Forecasting for Cocacola Prices.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "24b4e858",
   "metadata": {},
   "source": [
    "## Problem Statement:<br>\n",
    " Forecast the CocaCola prices data set. Prepare a document for each model explaining \n",
    "how many dummy variables you have created and RMSE value for each model. Finally which model you will use for \n",
    "Forecasting.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "bc4713de",
   "metadata": {},
   "outputs": [],
   "source": [
    "#importing libraries \n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import pyplot\n",
    "from pandas import DataFrame\n",
    "from numpy import sqrt\n",
    "import plotly.express as px\n",
    "import statsmodels.formula.api as smf\n",
    "from statsmodels.tsa.seasonal import seasonal_decompose\n",
    "from statsmodels.tsa.holtwinters import SimpleExpSmoothing # SES\n",
    "from statsmodels.tsa.holtwinters import Holt # Holts Exponential Smoothing\n",
    "from statsmodels.tsa.holtwinters import ExponentialSmoothing \n",
    "import itertools\n",
    "import statsmodels.api as sm\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "f6fd287e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#reading csv file using pandas\n",
    "data = pd.read_excel('CocaCola_Sales_Rawdata.xlsx',header=0,parse_dates=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ac4f155",
   "metadata": {},
   "source": [
    "## Performing EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "71a47555",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Quarter</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Q1_86</td>\n",
       "      <td>1734.827000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Q2_86</td>\n",
       "      <td>2244.960999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q3_86</td>\n",
       "      <td>2533.804993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Q4_86</td>\n",
       "      <td>2154.962997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Q1_87</td>\n",
       "      <td>1547.818996</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Quarter        Sales\n",
       "0   Q1_86  1734.827000\n",
       "1   Q2_86  2244.960999\n",
       "2   Q3_86  2533.804993\n",
       "3   Q4_86  2154.962997\n",
       "4   Q1_87  1547.818996"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#displaying  first 5 records \n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "8c0c80de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Quarter</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Q2_95</td>\n",
       "      <td>4936.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Q3_95</td>\n",
       "      <td>4895.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Q4_95</td>\n",
       "      <td>4333.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Q1_96</td>\n",
       "      <td>4194.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Q2_96</td>\n",
       "      <td>5253.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Quarter   Sales\n",
       "37   Q2_95  4936.0\n",
       "38   Q3_95  4895.0\n",
       "39   Q4_95  4333.0\n",
       "40   Q1_96  4194.0\n",
       "41   Q2_96  5253.0"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#displaying last 5 records\n",
