkyVCr1bCxKWrGhx9+iOjoaMTGxqJ169YICQnBd999V+K5QEREZD5lfbHV9C/8x8neBxnz+5c4nbV44LMWab9CCCHMvlUrptVqoVarodFo4ObmZunqEBERkQEM/f5+Yo74EBERERmLwYeIiIikweBDRERE0mDwISIiImkw+BAREZE0GHyIiIhIGgw+REREJA0GHyIiIpIGgw8RERFJg8GHiIiIpMHgQ0RERNJg8CEiIiJpMPgQERGRNBh8iIiISBoMPkRERCQNBh8iIiKSBoMPERERSYPBh4iIiKTB4ENERETSYPAhIiIiaTD4EBERkTQYfIiIiEgadpaugKEKCgrQtWtXNGzYEBs3btTN12g0ePbZZzFq1CiMHTsWXl5eOH78ONq1a2e5yhbjGbm9xLyM+f0tUBPLkb0PZG8/AHz9y3nM3HFW93pev5Z4s5u3BWtkXtwHiKzDE3PEx9bWFomJidi1axe++uor3fzw8HDUrl0b0dHRFqxd2Uob7MqbXxPJ3geytx8oauvjoQcAZu44K00fcB8gsh5PTPABgKeffhqxsbEIDw9HVlYWtm7divXr1yMxMREODg6Wrl4JFQ1qMgx6sveB7O0H2Aeyt5/I2jxRwQcoOsLTtm1bjBw5Eu+88w6io6Ot6rTWI4YOZjV50JO9D2RvP1B0esuU5Z403AeIrM8TF3wUCgWWL1+OPXv2oEGDBoiMjDRqfbm5udBqtXoTEZlG8dNbxpYjIjLWExd8ACAuLg7Ozs5IT0/HlStXjFpXbGws1Gq1bvLw8DBRLYmIiMjaPHHB59ChQ1i0aBG2bt2KgIAAvPXWWxBCVHl9UVFR0Gg0uikzM9OEtSUiIiJr8kQFn/v372PUqFEYN24cXnzxRaxevRrJyclYuXJlldepVCrh5uamNxGRaczr19Kk5YiIjPVEBZ/IyEgUFhbi448/BgA0bdoUCxcuxPTp05GRkaErd/bsWaSkpOhNeXl5Zq2roc/nqMnP8ZC9D2RvPwCDn9NTU5/nw32AyPoohDHnicxo37596NmzJ5KSktClSxe9ZSEhIXj48CFWr16N5s2bl/r+9PR0eHp6VrgdrVYLtVoNjUZjkqM/5d2tIctgJ3sfyN5+gH0ge/uJzMHQ7+8nJviYi6mDD8AntgLsA9nbD/DJzdwHiKoXg08VVUfwISIioupl6Pf3E3WNDxEREZExGHyIiIhIGgw+REREJA0GHyIiIpIGgw8RERFJg8GHiIiIpMHgQ0RERNJg8CEiIiJpMPgQERGRNBh8iIiISBoMPkRERCQNBh8iIiKSBoMPERERSYPBh4iIiKTB4ENERETSYPAhIiIiaTD4EBERkTQYfIiIiEgaDD5EREQkDQYfIiIikgaDDxEREUnDztIVkIFn5PYS8zLm97dATSxH9j6Qvf0AsCv5T4zfmKJ7vWJwO/Tp1NhyFTIz7gNE1uGJP+ITGhoKhUKB8ePHl1g2ceJEKBQKhIaGmr9i/19pg11582si2ftA9vYDRW19PPQAwPiNKdL0AfcBIuvxxAcfAPDw8MD69etx//593bwHDx7g//7v/9C0aVOL1auiQU2GQU/2PpC9/QD7QPb2E1mbGhF82rdvj6ZNm2LTpk26eZs2bYKHhwf8/f0tUidDB7OaPOjJ3geytx8oOr1lynJPGu4DRNanRgQfABg9ejTi4+N1r+Pi4jBmzJgK35ebmwutVqs3EZFpFD+9ZWw5IiJj1ZjgM2LECBw4cAAZGRm4dOkSfv31VwwfPrzC98XGxkKtVusmDw8PM9SWiIiILKHG3NVVt25d9O/fH4mJiRBCoH///qhbt26F74uKisLUqVN1r7VaLcMPERFRDVVjgg8AjBkzBpMmTQIALFu2zKD3KJVKKJXK6qwWkbRWDG5n0GmsFYPbVXtdiIiAGnSqCwD69OmDvLw85OXlISQkxKJ1MfT5HDX5OR6y94Hs7Qdg8HN6aurzfLgPEFmfGhV8bG1tkZaWhrS0NNja2lq6OhUOZjIMdrL3geztB9gHsrefyNrUqOADAG5ubnBzc7N0NXTKGtRkGuxk7wPZ2w8UtbX46awVg9tJ0wfcB4ish0IIISxdCWui1WqhVquh0WisKkARERFR2Qz9/q5xR3yIiIiIysLgQ0RERNJg8CEiIiJpMPgQERGRNBh8iIiISBoMPkRERCQNBh8iIiKSBoMPERERSYPBh4iIiKTB4ENERETSYPAhIiIiaTD4EBERkTQYfIiIiEgaDD5EREQkDQYfIiIikkaVg8/+/fsxfPhwBAQE4M8//wQArFu3DgcOHDBZ5YiIiIhMqUrBZ+PGjQgJCYGTkxOOHz+O3NxcAMCdO3cwb948k1aQiIiIyFSqFHzmzp2LFStWYNWqVbC3t9fNDwwMxO+//26yyhERERGZUpWCz9mzZ9GtW7cS893c3HD79m1j60RERERULaoUfBo2bIjz58+XmH/gwAE0b97c6EoRERERVYcqBZ9x48Zh8uTJOHz4MBQKBbKysvDVV19h2rRpmDhxoqnrSERERGQSdlV504wZM6DRaNCjRw88ePAA3bp1g1KpxLRp0zBp0iRT15GIiIjIJBRCCFHVN9+7dw9nzpxBYWEhfH19oVKpTFk3i9BqtVCr1dBoNHBzczPJOj0jt5eYlzG/v0nW/aSQvQ9kbz8A7DhyBRM3ndC9/vzVtujXuYkFa2Re3AeIqpeh399VOtW1du1apKWlwdnZGR07dkTnzp2hUqnw4MEDrF27ttLrKygoQGBgIAYPHqw3X6PRwMPDA7NmzcKOHTvg4OBQ4q6xTz75BHXr1sXVq1cBAKGhoXjllVeq0qxqUdpgV978mkj2PpC9/UBRWx8PPQAwcdMJafqA+wCR9ahS8AkNDUXnzp2xceNGvfkajQajR4+u9PpsbW2RmJiIXbt24auvvtLNDw8PR+3atREdHY1+/fph5MiRGDlypO65QWlpafjggw+wbNkyuLu7V6Up1aqiQU2GQU/2PpC9/QD7QPb2E1mbKj+5ec6cORgxYgRmz55tkoo8/fTTiI2NRXh4OLKysrB161asX78eiYmJcHBwAAAsWrQIOTk5iImJwcOHDzFy5EgMGDAA//jHP0xSB1MydDCryYOe7H0ge/uBotNbpiz3pOE+QGR9qnRxMwAMHz4cgYGBGDRoEE6dOoV169YZXZnw8HBs3rwZI0eORGpqKqKjo9GuXTvdcldXV8TFxSEkJATp6enIzMzEzp07jdpmbm6u7ggSUHSOkIhMo/jprfLKZUh0vQ8RWU6VjvgoFAoAwPPPP4/Dhw/j/PnzCAwMREZGhlGVUSgUWL58Ofbs2YMGDRogMjKyRJkXXngBr732Gr755ht89tlnqFu3rlHbjI2NhVqt1k0eHh5GrY+IiIisV5WCz+M3gjVt2hQHDx6Ep6cnevXqZXSF4uLi4OzsjPT0dFy5UvLwd1ZWFnbt2gVnZ2fs37/f6O1FRUVBo9HopszMTKPXSURERNapSsEnJiZG79Z1Z2dnbN68GREREaX+lIWhDh06hEWLFmHr1q0ICAjAW2+9heJ3248dOxZt27bFjh07sHz5cuzbt6/K2wMApVIJNzc3vYmITOPzV9uatBwRkbGqHHycnZ1LzJ8zZw727t1bpYrcv38fo0aNwrhx4/Diiy9i9erVSE5OxsqVK3VlVq9ejf379yM+Ph7BwcGYNGkSxowZg7t371Zpm9XJ0Odz1OTneMjeB7K3H4DBz+mpqc/z4T5AZH0MfoDhtm3b0LdvX9jb22Pbtm1lr1ChwIABAypdkcmTJ2P79u04ceIEXFxcAACrVq3C1KlTkZqaChsbG/j5+WHBggUYN24cgKIHKLZt2xZ9+vTB0qVLARTdan/p0iUsWrRIb/21a9dG06ZNK6yHqR9gWN7dGrIMdrL3geztB9gHsrefyBwM/f42OPjY2Njg6tWrqF+/Pmxsyj5QpFAoUFBQUKnK7tu3Dz179kRSUhK6dOmitywkJAQPHz4EANjZ2WH37t16yw8cOIDu3btjz549CA4ORmhoKBITE0tsY9SoUUhISKiwLnxyc/WQvQ9kbz/AJzdzHyCqXiYPPrKojuBDRERE1atafrLi8OHDJZ6bs3btWnh5eaF+/fp455139J6JQ0RERGRNKhV8Zs+ejZMnT+pep6am4q233sKLL76IyMhIfPfdd4iNjTV5JYmIiIhMoVLBJyUlBT179tS9Xr9+PZ577jndRcifffYZvvnmG5NXkoiIiMgUKhV8bt26hQYNGuhe79u3D3369NG97tSpEx8ASERERFarUsGnQYMGSE9PBwDk5eXh999/R0BAgG75nTt3YG9vb9oaEhEREZlIpYJPnz59EBkZif379yMqKgrOzs7o2rWrbvnJkyfRokULk1eSiIiIyBQq9evsc+fOxauvvorg4GCoVCokJibCwcFBtzwuLg69e/c2eSWJiIiITKFKz/HRaDRQqVSwtbXVm3/z5k2oVCq9MPSk4XN8iIiInjyGfn9X6ojPI2q1utT5tWvXrsrqiIiIiMyiSj9SSkRERPQkYvAhIiIiaTD4EBERkTQYfIiIiEgaDD5EREQkDQYfIiIikgaDDxEREUmDwYeIiIikweBDRERE0mDwISIiImkw+BAREZE0GHyIiIhIGgw+REREJA2rCj5//vknhg8fjjp16sDZ2Rnt2rXDsWPHAAA5OTlo0aIFpk6dqveejIwMuLm5YfXq1QCApKQkKBQK3L5929zVL1Pew0Ks2X8R0VtPYc3+i8h7WGjpKpmdZ+T2EhMREZG52Vm6Ao/cunULQUFB6NGjB3bu3In69evjwoULqFWrFgBApVIhPj4ePXv2xKBBg9C1a1cIITB69GgEBQVh7Nixlm1AGWJ3nMGq/ekoFP+d99GONLzd1QtR/XwtVzEzKivkeEZuR8b8/mauDRERycxqgs/HH38MDw8PxMfH6+Z5enrqlenWrRvCw8MxevRonDhxAqtWrUJKSgpOnTpl5toaJnbHGaz8Jb3E/EIB3fyaHn4qOrLD8ENEROZkNae6tm3bho4dO2LIkCGoX78+/P39sWrVqhLl5s2bB3t7ewwfPhwzZ87E0qVL0bhxYwvUuHx5Dwuxan/J0PO4VfvTa/RpL0NPZ/G0FxERmYvVBJ+LFy9i+fLlePrpp7F7926MHz8e7777LtauXatXztHREYsXL8aWLVvQvXt3DB8+3Kjt5ubmQqvV6k2msO5Qht7prdIUiqJyREREZB5WE3wKCwvRvn17zJs3D/7+/hg3bhzefvttLF++vETZNWvWwNnZGampqdBoNEZtNzY2Fmq1Wjd5eHgYtb5HLt28Z9JyREREZDyrCT4NGzaEr6/+9S6tW7fG5cuX9eZt2LAB27Ztw4EDB6BWqxEREWHUdqOioqDRaHRTZmamUet7pFltZ5OWIyIiIuNZTfAJCgrC2bNn9eb98ccfaNasme71tWvXEBYWhrlz58Lf3x8JCQlYt24ddu7cWeXtKpVKuLm56U2mMCLAEzaK8svYKIrKERERkXlYTfCJiIjAb7/9hnnz5uH8+fP4+uuv8cUXXyAsLExXZty4cWjZsqXuWT4dO3bEjBkz8M4775Q45ZWamoqUlBS9yZwc7Gzwdlevcsu83dULDnZW8xGYnKF3a/GuLiIiMheFEKKCS3DN5/vvv0dUVBTOnTsHLy8vTJ06FW+//TYAYO3atZgwYQJSUlLw9NNP696Tl5eHDh06oFOnToiLi0NSUhJ69OhR6voNaapWq4VarYZGozHJ0Z/SnuNjowCf4/P/MfQQEZEpGPr9bVXBxxqYOvgARbe2rzuUgUs376FZbWeMCPCs0Ud6SlNa+GHoISIiU2HwqaLqCD5ERERUvQz9/pbrsAMRERFJjcGHiIiIpMHgQ0RERNJg8CEiIiJpMPgQERGRNBh8iIiISBoMPkRERCQNBh8iIiKSBoMPERERSYPBh4iIiKTB4ENERETSYPAhIiIiaTD4EBERkTQYfIiIiEgaDD5EREQkDQYfIiIikgaDDxEREUmDwYeIiIikweBDRERE0mDwISIiImkw+BAREZE07CxdARl4Rm4vMS9jfn8L1MRyZO8D2dsPAHkPC7HuUAYu3byHZrWdMSLAEw528vzfi/sAkXV4IkadgoICBAYGYvDgwXrzNRoNPDw8MGvWLADAxo0b8dxzz0GtVsPV1RXPPPMM3nvvPUtUWae0wa68+TWR7H0ge/sBIHbHGbT6YCc+3J6GtYcu4cPtaWj1wU7E7jhj6aqZBfcBIuvxRAQfW1tbJCYmYteuXfjqq69088PDw1G7dm1ER0fjp59+whtvvIHXXnsNR44cwbFjx/DRRx8hLy/PYvWuaFCTYdCTvQ9kbz9QFHpW/pKOQqE/v1AAK39Jr/Hhh/sAkXVRCCFExcWsw2effYbZs2fj1KlTSE5OxpAhQ3DkyBG0a9cOU6ZMwYkTJ7B3716jtqHVaqFWq6HRaODm5lbl9VRmMKuph7tl7wPZ2w8Und5q9cHOEqHncTYK4D8f9q2Rp724DxCZj6Hf30/USBMeHo62bdti5MiReOeddxAdHY127doBANzd3XH69GmcOnWqUuvMzc2FVqvVm4jINNYdyig39ABFR37WHcowS32IiJ6o4KNQKLB8+XLs2bMHDRo0QGRkpG5ZeHg4OnXqBD8/P3h6euKNN95AXFwccnNzy11nbGws1Gq1bvLw8KjuZhBJ49LNeyYtR0RkrCcq+ABAXFwcnJ2dkZ6ejitXrujmu7i4YPv27Th//jxmzZoFlUqF9957D507d8a9e2UPqlFRUdBoNLopMzPTHM0gkkKz2s4mLUdEZKwnKvgcOnQIixYtwtatWxEQEIC33noLxS9RatGiBcaOHYvVq1fj999/x5kzZ7Bhw4Yy16lUKuHm5qY3EZFpjAjwhI2i/DI2iqJyRETm8MQEn/v372PUqFEYN24cXnzxRaxevRrJyclYuXJlme/x9PSEs7Mz7t69a8aaFjH0QsWafEGj7H0ge/sBwMHOBm939Sq3zNtdvWrkhc0A9wEia/TEjDaRkZEoLCzExx9/DABo2rQpFi5ciOnTpyMjIwOzZ8/GjBkzkJSUhPT0dBw/fhxjxoxBfn4+evXqZZE6VzSYyTDYyd4HsrcfAKL6+WJcN68SR35sFMC4bl6I6udrmYqZCfcBIuvyRNzOvm/fPvTs2RNJSUno0qWL3rKQkBA8fPgQs2bNwrJly3DkyBFcu3YNTz31FPz9/fHPf/6zxHvKY6rb2R/HJ7ayD2RvP8AnN3MfIKpehn5/PxHBx5yqI/gQERFR9aqRz/EhIiIiMgaDDxEREUmDwYeIiIikweBDRERE0mDwISIiImkw+BAREZE0GHyIiIhIGgw+REREJA0GHyIiIpIGgw8RERFJg8GHiIiIpMHgQ0RERNJg8CEiIiJpMPgQERGRNBh8iIiISBoMPkRERCQNBh8iIiKSBoMPERERSYPBh4iIiKTB4ENERETSYPAhIiIiaTD4EBERkTTsLF2B6hAaGorbt29jy5Ytlq4KAMAzcnuJeRnz+1ugJpYjex/I3n4A+ObARcz4Pk33esFLrfF6l+YWrJF5cR8gsg484lPNShvsyptfE8neB7K3Hyhq6+OhBwBmfJ8mTR9wHyCyHgw+1aiiQU2GQU/2PpC9/QD7QPb2E1kbBp9qYuhgVpMHPdn7QPb2A0Wnt0xZ7knDfYDI+kgffHJzc6HVavUmIjKN4qe3jC1HRGQs6YNPbGws1Gq1bvLw8LB0lYiIiKiaSB98oqKioNFodFNmZqalq0RERETVRPrgo1Qq4ebmpjcRkWkseKm1ScsRERmrxgYfjUaDlJQUveny5ctm276hz+eoyc/xkL0PZG8/AIOf01NTn+fDfYDI+tTY4JOUlAR/f3+9KTo62qx1qGgwk2Gwk70PZG8/wD6Qvf1E1kYhhBCWroQ10Wq1UKvV0Gg0JjvtxSe2sg9kbz/AJzdzHyCqXoZ+fzP4FFMdwYeIiIiql6Hf3zX2VBcRERFRcQw+REREJA0GHyIiIpIGgw8RERFJg8GHiIiIpMHgQ0RERNJg8CEiIiJpMPgQERGRNBh8iIiISBoMPkRERCQNBh8iIiKSBoMPERERSYPBh4iIiKTB4ENERETSYPAhIiIiaTD4EBERkTQYfIiIiEgaDD5EREQkDQYfIiIikgaDDxEREUmDwYeIiIikYWfpCsjAM3J7iXkZ8/tboCaWI3sfyN5+APj6l/OYueOs7vW8fi3xZjdvC9bIvLgPEFkHqznis3z5crRp0wZubm5wc3NDQEAAdu7cCQDIyclBixYtMHXqVL33ZGRkwM3NDatXrwYAJCUlQaFQ4Pbt2+aufplKG+zKm18Tyd4HsrcfKGrr46EHAGbuOCtNH3AfILIeVhN8mjRpgvnz5+Po0aM4evQoXnjhBQwcOBCnT5+GSqVCfHw8li5div379wMAhBAYPXo0goKCMHbsWAvXvnQVDWoyDHqy94Hs7QfYB7K3n8jaWE3wGTBgAPr16wcfHx/4+Pjgo48+gkqlwm+//QYA6NatG8LDwzF69GjcvXsXS5YsQUpKiu5oj7UxdDCryYOe7H0ge/uBotNbpiz3pOE+QGR9rCb4PK6goADr16/H3bt3ERAQoJs/b9482NvbY/jw4Zg5cyaWLl2Kxo0bG7Wt3NxcaLVavYmITKP46S1jyxERGcuqgk9qaipUKhWUSiXGjx+PzZs3w9fXV7fc0dERixcvxpYtW9C9e3cMHz7c6G3GxsZCrVbrJg8PD6PXSURERNbJqoJPy5YtkZKSgt9++w0TJkzAqFGjcObMGb0ya9asgbOzM1JTU6HRaIzeZlRUFDQajW7KzMw0ep1ERERknawq+Dg4OMDb2xsdO3ZEbGws2rZtiyVLluiWb9iwAdu2bcOBAwegVqsRERFh9DaVSqXuTrJHExGZxrx+LU1ajojIWFYVfIoTQiA3NxcAcO3aNYSFhWHu3Lnw9/dHQkIC1q1bp7vl3doY+nyOmvwcD9n7QPb2AzD4OT019Xk+3AeIrI/VBJ+ZM2di//79yMjIQGpqKv75z38iKSkJw4YNAwCMGzcOLVu21D3Lp2PHjpgxYwbeeeedEqe8UlNTkZKSojdZQkWDmQyDnex9IHv7AfaB7O0nsjYKIYSwdCUA4K233sKePXuQnZ0NtVqNNm3a4P3330evXr2wdu1aTJgwASkpKXj66ad178nLy0OHDh3QqVMnxMXFISkpCT169Ch1/YY2U6vVQq1WQ6PRmOy0F5/Yyj6Qvf0An9zMfYCoehn6/W01wcdaVEfwISIioupl6Pe31ZzqIiIiIqpuDD5EREQkDQYfIiIikgaDDxEREUmDwYeIiIikweBDRERE0mDwISIiImkw+BAREZE0GHyIiIhIGgw+REREJA0GHyIiIpIGgw8RERFJg8GHiIiIpMHgQ0RERNJg8CEiIiJpMPgQERGRNBh8iIiISBoMPkRERCQNBh8iIiKSBoMPERERSYPBh4iIiKTB4ENERETSsLN0BWTgGbm9xLyM+f0tUBPLkb0PZG8/ABz8z994M+Gw7vXXoc8hsFVdC9bIvLgPEFmHGnfE5/r16xg3bhyaNm0KpVIJd3d3hISE4NChQxapT2mDXXnzayLZ+0D29gNFbX089ADAmwmHpekD7gNE1qPGBZ/BgwfjxIkTSExMxB9//IFt27ahe/fuuHnzptnrUtGgJsOgJ3sfyN5+gH0ge/uJrI1CCCEsXQlTuX37Np566ikkJSUhODi4SuvQarVQq9XQaDRwc3Orcl0qM5jV1MPdsveB7O0HSp7eKktNPe3FfYDIfAz9/q5RR3xUKhVUKhW2bNmC3Nxcg96Tm5sLrVarNxGRaRgSeipTjojIWDUq+NjZ2SEhIQGJiYmoVasWgoKCMHPmTJw8ebLM98TGxkKtVusmDw8PM9aYiIiIzKlGBR+g6BqfrKwsbNu2DSEhIUhKSkL79u2RkJBQavmoqChoNBrdlJmZad4KExERkdnUuOADAI6OjujVqxeio6Nx8OBBhIaGIiYmptSySqUSbm5uehMRmcbXoc+ZtBwRkbFqZPApztfXF3fv3jXrNg29ULEmX9Aoex/I3n4ABl+wXBMvbAa4DxBZoxoVfG7cuIEXXngBX375JU6ePIn09HT8+9//xoIFCzBw4ECz16eiwUyGwU72PpC9/QD7QPb2E1mbGnU7e25uLmbPno0ffvgBFy5cQH5+Pjw8PDBkyBDMnDkTTk5OFa7DVLezP45PbGUfyN5+gE9u5j5AVL0M/f6uUcHHFKoj+BAREVH1kvI5PkRERETlYfAhIiIiaTD4EBERkTQYfIiIiEgaDD5EREQkDQYfIiIikgaDDxEREUmDwYeIiIikweBDRERE0rCzdAWszaMHWWu1WgvXhIiIiAz16Hu7oh+kYPAp5s6dOwAADw8PC9eEiIiIKuvOnTtQq9VlLudvdRVTWFiIrKwsuLq6QqFQmGy9Wq0WHh4eyMzMlPY3wGTvA9nbD7AP2H652w+wD6qz/UII3LlzB40aNYKNTdlX8vCITzE2NjZo0qRJta3fzc1Nyp39cbL3geztB9gHbL/c7QfYB9XV/vKO9DzCi5uJiIhIGgw+REREJA0GHzNRKpWIiYmBUqm0dFUsRvY+kL39APuA7Ze7/QD7wBraz4ubiYiISBo84kNERETSYPAhIiIiaTD4EBERkTQYfMwkISEBtWrVKrdMaGgoXnnlFbPUpzopFAps2bKlzOVJSUlQKBS4ffu22epkKhkZGVAoFEhJSbF0VWoUT09PLF682NLVIDMo/vdvyNj4pPriiy/g4eEBGxubGr9/VzTuWxMGnzIoFIpyp9DQUJNvc8mSJUhISDCobpbcwa5fv45x48ahadOmUCqVcHd3R0hICA4dOmTQ+wMDA5GdnV3hg6YsEQRDQ0P1Puc6deqgT58+OHnypFnrYW2M/cytlSX+zp8kK1asgKurKx4+fKibl5OTA3t7e3Tt2lWv7P79+6FQKPDHH39Ue71MPQY+/ndvb2+P5s2bY9q0abh7926V16nVajFp0iS8//77+PPPP/HOO++YrL6WUJPGAD65uQzZ2dm6f2/YsAHR0dE4e/asbp6Tk5PJt1lREMjLy4ODg4PJt1tZgwcPRn5+PhITE9G8eXNcu3YNe/bswc2bNw16v4ODA9zd3ctcXlBQYNKfC6msPn36ID4+HgBw9epVzJo1Cy+99BIuX75ssToZ6lHflfe49qow9jO3VpX9O8/Pz4e9vb3Z6meo6hobevTogZycHBw9ehTPP/88gKKA4+7ujuTkZNy7dw/Ozs4Aio7kNGrUCD4+Piavhzk8+rvPz8/H/v37MXbsWNy9exfLly+v1HqEECgoKMDly5eRn5+P/v37o2HDhtVUa/OpUWOAoArFx8cLtVpdYbmUlBTRvXt3oVKphKurq2jfvr1ITk7WW8euXbtEq1athIuLiwgJCRFZWVm6948aNUoMHDhQ9zo4OFiEhYWJiIgIUadOHdGtWzfRrFkzAUA3NWvWzMStLd+tW7cEAJGUlFRmGQBi1apV4pVXXhFOTk7C29tbbN26Vbd87969AoC4deuWEOK/ffPdd9+J1q1bC1tbWzFy5Ei9dgIQe/furebWlfwMhBDil19+EQDE9evXRXp6ugAgjh8/LoQQ4uHDh2LMmDHC09NTODo6Ch8fH7F48WK99xdvx+Of26hRo0pd/qitubm5Yvr06aJRo0bC2dlZdO7cWa8fSuu7ixcvmrRPDPnML126JF5++WXh4uIiXF1dxZAhQ8TVq1f1ymzdulV06NBBKJVKUadOHTFo0CDdsmbNmolFixbpXsfFxQk3Nzfxww8/CCGE+Pe//y2effZZ4ejoKGrXri169uwpcnJyTNrO4n/njz7rDRs2iODgYKFUKkVcXJwoKCgQc+bMEY0bNxYODg6ibdu2YufOnbr3Fd+/hRDi+PHjAoBIT08XQgiRkZEhXnrpJVGrVi3h7OwsfH19xfbt23XlT58+Lfr27StcXFxE/fr1xfDhw8Vff/2lW17a2CCEEDExMcLDw0M4ODiIhg0bivDwcKP7pVGjRiI2Nlb3esaMGSIsLEz4+vqKH3/8UTf/hRdeEMOGDRPr1q0THTp0ECqVSjRo0EAMHTpUXLt2rcz+KW183bZtm2jfvr1QKpXCy8tLzJ49W+Tn5wshRLWMgaX93Y8dO1a4u7uLwsJC8fHHHwsvLy/h6Ogo2rRpI/7973+XaM+uXbtEhw4dhL29vYiLiyvxN52enl7qdiZPniyCg4N1r4ODg8WkSZPE5MmTRa1atUT9+vXFypUrRU5OjggNDRUqlUo0b95c7NixQ289Fe0zxjDFuC+EEElJSaJTp07CwcFBuLu7i/fff1/3uQohKuzrmzdvijfffFPUrVtXODo6Cm9vbxEXF1fp9vBUlwkNGzYMTZo0QXJyMo4dO4bIyEi9/x3eu3cPn3zyCdatW4dffvkFly9fxrRp08pdZ2JiIuzs7PDrr79i5cqVSE5OBgDEx8cjOztb99pcVCoVVCoVtmzZgtzc3DLLzZkzB6+//jpOnjyJfv36YdiwYeX+z+DevXuIjY3F6tWrcfr0aXz22Wd4/fXX0adPH2RnZyM7OxuBgYHV0aRy5eTk4KuvvoK3tzfq1KlTYnlhYSGaNGmCb775BmfOnEF0dDRmzpyJb775RlfmUf2zs7Nx/vx5eHt7o1u3bgCKTm8+vnzy5MmoX78+WrVqBQAYPXo0fv31V6xfvx4nT57EkCFD0KdPH5w7d063/uJ9V79+fZP2QUWfuRACr7zyCm7evIl9+/bhxx9/xIULF/CPf/xDV2b79u149dVX0b9/fxw/fhx79uxBx44dS93eJ598gmnTpmH37t3o1asXsrOzMXToUIwZMwZpaWlISkrCq6++CmGmR5C9//77ePfdd5GWloaQkBAsWbIECxcuxCeffIKTJ08iJCQEL7/8st5nUpGwsDDk5ubil19+QWpqKj7++GOoVCoARftLcHAw2rVrh6NHj2LXrl24du0aXn/9db11FB8bvv32WyxatAgrV67EuXPnsGXLFvj5+Rnd/u7du2Pv3r2613v37kX37t0RHBysm5+Xl4dDhw6hR48eyMvLw4cffogTJ05gy5YtSE9Pr9Qpw927d2P48OF49913cebMGaxcuRIJCQn46KOPAMBsY6CTkxPy8/Mxa9YsxMfHY/ny5Th9+jQiIiIwfPhw7Nu3T6/8jBkzEBsbi7S0NPTu3Rs//fQTAODIkSPIzs6Gh4eHwdtOTExE3bp1ceTIEYSHh2PChAkYMmQIAgMD8fvvvyMkJAQjRozAvXv3ABi+z1SVKcb9P//8E/369UOnTp1w4sQJLF++HGvWrMHcuXN176+orz/44AOcOXMGO3fuRFpaGpYvX466detWvkGVjkoSMvSIj6urq0hISChzHQDE+fPndfOWLVsmGjRooHtd2hGfdu3alVgXALF582aD629q3377rXjqqaeEo6OjCAwMFFFRUeLEiRN69Zs1a5budU5OjlAoFLr/FZf2Pz4AIiUlRW87pf3vqLqNGjVK2NraChcXF+Hi4iIAiIYNG4pjx44JIUSJIz6lmThxohg8eHCJ+YWFhWLQoEGiQ4cO4t69eyWWb9y4USiVSrF//34hhBDnz58XCoVC/Pnnn3rlevbsKaKiooQQZfedqZX3mf/www/C1tZWXL58WVf+9OnTAoA4cuSIEEKIgIAAMWzYsDLX/+iIT2RkpGjYsKE4efKkbtmxY8cEAJGRkVFNrStS1hGf4kfwGjVqJD766CO9eZ06dRITJ04UQhh2xMfPz0/Mnj271Hp88MEHonfv3nrzMjMzBQBx9uxZIUTpY8PChQuFj4+PyMvLM7jNhvjiiy+Ei4uLyM/PF1qtVtjZ2Ylr166J9evXi8DAQCGEEPv27RMAxIULF0q8/8iRIwKAuHPnjhCi4iM+Xbt2FfPmzdNbx7p160TDhg11r009BhYfaw4fPizq1KkjXnvtNeHo6CgOHjyoV/6tt94SQ4cO1WvPli1b9MoU/8xL244QpR/x6dKli+71w4cPhYuLixgxYoRuXnZ2tgAgDh06JIQwbJ8xlrHj/syZM0XLli1FYWGhrsyyZcuESqUSBQUFIicnp8K+HjBggBg9erTRbeERnyp6lIBVKhXGjx8PAJg6dSrGjh2LF198EfPnz8eFCxf03uPs7IwWLVroXjds2BDXr18vdztl/a/YkgYPHoysrCxs27YNISEhSEpKQvv27fUuzG7Tpo3u3y4uLnB1dS23rQ4ODnrvsaQePXogJSUFKSkpOHz4MHr37o2+ffvi0qVLpZZfsWIFOnbsiHr16kGlUmHVqlWlXg80c+ZMHDp0CFu2bClx7cjx48cxcuRILFu2DF26dAEA/P777xBCwMfHR29/27dvn96+ZY6+K+8zT0tLg4eHh97/aH19fVGrVi2kpaUBAFJSUtCzZ89yt7Fw4UKsXLkSBw4c0DtS0bZtW/Ts2RN+fn4YMmQIVq1ahVu3blVPQ0vx+N+gVqtFVlYWgoKC9MoEBQXp2mqId999F3PnzkVQUBBiYmL0Lp4/duwY9u7dq/eZPzoC+PjnXnxsGDJkCO7fv4/mzZvj7bffxubNm/UuSq6qHj164O7du0hOTsb+/fvh4+OD+vXrIzg4GMnJybh79y6SkpLQtGlTNG/eHMePH8fAgQPRrFkzuLq6onv37gBg8DVyx44dw//8z//otf/tt99Gdna27ghHdfj++++hUqng6OiIgIAAdOvWDdOmTcODBw/Qq1cvvfqsXbu2xPhuyrH68b9nW1tb1KlTR+9vokGDBgCgG1MN3WeMYey4n5aWhoCAAL3rN4OCgpCTk4MrV67gzJkzFfb1hAkTsH79erRr1w4zZszAwYMHq9QWBp8qevTFmJKSgv/5n/8BAMyePRunT59G//798fPPP8PX1xebN2/Wvaf4RZEKhaLCw/UuLi6mr7wJODo6olevXoiOjsbBgwcRGhqKmJgY3fLS2lpYWFjm+pycnCx6QfPjXFxc4O3tDW9vb3Tu3Blr1qzB3bt3sWrVqhJlv/nmG0RERGDMmDH44YcfkJKSgtGjRyMvL0+v3JdffolFixZh8+bNaNKkid6yq1ev4uWXX8Zbb72Ft956Sze/sLAQtra2OHbsmN7+lpaWhiVLlujKmavvyvrMhRClbv/x+YbcDNC1a1cUFBTonSYEigb+H3/8ETt37oSvry+WLl2Kli1bIj093TQNq0Bpf4PF2/t4Wx9dWP7433Z+fr5e+bFjx+LixYsYMWIEUlNT0bFjRyxduhRA0ec+YMAAvc88JSUF586d050iLa1eHh4eOHv2LJYtWwYnJydMnDgR3bp1K7HtyvL29kaTJk2wd+9e7N27F8HBwQAAd3d3eHl54ddff8XevXvxwgsv4O7du+jduzdUKhW+/PJLJCcn68bA4n8TZSksLMScOXP02p6amopz587B0dHRqLaU59F/eM6ePYsHDx5g06ZNumXbt2/Xq8+ZM2fw7bff6r3fkLHaxsamxJhf2udT2vj5+LxH+9qjMdXQfcZYxoz7pY0Tj/ri8XLl9fWj/4BOmTIFWVlZ6NmzZ4WXi5SGd3VVkbe3d6nzfXx84OPjg4iICAwdOhTx8fEYNGiQSbdtb2+PgoICk67TWL6+via/xd7BwcEq2vnoLqn79++XWLZ//34EBgZi4sSJunnF/4d16NAhjB07FitXrtTdGfPIgwcPMHDgQLRq1Qqffvqp3jJ/f38UFBTg+vXrJW4dtgaPPnNfX19cvnwZmZmZuqM+Z86cgUajQevWrQEU/U9wz549GD16dJnr69y5M8LDwxESEgJbW1tMnz5dt0yhUCAoKAhBQUGIjo5Gs2bNsHnzZkydOrV6G1mMm5sbGjVqhAMHDuh9oRw8eBCdO3cGANSrVw9A0XUXTz31FACU+twnDw8PjB8/HuPHj0dUVBRWrVqF8PBwtG/fHhs3boSnpyfs7Co3RDs5OeHll1/Gyy+/jLCwMLRq1Qqpqalo3759FVtcpEePHkhKSsKtW7f0Ppfg4GDs3r0bv/32G0aPHo3//Oc/+PvvvzF//nzdvnD06NFKbat9+/Y4e/ZsmWMsUD1j4KP/8DzO19cXSqUSly9f1gU+Y9SrVw+nTp3Sm5eSkmL0nYLG7DPGqMy47+vri40bN+oFoIMHD8LV1RWNGzdGrVq1DOrrevXqITQ0FKGhoejatSumT5+OTz75pFL1ZvAxkfv372P69Ol47bXX4OXlhStXriA5ORmDBw82+bY8PT2xZ88eBAUFQalU6gZXc7hx4waGDBmCMWPGoE2bNnB1dcXRo0exYMECDBw40KTb8vT0xO7du3H27FnUqVMHarXaLLcS5+bm4urVqwCAW7du4X//93+Rk5ODAQMGlCjr7e2NtWvXYvfu3fDy8sK6deuQnJwMLy8vAEVHcwYNGoQ33ngDISEhuvXa2tqiXr16GDduHDIzM7Fnzx789ddfuvXWrl0bPj4+GDZsGEaOHImFCxfC398ff//9N37++Wf4+fmhX79+1d4XQMWf+Ysvvog2bdpg2LBhWLx4MR4+fIiJEyciODhYd/g/JiYGPXv2RIsWLfDGG2/g4cOH2LlzJ2bMmKG3rYCAAOzcuRN9+vSBnZ0dIiIicPjwYezZswe9e/dG/fr1cfjwYfz111+6UGVu06dPR0xMDFq0aIF27dohPj4eKSkp+OqrrwAU7RMeHh6YPXs25s6di3PnzmHhwoV665gyZQr69u0LHx8f3Lp1Cz///LOuPWFhYVi1ahWGDh2K6dOno27dujh//jzWr1+PVatWwdbWttR6JSQkoKCgAM899xycnZ2xbt06ODk5oVmzZka3uUePHggLC0N+fr7el1JwcDAmTJiABw8eoEePHnB0dISDgwOWLl2K8ePH49SpU/jwww8rta3o6Gi89NJL8PDwwJAhQ2BjY4OTJ08iNTVVdyGsucZAV1dXTJs2DRERESgsLESXLl2g1Wpx8OBBqFQqjBo1qlLre+GFF/Cvf/0La9euRUBAAL788kucOnUK/v7+RtWzqvuMoUwx7k+cOBGLFy9GeHg4Jk2ahLNnzyImJgZTp06FjY2NQX0dHR2NDh064JlnnkFubi6+//77qo0DRl8lJAFDLm7Ozc0Vb7zxhu5W0kaNGolJkyaJ+/fvl7mOzZs3i8c/gtIubp48eXKJbW3btk14e3sLOzs7s9/O/uDBAxEZGSnat28v1Gq1cHZ2Fi1bthSzZs3SXbCLUi48VKvVIj4+Xghh2O2sQghx/fp10atXL6FSqcx6OzseuwXV1dVVdOrUSXz77bdCiJIXNz948ECEhoYKtVotatWqJSZMmCAiIyNF27Zt9dpafHr0uRW/NffR9KiteXl5Ijo6Wnh6egp7e3vh7u4uBg0apLv419AL741hyGduyO3sGzduFO3atRMODg6ibt264tVXX9UtK347+759+4SLi4tYsmSJOHPmjAgJCRH16tUTSqVS+Pj4iKVLl5q8nWVd3Fz8QvbHb2e3t7cvcTu7EEIcOHBA+Pn5CUdHR9G1a1fx73//W+9C10mTJokWLVoIpVIp6tWrJ0aMGCH+/vtv3fv/+OMPMWjQIFGrVi3h5OQkWrVqJaZMmaK7MLS0sWHz5s3iueeeE25ubsLFxUU8//zz4qeffjJJ3zzqi1atWunNf3QBbYsWLXTzvv76a+Hp6SmUSqUICAgQ27Zt0+tHQ/7+d+3aJQIDA4WTk5Nwc3MTnTt3Fl988YVuuanHwPJupCgsLBRLliwRLVu2FPb29qJevXoiJCRE7Nu3r9T2PFLaxc1CCBEdHS0aNGgg1Gq1iIiIEJMmTSpxcXPxz7b434cQJcfZivYZY5hi3BfCsNvZy+vrDz/8ULRu3Vo4OTmJ2rVri4EDB1bp8R2K/19hIiIiohqPFzcTERGRNBh8iIiISBoMPkRERCQNBh8iIiKSBoMPERERSYPBh4iIiKTB4ENERETSYPAhIiIiaTD4EJHFXL16FeHh4WjevDmUSiU8PDwwYMAA7Nmzx6D3JyQkoFatWtVbSSKqUfhbXURkERkZGQgKCkKtWrWwYMECtGnTBvn5+di9ezfCwsLwn//8x9JVrLT8/Hyz/J4cEVUdj/gQkUVMnDgRCoUCR44cwWuvvQYfHx8888wzmDp1Kn777TcAwKeffgo/Pz+4uLjAw8MDEydORE5ODgAgKSkJo0ePhkajgUKhgEKhwOzZswEAeXl5mDFjBho3bgwXFxc899xzSEpK0tv+qlWr4OHhAWdnZwwaNAiffvppiaNHy5cvR4sWLeDg4ICWLVti3bp1essVCgVWrFiBgQMHwsXFBXPnzoW3t3eJX4s+deoUbGxscOHCBdN1IBFVTaV/3YuIyEg3btwQCoVCzJs3r9xyixYtEj///LO4ePGi2LNnj2jZsqWYMGGCEKLoh4EXL14s3NzcRHZ2tsjOzhZ37twRQgjx5ptvisDAQPHLL7+I8+fPi3/9619CqVSKP/74QwhR9COiNjY24l//+pc4e/asWLZsmahdu7bej2Vu2rRJ2Nvbi2XLlomzZ8+KhQsXCltbW/Hzzz/rygAQ9evXF2vWrBEXLlwQGRkZ4qOPPhK+vr567YiIiBDdunUzRdcRkZEYfIjI7A4fPiwAiE2bNlXqfd98842oU6eO7nVpv+x9/vx5oVAoxJ9//qk3v2fPniIqKkoIIcQ//vEP0b9/f73lw4YN01tXYGCgePvtt/XKDBkyRPTr10/3GoCYMmWKXpmsrCxha2srDh8+LIQQIi8vT9SrV08kJCRUqq1EVD14qouIzE4IAaDoVFF59u7di169eqFx48ZwdXXFyJEjcePGDdy9e7fM9/z+++8QQsDHxwcqlUo37du3T3eq6ezZs+jcubPe+4q/TktLQ1BQkN68oKAgpKWl6c3r2LGj3uuGDRuif//+iIuLAwB8//33ePDgAYYMGVJuW4nIPBh8iMjsnn76aSgUihIh4nGXLl1Cv3798Oyzz2Ljxo04duwYli1bBqDoIuKyFBYWwtbWFseOHUNKSopuSktLw5IlSwAUBa/ioetRGHtcaWWKz3NxcSnxvrFjx2L9+vW4f/8+4uPj8Y9//APOzs5l1pmIzIfBh4jMrnbt2ggJCcGyZctKPXpz+/ZtHD16FA8fPsTChQvx/PPPw8fHB1lZWXrlHBwcUFBQoDfP398fBQUFuH79Ory9vfUmd3d3AECrVq1w5MgRvfcdPXpU73Xr1q1x4MABvXkHDx5E69atK2xfv3794OLiguXLl2Pnzp0YM2ZMhe8hIvNg8CEii/j8889RUFCAzp07Y+PGjTh37hzS0tLw2WefISAgAC1atMDDhw+xdOlSXLx4EevWrcOKFSv01uHp6YmcnBzs2bMHf//9N+7duwcfHx8MGzYMI0eOxKZNm5Ceno7k5GR8/PHH2LFjBwAgPDwcO3bswKeffopz585h5cqV2Llzp97RnOnTpyMhIQErVqzAuXPn8Omnn2LTpk2YNm1ahW2ztbVFaGgooqKi4O3tjYCAANN2HhFVnUWvMCIiqWVlZYmwsDDRrFkz4eDgIBo3bixefvllsXfvXiGEEJ9++qlo2LChcHJyEiEhIWLt2rUCgLh165ZuHePHjxd16tQRAERMTIwQouiC4ujoaOHp6Sns7e2Fu7u7GDRokDh58qTufV988YVo3LixcHJyEq+88oqYO3eucHd316vf559/Lpo3by7s7e2Fj4+PWLt2rd5yAGLz5s2ltu3ChQsCgFiwYIHR/UREpqMQopQT20REknn77bfxn//8B/v37zfJ+n799Vd0794dV65cQYMGDUyyTiIyHp/cTERS+uSTT9CrVy+4uLhg586dSExMxOeff270enNzc5GZmYkPPvgAr7/+OkMPkZXhNT5EJKUjR46gV69e8PPzw4oVK/DZZ59h7NixRq/3//7v/9CyZUtoNBosWLDABDUlIlPiqS4iIiKSBo/4EBERkTQYfIiIiEgaDD5EREQkDQYfIiIikgaDDxEREUmDwYeIiIikweBDRERE0mDwISIiImkw+BAREZE0/h82tiPL9PyH1QAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# we use scatter plot to find how many data and how much and different types of size\n",
    "# prepare data for scatter plot\n",
    "x_data = data['Category']\n",
    "y_data = data['Size']\n",
    "\n",
    "# plot the scatter plot\n",
    "plt.scatter(x_data, y_data)\n",
    "plt.xlabel('Category')\n",
    "plt.ylabel('Size')\n",
    "plt.title('Scatter Plot')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 498,
   "id": "8acb5b8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot count of cities by state\n",
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(data=data, x='ship-state')\n",
    "plt.xlabel('ship-state')\n",
    "plt.ylabel('count')\n",
    "plt.title('Distribution of State')\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 500,
   "id": "f37ca504",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1E0xh+9g2tm4CAAAAALwS6LEHAAAAAMDECPYAAAAAAJgYwR4AAAAAABMj2AMAAAAAYGIEewAAAAAATIxgDwAAAACAiRHsAQAAAAAwMYI9AAAAAAAmRrAHAAAAAMDECPYAAAAAAJgYwR4AAAAAABOzebA/c+aMvPfee+Lq6ioODg5SqlQp2b59u7FdVSU0NFS8vb3F3t5eqlevLpGRkVbPER8fLz169BA3NzfJkiWLBAYGyunTp63qREdHS0hIiDg7O4uzs7OEhITI1atX0+ItAgAAAADwwtg02EdHR0ulSpUkY8aM8scff8i///4r48aNk2zZshl1xowZI+PHj5fJkyfLtm3bxNPTU+rUqSPXrl0z6vTq1UsWL14sCxYskA0bNsj169elcePGcvfuXaNOcHCwRERESHh4uISHh0tERISEhISk5dsFAAAAAOC5s6iq2urFBwwYIBs3bpT169enul1VxdvbW3r16iX9+/cXkXu98x4eHjJ69Gjp0qWLxMTESI4cOeSHH36Qli1biojI2bNnJXfu3PL7779LvXr1ZN++fVKsWDHZvHmz+Pv7i4jI5s2bJSAgQPbv3y9FihR5ZFtjY2PF2dlZYmJixMnJ6YH1yn4y+0l3w2tp+9g2tm4CAAAAALzUHjeH2rTHfunSpVKuXDlp0aKFuLu7S+nSpWX69OnG9mPHjklUVJTUrVvXKLOzs5Nq1arJ33//LSIi27dvl9u3b1vV8fb2Fj8/P6POpk2bxNnZ2Qj1IiIVKlQQZ2dnow4AAAAAAGZk02B/9OhRmTJlihQqVEiWL18uH3zwgfTs2VNmz77X6x0VFSUiIh4eHlaP8/DwMLZFRUVJpkyZJHv27A+t4+7unuL13d3djTr3i4+Pl9jYWKsfAAAAAABeNhls+eKJiYlSrlw5CQsLExGR0qVLS2RkpEyZMkXatPnfUG2LxWL1OFVNUXa/++ukVv9hzzNq1CgZOnToY78XAAAAAABswaY99l5eXlKsWDGrMl9fXzl58qSIiHh6eoqIpOhVv3DhgtGL7+npKQkJCRIdHf3QOufPn0/x+hcvXkwxGiDJwIEDJSYmxvg5derUU7xDAAAAAABeLJsG+0qVKsmBAwesyg4ePCh58+YVEREfHx/x9PSUlStXGtsTEhJk3bp1UrFiRRERKVu2rGTMmNGqzrlz52Tv3r1GnYCAAImJiZGtW7cadbZs2SIxMTFGnfvZ2dmJk5OT1Q8AAAAAAC8bmw7F//jjj6VixYoSFhYmQUFBsnXrVpk2bZpMmzZNRO4Nn+/Vq5eEhYVJoUKFpFChQhIWFiYODg4SHBwsIiLOzs7SoUMH6dOnj7i6uoqLi4v07dtXihcvLrVr1xaRe6MA6tevL506dZKpU6eKiEjnzp2lcePGj7UiPgAAAAAALyubBvvy5cvL4sWLZeDAgTJs2DDx8fGRiRMnSuvWrY06/fr1k7i4OOnatatER0eLv7+/rFixQhwdHY06EyZMkAwZMkhQUJDExcVJrVq1ZObMmZI+fXqjzty5c6Vnz57G6vmBgYEyefLktHuzAAAAAAC8ADa9j72ZcB/754v72AMAAADAw5niPvYAAAAAAODZEOwBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMRsGuxDQ0PFYrFY/Xh6ehrbVVVCQ0PF29tb7O3tpXr16hIZGWn1HPHx8dKjRw9xc3OTLFmySGBgoJw+fdqqTnR0tISEhIizs7M4OztLSEiIXL16NS3eIgAAAAAAL5TNe+zfeOMNOXfunPGzZ88eY9uYMWNk/PjxMnnyZNm2bZt4enpKnTp15Nq1a0adXr16yeLFi2XBggWyYcMGuX79ujRu3Fju3r1r1AkODpaIiAgJDw+X8PBwiYiIkJCQkDR9nwAAAAAAvAgZbN6ADBmseumTqKpMnDhRBg0aJM2aNRMRkVmzZomHh4fMmzdPunTpIjExMTJjxgz54YcfpHbt2iIiMmfOHMmdO7esWrVK6tWrJ/v27ZPw8HDZvHmz+Pv7i4jI9OnTJSAgQA4cOCBFihRJuzcLAAAAAMBzZvMe+0OHDom3t7f4+PjIu+++K0ePHhURkWPHjklUVJTUrVvXqGtnZyfVqlWTv//+W0REtm/fLrdv37aq4+3tLX5+fkadTZs2ibOzsxHqRUQqVKggzs7ORp3UxMfHS2xsrNUPAAAAAAAvG5sGe39/f5k9e7YsX75cpk+fLlFRUVKxYkW5fPmyREVFiYiIh4eH1WM8PDyMbVFRUZIpUybJnj37Q+u4u7uneG13d3ejTmpGjRplzMl3dnaW3LlzP9N7BQAAAADgRbBpsG/QoIG88847Urx4caldu7YsW7ZMRO4NuU9isVisHqOqKcrud3+d1Oo/6nkGDhwoMTExxs+pU6ce6z0BAAAAAJCWbD4UP7ksWbJI8eLF5dChQ8a8+/t71S9cuGD04nt6ekpCQoJER0c/tM758+dTvNbFixdTjAZIzs7OTpycnKx+AAAAAAB42bxUwT4+Pl727dsnXl5e4uPjI56enrJy5Upje0JCgqxbt04qVqwoIiJly5aVjBkzWtU5d+6c7N2716gTEBAgMTExsnXrVqPOli1bJCYmxqgDAAAAAIBZ2XRV/L59+0qTJk0kT548cuHCBRkxYoTExsbK+++/LxaLRXr16iVhYWFSqFAhKVSokISFhYmDg4MEBweLiIizs7N06NBB+vTpI66uruLi4iJ9+/Y1hvaLiPj6+kr9+vWlU6dOMnXqVBER6dy5szRu3JgV8QEAAAAApmfTYH/69Glp1aqVXLp0SXLkyCEVKlSQzZs3S968eUVEpF+/fhIXFyddu3aV6Oho8ff3lxUrVoijo6PxHBMmTJAMGTJIUFCQxMXFSa1atWTmzJmSPn16o87cuXOlZ8+exur5gYGBMnny5LR9swAAAAAAvAAWVVVbN8IMYmNjxdnZWWJiYh46377sJ7PTsFXmtX1sG1s3AQAAAABeao+bQ1+qOfYAAAAAAODJEOwBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJZbB1A4BnVfaT2bZugilsH9vG1k0AAAAA8ALQYw8AAAAAgIkR7AEAAAAAMDGCPQAAAAAAJkawBwAAAADAxAj2AAAAAACYGMEeAAAAAAATI9gDAAAAAGBiBHsAAAAAAEyMYA8AAAAAgIkR7AEAAAAAMDGCPQAAAAAAJkawBwAAAADAxAj2AAAAAACYGMEeAAAAAAATI9gDAAAAAGBiBHsAAAAAAEyMYA8AAAAAgIkR7AEAAAAAMDGCPQAAAAAAJkawBwAAAADAxAj2AAAAAACYGMEeAAAAAAATI9gDAAAAAGBiBHsAAAAAAEyMYA8AAAAAgIkR7AEAAAAAMDGCPQAAAAAAJkawBwAAAADAxAj2AAAAAACYGMEeAAAAAAATI9gDAAAAAGBiBHsAAAAAAEyMYA8AAAAAgIkR7AEAAAAAMLGXJtiPGjVKLBaL9OrVyyhTVQkNDRVvb2+xt7eX6tWrS2RkpNXj4uPjpUePHuLm5iZZsmSRwMBAOX36tFWd6OhoCQkJEWdnZ3F2dpaQkBC5evVqGrwrAAAAAABerJci2G/btk2mTZsmJUqUsCofM2aMjB8/XiZPnizbtm0TT09PqVOnjly7ds2o06tXL1m8eLEsWLBANmzYINevX5fGjRvL3bt3jTrBwcESEREh4eHhEh4eLhERERISEpJm7w8AAAAAgBfF5sH++vXr0rp1a5k+fbpkz57dKFdVmThxogwaNEiaNWsmfn5+MmvWLLl586bMmzdPRERiYmJkxowZMm7cOKldu7aULl1a5syZI3v27JFVq1aJiMi+ffskPDxcvv32WwkICJCAgACZPn26/Pbbb3LgwAGbvGcAAAAAAJ4Xmwf7bt26SaNGjaR27dpW5ceOHZOoqCipW7euUWZnZyfVqlWTv//+W0REtm/fLrdv37aq4+3tLX5+fkadTZs2ibOzs/j7+xt1KlSoIM7Ozkad1MTHx0tsbKzVDwAAAAAAL5sMtnzxBQsWyI4dO2Tbtm0ptkVFRYmIiIeHh1W5h4eHnDhxwqiTKVMmq57+pDpJj4+KihJ3d/cUz+/u7m7USc2oUaNk6NChT/aGAAAAAABIYzbrsT916pR89NFHMmfOHMmcOfMD61ksFqvfVTVF2f3ur5Na/Uc9z8CBAyUmJsb4OXXq1ENfEwAAAAAAW7BZsN++fbtcuHBBypYtKxkyZJAMGTLIunXr5Msvv5QMGTIYPfX396pfuHDB2Obp6SkJCQkSHR390Drnz59P8foXL15MMRogOTs7O3FycrL6AQAAAADgZWOzYF+rVi3Zs2ePREREGD/lypWT1q1bS0REhOTPn188PT1l5cqVxmMSEhJk3bp1UrFiRRERKVu2rGTMmNGqzrlz52Tv3r1GnYCAAImJiZGtW7cadbZs2SIxMTFGHQAAAAAAzMpmc+wdHR3Fz8/PqixLlizi6upqlPfq1UvCwsKkUKFCUqhQIQkLCxMHBwcJDg4WERFnZ2fp0KGD9OnTR1xdXcXFxUX69u0rxYsXNxbj8/X1lfr160unTp1k6tSpIiLSuXNnady4sRQpUiQN3zEAAAAAAM+fTRfPe5R+/fpJXFycdO3aVaKjo8Xf319WrFghjo6ORp0JEyZIhgwZJCgoSOLi4qRWrVoyc+ZMSZ8+vVFn7ty50rNnT2P1/MDAQJk8eXKavx8AAAAAAJ43i6qqrRthBrGxseLs7CwxMTEPnW9f9pPZadgq89o+ts1zey72+eN5nvscAAAAwIv3uDnU5vexBwAAAAAAT49gDwAAAACAiRHsAQAAAAAwMYI9AAAAAAAmRrAHAAAAAMDECPYAAAAAAJgYwR4AAAAAABMj2AMAAAAAYGIEewAAAAAATIxgDwAAAACAiRHsAQAAAAAwMYI9AAAAAAAmRrAHAAAAAMDECPYAAAAAAJgYwR4AAAAAABMj2AMAAAAAYGIEewAAAAAATIxgDwAAAACAiRHsAQAAAAAwMYI9AAAAAAAmRrAHAAAAAMDECPYAAAAAAJgYwR4AAAAAABMj2AMAAAAAYGIEewAAAAAATIxgDwAAAACAiRHsAQAAAAAwsacK9jVr1pSrV6+mKI+NjZWaNWs+a5sAAAAAAMBjeqpgv3btWklISEhRfuvWLVm/fv0zNwoAAAAAADyeDE9Seffu3cb///vvvxIVFWX8fvfuXQkPD5ecOXM+v9YBAAAAAICHeqJgX6pUKbFYLGKxWFIdcm9vby+TJk16bo0DAAAAAAAP90TB/tixY6Kqkj9/ftm6davkyJHD2JYpUyZxd3eX9OnTP/dGAgAAAACA1D1RsM+bN6+IiCQmJr6QxgAAAAAAgCfzRME+uYMHD8ratWvlwoULKYL+4MGDn7lhAAAAAADg0Z4q2E+fPl0+/PBDcXNzE09PT7FYLMY2i8VCsAcAAAAAII08VbAfMWKEjBw5Uvr37/+82wMAAAAAAJ7AU93HPjo6Wlq0aPG82wIAAAAAAJ7QUwX7Fi1ayIoVK553WwAAAAAAwBN6qqH4BQsWlM8++0w2b94sxYsXl4wZM1pt79mz53NpHAAAAAAAeLinCvbTpk2TrFmzyrp162TdunVW2ywWC8EeAAAAAIA08lTB/tixY8+7HQAAAAAA4Ck81Rx7AAAAAADwcniqHvv27ds/dPt33333VI0BAOBlUfaT2bZugilsH9vG1k0AAOC191TBPjo62ur327dvy969e+Xq1atSs2bN59IwAAAAAADwaE8V7BcvXpyiLDExUbp27Sr58+d/5kYBAAAAAIDH89zm2KdLl04+/vhjmTBhwvN6SgAAAAAA8AjPdfG8I0eOyJ07d57nUwIAAAAAgId4qqH4vXv3tvpdVeXcuXOybNkyef/9959LwwAAAAAAwKM9VbDfuXOn1e/p0qWTHDlyyLhx4x65Yj4AAAAAAHh+nirYr1mz5nm3AwAAAAAAPIWnCvZJLl68KAcOHBCLxSKFCxeWHDlyPK92AQAAAACAx/BUwf7GjRvSo0cPmT17tiQmJoqISPr06aVNmzYyadIkcXBweK6NBAAAr76yn8y2dRNMYfvYNrZuAgDgJfNUq+L37t1b1q1bJ7/++qtcvXpVrl69Kr/88ousW7dO+vTp87zbCAAAAAAAHuCpeux/+uknWbRokVSvXt0oa9iwodjb20tQUJBMmTLlebUPAAAAAAA8xFMF+5s3b4qHh0eKcnd3d7l58+YzNwrAy43hso+H4bIAAABIC081FD8gIECGDBkit27dMsri4uJk6NChEhAQ8NwaBwAAAAAAHu6peuwnTpwoDRo0kFy5cknJkiXFYrFIRESE2NnZyYoVK553GwEAAAAAwAM8VbAvXry4HDp0SObMmSP79+8XVZV3331XWrduLfb29s+7jQAAAAAA4AGeKtiPGjVKPDw8pFOnTlbl3333nVy8eFH69+//XBoHAAAAAAAe7qnm2E+dOlWKFi2aovyNN96Qb7755rGfZ8qUKVKiRAlxcnISJycnCQgIkD/++MPYrqoSGhoq3t7eYm9vL9WrV5fIyEir54iPj5cePXqIm5ubZMmSRQIDA+X06dNWdaKjoyUkJEScnZ3F2dlZQkJC5OrVq0/2pgEAAAAAeAk9VbCPiooSLy+vFOU5cuSQc+fOPfbz5MqVSz7//HP5559/5J9//pGaNWtK06ZNjfA+ZswYGT9+vEyePFm2bdsmnp6eUqdOHbl27ZrxHL169ZLFixfLggULZMOGDXL9+nVp3Lix3L1716gTHBwsEREREh4eLuHh4RIRESEhISFP89YBAAAAAHipPNVQ/Ny5c8vGjRvFx8fHqnzjxo3i7e392M/TpEkTq99HjhwpU6ZMkc2bN0uxYsVk4sSJMmjQIGnWrJmIiMyaNUs8PDxk3rx50qVLF4mJiZEZM2bIDz/8ILVr1xYRkTlz5kju3Lll1apVUq9ePdm3b5+Eh4fL5s2bxd/fX0REpk+fLgEBAXLgwAEpUqTI0+wCAAAAAABeCk/VY9+xY0fp1auXfP/993LixAk5ceKEfPfdd/Lxxx+nmHf/uO7evSsLFiyQGzduSEBAgBw7dkyioqKkbt26Rh07OzupVq2a/P333yIisn37drl9+7ZVHW9vb/Hz8zPqbNq0SZydnY1QLyJSoUIFcXZ2NuqkJj4+XmJjY61+AAAAAAB42TxVj32/fv3kypUr0rVrV0lISBARkcyZM0v//v1l4MCBT/Rce/bskYCAALl165ZkzZpVFi9eLMWKFTNCt4eHh1V9Dw8POXHihIjcmxKQKVMmyZ49e4o6UVFRRh13d/cUr+vu7m7USc2oUaNk6NChT/ReAAAAAABIa08V7C0Wi4wePVo+++wz2bdvn9jb20uhQoXEzs7uiZ+rSJEiEhERIVevXpWffvpJ3n//fVm3bp3VayWnqinK7nd/ndTqP+p5Bg4cKL179zZ+j42Nldy5cz/y/QAAAAAAkJaeKtgnyZo1q5QvX/6ZGpApUyYpWLCgiIiUK1dOtm3bJv/5z3+MW+bdv1DfhQsXjF58T09PSUhIkOjoaKte+wsXLkjFihWNOufPn0/xuhcvXkwxGiA5Ozu7p7pQAQAAAABAWnqqOfYvkqpKfHy8+Pj4iKenp6xcudLYlpCQIOvWrTNCe9myZSVjxoxWdc6dOyd79+416gQEBEhMTIxs3brVqLNlyxaJiYkx6gAAAAAAYFbP1GP/rD799FNp0KCB5M6dW65duyYLFiyQtWvXSnh4uFgsFunVq5eEhYVJoUKFpFChQhIWFiYODg4SHBwsIiLOzs7SoUMH6dOnj7i6uoqLi4v07dtXihcvbqyS7+vrK/Xr15dOnTrJ1KlTRUSkc+fO0rhxY1bEBwAAAACYnk2D/fnz5yUkJETOnTsnzs7OUqJECQkPD5c6deqIyL1F+uLi4qRr164SHR0t/v7+smLFCnF0dDSeY8KECZIhQwYJCgqSuLg4qVWrlsycOVPSp09v1Jk7d6707NnTWD0/MDBQJk+enLZvFgAAAACAF8CmwX7GjBkP3W6xWCQ0NFRCQ0MfWCdz5swyadIkmTRp0gPruLi4yJw5c562mQAAAAAAvLReujn2AAAAAADg8RHsAQAAAAAwMYI9AAAAAAAmRrAHAAAAAMDECPYAAAAAAJgYwR4AAAAAABMj2AMAAAAAYGIEewAAAAAATIxgDwAAAACAiRHsAQAAAAAwMYI9AAAAAAAmRrAHAAAAAMDECPYAAAAAAJgYwR4AAAAAABMj2AMAAAAAYGIEewAAAAAATIxgDwAAAACAiRHsAQAAAAAwMYI9AAAAAAAmRrAHAAAAAMDECPYAAAAAAJgYwR4AAAAAABMj2AMAAAAAYGIEewAAAAAATIxgDwAAAACAiRHsAQAAAAAwMYI9AAAAAAAmRrAHAAAAAMDECPYAAAAAAJgYwR4AAAAAABMj2AMAAAAAYGIEewAAAAAATIxgDwAAAACAiRHsAQAAAAAwMYI9AAAAAAAmRrAHAAAAAMDECPYAAAAAAJgYwR4AAAAAABMj2AMAAAAAYGIEewAAAAAATIxgDwAAAACAiRHsAQAAAAAwMYI9AAAAAAAmRrAHAAAAAMDECPYAAAAAAJgYwR4AAAAAABMj2AMAAAAAYGIEewAAAAAATIxgDwAAAACAiWWwdQMAAACA10XZT2bbugmmsH1sG1s3ATAVeuwBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZm02A/atQoKV++vDg6Ooq7u7u89dZbcuDAAas6qiqhoaHi7e0t9vb2Ur16dYmMjLSqEx8fLz169BA3NzfJkiWLBAYGyunTp63qREdHS0hIiDg7O4uzs7OEhITI1atXX/RbBAAAAADghbJpsF+3bp1069ZNNm/eLCtXrpQ7d+5I3bp15caNG0adMWPGyPjx42Xy5Mmybds28fT0lDp16si1a9eMOr169ZLFixfLggULZMOGDXL9+nVp3Lix3L1716gTHBwsEREREh4eLuHh4RIRESEhISFp+n4BAAAAAHjeMtjyxcPDw61+//7778Xd3V22b98uVatWFVWViRMnyqBBg6RZs2YiIjJr1izx8PCQefPmSZcuXSQmJkZmzJghP/zwg9SuXVtERObMmSO5c+eWVatWSb169WTfvn0SHh4umzdvFn9/fxERmT59ugQEBMiBAwekSJEiafvGAQAAAAB4Tl6qOfYxMTEiIuLi4iIiIseOHZOoqCipW7euUcfOzk6qVasmf//9t4iIbN++XW7fvm1Vx9vbW/z8/Iw6mzZtEmdnZyPUi4hUqFBBnJ2djTr3i4+Pl9jYWKsfAAAAAABeNi9NsFdV6d27t1SuXFn8/PxERCQqKkpERDw8PKzqenh4GNuioqIkU6ZMkj179ofWcXd3T/Ga7u7uRp37jRo1ypiP7+zsLLlz5362NwgAAAAAwAvw0gT77t27y+7du2X+/PkptlksFqvfVTVF2f3ur5Na/Yc9z8CBAyUmJsb4OXXq1OO8DQAAAAAA0tRLEex79OghS5culTVr1kiuXLmMck9PTxGRFL3qFy5cMHrxPT09JSEhQaKjox9a5/z58yle9+LFiylGAySxs7MTJycnqx8AAAAAAF42Nl08T1WlR48esnjxYlm7dq34+PhYbffx8RFPT09ZuXKllC5dWkREEhISZN26dTJ69GgRESlbtqxkzJhRVq5cKUFBQSIicu7cOdm7d6+MGTNGREQCAgIkJiZGtm7dKm+++aaIiGzZskViYmKkYsWKafV2AQAAAKSxsp/MtnUTTGH72Da2bgKegU2Dfbdu3WTevHnyyy+/iKOjo9Ez7+zsLPb29mKxWKRXr14SFhYmhQoVkkKFCklYWJg4ODhIcHCwUbdDhw7Sp08fcXV1FRcXF+nbt68UL17cWCXf19dX6tevL506dZKpU6eKiEjnzp2lcePGrIgPAAAAADA1mwb7KVOmiIhI9erVrcq///57adu2rYiI9OvXT+Li4qRr164SHR0t/v7+smLFCnF0dDTqT5gwQTJkyCBBQUESFxcntWrVkpkzZ0r69OmNOnPnzpWePXsaq+cHBgbK5MmTX+wbBAAAAADgBbP5UPxHsVgsEhoaKqGhoQ+skzlzZpk0aZJMmjTpgXVcXFxkzpw5T9NMAAAAAABeWi/F4nkAAAAAAODpEOwBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJZbB1AwAAAGAbZT+ZbesmmML2sW1s3QQAeCh67AEAAAAAMDGCPQAAAAAAJsZQfAAwAYbLPh6GywIAgNcRPfYAAAAAAJgYwR4AAAAAABMj2AMAAAAAYGIEewAAAAAATIxgDwAAAACAiRHsAQAAAAAwMYI9AAAAAAAmRrAHAAAAAMDECPYAAAAAAJgYwR4AAAAAABMj2AMAAAAAYGIEewAAAAAATIxgDwAAAACAiRHsAQAAAAAwMYI9AAAAAAAmlsHWDQAAAAAAvDrKfjLb1k0whe1j2zy356LHHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZm02D/119/SZMmTcTb21ssFossWbLEaruqSmhoqHh7e4u9vb1Ur15dIiMjrerEx8dLjx49xM3NTbJkySKBgYFy+vRpqzrR0dESEhIizs7O4uzsLCEhIXL16tUX/O4AAAAAAHjxbBrsb9y4ISVLlpTJkyenun3MmDEyfvx4mTx5smzbtk08PT2lTp06cu3aNaNOr169ZPHixbJgwQLZsGGDXL9+XRo3bix379416gQHB0tERISEh4dLeHi4RERESEhIyAt/fwAAAAAAvGgZbPniDRo0kAYNGqS6TVVl4sSJMmjQIGnWrJmIiMyaNUs8PDxk3rx50qVLF4mJiZEZM2bIDz/8ILVr1xYRkTlz5kju3Lll1apVUq9ePdm3b5+Eh4fL5s2bxd/fX0REpk+fLgEBAXLgwAEpUqRI2rxZAAAAAABegJd2jv2xY8ckKipK6tata5TZ2dlJtWrV5O+//xYRke3bt8vt27et6nh7e4ufn59RZ9OmTeLs7GyEehGRChUqiLOzs1EnNfHx8RIbG2v1AwAAAADAy+alDfZRUVEiIuLh4WFV7uHhYWyLioqSTJkySfbs2R9ax93dPcXzu7u7G3VSM2rUKGNOvrOzs+TOnfuZ3g8AAAAAAC/CSxvsk1gsFqvfVTVF2f3ur5Na/Uc9z8CBAyUmJsb4OXXq1BO2HAAAAACAF++lDfaenp4iIil61S9cuGD04nt6ekpCQoJER0c/tM758+dTPP/FixdTjAZIzs7OTpycnKx+AAAAAAB42by0wd7Hx0c8PT1l5cqVRllCQoKsW7dOKlasKCIiZcuWlYwZM1rVOXfunOzdu9eoExAQIDExMbJ161ajzpYtWyQmJsaoAwAAAACAWdl0Vfzr16/L4cOHjd+PHTsmERER4uLiInny5JFevXpJWFiYFCpUSAoVKiRhYWHi4OAgwcHBIiLi7OwsHTp0kD59+oirq6u4uLhI3759pXjx4sYq+b6+vlK/fn3p1KmTTJ06VUREOnfuLI0bN2ZFfAAAAACA6dk02P/zzz9So0YN4/fevXuLiMj7778vM2fOlH79+klcXJx07dpVoqOjxd/fX1asWCGOjo7GYyZMmCAZMmSQoKAgiYuLk1q1asnMmTMlffr0Rp25c+dKz549jdXzAwMDZfLkyWn0LgEAAAAAeHFsGuyrV68uqvrA7RaLRUJDQyU0NPSBdTJnziyTJk2SSZMmPbCOi4uLzJkz51maCgAAAADAS+mlnWMPAAAAAAAejWAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACZGsAcAAAAAwMQI9gAAAAAAmBjBHgAAAAAAEyPYAwAAAABgYgR7AAAAAABMjGAPAAAAAICJEewBAAAAADAxgj0AAAAAACb2WgX7r7/+Wnx8fCRz5sxStmxZWb9+va2bBAAAAADAM3ltgv3ChQulV69eMmjQINm5c6dUqVJFGjRoICdPnrR10wAAAAAAeGqvTbAfP368dOjQQTp27Ci+vr4yceJEyZ07t0yZMsXWTQMAAAAA4KllsHUD0kJCQoJs375dBgwYYFVet25d+fvvv1N9THx8vMTHxxu/x8TEiIhIbGzsQ1/rbnzcM7b29fCo/fgk2OePh32e9tjnaY99nvbY52mPfZ722Odpj32e9tjnae9x9nlSHVV9aD2LPqrGK+Ds2bOSM2dO2bhxo1SsWNEoDwsLk1mzZsmBAwdSPCY0NFSGDh2als0EAAAAACCFU6dOSa5cuR64/bXosU9isVisflfVFGVJBg4cKL179zZ+T0xMlCtXroirq+sDH/Myio2Nldy5c8upU6fEycnJ1s15LbDP0x77PO2xz9Me+zztsc/THvs87bHP0x77PO2ZeZ+rqly7dk28vb0fWu+1CPZubm6SPn16iYqKsiq/cOGCeHh4pPoYOzs7sbOzsyrLli3bi2riC+fk5GS6D7HZsc/THvs87bHP0x77PO2xz9Me+zztsc/THvs87Zl1nzs7Oz+yzmuxeF6mTJmkbNmysnLlSqvylStXWg3NBwAAAADAbF6LHnsRkd69e0tISIiUK1dOAgICZNq0aXLy5En54IMPbN00AAAAAACe2msT7Fu2bCmXL1+WYcOGyblz58TPz09+//13yZs3r62b9kLZ2dnJkCFDUkwrwIvDPk977PO0xz5Pe+zztMc+T3vs87THPk977PO09zrs89diVXwAAAAAAF5Vr8UcewAAAAAAXlUEewAAAAAATIxgDwAAAACAiRHsAQAAAAAwMYI9AAAAAAAmRrAHgMfETUTM4+TJkzJo0CC5ceOGrZvySjpy5IisW7dO7ty5Y+ummN6JEydk9OjRtm4GgJfQ3bt3bd2E115iYqKtm/DYCPZ44QhDMLOTJ0/KmjVrRETEYrGICF+0ZvDjjz/KTz/9JJ999pncvHnT1s155QwYMEDq1q0r69at4+/hGSQmJsoPP/wg33zzjQwbNszWzXltqSrnKk+BffZiHTx4UD755BM5c+aMrZvyWkuX7l5cjoiIsG1DHgPBHi/MrVu3ROR/YchMV7xeRsn3H1+maePixYvi6+srtWrVks6dO8usWbPkzp07kj59eqMO/xYvp+7du8t7770nmzZtkoEDBxLun7Mff/xRatWqJSEhIbJmzRq5ffu2rZtkSunSpZMOHTrIe++9J0uWLJEhQ4bYukmvlcOHD8sff/xhnKdwPH88CQkJInLv/I5zuxfnzJkzMnHiRBk5cqRERUXZujmvnR9//FEGDx4sIiIff/yx9OnTR2JiYmzcqocj2OOF2Lt3r5QrV04mT54su3fvFpH/XfHCk9u/f78MHz5cVq5cKSL0HKcVOzs7admypUyePFmyZcsmc+bMEV9fX5k3b57s2bNHRLhw9TK6e/eu2NnZSf/+/aVVq1ayYsUKGTx4MOH+OUkafv/777+Lv7+/dOvWTdasWcOw/KeQmJgoXl5e0r17d6lfv778+uuvhPs0cufOHZk2bZo0atRIli5dSrh/TPv27ZPmzZunmOrEfnt+4uPj5c6dO1KjRg1Zvny5TJs2TYYMGSLnzp2zddNeG3fv3pUrV67IiBEjpFq1ajJjxgyZMGGCODs727ppD0XSwgvx448/yuHDh2XOnDkSGhoqTZs2lcOHD0t0dLSI/O8LgC+CR4uPj5cePXrIwoULpUOHDtK2bVuZN2+eiIjRc8x+fDGcnJzE3t5eVq1aJWPGjJGlS5caPWsNGjSQL7/8UrZt2yYiXLiytejoaLl27ZqI3Pu3SExMlIwZM0psbKwcPXpUVq1aRc/9M0jab0nHmqSLilWrVpVDhw7JBx98IGvXruVi42O4ceOGMcIhXbp0oqri4eEhH330kRHuR44caeNWvvoyZMggXbp0ke7du0tISIj88ssvDwz3fMfec/fuXZk5c6YcPnzY6MAJDQ2VjRs3GvtOhAvdz+L48eNSu3Zt2bJli9y5c0fq1Kkjy5YtkxkzZkhoaCg992kkffr00qVLF6lUqZKsX79eQkJCpESJEi/9tB3ORPFCNG7cWDp27Cjjxo2T0NBQuXbtmrRv317atGkjq1atktjYWBERqy8CpC5Tpkzi5+cnJUqUkF27domjo6NMmTJFSpUqJT/++KMcP37caj++zAccM0nqffziiy/kyJEjMnXqVLG3t5chQ4bIlStXJCEhQb755hvp0aOH1KhRQw4dOmTjFr++oqOjpXDhwjJ+/Hi5evWqWCwWSZcunYSFhcl//vMf+fnnn+Xdd9+VrVu3Eu6fwvnz56V48eKyZMkSsVgskiFDBkmfPr2EhYVJWFiYrFu3TooWLSpt2rSRNWvWEO4f4ty5c1K8eHH5+eefrYYzJw/3tWrVkqVLl8rixYtt3NpXV1LwLFCggPTu3Vvee+89adOmjRHuk3+PJiQkyMCBA+X333+3VXNfGunTp5eAgACJj4+XefPmyfDhw+XChQvSoEED6du3r/GZTbrQTcB/crly5ZJjx45Jjx49ZMeOHXLnzh2pV6+eEe6HDBlCuE8jqio1atSQgQMHyrRp0yQ0NFQsFotYLJaX93tOgRcgPj5eK1asqL169TLKtm3bpq6urpo1a1YNCgrSL774QmNiYvTu3bs2bKk5XLp0SQsWLKi///673rp1S+Pi4nTIkCGaJUsWzZcvn44bN0737t1r62aa3qlTp/S3334zfk9ISNCEhATt3bu3fvzxx6qq2qZNG/X09NSTJ0/qmTNndMGCBVqpUiU9dOiQrZoNVR06dKhmypRJx44dq6qqY8aMURcXF/39999VVfXWrVs6bNgwrVy5srZv315v3Lhhy+aaypEjR7RVq1bq5uZm7M+wsDCr/auqWrduXc2TJ48uW7ZM79y5Y6vmvvQaNWqkbm5uunjxYo2PjzfKExMTVVX13Llz6u/vb/X9iecj+f6+ffu28f/Hjh3Tbt26qZOTk/78889G+a1bt7RHjx6aMWNG3bVrV5q29WXWokUL7devn7E/d+7cqXZ2durk5KTVq1fXn3/+WU+ePGnjVppP0nEzLi5O/fz81NfXVzdt2mTs5/DwcE2fPr127txZz507Z8umvpIelEfu3r2rU6ZM0fTp0+uQIUOstq1fvz4NWvb4CPZ4bpJOShISElRVdcOGDVqiRAndvn27qt4LRIUKFdLZs2frwIEDNXPmzFq5cmW9fv26zdr8sjp8+LBu3rxZVe+dfNy+fVv79etndaLXuXNnLVy4sA4dOlQLFCigefLk0W7dutmqyaZ369YtbdWqlZYvX14XL15stW3Dhg2aNWtWLVu2rHp7e+s///xjtZ2LU7Zx7do1jYmJMX7/4osvNF26dFqnTh3NkSOH/vnnn6r6vxP4W7du6YABA7ROnToaFRVlkzabyc2bN43/P3TokHbu3FmzZ8+u7733nnp4eGh4eLiqWgckf39/LVq0KBdOkkn6bkweKlu2bKnOzs5W4T4xMdE4lvTs2VNr165tPBbP7t9//9WmTZvqZ599pjdv3kxx3D5y5IgR7pO+A7p166b29va6Y8cOG7T45ZP0efzuu++0Ro0axj788MMPNW/evLpmzRp9++23tXDhwlqyZEmNj4/nM/yYkvblrVu3jLLs2bNrnTp1dPPmzcZxNjw8XDNnzqytWrXie+w5Sn48+OWXX/S7777Tr776yihLSEjQb775RjNmzKgDBw7UU6dOaePGjfWdd955qT7jBHs8s+vXr+v169f14sWLRlliYqKeOXNG69Wrp/PmzdP27durp6enEYgSExP1/PnzeuTIEVs1+6UVGxur3t7eOmPGDKvy5cuXq5OTkx46dEg/+OAD9fLyMvbn4cOHdfr06bp//35bNPmVsWnTJm3atKnWqVPHqtdG9d4JXu7cufXvv/+2UeuQ3P79+/Wtt97SiRMnWvVcfPnll2qxWLR9+/ZWQSqpJyQ+Pt7qWIXUHTp0SDt16mR1HDpy5Ih27dpV06dPr0OHDlXV/50MJQ/3J06cSNvGmsT9FzuCgoKMcJ+0LTExURMTE7V169bau3dvWzTzlXTnzh3t27ev+vr6aqNGjbRYsWI6ePBg3bRpk1W9Q4cOadeuXdXV1VWrVKmiWbJkMTon8D/x8fFapEgRHTt2rHbp0kW9vLx027ZtxvaNGzdyHHhMhw8fNkZcJv/OmjRpkmbPnl1z5cqlb7zxhm7ZssU4zi5dulRdXV317NmzNmnzqyZ5MO/fv7/myZNHy5cvrwULFlR/f389evSoqt4L97NmzdKMGTOqr6+vlixZ0ujMfFkQ7PFMIiMjtUmTJurn56c1atTQefPmWW3/+uuv1WKxqJeXl/77779GOT2cDxYTE6O5cuXSv/76S1WtDzgffvihZs6cWfPkyWN1keT+engyyT+PW7du1UaNGmnt2rWtwv3s2bM1V65cxpB7PsO2s2vXLvXw8NAOHTrookWLVNX68z9+/Hi1WCw6ZswYqx59hoc/nt27d2uuXLm0Q4cOOn36dKttBw4c0A8++ECzZcumy5YtU9V7fwuJiYns31QcP35cR48erTVq1NAiRYpo586djc+s6r0hza6urjpt2jQ9ceKEXrlyRf/v//5Pvb29dd++fTZs+avnp59+0gIFCujNmzd1wYIF2qlTJ3V0dNR+/fpZHevPnTun7dq10xw5ctBTn4qkv/OZM2eqvb29FipUyDgf4XvxycTHx2ubNm00U6ZMunPnTqN81KhRmj17dt2yZYuqqvr5+amfn59u3brVCJKMdn3+xo8fb9VpNnv2bLVYLFqmTBk9ePCgUe/IkSO6YsUK428h+YVtWyPY46lFRESok5OTdu/eXUeMGKHVq1dXd3d3qx7NK1euaIMGDfTTTz9VVcLn4zh37pz6+PhYXQhJMmfOHHV0dDTm9PAl+myOHj2qmzdv1uPHj1uVb9q0SRs1aqQ1a9a0OgmvUqWK1q1bN62biWSOHz+uPj4+xjElueTHl1GjRqnFYtEvvvhCr169mpZNNLWDBw+ql5eXfvrppxoXF5dqnaNHj2qHDh3U2dlZ//jjD1Xl2J6a3bt3a5EiRTQoKEjbtGmj/fr1U29vb82dO7cOHz7cqNepUyctXLiwurm5abVq1bRgwYJWJ/l4ft555x0dMGCA0TP6zz//GHPDa9Soob/88oueP39eY2Nj9fz58zZure1cu3bNqvc4Nfv27dOcOXPqmDFjVJVjwNPasWOHNm/eXL28vDQqKkqnTJmi2bNn1+XLlxt1EhIStHTp0pozZ84UnTp4esnPoWNiYrRTp066YMECVb03HN/JyUnHjh2rpUqV0nLlyumBAwdSPMfLdkGbYI+nEhkZqfb29lYnJ3PnzlWLxZKi175Hjx7q5+f30n34Xybnzp0zTuROnTqlTk5ODzyxe/PNN7VVq1Zp17hX1JkzZ9RisajFYtHChQtrcHCwTp482Vjw58SJE9qwYUNt2LCh8Zn+z3/+o+XLl9fLly/bsumvtalTp2qNGjWswvqxY8d0+fLlOnz4cJ01a5ZRPnbsWLVYLPrll19yEvQYEhMTdfDgwRocHKwJCQnGPouKitIdO3bo999/r8ePH9fExEQ9ffq0fvDBB2qxWHTFihU2bvnLJyIiQrNmzar9+vWzOl4kncR7eHjoxIkTjfINGzbovHnzdPny5Xr69GlbNPmVlnQC/+2332qtWrWMz3bS3PA///xTAwMDtUCBAlq2bNmXbnhtWjp37pzmy5dP586d+8hwP3ToUC1UqBAL5T2j3bt3a9OmTTVLliwp1nRI6g1OSEjQihUrMoX1OUl+TjB79mxVvTflNel8vECBAjp58mRVvXfcsFgsmidPnpf+s06wxxO7deuWlitXTn18fKzmdIeGhqrFYtG+ffvqX3/9Zcy3un79unp6eur//d//2arJL7Vr165p7dq1NTAwUHft2qXR0dHq7OxszLm6/4LIwoULtVixYrpx40ZbNPeVUqNGDbVYLPrJJ59ovXr11N/fXx0dHbVmzZo6bdo0HTdunDZt2lQbNmyoy5cv1xs3buipU6ds3ezXVmJiovbt21cDAgKMsvnz52tgYKDmzJnT6A3t0KGDsX3SpEkaGRlpi+aa0ltvvaVNmzY1fv/555+1VatWmi1bNs2cObPmy5dPlyxZoqr31jno1asXa3vc5+DBg2pnZ2esnpx0DE/67549e7RatWpavnz5VHuA8OxiYmL08OHDKe5WEhcXpwULFtTx48cba9Uknxu+fv36FCO4XkdNmzZVV1dXXbRo0UPD/Y4dOzR37tz6/fffc/H0GUVERGhISIhmz57dmIbzMg71fhUk/6yOHTtWM2XKZHVnqWnTpmmdOnWM9XgWLFigH374oX7wwQcvfSclwR5PZP/+/Xru3DldtGiRVqhQQdu1a6dnzpzRCRMmaJYsWbRFixbav39/LVasmHp5eWnTpk21c+fO2rlzZ64yPsS8efO0QoUKGhwcrN9++62WKlVK//33Xz179qweP35cz5w5o2fPntULFy7oDz/8oHny5NEzZ87YutmmlfzAXKVKFS1ZsqSuXbtW4+PjddGiRTp06FDNly+f+vv7G736NWrUeODQZLxYhw4dMq6Sr1y5UtOlS6fvv/++vvPOO5otWzb9+OOPdcOGDaqqOmLECPX19SVsPoGoqCjjeDJx4kQtW7asjh49Wvv06aNeXl7apUsXI8xXrlxZq1SpYjz2de7ZTM2dO3f0448/Vjc3N/3222+N8vunTS1btozRDi/Ivn37tGnTplq/fn0dP358iu3fffedZs6cWQsWLMjc8Psk/25877331MnJ6YHhPjExUQ8ePKitWrXiAtVjetQIiF27dulbb72lXl5exu0VX/YgaWabNm3SHj16WE17UL23gF7u3Ln1xo0bGh0drYGBgTps2DBj+8v8b0Kwx2OLiIgwhrWq3pvvXa5cOS1Xrpw6Ojoat2dTvTeU659//tEWLVpozZo1U50vDuurhj/99JNWqFBBK1asqBaLRbNly6ZOTk6aLVs2zZIlizo4OGjWrFm1VKlSfIk+g/tvy6iqGhAQoHnz5jXCoarq+fPn9fDhwzp8+HANCQmh19dGIiIiNFOmTPrNN98YZXPmzNGaNWtq/fr19c8//9To6Ghj248//qgFChRgZMVj2r59u+bLl09Xr16tqvd6kzt37qzFihXTIkWK6M8//2x114EJEyZomTJlrBYlhLUjR45oly5dtEKFCsb3peq98JgUIGNjY9XFxSXF3U/wbHbv3q1eXl76ySefWK338++//xon47t371Zvb28dN26cqjJX+X7JvxuTh/vkt2FLWvStbNmyGhsba4tmms7Jkye1TJkyj1w/Y/fu3frWW29pnjx5uCPDC7R06VItXry45suXL8UI2TNnzmjevHnVzc1NCxYsqH5+fqa5iE2wx2OJiIhQe3t7HTRokFX5ggULtGjRolqvXj2r8J78vtHcz/jhkh8sFi9erCVKlFB/f38dNWqU7t69W3fv3q0bN27UjRs36t69e/XYsWO2a6yJnThxIkUvbvIe+EqVKmnevHl17dq1KQ7gZjmgv2qSjjupLZR348aNVHs/+vTpo3Xq1GHBvMcQERGhWbJk0b59+1qVx8XF6Y0bN1Jddbljx44aHBxsdZKP/0kK7kePHtWOHTtqhQoVdNKkScb2pBPH1atXq5+fn+7Zs8cm7XwVnThxQn18fPTjjz+2OmaPHz9eixUrppMmTTLKBw0apIULF2bkm967ELV27VqrsuTfjUnh/qeffjLuS9+9e3fNmjWrsWo7Hu3GjRtasmRJLVy4cKp/98lHjezZs0dr1KihRYsW1Vu3bnHx6QWIiIjQd999VzNnzmwsAKn6v2P0+fPnddy4cTpt2jQj05hhSgTBHo+0f/9+zZ49u9U9dZN/uOfNm6dly5bVtm3bakREhFHO0LbU7dmzR//v//5Pt27danx5Jj9o//zzz/rmm29qSEiIMUzw/jp4MkkL5WXNmlWHDh2qP/zwQ6r1KlWqpPny5dO//vrrpR5q9TqIiIhQBwcHHTBggFX5ypUrU70P/aVLl7Rfv37q4uKiu3fvTqtmmlbSRZOBAwdalR85ciTV49K1a9d04MCBmiNHDkZg3Sf5sSJ5r/yDwr2qaq9evbRhw4ZWo03wbCZOnKjVq1fXCxcuGGX/93//p9mzZ9fKlStr5cqVdfLkyXrnzh3dt2+fenl56axZs17r79aLFy9qunTp1GKxaK9evVKduqCq2rp1a3VyctKFCxdq165dUyzwhgc7efKk0Ut/7do1rVGjhubLl++B31OJiYl68eJFPXToECPPnpMH5ZF9+/Zp69attXTp0vrdd98Z5akFeLOcExLs8VBJPToWi0XbtGljNfwy+R/KnDlztGzZstqxY0erMIr/SUxM1Li4OPXz89OMGTNqt27dtEKFCvrXX3+lWAV54cKFWq5cOW3Tpg2L5D0HcXFxGhQUpN26ddMBAwZo4cKFtW7duvrDDz+kCImVK1dWR0dH9rsNnTx5Uh0cHLR79+6q+r9jzYgRI7Rw4cIpRl6MHDlSGzVqpEWKFOE2YY9h37596uTkpL169bIqHzJkSKp3ffj222+1VatWmjdvXk7m7/Pvv/9qzZo1ddKkSanum9TC/bBhw9TFxcVqsSY8u2bNmmnDhg1V9X8XpVq1aqV//fWX3rhxQ99//30NCAgwpke89957TGtT1S5duugnn3yiI0eOVH9/f/Xz80t10dH33ntPLRaLZsmShePAY9qxY4c6OjrqTz/9ZJTFxsZq9erVUw338fHxGhISogEBAY+cj4/HkzyrbN26VcPDw3XXrl3GBexdu3bpe++9pxUrVtTvv/8+1ceZCcEeDxQREaF2dnYaGhqqu3fv1uzZs2tQUNADw/28efM0f/782q1bN4ZpPsRXX32lFSpU0PXr12vv3r21ePHiWq9ePZ00aZJVyFy0aJEWKFBAO3XqxKJtzyAxMVFv3bql3bp10/79+6uq6tmzZ7V79+76zjvvaKFChXTevHlWa0Q0btxYDx48aKsmv/aWLFmifn5+2qRJE6P3beTIkeri4qLh4eFWdePi4nTx4sU6fPhwPXr0qC2aazojR45Ui8Wi06ZNM3qMR40apW5ubvrbb79Z1T127JgOGjRI+/Tpk2KF8dddYmKidu3aVdOlS6cjR45UJycnHT58uP7+++9W9Q4dOqQdO3bUqlWrauXKlTVz5szMnX0BWrRooZUqVXrg9piYGC1VqpS2adMmDVv1crt7965++umnxj65e/eujhgxQtu2basuLi46YcIEq2Pu//3f/1mNzMSDJb/l5f1S67lPSEhgisNzlnw0zoABA7RIkSLq5uamVapU0Y4dO+q1a9dU9X93JKhSpYp+9dVXtmruc0GwR6quXr2qefPmtZrb+vfffz8y3P/3v//l5DoVBw8e1Pnz52tiYqLu2rVL3377beOK986dO3XhwoVqsVi0fv362rVrV2P/rlu3jv35jJIO7JGRkeri4qI//vijsa127dqaOXNmrVChgvr6+mrr1q317Nmztmoq/r/ExET973//q1WqVNHAwED99NNPNUeOHPrHH3+kqHvlyhVVNcfct5fJRx99pD4+Pjp79mwdPHiwurq6plgZWFWNi7RcrE1dRESE5suXTzdu3KgrV67UZs2aably5TQwMFDXrFljXDg5duyYtmrVSvPkycOokufk7Nmzxsrhqqp9+/bV7Nmz65o1a4zjftL5yZ07d/TOnTv63nvv6ahRozQxMfG1HoKv+r/vxujoaM2dO7dOmDDB2NawYUN1dnbWKlWqaNGiRbVSpUp8bp/Arl27Ul2Xatu2bcb6L7GxsUa43759u3700UdMcXhBRo0apZ6enrpu3TpNTEzUbt26qYODgzZr1sw43961a5c2atRIu3TpYupjA8EeKRw7dkyvXbtm3F5K9X9fAJs2bUo13Jtl7okt7Ny5Uy0Wi06ZMsUoa9asmVatWtX4vX379url5aVDhgzRsmXLqr29vfbv39/UB5eXSdLJXd++fY2LVe+//756eXnpkSNHNDIyUmfMmKEFCxbkQspL4u7duzp//nytVKmSWiwWXbBggapaB/i+ffuqj4+PsaATnsyHH36oLi4umiVLFl20aJGqWl+oHTFihHbu3JkhoQ9w9+5djY+P1w8++EDHjh2rqvdO1q9evaoWi0V9fX3Vz89Ply5dqqdOndLr169b3WEAT+/atWvaqFEjrV+/vjH97/Lly5orVy719/fX7du3GwvlJYX4AQMGqI+PD7feTSbpb3vUqFHarVs3Vb333ejp6anHjh3T06dPa3h4uAYEBDBi5zEdOnRIs2bNqp07d7YqHzp0qHp6elqdW8fGxmrdunWZ4vAczZs3z+r3gwcPauXKlXXp0qWqqrp8+XLNkiWLtmnTRn19fTUoKMjouT906JDxHWjWcwqCPazcunVLGzVqpJ6enkbP5f0rgicP99zm5OF2796tDg4OxhDw5IsqVa1aVbds2aJt2rRRT09PqwWpRo4cyZfoUzpx4oROmTJF+/Xrl2KRr/nz52uuXLm0Vq1amitXLt26davVdla/t40LFy7o+vXrdciQIfrNN9/oypUrVfV/PfeVK1fWBg0aWIWiwYMHa9asWa2mUCB1V69e1X///Vdnzpypq1evtppm0q9fP/X09NQpU6bopUuXjPLBgwerxWKhl+4+qR0jvvnmG3V3dzfuANOpUyf19vbWRYsWaffu3dXBwUFr166d6l0G8PRmzZqlNWrU0KCgIGPo8p9//qleXl5arFgxHT9+vJ4+fVp//vln7dq1qzo6Or7WwenkyZP67bff6pQpU3TNmjVW29asWaNubm5avnx5zZ07t27bts02jXwF/Pbbb5o+fXr95JNPjPO4zz//XHPkyJFimo7qvSki77//PlMcnoNFixZpyZIlU8yPnz9/vp45c0Y3btyoXl5eOnXqVFVVDQkJ0XTp0mnVqlWtjs9mnV+vSrBHKtavX6+1atWyuhXM/cNcN23apO7u7lq/fn3C/QP8+++/6uLiosHBwaqqVkP/oqOjtXHjxuri4qKFChUy5lua9Qrhy2LPnj3q5+en7du3N+5RfL933nlHXVxcUp3Dxv5Pe5GRkVq9enUtU6aMenl5qaurq1osFh04cKDRm7RgwQKtUqWK1q1bV2/cuKFjxozRzJkzs1DnY9i3b582adJE/fz81NnZWS0Wi7755ps6efJko07Xrl3Vx8dHv/zyS42Pj9fhw4ezf1Nx6tQpLV68uDEnNvnJX2BgoI4dO1ZbtWqlnp6eVkPE16xZY9VLh2eTfIRg0rEhKCjIuAi1Z88eLVeunGbNmlUtFovmy5dP69at+1rfLWPXrl2aN29erVChgrq5uWn+/Pl17ty5VnU++ugjzZEjh/711182auWr44cfflBvb28dOHCg9u3bV11dXXXFihUp6iUFf849np+k4/KmTZtSjCbu37+/dujQwTi3GDFihNapU0f79Olj6jCfHMEehuRz0TZv3qz169fXN954Q8+fP6+qKcP9+vXr1cfHJ8WK7vjfoileXl7q7++vf//9t6pa3wppzZo16ujoaHWLDTy9pAspAwYMsLrd0fTp0/XXX39V1XtfntOnT9fy5cvr4cOHVdXcV2bNLiIiQrNnz659+vQxQuSuXbv0s88+0wwZMhir4icmJur8+fO1Ro0ami1bNs2UKROh8zFERESom5ub9ujRQ1esWKFXrlzRJUuWaNWqVdXDw0NHjx5t1O3evbsWKVJEq1evrvb29uzfVFy6dEnffPNNzZcvnzEaKOn4MWrUKM2cObP6+voaAZKT9efr9OnTevbsWWOOcpK5c+dqpUqVtEWLFkZP8+3btzUyMlJXrVqlZ86cSfGY18muXbuMW4feuHFD165dq7lz59Z69erp9evXjXO7RYsWaYkSJYyOBqZYPr4bN27oxYsXddWqVcY58dKlS9XNzU3Tp09vtdp60nFhyJAh2rBhQzrHXoBt27apxWLRzz//3Oo4nLT6fZJ33nnH6iL3q3A+SLCH1YrryedSduvWzZgnmDQs//5wz2rtKW3btk2zZs2qgwcP1q1bt2qzZs20VKlSKcJ9TEyMtmzZ0rhS+CocUGwlJiZG69atq+3bt7c6GQkLC1OLxaJ2dnbGonk3btzQAgUKaPv27W3VXOi9k82sWbMaiwvdf8/0L774Qi0Wi/Glm5iYqLNnz9b69eu/1j1vjytpGtDgwYNTBMyIiAh9++23NW/evPrLL78Y5R988IFmy5aNIaGpSNqHFy5c0Lp162quXLmspvpcu3ZNfX19jYtReL6OHDmiFotFXVxctEyZMjpq1ChdsmSJsX3VqlVasWJFfffdd43vWlUurhw9elSzZ8+e4k4AFSpU0Pz586e4tWX16tW1WrVqadhC8ztw4IC2adNGixYtqpkzZ1ZHR0cNDg7WkydP6oYNG9Td3V179epldWvFwYMHa7p06bg7xnOS2vnzf/7zH82UKZOOGTPG2D5r1iwtU6aMli1bVv39/dXX19fINa/KsYJg/5o7ceKEtmvXTv/880+r8jFjxqiLi4t++eWXWrNmTS1SpMgDwz3+Jz4+XsuVK6c9evQwytasWaNvv/22li5dWjdt2mRVf+LEiZoxY0ZjygOezqFDh7RQoUJGz7yq6uLFizVnzpw6a9Ys7d27t2bLlk3nz5+vqqpjx47VEiVK6NWrV1+Zg7mZJIWgggULGmX3r1J9/vx5bdKkiZYoUcJYWTwxMZHejccQFRWlPj4+WrlyZaPszp07Vic/W7ZsUQ8PjxRBNPloF6gxbz65CxcuGOt0JA/3Y8eO1Zo1a+rx48fTsomvhTNnzqizs7Pa2dlphw4dtGTJkpo/f34tVKiQtm3bVjds2KBDhw7Vpk2bauvWrQlM/9/ixYs1V65c2qVLF+OCXdIF79KlS2v9+vW1devWGhYWphcuXNCpU6dqpUqVOA48pl27dqmXl5d+8MEHOnPmTN23b5/2799ffXx8tEiRInrkyBENDw9XLy8v7dGjh549e1aHDx+udnZ2fEZfgNmzZ1tdQJk0aZJaLBZjdNr169d15syZ2r17d+3du7eRZ16l0SkE+9fcqlWrtEiRItqyZUtdv369qqqOHj1as2fPboT9TZs2afXq1fWNN95g2P1jSPpCTB5S1q5dq82aNUsR7mNiYrRq1arGsHA8nV9//VWzZs2qx44dM8p27dqle/bsUdV7Qzg/+ugjtVgsGhkZqfv372fOqw3FxcXpjBkz1MHBQT/55BOj/P6LLF999ZVmz55dL126xIiWJ3D8+HFt3ry5VqtWzepuHEn7MOm/ffr00TfeeEPj4uJYODIVBw4c0EqVKmlwcLCGh4dbjRRJGiXk6empkZGRqvq/4Z+zZs2yVZNfOadPnzaO66dPn9YcOXLou+++q9u2bdNz587p559/ri1btlRPT08tVaqUWiwWtVgs2qZNm9f6bg7JOwvmz5+vZcuW1a5du2r37t3V1dVVf/zxRz169KguXbpUhw8frl5eXurj46N+fn564sQJG7bcPJKmOAwcODBFh9fChQu1ZMmS+uabb+r169f1v//9r+bLl099fX3VwcGBqU4vwLVr19TR0VErVKhgdeeLpHA/atSoVB/3qnVWEuxfU8lP4pYvX64VKlTQkJAQ7dy5s7q6uhqrUifZvHmzlipVSsuXL6937tyhl/M+hw4d0o0bN6b4Qky+n5OH+6SVvG/fvs1Kyc/Brl27NEOGDDpt2rQH1vnpp5/0zTff5HZ2L4nbt2/rDz/8oJkyZdK+ffsa5cmPLSNHjtQyZcrYonmmlbT/Dh8+rO3bt9cKFSro119/bWxPfoEkJCREa9SokeZtNIOEhATt2bOnERTr1KmjDg4O2rJlSw0NDdUTJ07o8ePHNSgoSPPly6f79u1TVdWBAwcaQR/PZseOHZorVy5dunSp1R1lXFxctHbt2nrq1CmjbkREhK5du1bfe+89rVmz5mv9b5C0xk/yEWxz5szREiVKqL29vX711VcpHnP16lX98ccfrS6O48FOnjypbm5u2qJFC6MsMTHRKiROmzZNs2TJYpyXzJgxQ318fKwW1sTTSy2HnD59WgsWLKiVK1e26jBL3nNv9tvZPQrB/jV05MgRHT16tC5btswoCw8P1/Lly6u9vb1+8cUXRnny4Snbtm1jiGEqLl26pNmzZ9fKlStrzZo1ddKkSVa35Up+Ir127Vpt0aKF5suXL9VV2fF4jhw5om+99Zbx+5kzZ7ROnTpavHhxY0XfpIN20v7v16+fNmzY0BjWDdtIfuLzsHB/8+ZNbdOmjX700UdcTHwCyac0HDp0SNu3b68BAQFWPfd37tzRy5cva1BQkI4ZM8Z4HKzt3LlTe/TooeXKldPx48fr33//rT179tS8efNq4cKFtWjRovrxxx+rxWLRvHnzcovS5ygiIkIdHBy0X79+RlnycO/m5qa1a9c2LqgkuXPnjt68eTNN2/oyiYiIUHt7e/30009V1frveuHChVqqVCnt0KGD1W0sGa3z5I4dO6bly5fXwMBAY7RrkuT7vGrVqlbnKkn3S8fzkzQyJ2m/nz59WvPly5ci3H/55ZeaLl06q3V7XkUE+9fM7t27NX/+/Pruu+9aLZqkqrp69Wp98803tWXLlla3O3mV5p68CHFxcVq6dGlt3bq1Llu2TIsUKaKNGjXSDz/8UC9dupRigcHly5drSEgIPcfP4K+//lJ7e3utW7euUfbDDz+oh4eHVq9e3WrESVRUlPbt21ezZctmDM1H2jp06JB+8803qV5USUhIMMJ9nz59jPJBgwZp3rx5re65jtQdO3ZM9+3bZyyElfxiYvJwn7znfuDAgVqoUCGOQ4+wY8cO7dy5sxYuXFjDw8NV9d534qpVq3To0KFaq1YtdXJyUovFwr58TpLC6cCBA63K9+zZo1euXFHVe595Nzc3rVu3rtWc2tfZzp071d7eXgcMGGBVvmPHDuP/586dq2XLltW2bduySOYzOnjwoNavX1/r1atnFe6TB8bq1asbtzzG85F8/06YMEHr1aunMTExVttOnTqluXPn1rp161qdQ0yYMEEtFovVha1XDcH+NbJ//37jdmAXL15Mtc5vv/2mFSpU0ObNm6e4ComUkk6gw8PDNTAwUG/evGnMW6tZs6bmypVL27dvn6J3PrUFmfD47ty5o6tXr9ZcuXJp9erVjfIpU6Zo/vz51cnJSYODgzUwMFAbNmyouXLlsjq5Qdq5fv26Fi5cWJ2dndXHx0fHjx+v69ats6oTFxdnhPvPPvtMP//8c82cOTP/Zo/h/Pnz6uDgoPXr19c6dero77//nuICyoEDB4xwP2vWLB0xYoRmyZLllT65eZ527dqlHTp00KJFi+qcOXOstl27dk3PnTvHvOTn5NChQ+rk5GS1AK2qamhoqJYvX17Pnj1rdDYcO3bMuKXs675OzZEjRzRdunQ6bNgwVf3fuUlYWJhWqlTJak2ZuXPnqr+/v77zzjtc7H5GycP9hg0bjPK7d+/qqVOntEGDBjpz5kxVfXV7iNPSX3/9pePGjdNx48bplStXdP369ero6KhBQUFGuE/67E+fPl0tFouWK1fOWB/s/PnzWqpUKasRy68agv1rIj4+Xjt06KCdO3e2Kr927ZoePHhQ16xZYwzHWrZsmVauXFnr1atnddsYPFhkZKSWLFlSFyxYYJS9//776uXlpW+//bZmzJhRGzZsqHPnzrVhK83t/gVO4uPj9c8//9ScOXNa3Z7nzz//1KFDh2rlypW1fv36OmrUKKuFVJC2rl+/ru3bt9dp06bp4sWLtW3bturu7q49e/ZM8eU6e/ZsY04ziws9nqioKPX29taPPvpIp06dqnny5NEWLVro8OHDNSEhwTiu79u3Tzt16qSurq6aMWNG9u8T2rVrl3bs2FGLFi1qdZxnGPPzNW7cOHVxcdHhw4cbHRBhYWHq6uqqv//+u1Ev6fvg0KFDmj9//tf6wsqVK1d07Nixxn5LEhYWps7Ozrp8+XJVtR7JM336dK1evTp35HkOHtRz379/fy1ZsqTVWhB4erNnz9bChQtrz5499ZtvvjHKt2/frh4eHtqsWTO9evWqUT5v3jz98MMPtUWLFsbFwF9//VXz5s37Sq8lQbB/jTRo0MBqvtqvv/6qXbp00SxZsqibm5sWLFhQL126pKqqS5Ys0Tp16rAKfioOHjyoGzduTFE+fPhwLVmypN69e1fbtWun3t7exlC3xYsXa8uWLV/7XoWndeDAAe3YsaOOHTtWT548aXxOVe/dTtDb29vq1l6qqd/XFLbx3//+V7Nly6anTp3SxMRE3blzp7Zq1Urd3Ny0fv36umLFCj1//ryqqv78888Mv39MST1AM2fONBZx2rp1q86cOVOLFi2qZcqU0b59+xq9dWfOnNHu3btb3aINjy8p3BcvXlxnz55t6+a8sj777DMtU6aMfv755zpo0CB1c3MzpkEkxy14712wa9y4sW7dulVHjhypvr6+Onr0aB0/fry6urrqH3/88cDHJg9BeDbJw/2OHTt09OjRmjVrVqY7PCezZ89We3t7nT17ttU6BePGjdPw8HCNiIhQT09Pbdq0qe7YsUPPnTunb731lk6aNMnqeS5cuPDKrxVGsH8NJC1EVb9+fQ0MDNQ//vhDhwwZoj4+Ptq6dWv97rvvdMOGDVq8eHGrRT5YrT11Xbt2VYvFYqxDkBQg9+/fr40bN1Y/Pz/NkydPiuH3r/Otd57F9evXtWbNmkZPboUKFbRgwYI6evRo/fXXX/X27dv6559/arFixbRmzZrG4+5fUAVpL/m+b9eunVVv0jvvvKPFihXTevXqaalSpdTb21sXLVpki2aa3saNG7VkyZJWFxyDgoLU29tbq1atqo6OjhoSEqLbtm3j7yEVT7JPdu/ere+++66++eabGhsby/58Du7evZviQuynn36qhQoVUnt7e124cKGqWq/3M2zYMH3rrbc0Li7utb6I+/333+ubb76pqvcudAwbNkwLFCigFovF6D1OfuGjT58+2rp1a1Xlu/F5O3jwoDZu3Fjd3d0ZFfUc/fvvv1q8eHGdOnWqVXnz5s3VYrFovXr1dOXKlXrw4EH18fHRHDlyaM6cObVUqVJWI6pel+MEwf41kPRhjoyMNFbzzZEjh86cOdPqylWHDh20UaNGtmqmaVy7dk3btWunjo6OunbtWqtt7dq1U4vFwmI+z9nChQu1QYMG2rRpU/3iiy/0yy+/1MqVK2uWLFm0UqVK2qRJEx0wYIBaLBZt0KCBrZuLZJKOP6NGjTJOQDt06KAeHh5Gz/Hq1au1b9++unfvXpu104ySn6h06NDBuLDVtm1b9fb21u3bt6vqvQWDGjZsyJSU+yRf6+RJQs7evXuN3mI8mwMHDujHH3+sgYGB+v333+uFCxeMbSNGjNBixYrpkCFDNCoqyigfPHiwZsiQgTU49N5w+zJlyhjHgqioKB02bJgWLlxYhwwZYlV3yJAham9vb9xuF8/f/v37NTAwkO+y52j58uXGLUWTPuddu3bVggUL6rJly7R27draoEED3bBhg968eVOXLFmiP/30k3Eh8HUb0UOwf0XduHHDOGlJTEw0PuCXLl3So0ePpjoEKyQkRHv06MGtpR4i6aASGxurISEhKcL98ePHtVixYvr999/bqIWvluTBZe7cudqgQQNt0qSJMS/w8OHDOn78eH3nnXe0YMGCRq8+U0hs48iRIzp27Fj9+OOP9ddffzUWs0lSpkwZzZYtm3p6eqY4KeeY82gnT57U//73vzpx4kQjACX9jfzzzz/aqFEjLVu2rObMmVO3bt1q9djX+RZgqTl9+rS+9dZbunTpUqPsUZ9BPqPPV0REhLq5uenbb7+tTZo00QwZMqSY4jBw4EAtXbq0Dho0SG/cuKFhYWGaOXPm17o3NPmddoYNG2Zc0Ls/3Pv6+uqgQYNU9d5UwcyZMxsX+/DisO7G8zVixAh1dXW1Kjt79qyxdsG///6rlSpV0vLly1tdGFR9Pe/qRbB/BR06dEiLFi2qnTp10p9++slqW9KJSfITlBs3buinn36q7u7uun///jRtqxkcO3ZMp0+frufOnbPq4UlISNDg4GDNmjWrrlmzRlXvLWLTokULq8U68GySf0kuXLhQq1evroGBgSlO7A4fPqx//fUX87NtZNeuXerl5aV169ZVb29vdXNz09DQUE1ISDCumI8fP15z586tmzZtsnFrzWfXrl1aqFAhLVWqlDo5OWm+fPms/gbi4uK0Xr16mi5dOquRWITR1K1bt06rVaumdevWtZq//bD9xb58fpLuUz9w4EAjkL7//vvauXNnvX79utVUwIEDB6q/v7+WKVNG7ezsXutQf/r0aW3RooWuWLFCVe/1wgcFBanqvRCTtC/PnDmjw4YNUz8/P33jjTde+4shMK8FCxaog4OD8ZlPLunzPnr0aG3YsCFTiFU1neCVs3z5cjl79qyULVtW2rdvLx07dpSxY8eKiIjFYrH675QpU6Rv374yc+ZMCQ8PlyJFitis3S+jixcvSrVq1aRz585SuXJladmypQwfPlw2b94sGTNmlGnTpknHjh2lcePG8tdff0n27NmlWbNmsmrVKomJibF1800pMjJSRo4cKatWrRIRkYwZMxrbgoKC5MMPP5QbN27IsGHDJCIiwtjm4+MjVapUkUKFCqV1k197e/bskYCAAOncubMsXbpUzpw5I/nz55cFCxZIQkKCZMiQQUREGjVqJFevXpVdu3bZuMXmsmvXLqlQoYI0b95cfvvtN1m9erVcu3ZN+vfvLyIiiYmJkjlzZhk5cqTky5dPIiMjjccmHetxz5UrV0REpGrVqjJ48GDJnDmzjBkzRpYvXy4i9/ZXYmKiUf/OnTty8OBBYxue3dmzZ6VChQrStm1bCQsLkzt37oiISEJCgkRGRkqpUqUkODhYvv32WxERCQsLkypVqsi1a9dk69atUrZsWVs236bi4+Pl9OnTMmHCBNmxY4fcvn1b7OzsREQkffr0ki7dvdN6b29v+eyzz6ROnTpiZ2cnf//992u932Be5cuXlwwZMsjUqVPl5MmTVtvSpUsn165dk/Xr10uRIkUkS5YsNmrly8OiqmrrRuD5unLlipQpU0YmT54sJUqUkO+//15+++03sVgs8t5770njxo0lf/78cunSJWnfvr04OjrK4MGDCfWpOHXqlISFhcmGDRvEyclJWrduLRMmTJDExESxs7OThg0bSsWKFeXrr7+WgwcPypw5c6Rq1apy8eJFyZEjh62bbzpxcXFSvXp1iYqKkipVqsixY8dk1KhRUrBgQfH29jbqzZ8/X2bMmCHOzs7y6aefcsJiQ6dOnZK8efNKmzZtZObMmUb5u+++K7/88ots375dihUrJnfv3pX06dPLiBEjZN68ebJkyRIpXLiw7RpuEidPnpQCBQrIgAEDZPjw4Ub5m2++KXFxcbJnzx6j7OLFi9K6dWspVqyYTJw40QatfblduHBBQkJCpFy5cjJy5EgREfnzzz/lyy+/lOvXr0u/fv2kXr16IiKiqnL79m355JNP5PDhw7Jw4ULJmjWrLZv/ytiyZYv07NlTbt26JStWrBAPDw/5/PPPZejQoRIWFia3bt2S1atXy+HDh+W7776TGjVqiIjI5cuXxdXV1catt73Dhw9L9+7dJUuWLHLixAlJTEwUPz8/sVgskj59eomPjzf+Py4uTiZNmiQeHh62bjbw1ObPny/t2rWT5s2bS9++faVUqVIiInLixAnp1KmTXLhwQf755x/JkCGDqOrrfRHWtgMG8LwlDf8eO3astm/f3mqbs7Oz5s6dW52cnDQsLMxY1Z2hKw936NAh7devn9Utjk6cOKG9e/fW5s2bq4ODg5YsWVItFov6+flZzX/Dkxs6dKgWLVpUjxw5ol26dNEaNWpouXLl9IcffrAaYvzjjz9q6dKlNTg4WG/dumXDFr/eEhISNE+ePFq+fHljqOeYMWPUYrForly59K233tKSJUtqhw4ddPPmzTpy5EitUqWKcXs7PNyyZcvU29tbmzZtapR9/vnnarFYNEeOHNqxY0etWbOm/vzzzxoTE6MTJ05Ud3d3q1sC4Z5z585pu3bttFKlSjpixAijfNWqVRoYGKg1a9Y0huUnJCRo9+7dWaTtBdm8ebNWrVpVixcvrgMGDFAPDw+r+9SvW7dO7ezs9Ntvv7VhK19e+/fv1wYNGmjWrFnV1dVVP/jgA61Xr542aNBAmzdvrm+99ZY2atSIRdzwSrhz545Onz5dM2bMqLly5dL69etr7dq11d/fX/39/Y0pm0yBZY79KyX5/L/Vq1eru7u77t69W1XvrZjs6empW7Zs0a+//lp9fX31jTfesLofOO65fft2iqB48OBB7d27txYsWFAnT55stW3nzp26ZMkSfe+993TXrl1p2dRXStLn98yZM/rWW2/phg0bVPXeCcx3332nFotFq1Spor169TIWZVu9evUrf09SM4iLi9MiRYrom2++qT169FBXV1ddtWqVnjp1Sm/evKnjxo3Tli1baqZMmTQwMJB1EJ5AfHy8Llu2TPPnz6/NmjXT0aNHa44cOXTOnDm6e/duXblypbZp08a4uNi9e3f+Ju5z4cIF40LS2bNntUePHurv7//AcP/bb79pv3791N7enlD/nCU/T9m0aZPWqVNHLRaLzps3T1X/tzDcxYsXtXTp0jp37lybtNMMDh06pI0aNdI6deoY53rAq2znzp3arVs3rVOnjnbo0EG/+uqr13b1+wdhKL7JxcbGSmxsrNjZ2aUY+t2tWzeJjY2VW7duyfr16+WPP/6Q0qVLi8i9oVxOTk7i7u5ui2a/tA4cOCCff/65HDt2THx9feWjjz6SokWLiojI0aNH5euvv5bffvtNPvzwQ/noo49s3NpX0+3bt+Xdd98Vi8UiixYtEhGRrl27ypIlS+Sjjz6SqVOnys2bNyU4OFjGjx9v49a+nk6cOCFLly6VK1euSMmSJeWtt96SW7duSYUKFWT37t0yefJk6dq1a4rHrV27VgoWLCi5cuWyQavN49y5c/LPP//InTt3pESJElKgQAH5/fff5ZNPPpF9+/bJqlWrpGbNmlaPOXnypPzzzz/i6+srvr6+Nmr5y+fIkSNSq1YtqVmzpgwfPlxy5swpZ8+elc8//1y2bt0qTZo0kUGDBonIvWH5X331laxZs0Zu3rwpmzZtkjJlytj4HZjf7du3JWPGjMYQWU02VHbjxo0yePBgOXfunPz555/i5eUlIiKDBg2S+fPny7p16yR37ty2bP5L7eDBg9KzZ08RubfPqlSpYmzT131IMl4bSVP9IAzFN7PIyEitVKmS+vr6arZs2XTq1KkaExNjXBH/9ddf1dXVVX19fY37RbOq74Ml3XqnZcuW2q1bN3V2dtbGjRtbDWk9cuSI9unTR4sUKaJfffWVDVv7akr6fB44cEALFSqkGzdu1Hbt2qmXl5fRI5GQkKCjRo3Sw4cP27Kpr61du3Zpnjx5tGzZsuru7q4Wi0XHjh2rqqq3bt3S4sWLa+nSpXXbtm3Gv2fy2xbi4Xbv3q0FCxbUIkWKqMVi0fLlyxu3ZPvll1/U19dXGzVqZNRn6s+D3b17V4cOHaoWi0Vr1qypXbt21ZMnT6rqvZFBqfXcL1++XIOCgjQyMtJWzX6l7NixQwMCAjQ6Otqq/P6e+6pVq2rRokX12rVr+sUXXzBa4gkcPHhQGzdurBUqVOAe9XjlkWMejmBvUjt37lRHR0ft1auX/vTTT9q2bVur264lqVOnjtavX982jTSRXbt2aZYsWfTTTz81ypJOCJcvX25VN2nOfY4cOXTq1Klp3dRXXmJiosbGxur777+v7u7uWrhwYeOe3Myfsq1du3apg4OD9u/fX2NjYzUyMlJ79uypGTJk0PXr16vqvXDv6+urJUqU0O3bt/Ml/ASS799Dhw7pH3/8ocWLF9fq1avrxYsXNS4uTn/55RctVKiQ1XGdIYgPFhkZqa6urlqzZk2tV6+eduvWTU+fPq2q1uF+1KhRxmNu3rxpq+a+UpJuadevX79Utyc/Nvz9999as2ZNtVgsmjFjRm7N9oT27dunzZs31xMnTti6KQBsiGBvQpGRkZo5c2arXoZNmzZpxowZtUePHlZ1//jjD33jjTd01apVad1M04iNjdX8+fNr8eLFrco/+OADtVgsumTJEo2IiFDV/52IHD58WAcNGkSv8VN6nJ7cJUuWqMVi0UWLFqVVs/AQZ8+eVTc3N23WrJlV+Z9//qnZsmXTP//80yi7deuWlihRQvPkyaM7d+5M45aa08GDBzVr1qzauXNnq/Kvv/5aHRwc9MCBA6p6b8790qVLtVixYhoQEGCLpppCYmKicSEwNDRUe/furcOGDdOyZctq9+7drcJ9r169tHDhwvrFF18Yj8WziYyMVAcHB6uL5alJvq/Xrl2rwcHBzBd/SvHx8bZuAgAb4z72JnP79m2ZOHGixMfHS+fOnY3yP/74Q+7cuSOXLl2SqVOnyo4dOyQqKkrq1q0rly9fltWrV1vdmxf/kz59evn444/l0KFDMmLECBER+fzzz2XmzJlSs2ZNWbRokdSoUUNq1qwpnTp1klWrVom7u7sMGzZMChQoYOPWm8/x48elZs2aEhsbK+nSpXvg57Jp06bSvHlzWblypdy6dSuNW4n7nTp1SsqVKyenTp2SdevWGeVOTk5y9+5dyZw5s4jcu++3nZ2dbNmyRby8vMTJyclWTTaVffv2yc2bN8XV1VWOHDlilHt6eoqzs7PcuXNHVFUyZcok9erVk6FDh8rt27dT3Nf3dXflyhU5e/ascbsvEREfHx9Zt26d9OzZUzp06CCbN2+Wzz//XM6cOSPe3t7Sp08fefvtt+Wdd94REe5X/6z27Nkj1apVE09PT+O2gg+SfF9Xq1ZNvv32WylevPiLbuIrKVOmTLZuAgBbs/WVBTy5AwcOaK1atTRPnjwaHx+vEydOVCcnJx06dKiGhoZq8+bNNWfOnOrn56f9+/fX3r17c8uTR0hISNApU6aoxWLRqlWrqqenp3Hbo8TERD1z5oyGhYVpQECA5smTR8+dO2fjFpvX/v371dvbW8uVK2esX/Cgnvtx48Zpjhw59NixY2nYQjzIxo0bNSgoSIsXL6579uzRmzdvqoeHh/bp08eqHkPDn86sWbM0Z86c2rNnT7169apeuHBB3dzcdODAgSnqJiQkcEu7+xw8eFB9fHy0cOHC+uOPP1rNk69fv7726tVLVe/dLtDf318/+ugjY+gy03yej507d6qDg4O2aNFCs2fPru3ateOWugCQRgj2JpJ8yNrRo0e1SpUqam9vr05OTrpp0yarups2bdKpU6dqyZIlmXP1EMkDSEJCgk6fPl2dnZ01ODg41Tqq927DgycXFRWlZ8+eVVXVvXv3aokSJbRkyZIaGxurqtbhPumzfvnyZa1bt64eOXIk7RsMQ/Jjz4YNGzQoKEh9fX3V2dnZKtTff4GGIc2PJ/l+mzlzpubKlUvbt2+vXl5e2r1791TrwVpiYqIOGTJEHR0dNWfOnFqqVClt0aKFtmvXTi9fvqzfffedvv/++8b8+dGjR2uRIkX0k08+0Tt37vBZfQ727t2rmTNnNi5E/fnnn5o1a1Zt166d3rhxw8atA4BXH7e7M4E7d+5IhgwZRMT69iVHjhyRTz/9VFauXCn79+8Xd3d347YySbgFREpHjx6V9evXS8uWLY3hw0lu3Lghc+fOlQ8//FBCQ0Pls88+ExExhounS5eOW8g8hR07dkiNGjXkp59+ktq1a4uISGRkpLRq1UrSpUsn69evF0dHR2Pf3r59W9q2bStnz56V33//Xezt7W38DqD33aLqyy+/lDVr1sjChQulRo0akvRVwt/G00m+f2fPni29evWSnDlzyk8//SSFCxe2cevM4dKlS/L555/L4cOHxcXFRUJCQmTw4MHi7Ows8fHxxu3sPvzwQxER+c9//iNNmzaVfPny2bbhr4hp06bJhQsX5P/+7/+MstWrV0vTpk2lRYsWMnnyZHFwcLBhCwHgFWe7awp4HJGRkfr/2rvzgBrz/Q/g76eSIsvQQmqEokQhRYvlGjE17h37MkMy1hmym1BqMNYsZWes13qvISbL2AZZxlKUhlBGhFCWMjRt5/P7w68znYmZ4Rqnk/frn5nzPM853uepTn2e7/f5fPv16ycbNmx44f7k5GRp1aqVWFtbq5fxKTqlkKMQmrKyssTGxkYqVKgg9vb2smTJEnXH9UJPnz6VpUuXir6+vkybNk1LSUuPuLg4MTExkbFjxxbbl5CQIA0bNtQYuX/27JkMGzZMTExMuHRPCVP086RwWr6Tk5McPXpUi6lKj6Lnd9OmTVKjRg0ZNWoUm3T+BYW/9+7fvy8jRowQd3d3CQ8PFxGRAwcOyMSJE0VfX1/+85//aDNmqXTjxg1Zv3695ObmvnA/R+6JiN4OFvYlWH5+vvTp00dq164t1atXlx49esiUKVM0fjGqVCq5du2atGzZUmrXrs17kf/Eo0ePpE+fPrJ27VpZv369fPrpp2Jubi5BQUEaKwcUFBSo77mfPXu2FhPrtvj4eDE2Ni7WGfny5cvq/y86LT8jI0PGjBnDNYy17I+mfP9+Wn6vXr3E2tpajh8//jailTq/v/ha9PGaNWukZs2aMnDgQPn555/fdrQS7/ddwAuL+/T0dBk1apS4uLjIzJkz1ftTUlLear53QUJCgjRo0EA+/PBD2bRp00uPKyzuBwwYwHvuiYj+JizsS7gFCxaIn5+fPHz4UBYuXCgtW7YUW1tbmTVrlsYyUrdv35aGDRtKgwYN2LjqBQpHg0VEVq1aJRYWFpKRkSG5ubkSHR0tXbp0EQsLC+nSpYtER0fLo0ePRERk5cqVcunSJS2l1m2XLl0SAwODYiP1X331lVhaWsrdu3fV23766SdxcXERRVGkXLlyEhsb+7bjkojcu3dP4/HLCvyixefhw4elX79+7IPwF6SmpsqWLVtk9erVf9jQtOj5XbZsmdSvX1/j54Wer9vdpEkTmTlzpuzfv7/Y/sLi3s3NTUJDQ9Xb2STvzbl48aJUrVpVxo0bJ7dv3y62v/Dzo/D7+fDhw6IoigwdOvSt5iQielewsC+hCn8hZmdnS82aNWXx4sXqfStXrpQKFSqIiYmJjB49Wt29PS0tjSMSL5CYmCht2rSR1NRU9bZevXppjMR37NhRHBwcpEWLFtK4cWOxsbFRn1d6dQUFBbJ7925RFEXmzZsnmZmZIiIyY8YMMTc3l927d4uIZgFz/vx56dy5s8TFxWkl87suOTlZFEWRzp07y7x589Trphf6o8Z4hQ3J6OXi4+PFxsZG3NzcRFEUady48R9OCy96fh8/fvw2IuqEwvMyYcIEURRF5s+fL5UrV5YRI0bIli1bNI69e/eujBw5Ujw8PGT8+PHaiFtq/fLLL9K+fXsJCAjQ2F5QUCCZmZny5MmTF14YjI6OlsTExLcVk4joncJ17EuY7OxsAM+btOXl5cHIyAgTJkzAsWPH1Gt5//jjj6hRowZmz56N8+fPo3fv3ujWrRssLCxQs2ZNbcYvkU6dOoWnT5/CyspK3eDLzs4Ou3fvBgD0798fP/74I3bs2IHo6GhMnz4dPj4+sLa21mZsnZWQkIBBgwbB19cXERERGDNmDDZs2IApU6YgLCwMGzZsgK+vL4DfGq2lp6ejUaNG2Lx5M5ydnbUZ/531yy+/wMLCAmXKlMG1a9fg5uaGsLAw7N+/H8DzzyTgt0aSiqKof57Y3PCPJSQkoHnz5ujduzf27duH+Ph4pKSkYNu2bS99TtHzW7FixbcVtcTLy8sDAAwZMgT16tWDvb09jh49igcPHmDRokXw8PBAVFQUbt68CQsLCwQHB8PJyQmnT59GRkaGltOXHllZWUhNTUW7du3U2w4fPowvv/wSdnZ2qFevHqZMmYK7d+9qPK9Fixawt7d/23GJiN4NWr6wQEXcuHFD/P395cCBAxrbY2NjpXr16vLjjz/K0KFDpXr16nL27FkReT51dv/+/cVG1+g306dPFxcXF1GpVOrRnry8PKlfv76Ym5tLtWrVit3PzWWlXk9cXJzo6+tLSEiIelt4eLgoiiKKosiOHTuKPeerr76SgQMHSnZ29tuMSkWoVCrJzs6WUaNGyZIlS0Tk+cwgPz8/cXR0lM8++0z279/Pe2Nfw5UrV0RRFBk+fLjGdg8PD6lZs2ax5TPZ8PTlLly4IP3795d79+5JXl6ejB49WoKCgkTkt/vtDQwMpG7dumJjYyMrVqyQxMREyc3NLXabCb2ewh4/mZmZ4uLiIkOHDpXs7GyZM2eONGzYUP75z3/K3LlzZdKkSVKhQgWJjIzUbmAioncIC/sS5MiRI2Jvby89evSQI0eOaOwLDg4WRVGkRo0aGvfW04sVLRKnTJkibdq0UT8uLNqnT58u1tbWxbri0+u5ePGiGBkZqe9nLXpxZNWqVaIoioSFhan7F4iIhISEiKIovKe+hJg/f77UqlVL42vk7u4uxsbG4uXlJa6urrJ582a5deuW9kLqmFOnTomiKBIQECBpaWki8vyWFEVRxNbWVjp16iT9+/eXuXPnytOnT9W3rZCmwouGkydPVm/bvn27VKhQQW7cuCEiIv379xdLS0uJioqSadOmScWKFaVFixY8p29IXFyc+Pv7S2pqquTl5cnMmTPFzs5OzM3NxcTERBYsWKAxzd7JyUkGDRqkxcRERO8WFvYlzP79+8Xd3V3dxK3Q4cOHpVatWup7MtkA6OVu3bol3bp1UzdUCg0Nle7du4vI82KzcEQsLi5OjI2NZePGjVrLWlokJCSIqampODg4qLfl5eVpFPeFI/fTp0+X/Px8+eqrr6Rs2bIs6kuAostUtW3bVmbNmiUiIv7+/lKzZk05ffq0REdHS9euXaVmzZpy584dbUXVKYXf/wcOHBB9fX0ZPXq0BAcHy3vvvSeRkZESGxsrhw8flkGDBomDg4NUrlxZevbsKTk5ORy5L+L3Fw2L8vPzk5CQEOnevbtYWFho9Og4d+4cL0K9IXFxcaKnp6exwsnTp08lLi5OduzYoV5uV+T59/3jx4/F29tbFi5cqI24RETvJBb2JURBQYG6WI+LixMbGxvp2LGjxsi9j4+PtGjRQlsRdca1a9fE3d1dfHx8JDY2ViZOnCh9+vR54bHBwcHi5OTEZQL/B3FxcVKuXDlp3bq1WFpaakw5zs/P1yjuIyIixNDQUJo2bSoVKlSQmJgYbUR+5927d0/Onj2rsf58YTH59ddfS/fu3aVTp05iaWlZbEbLw4cP33ZcnZSfny8qlUr9/b9v3z4xMDAQRVGKNc3Lz8+XnJwcWbx4MVcX+J2XXTQstHjxYjEyMhJ7e3u5ePGiNiKWeufPn3/hsqUvW7de5PlsrNq1a/P7mYjoLVJE/r87D711qampMDQ0hIWFhbpJkqIoWLx4McaMGYM6derAwcEBX3zxBdq0aYOYmBj4+vpi6dKl6NKli5bTl2zJyckYNmwYypcvjxs3bkClUqFBgwZQFAUGBgbIzs6GkZERzp07h0qVKuHbb7+FmZmZtmPrnJiYGHh4eCAoKAjBwcFYtWoVgoKC8MknnyAiIgIAUFBQAEVR1M3XwsPDMW7cOJw9exaNGjXSYvp3U0JCAvr27YvMzExkZmaiWbNm6kaSAJCRkYGGDRvi2bNniImJgZ2dHYDnTfP09PQgIuqmh1TcgwcPULVqVfVjlUoFEYG+vj6OHz+O1q1bY9CgQQgODoalpSWA5z8j+vr62opcYsXHx8PDwwNubm64evUqunbtqv5cyc/Ph4GBAQDAy8sLNjY22LBhgzbjlkoXL15E8+bNMXr0aEyePFm9fdasWShbtiyGDRum/joAwJ49e7Bnzx5s3rwZBw8eROPGjbURm4joncSu+FqSn5+Pzp07o23btrh16xYURYGiKJgxYwZCQkIQHR2NpUuX4s6dO1iyZAlOnjwJe3t7NG7cGC4uLtqOX+LZ2toiIiIC2dnZuHLlCm7evIny5cvj3r17SEtLQ05ODrKysmBtbY1ly5axqH9Nz549w+eff47Q0FDo6+ujR48emDZtGjZt2oQRI0YAAPT19SEi6m7qI0eOREZGBot6LYiPj4e7uzu8vb2xefNmBAYGYu/evQgODgbwvOO4qakpRo8eDXd3d5QvX1793MILMyzqX+7q1auoUaMGfH19ERkZieTkZOjp6anPnZeXF/bs2YMVK1Zg8uTJ6o7hLOqLi4mJgaurK7788kscPHgQoaGhGp8rBgYGyMnJAQD4+fnhxo0buHz5sjYjlzrZ2dno1q0bzMzM0LdvX/X2WbNmITQ0FI6OjhpFfWRkJNatW4cbN27g2LFjLOqJiN42bU4XeNclJSWJvb29eHl5iYjIrFmzpEqVKrJ37171MQcOHBAvLy9p06aNXL16VWMKIv25pKQk+eijj8Tb21suXLig7TilWuE9wZmZmbJ8+XIxNTUtNi2/8BjeP/z2Xb16VYyMjGTSpEnqbffu3ZMqVapI3759NY49dOiQmJuby/bt299ySt12/PhxqV+/vnTo0EH8/PzEyspKli5dWuyWk71794qRkZH06tVL7t69q6W0JdvRo0c1Pj8eP378ws8VEZHk5GTR19eXuXPnvu2YpVZhA9qtW7dKrVq1ZODAgZKeni5hYWFSpUoV2bdvX7Hn5ObmSlJSkjx48OBtxyUiIuE99lr3888/S61atcTMzEyqVq2qXuqu6H3Ju3fvFm9vb0lNTdVWTJ125coVad++vbRv316jIaEIC8y/S9HiftSoUdqO805TqVSSn58vgYGBYmZmJhEREep9M2fOFEVRxM3NTSZPnixTp05VLws2aNAgcXZ21rggQy/27Nkzyc/Pl7S0NOnTp4/s2LFDVCqVLF68WFq3bi2tWrWSgIAAuXjxojx+/FhERHbt2iWmpqZsRPgX/NlFQ5HnKzr89NNP2ohX6ty6dUvq1asnKSkpIiKybds2sba2FhcXF6lcubIcPnxYRDT/Tvnmm29kz5492ohLRET/j4X9W1T4S/D3/71+/bo0a9ZM7OzsJCMjo9jxIr+tHUuv5+rVq9KhQwdp3ry5nDp1Sttx3gmZmZnyzTffiKIoMn78eG3HeWcVNuVMSUmRgIAAadasmSxfvlxmz54tVapUkWnTpklUVJQMGzZMXF1dxcrKSurVqycBAQHqZcTo5WJiYsTb21tdoE+ePFnq1aunLuCfPn0qzs7OoiiKtGjRQj788EPZtWuXiDy/IECvpmhxP3r0aPV2Xnx6c27fvi116tSRHj16yK+//ioiIlFRUVKtWjX58MMPJSkpSeP4oKAgMTIykitXrmgjLhER/T8W9m/JxYsXZeDAgXLy5En1L0oRzeLe1tZWPD095fbt2+r9nLr85iQmJkrXrl1ZrLxFjx8/lrVr1/IPPi25efOmfPHFF+qRt8LH9erVEwMDA/nhhx+KPec///mPjB8/XhISEt52XJ1TuCLEiBEj1NuePHki7dq1kw0bNoiISL9+/cTGxkbOnj0rW7ZskY8++khMTU3l/v37Wkqt+4peNAwMDNR2nFKlcCWHuXPnipOTk0RGRqr3RUVFibW1tQwYMEA9OyI0NFTKlSsnZ8+e1VJiIiIqxK74b0FBQQH++c9/4tChQzA3N4ePjw/q16+PkSNHqjtNA0BKSgratm0LKysrbNiwAVZWVlpOXvrk5ubC0NBQ2zHeKcIu6lqzcuVKhIeHw83NDVOmTIGVlRVu3bqFWbNmITo6Gv7+/hg1ahQAICcnB2XLlgXAr9lfcenSJbi5uSEwMBCTJk1Sn7OCggIMHz4cDx48QJkyZfDDDz8gMjISbm5u6udmZGTA1NRUi+l1X2ZmJnbs2AF3d3fUrVtX23F03sOHD1GlShX148zMTPzjH/+Aubk5vv/+e/X27777DsOGDUPHjh2Rk5ODf//73zh+/Dib+hIRlQAs7N+SZcuW4f79+/D19cXJkycxe/ZsODo6okWLFhgyZIj6j7yUlBQ0adIEbm5u2L17N7slE9H/ZNGiRdiyZQvq1KmD6dOno0aNGkhNTcXMmTMRGxuLLl26YNy4cQC47NpflZCQgNatW8PExAS7d+9GgwYNAPx2/u7evQsHBwfo6+sjOjoa9evXB/DbBRNeOHkzeB7fjJ9//hmurq7w9PTEihUrUKFCBZQvXx7nzp2Dl5cXQkNDERgYqD4+KioK3bt3h6IoOHHiBLvfExGVECzs35LLly/D3d0d69atw7/+9S+oVCosWrQI48ePR7Vq1dC/f3+0bNkSLVq0wM2bN5GXl4c6depoOzYR6aii63xv3LgRU6dOhYeHB6ZOnapR3MfHx6Ndu3YICQnRcmLdEB8fj+bNm8Pb2xuPHj2CtbU1hg8fjubNmwN4ft719PQwevRo3LlzB+vXr4ehoSELUCqxkpKS4ObmhszMTHh7e6Ndu3bw9vaGk5OTernBxYsXw93dXf2cI0eOwNLSkrMliIhKEK5j/zdJSUnBd999p35sb2+P4OBgrFmzBpmZmdDT08OZM2dgY2OD7t2748SJE2jVqhVGjhwJa2trFvVE9MrS09Px4MEDAM/XRlepVACA27dvIyUlBefOncPEiRNx69YtWFtbY/z48ahTpw6OHTuGhw8fajO6Tvjpp5/g6uqK0aNH47vvvsOYMWOQnJyMBQsW4PTp0wCer6+up6eH9u3bY8+ePThx4gSLeipxCsd08vPzYWdnh8mTJ2PkyJFwc3NDcnIy/P39sWvXLnTt2hW5ubnq6fj5+fkAgNatW7OoJyIqYVjY/w3u3LkDV1dXjB8/Hhs3blRvb9iwIW7cuIHs7GwMHjwYhw4dwubNmzFz5kysWrUK27Ztw+DBg/lHIBG9EhHBL7/8AgcHBwQFBeHevXtQFAV6enqYPn06Zs+ejV27duHzzz/HtWvXEBQUhNu3b8Pa2hrTp0/H+vXrNe6vpeIuXLiArl27YuLEiZg2bRoAoGPHjpg4cWKx4h4AfHx84OnpiVmzZiE/Px+cHEclydOnTwFAPavH2dkZiYmJ8PDwwPz589G/f3/06dMH0dHRsLKywoIFCxAfH68+noiISh4W9n+DK1eu4MGDBzAxMcG3336LtWvXAgDatWsHW1tbWFpaIioqCvv27YOzszMAoHr16ujUqRMcHBy0mJyIdJGiKDAxMUF4eDhWr16NsLAwAMDs2bMxd+5crF+/Hm3btsXgwYPRs2dP3LhxAwEBAbhz5w5q1KiBatWqafkdlGzx8fFo2rQpunbtiq+++goA1LMhOnbsiKCgICQlJSEiIkKjuO/Xrx+WLFkCAwMDXrClEuPu3buoX78+goKCcPPmTQBAq1at4OnpCT8/Pzx48ABDhw7Frl27cPXqVRgYGCAzMxMTJ05EQUEBL1IREZVQvMf+b9K/f3/ExsbC1tYWjx49gp+fH/r27YuYmBj07t0boaGh6NWrl0ZXfCKi11G06d1///tf9OzZE66urkhJScGmTZvwwQcfaNxzHxYWhh9++AGrVq2CpaWlNqOXeJcvX0bTpk0xatQoTJ06VWNf0eZtO3fuxLRp02Bvb48BAwagZcuW2ohL9KceP36MBQsWYP78+XBxcUGHDh0wcuRIAIC/vz8AICIiApUqVcL9+/dx+fJlhIWFYdq0aXByctJecCIi+kMs7N+wwiWj9uzZg61bt6JXr15Yvnw50tPT8cUXX6Bnz57w9PRE7dq1sX79em3HJSIdVnhhMC0tDdWrV1c/3rZtG7p164aPP/4Y//73v1GhQgUAmg31Hj16hPfee0+b8Uu8+Ph4tGnTBpmZmUhNTUX16tWLHVO0uI+KisKYMWPQqlUrLFiwAEZGRhyppxLr0qVLCA0NRVxcHKysrLBs2TJcuHABu3fvRu/evdG2bVv1sVyBgIio5GNh/wakpqYiNjYWHTt2VG9LT09Hy5YtMWzYMHTv3h1DhgzB/fv3ERQUhIoVK8LX1xcbNmxAhw4dtBeciHTW9evXsWbNGuzbtw/37t2Dg4MDevbsiW7duqFcuXLqkftRo0ZhwoQJ6iU1uaTdXxMXFwdPT08MGDAAsbGxePz4MSIjI2FnZ1fs2KJFz969e2Fvb49atWq97chEr+zhw4c4efIkQkJCkJmZie7du+PAgQNwcXHB8uXLtR2PiIheAQv7/1FqaioaN26Mhw8fwsfHB3379kWjRo1Qt25dREVFISwsDNu2bUNGRgaCg4Px5MkTODk54eeff0ZERASsra21/RaISMckJCSgU6dOaNasGczMzFCnTh0sXrwYjx8/RpcuXTBr1iyYmJhgy5Yt+OSTTzB27FiMHTsW5ubm2o6uE65cuYLGjRtjxIgRmDFjBjIyMuDj44Ps7Gzs2LEDtra2xZ7DEU3SdaNGjcLly5eRkJCAO3fuYMWKFRgwYIC2YxER0V/Em7v/RyqVCrVq1ULz5s1x7949HDhwAO3atcPy5cuRnZ2NSpUqISYmBg4ODpgyZQpEBBkZGVi4cCGLeiJ6ZfHx8fDw8EDXrl2xZMkShIeHIyAgABcuXICPjw+ioqIwY8YM5OTkoGfPnti6dSvmzJmDhQsXqhu+0cv9+uuv0NPTw4wZMzBjxgwAgKmpKfbu3QtjY2N07NgRycnJxZ7Hop50VeH4zvz58xEYGIjevXvDxMQEXl5eWk5GRESvgiP2b0BSUhLGjx8PlUoFPz8/6OnpITw8HJUrV8bOnTvh6uqKY8eOwdDQEImJiahQoQKsrKy0HZuIdExSUhJcXFwwYMAAzJs3T31PfW5uLgwNDfH06VP07NkTCQkJ2L9/v3qd6Z07d8LOzg7169fX8jso2e7fvw9HR0esWbMGHTp0UF8IKWxw+ldG7ol00e9nnGRlZaFixYpaTERERK+KI/ZvgJ2dHaZPn46cnBwsW7YMDg4O2LVrFwIDA/HRRx9h2LBhMDQ0hIjAwcGBRT0RvZZNmzbBwMAA1tbWyMrKgp6eHlQqFQwNDaFSqVC+fHksXrwY6enpOHr0KIDnf7B//PHHLOr/Aj09PXTo0AFdunTBzp071QV94fXvoiP3Xbt2xZUrV7QZl+iN+f2MExb1RES6hyP2b1BSUhKGDRsGAAgJCYGnp6eWExFRaZCXl4cyZcoAAEaOHInjx4+jU6dOCAgIQMWKFTVG27KyslC3bl0EBgZi1KhR2oytk9LT0/H1119j4cKFiIyMxMcff6wu7AvP8YMHD9C8eXOYmZnh6NGj6q8NERERkbZwxP4NsrOzw6JFi6Cnp4epU6fi+PHj2o5ERDru+vXrCA0NRUJCAgAgPDwcHh4eiIyMxKJFi5CVlQVFUdTTxpOSkvD+++/D3d1dm7F1TkFBAQDAzMwMQUFBCAgIQKdOnbBz5051QV9Y4FetWhWnT5/Gxo0bWdQTERFRicDC/g2zs7PDggULUKZMGYwbNw6nTp3SdiQi0mHHjx/HypUrsWbNGly6dAkAsGDBAnh6emL79u1YuHAhHj9+rJ42vnnzZpQvX573f/8Fqamp2LZtGwBAX19fXdybm5uri/sePXpg3759UBRFY7pylSpVuKQdERERlRgG2g5QGtnZ2SEsLAyTJk2CpaWltuMQkQ7r06cPcnNzERYWhoKCAgwePBj169dHREQERowYgcjISADAhAkTMGvWLKxevRrR0dHqdevpxfLz8xEYGIjLly8jLy8PPXv2VBf3+vr6MDc3x7hx45CVlYWgoCA4OzujWrVq2o5NRERE9EK8x/5vVNipmojof7V8+XLMnz8f7du3Vxf3ADBixAicPXsWKpUKcXFxOHHiBFxcXLScVjckJydj7NixyMrKwoABA/DJJ58AgLq4B4C9e/eiX79+OHToEBwdHbUZl4iIiOilOBX/b8Sinohe1cWLF9GrVy9s27YNMTEx6u2DBw/G2LFjsWfPHixbtgw//fQTACAiIgINGzbE/fv3cfr0aRb1r8DW1hbz589HuXLlsHLlSmzevBnA82n5eXl5AAAbGxtYWFhwnXoiIiIq0ThiT0RUQuTk5MDLywuxsbFo0KABrl+/jrZt28La2hojRoxAnTp1sHXrVkyZMgXt2rXDZ599ph5FTk9Ph5mZmZbfgW66fv06AgIC8OzZM/j7+8PPz0+9b/z48Th06BD27duHKlWqaDElERER0cuxsCciKkHOnDmDTz/9FBYWFhg3bhxOnjyJ77//Hk+ePIGIYPTo0di6dSsePHgAd3d3BAYGws7OTtuxdd7169cxZswY3L59G25ubvDw8MCJEyewdetW7N+/H87OztqOSERERPRSLOyJiEqYs2fPwtvbGz179sTs2bNRsWJFnDlzBkeOHMGxY8eQnJyMK1euoFq1ajh//jwsLCy0HblUuHXrFlavXo3t27dDX18f77//Pr7++mveW09EREQlHgt7IqISoLBhm4hAURScPn0aPj4+aN26NTZu3AhjY2MAQHZ2Np49e4bvvvsOrVq1Qu3atbWcvHR69uwZ9PX1UbZsWW1HISIiIvpTLOyJiLTk8uXLWLduHQYOHIj3338fBgbPVyAtWtz7+vrigw8+wIoVK1C5cmWoVCr1mvX05hWeeyIiIiJdwsKeiEgLcnNz4eXlhZiYGNSpUwcdOnSAu7s7unfvrnFc4cj9hx9+iKVLl6JSpUpaSkxEREREJRULeyIiLQkLC4OBgQEaNmyI48ePIzw8HL6+vvDw8MAXX3yhHpk/deoUPDw84OfnhzVr1nBEmYiIiIg0sLAnItKSI0eOoGPHjjh48CCaNm2KtLQ0rFixAjNnzoSTkxP8/f3RunVrODg44Ny5cyhfvjzq1aun7dhEREREVMLwRk0iIi1p3bo1Bg4ciPDwcPz666+oXr06EhMTYWNjA0dHR/z3v/9FgwYNMHv2bDRp0oRFPRERERG9kIG2AxARvcuaNWuGefPmoUyZMhgwYACOHDmCQ4cOwdHREdeuXcO+ffvQqlUrbcckIiIiohKMU/GJiLSsVatWOH78OKpVq4Y9e/bA2dlZ25GIiIiISIdwKj4RkZYUXlcNDAyEra0tFi9eDGdnZ/B6KxERERG9Chb2RERaUtjd3sXFBSqVCrGxsRrbiYiIiIj+Chb2RERaZmFhgdDQUMyfPx9nzpzRdhwiIiIi0jEs7ImISoB//OMfcHV1haWlpbajEBEREZGOYfM8IqIS4tdff4WRkZG2YxARERGRjmFhT0RERERERKTDOBWfiIiIiIiISIexsCciIiIiIiLSYSzsiYiIiIiIiHQYC3siIiIiIiIiHcbCnoiIiIiIiEiHsbAnIiJ6R/n7+6Njx45/eIyNjQ3Cw8PfSh4iIiJ6PSzsiYiI6KXOnj2LQYMG/W2vn5KSAkVREBcX98rPVRQFO3bseOOZiIiIdI2BtgMQERFRyWVmZqbtCERERPQnOGJPRERUyn377bdo2LAhjI2NUbVqVbRt2xZPnz5V758zZw6qV6+OqlWrYujQocjLy1Pv+/1UfEVRsHTpUvj4+MDY2Bi1atXC1q1b//Dff/ToET799FOYmZnB2NgYdnZ2WLNmDQCgVq1aAIDGjRtDURS0bt0awPOZAt7e3jA1NUWlSpXQqlUrnDt3TiMXAHTq1AmKoqgfA0BUVBRcXFxgZGSE2rVrY/LkycjPz3+dU0dERKQTWNgTERGVYmlpaejVqxc+++wzJCYm4siRI+jcuTNEBABw+PBhXLt2DYcPH8a6deuwdu1arF279g9fc9KkSejSpQvi4+PRu3dv9OrVC4mJiX94/KVLl7B3714kJiZi6dKlMDU1BQCcOXMGAHDw4EGkpaVh+/btAIAnT56gb9++OHbsGE6dOgU7Ozv4+vriyZMnAJ4X/gCwZs0apKWlqR/v27cPvXv3xvDhw3Hp0iUsX74ca9euxbRp017/JBIREZVwihT+ZiciIqJS59y5c3BxcUFKSgpq1qypsc/f3x9HjhzBtWvXoK+vDwDo3r079PT0sGXLFgDPR8ZHjhyJkSNHAng+Yj9kyBAsXbpU/TrNmzdHkyZNsGTJkhdm+Ne//gVTU1OsXr262L6UlBTUqlUL58+fR6NGjV76PgoKCvDee+9h06ZN6NChgzpLZGSkRgPAli1bwsfHBxMmTFBv27BhA7788kvcuXPn5SeKiIhIh3HEnoiIqBRzdnbGBx98gIYNG6Jbt2745ptv8OjRI/V+R0dHdVEPANWrV8f9+/f/8DXd3d2LPS4csffx8YGJiQlMTEzg6OgIAPj888+xZcsWNGrUCF9++SVOnjz5p7nv37+PIUOGoG7duqhUqRIqVaqEX375BTdv3vzD58XGxmLKlCnqDCYmJhg4cCDS0tLw7NmzP/13iYiIdBGb5xEREZVi+vr6OHDgAE6ePIn9+/dj4cKFCAoKwunTpwEAZcqU0TheURSoVKpX/ncURQEArFy5EtnZ2Rqv7ePjgxs3bmD37t04ePAgPvjgAwwdOhRz5sx56ev5+/sjPT0d4eHhqFmzJsqWLQt3d3fk5ub+YQ6VSoXJkyejc+fOxfYZGRm98vsiIiLSBSzsiYiISjlFUeDp6QlPT0+EhISgZs2aiIyMfO3XO3XqFPz8/DQeN27cGABQo0aNFz7HzMwM/v7+8Pf3R4sWLTBu3DjMmTMHhoaGAJ5PtS/q2LFjWLJkCXx9fQEAqampyMjI0DimTJkyxZ7XpEkTXLlyBba2tq/9/oiIiHQNC3siIqJS7PTp0zh06BDatWsHc3NznD59Gunp6XBwcMCFCxde6zW3bt2Kpk2bwsvLCxs3bsSZM2ewatWqlx4fEhICFxcXODo6IicnB7t27YKDgwMAwNzcHMbGxvj+++9hZWUFIyMjVKpUCba2tli/fj2aNm2KrKwsjBs3DsbGxhqva2Njg0OHDsHT0xNly5bFe++9h5CQEHTo0AHW1tbo1q0b9PT0cOHCBSQkJODrr79+rfdLRERU0vEeeyIiolKsYsWKiI6Ohq+vL+rWrYvg4GDMnTsXPj4+r/2akydPxpYtW+Dk5IR169Zh48aNqF+//kuPNzQ0xIQJE+Dk5ISWLVtCX19f3ZzPwMAACxYswPLly2FpaYmPP/4YALB69Wo8evQIjRs3Rp8+fTB8+HCYm5trvO7cuXNx4MABWFtbq2cMtG/fHrt27cKBAwfg6uqK5s2bY968ecUaBxIREZUm7IpPREREf9mLOtETERGRdnHEnoiIiIiIiEiHsbAnIiIiIiIi0mFsnkdERER/Ge/gIyIiKnk4Yk9ERERERESkw1jYExEREREREekwFvZEREREREREOoyFPREREREREZEOY2FPREREREREpMNY2BMRERERERHpMBb2RERERERERDqMhT0RERERERGRDmNhT0RERERERKTD/g8mEyDx6DrB1AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Top 10 states\n",
    "top_10_states = data['ship-state'].value_counts().head(10)\n",
    "\n",
    "# Plot count of cities by state\n",
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(data=data[data['ship-state'].isin(top_10_states.index)], x= 'ship-state')\n",
    "plt.xlabel('ship-state')\n",
    "plt.ylabel('count')\n",
    "plt.title('Distribution of State')\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 502,
   "id": "5b88de25-80ac-4953-a761-8501eae47fbe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "# Feature Scaling\n",
    "scaler = StandardScaler()\n",
    "data['Scaled_Amount'] = scaler.fit_transform(data[['Amount']])\n",
    "\n",
    "# K-means Clustering\n",
    "kmeans = KMeans(n_clusters=4, random_state=42)\n",
    "data['Cluster'] = kmeans.fit_predict(data[['Scaled_Amount', 'Qty']])\n",
    "\n",
    "# Visualize clusters\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.scatterplot(data=data, x='Scaled_Amount', y='Qty', hue='Cluster', palette='viridis')\n",
    "plt.title(\"Customer Segmentation\")\n",
    "plt.xlabel(\"Amount (Scaled)\")\n",
    "plt.ylabel(\"Quantity\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 507,
   "id": "b8daf3eb-1347-4132-8d2d-6d2a169588db",
   "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>index</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Date</th>\n",
       "      <th>Status</th>\n",
       "      <th>Fulfilment</th>\n",
       "      <th>Sales Channel</th>\n",
       "      <th>ship-service-level</th>\n",
       "      <th>Category</th>\n",
       "      <th>Size</th>\n",
       "      <th>Courier Status</th>\n",
       "      <th>...</th>\n",
       "      <th>currency</th>\n",
       "      <th>Amount</th>\n",
       "      <th>ship-city</th>\n",
       "      <th>ship-state</th>\n",
       "      <th>ship-postal-code</th>\n",
       "      <th>ship-country</th>\n",
       "      <th>B2B</th>\n",
       "      <th>fulfilled-by</th>\n",
       "      <th>Scaled_Amount</th>\n",
       "      <th>Cluster</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>405-8078784-5731545</td>\n",
       "      <td>2022-04-30</td>\n",
       "      <td>Cancelled</td>\n",
       "      <td>Merchant</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Standard</td>\n",
       "      <td>T-shirt</td>\n",
       "      <td>S</td>\n",
       "      <td>On the Way</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>647.62</td>\n",
       "      <td>MUMBAI</td>\n",
       "      <td>MAHARASHTRA</td>\n",
       "      <td>400081</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>Easy Ship</td>\n",
       "      <td>0.003808</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>171-9198151-1101146</td>\n",
       "      <td>2022-04-30</td>\n",
       "      <td>Shipped - Delivered to Buyer</td>\n",
       "      <td>Merchant</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>3XL</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>406.00</td>\n",
       "      <td>BENGALURU</td>\n",
       "      <td>KARNATAKA</td>\n",
       "      <td>560085</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>Easy Ship</td>\n",
       "      <td>-0.859279</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>403-9615377-8133951</td>\n",
       "      <td>2022-04-30</td>\n",
       "      <td>Cancelled</td>\n",
       "      <td>Merchant</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Blazzer</td>\n",
       "      <td>L</td>\n",
       "      <td>On the Way</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>753.33</td>\n",
       "      <td>PUDUCHERRY</td>\n",
       "      <td>PUDUCHERRY</td>\n",
       "      <td>605008</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>Easy Ship</td>\n",
       "      <td>0.381413</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>406-7807733-3785945</td>\n",
       "      <td>2022-04-30</td>\n",
       "      <td>Shipped - Delivered to Buyer</td>\n",
       "      <td>Merchant</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>S</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>399.00</td>\n",
       "      <td>HYDERABAD</td>\n",
       "      <td>TELANGANA</td>\n",
       "      <td>500032</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>Easy Ship</td>\n",
       "      <td>-0.884283</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>405-5513694-8146768</td>\n",
       "      <td>2022-04-30</td>\n",
       "      <td>Shipped - Delivered to Buyer</td>\n",
       "      <td>Merchant</td>\n",
       "      <td>Amazon.in</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>XS</td>\n",
       "      <td>Shipped</td>\n",
       "      <td>...</td>\n",
       "      <td>INR</td>\n",
       "      <td>399.00</td>\n",
       "      <td>Amravati.</td>\n",
       "      <td>MAHARASHTRA</td>\n",
       "      <td>444606</td>\n",
       "      <td>IN</td>\n",
       "      <td>False</td>\n",
       "      <td>Easy Ship</td>\n",
       "      <td>-0.884283</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    index             Order ID       Date                        Status  \\\n",
       "0       0  405-8078784-5731545 2022-04-30                     Cancelled   \n",
       "1       1  171-9198151-1101146 2022-04-30  Shipped - Delivered to Buyer   \n",
       "3       3  403-9615377-8133951 2022-04-30                     Cancelled   \n",
       "7       7  406-7807733-3785945 2022-04-30  Shipped - Delivered to Buyer   \n",
       "12     12  405-5513694-8146768 2022-04-30  Shipped - Delivered to Buyer   \n",
       "\n",
       "   Fulfilment Sales Channel ship-service-level Category Size Courier Status  \\\n",
       "0    Merchant     Amazon.in           Standard  T-shirt    S     On the Way   \n",
       "1    Merchant     Amazon.in           Standard    Shirt  3XL        Shipped   \n",
       "3    Merchant     Amazon.in           Standard  Blazzer    L     On the Way   \n",
       "7    Merchant     Amazon.in           Standard    Shirt    S        Shipped   \n",
       "12   Merchant     Amazon.in           Standard    Shirt   XS        Shipped   \n",
       "\n",
       "    ...  currency  Amount   ship-city   ship-state ship-postal-code  \\\n",
       "0   ...       INR  647.62      MUMBAI  MAHARASHTRA           400081   \n",
       "1   ...       INR  406.00   BENGALURU    KARNATAKA           560085   \n",
       "3   ...       INR  753.33  PUDUCHERRY   PUDUCHERRY           605008   \n",
       "7   ...       INR  399.00   HYDERABAD    TELANGANA           500032   \n",
       "12  ...       INR  399.00   Amravati.  MAHARASHTRA           444606   \n",
       "\n",
       "    ship-country    B2B  fulfilled-by Scaled_Amount  Cluster  \n",
       "0             IN  False     Easy Ship      0.003808        2  \n",
       "1             IN  False     Easy Ship     -0.859279        0  \n",
       "3             IN  False     Easy Ship      0.381413        2  \n",
       "7             IN  False     Easy Ship     -0.884283        0  \n",
       "12            IN  False     Easy Ship     -0.884283        0  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 507,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9bec0db0-8f1f-4563-bf26-cf18af6914b8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 406,
   "id": "5e7707e4-04c8-40f6-b812-60dfdbfcd97e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Squared Error: 46657.06452553317\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "# Preprocess data\n",
    "data['Date'] = pd.to_datetime(data['Date'])\n",
    "data['Year'] = data['Date'].dt.year\n",
    "data['Month'] = data['Date'].dt.month\n",
    "\n",
    "# Select features and target\n",
    "features = ['Year', 'Month', 'Category', 'Fulfilment', 'Sales Channel']\n",
    "data = pd.get_dummies(data[features + ['Amount']], drop_first=True)\n",
    "X = data.drop('Amount', axis=1)\n",
    "y = data['Amount']\n",
    "\n",
    "# Train-test split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# Train model\n",
    "model = RandomForestRegressor()\n",
    "model.fit(X_train, y_train)\n",
    "predictions = model.predict(X_test)\n",
    "\n",
    "# Evaluate\n",
    "mse = mean_squared_error(y_test, predictions)\n",
    "print(f\"Mean Squared Error: {mse}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 410,
   "id": "67065a0d-b032-47ad-a93b-65fb8a1b252f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 37514 entries, 0 to 128892\n",
      "Data columns (total 10 columns):\n",
      " #   Column             Non-Null Count  Dtype  \n",
      "---  ------             --------------  -----  \n",
      " 0   Year               37514 non-null  int32  \n",
      " 1   Month              37514 non-null  int32  \n",
      " 2   Amount             37514 non-null  float64\n",
      " 3   Category_Perfume   37514 non-null  bool   \n",
      " 4   Category_Shirt     37514 non-null  bool   \n",
      " 5   Category_Shoes     37514 non-null  bool   \n",
      " 6   Category_Socks     37514 non-null  bool   \n",
      " 7   Category_T-shirt   37514 non-null  bool   \n",
      " 8   Category_Trousers  37514 non-null  bool   \n",
      " 9   Category_Wallet    37514 non-null  bool   \n",
      "dtypes: bool(7), float64(1), int32(2)\n",
      "memory usage: 1.1 MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5082ac4",
   "metadata": {},
   "source": [
    "## Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aee59a6f",
   "metadata": {},
   "source": [
    "The data analysis reveals that the business has a significant customer base in Maharashtra state, mainly serves retailers, fulfils orders through Amazon, exeriences high demand for T-shirts, and sees M-size as the preferred choice among buyers. "
   ]
  }
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