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "845faa89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(42, 2)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#shape of dataset\n",
    "data.shape  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70529523",
   "metadata": {},
   "source": [
    "Dataset has `42` rows and `2` columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "e569159f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 42 entries, 0 to 41\n",
      "Data columns (total 2 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   Quarter  42 non-null     object \n",
      " 1   Sales    42 non-null     float64\n",
      "dtypes: float64(1), object(1)\n",
      "memory usage: 800.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "3b8e5772",
   "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>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>42.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2994.353308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>977.930896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1547.818996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2159.714247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2782.376999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3609.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5253.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Sales\n",
       "count    42.000000\n",
       "mean   2994.353308\n",
       "std     977.930896\n",
       "min    1547.818996\n",
       "25%    2159.714247\n",
       "50%    2782.376999\n",
       "75%    3609.250000\n",
       "max    5253.000000"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a70b481",
   "metadata": {},
   "source": [
    "#### The describe() method returns description of the data in the DataFrame. If the DataFrame contains numerical data, the description contains these information for each column: count - The number of not-empty values. mean - The average (mean) value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "efb764c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.ndim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "1def9a8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[RangeIndex(start=0, stop=42, step=1),\n",
       " Index(['Quarter', 'Sales'], dtype='object')]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.axes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "74aeeda0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Quarter', 'Sales'], dtype='object')"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "6b1a6f53",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Quarter    0\n",
       "Sales      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking for missing data\n",
    "data.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96cd5e16",
   "metadata": {},
   "source": [
    "#### Dataset has no any NA values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "27580a87",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 2)"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking for duplication of data\n",
    "data[data.duplicated()].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f16e16eb",
   "metadata": {},
   "source": [
    "#### There is no any duplicate values in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "cbf0738c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Quarter    42\n",
       "Sales      42\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f57d1afc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Q1_86', 'Q2_86', 'Q3_86', 'Q4_86', 'Q1_87', 'Q2_87', 'Q3_87',\n",
       "       'Q4_87', 'Q1_88', 'Q2_88', 'Q3_88', 'Q4_88', 'Q1_89', 'Q2_89',\n",
       "       'Q3_89', 'Q4_89', 'Q1_90', 'Q2_90', 'Q3_90', 'Q4_90', 'Q1_91',\n",
       "       'Q2_91', 'Q3_91', 'Q4_91', 'Q1_92', 'Q2_92', 'Q3_92', 'Q4_92',\n",
       "       'Q1_93', 'Q2_93', 'Q3_93', 'Q4_93', 'Q1_94', 'Q2_94', 'Q3_94',\n",
       "       'Q4_94', 'Q1_95', 'Q2_95', 'Q3_95', 'Q4_95', 'Q1_96', 'Q2_96'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.Quarter.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3bb5356b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot()\n",
    "plt.title('Quterwise Sales',fontdict={'fontsize': 16,'color': 'black'})\n",
    "plt.xlabel('Quaters')\n",
    "plt.ylabel('Sales')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1735e9b",
   "metadata": {},
   "source": [
    "<h3>Observations:</h3>\n",
    "The graph shows the data has Trend as well as multiplicative seasonality <br>\n",
    "There is an upward trend in the sales as the number of Quters increases<br>\n",
    "at some intervals' the peak is getting up and down which know as seasonality <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "e4254442",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#checking for outleries\n",
    "sns.boxplot(data =data,width=0.4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e49d9d3",
   "metadata": {},
   "source": [
    "<h3>Observations:</h3>\n",
    "The sales has Mean: 2994 <br>\n",
    "There is no any outlier has been detected<br>\n",
    "IQR is between 2150 to 3609"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1bf12f33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#histogram for sales\n",
    "sns.histplot(data)\n",
    "plt.xlabel('sales')\n",
    "plt.ylabel('Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "68ce10d4",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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0+vbta4fvAjm7ixrzeqU+3RynWOrf3Q/enu6orjNYj2EhIqL2cZPyxQsLCwEAYWFhDa6HhISgoKCgUfuioqJGbRUKBfz9/VFQUACtVouamhqo1epm+2utj2t99dVXePbZZyGKIhYuXIjo6GgAQFlZGUpKSpCeno6PP/4YFRUViImJwdNPP43evXu34zvxKze35utXuVzW4L/OzJVyyS82F0u9u/o5TD5ukCG2fzD2H7mMw+dKEN23S5ue70rvD+Ba+bhSLoDr5UOuSdJiqba2FoC5WLmWUqlEZWVlk+2vb2tpr9PpUFdX12x/Op3Opj6uFR8fj+3bt+PgwYNYuXIlAgMDMWvWLJw5cwYAIJfL8dZbb6GmpgbJycmYNWsWduzYgS5d2vaDyUImExAQ4NVqO19fz3b174icPReTSUR+cTUAoFeYr0Plc2tcd3OxdLYEC3+rgkwmtLkPR8rHHlwpH1fKBXC9fMi1SFoseXh4ADCvXbL8GQB0Oh08PRv/w/Hw8Ghy4bdOp4NKpYJSqbT2d/3jlv5a6+NaYWFhCAsLQ2RkJHJycrB+/XrMmjULCQkJSEtLg5/fr9MuH3zwASZMmIBt27Zh/vz5tn4LGjCZRGi1Nc0+LpfL4OvrCa22Fkajc69DcZVcistrodMb4SYX0LWLl0Pl0yNYBQ+FHKWVdTh0sgARbZgmdJX3x8KV8nGlXADXyseWX3bJOUlaLFmmwzQaDXr06GG9rtFoEBkZ2ai9Wq3G3r17G1zT6/WoqKhAaGgo/P39oVKpoNFoGrTRaDTWqbnW+qivr8cPP/yAqKioBtN1/fv3x+eff279/2sLJQBQqVQIDw+3LhJvL4Oh9Q8Lo9FkUztn4Oy55FqOOeniBblc5lD5yCBgSEQQ0k5pkHayqF17QDlSPvbgSvm4Ui6A6+VDrkXSSeLIyEh4e3s3uMtMq9Xi5MmTiIuLa9Q+Pj4ehYWFDfYysjw3NjbWvHtxbCzS0tIaPC81NRXDhw+3qQ+5XI4XXngB//rXvxr0ceTIEeuC7k8//RQjR460TvsBQFVVFXJycrjo+yZzqcS8XqlbF2l37m6O5a64zDPFEEVR4miIiJyTpMWSQqFAUlISVq5ciX379iErKwtLliyBWq1GYmIijEYjiouLrUVJTEwMYmNjsWTJEhw9ehQpKSlYtmwZpk+fjtDQUADAnDlzsHPnTmzcuBHZ2dl4++23cerUKcyePdumPmQyGebOnYtNmzZh586dyMnJwYcffogdO3Zg4cKFAIAJEyZAFEU8++yzOHv2LI4dO4aFCxciMDAQM2bMkOabSZK4VGJerxQe4pjD79F9guAml0FTXmuNlYiI2kbSaTjAvEGkwWDAiy++iLq6OsTHx2P9+vVQKBTIz8/HpEmTsGLFCsycOROCIGDNmjVYvnw5Zs+eDaVSicmTJ+P555+39jdmzBi8+eabSE5OxqpVq9C3b1+sXbvWulWALX3MmzcPSqUS77//PgoKCtCnTx/89a9/xaRJkwCYpw83b96MlStX4sEHH4Qoihg9ejQ++uijBmuvyPVdurq4u1uwY44seSrdMLh3IH45V4JDp4sR7qBxEhE5MkHk2LzDMBpNKCtr/rd/NzcZAgK8UF5e7fRz+66Qi9FkwhPv/gCDUcTKBbdgQJ9gh8znx6OXsXFXFrqHeGP53BE2PccV3p9ruVI+rpQL4Fr5BAdLf9wRdQxubEHUTpryWhiMIhTuMnTxd9zbnof27QKZICBPUwVNRa3U4RAROR0WS0TtZJmC6xrkBZnQ9j2MOouPSoEBPfwB8Kw4IqL2YLFE1E6WBdPdgh1zcfe1rAfrnmGxRETUViyWiNqpoPTqyFIX5ymWzl2qREWVrpXWRER0LRZLRO10ucS823pYkOMXSwE+SvTp6gsAOMzRJSKiNmGxRNQOJpOIonJLsaRqpbVjGM6pOCKidmGxRNQOpdo61BtMcJML6OLnHHtrWabisi5WoKq2XuJoiIicB4slonYoKDWPKoUGqCCXOcc/o9BAFboFe8FoEnHkXInU4RAROQ3n+JQncjCWxd3OMgVnwak4IqK2Y7FE1A6WkSW1EyzuvpZlKu74hTLo9EaJoyEicg4slojaodBJR5a6h3gj2N8D9QYTjp0vlTocIiKnwGKJqB0uXx1Z6upkI0uCIHCDSiKiNmKxRNRGV2r01rvJQgMd90y45gzvHwIAOJJdAoPRuQ8uJSLqDCyWiNqosMw8qhToq4SHwk3iaNquTzdf+HkpUKsz4lRuudThEBE5PBZLRG1UVFYLwLxtgDOSXTMVl3laI3E0RESOj8USURtZdu4ODXTOYgkAhg+wrFviVBwRUWtYLBG1kabcPLIU4u9865UsBvTwh4/KHVW19cjiVBwRUYtYLBG10a8jS85bLMllMsQNMC/0TjvFqTgiopawWCJqA1EUUVTu3GuWLEYMNBdLh84UcyqOiKgFLJaI2kBbUw+d3ggBQLATT8MBQL9wf/h5K1CjM+D4hTKpwyEiclgslojaoMi6bYAH3N2c+5+PTCYg/upUXPqpIomjISJyXM79aU/UyVxhvdK1RgwMBQAcPluCegPPiiMiagqLJaI20LjIeiWLPt18EeirRJ3eiKPZnIojImoKiyWiNrAs7g4JcI2RJZkgID7y6lRcFqfiiIiawmKJqA00V9csucrIEvDrVNwv50qg03MqjojoeiyWiGwkiiKKKq5Ow7nImiUA6KX2QYi/J/T1Jhw+Wyx1OEREDofFEpGNtNV687YBAtDFz3WKJUEQkBBlHl06eIJTcURE12OxRGQjy3qlIBfYNuB6CVFqAMCJC2WorNZLHA0RkWNxrU98og5k3TbARRZ3X0sdqELvMF+YRBFp3HOJiKgBFktENrIeoOtCi7uvNerqVFzKiUKJIyEiciwslohs9OuZcK43sgSY74qTCQIuFFxBQWm11OEQETkMFktENrJsGxAS6JojS75eCgzuEwgAOHico0tERBYslohsIIqiy48sAbDeFffzsUKIoihxNEREjoHFEpENtNV66OrN2wYE+7tusTSsXzCUCjk0FbXIyimXOhwiIofAYonIBtduG+Amd91/Nkp3OYb3DwYAfJeZJ3E0RESOwXU/9YnsqMhyzImLrle61ujoMADA/sP50NXz+BMiIhZLRDbQVLjWAbotGdDDH8H+nqipMyAjSyN1OEREkmOxRGQDyx5LoS68XslCJggYG3N1dOmXyxJHQ0QkPRZLRDYovjqy5MqLu681ZkhXCAJwKrfcOqpGRHSzYrFEZIOSyjoAQJebpFjq4ueBmH7mhd4HjhZIHA0RkbRYLBG1olZnQFVtPQBzEXGzSBzRAwBw4HgBTCbuuURENy/JiyWTyYTVq1dj7NixiImJwdy5c5Gbm9ts+/Lycjz11FOIj49HfHw8XnrpJdTU1DRos3v3bkyZMgXR0dGYNm0a9u/f36Y+jEYjVq9ejQkTJmDIkCGYOXMmvvvuuzbHQa7BMgXn7ekOT6WbxNF0noTBYVB5uKFMq8OpXO65REQ3L8mLpeTkZGzZsgWvv/46tm7dCkEQMG/ePOj1+ibbL1q0CHl5edi0aRNWr16NAwcOYPny5dbHU1JS8Mwzz2DWrFnYvn07xowZgwULFiA7O9vmPlatWoUtW7Zg+fLl2LlzJxITE/GHP/wBx44ds7kPch3FFeYpuJtlvZKFwl2OUVFqAMCPR7nQm4huXpIWS3q9Hhs2bMDChQsxfvx4REZGYtWqVSgqKsKePXsatT98+DDS0tKwYsUKREVFYdSoUXj11Vfx5ZdfoqioCACwbt06JCYmIikpCREREVi6dCmioqKwefNmm/swGAx44YUXMG7cOHTv3h1PPPEEvLy8kJqaanMf5DpKKi2Lu2+eKTiL8UO7AgAOnSmGtqbpX2CIiFydpMVSVlYWqqurkZCQYL3m6+uLQYMGIT09vVH7jIwMBAcHIyIiwnptxIgREAQBmZmZMJlMOHToUIP+AGDkyJHIyMiwqQ8AeO655zB16lQAQG1tLTZt2oTa2lqMHDnS5j7IdVim4br43VwjSwDQK8wXPdU+MBhFHDjGhd5EdHOSdAFGYaH5ZPOwsLAG10NCQlBQ0PiDuaioqFFbhUIBf39/FBQUQKvVoqamBmq1utn+WuvjWl999RWeffZZiKKIhQsXIjo6us19tJWbW/P1q/zqMRtyFzhuw5lyKdWap+FCA1XNvj/OlI8trs1n0vBwbNh5Cj/8chlTb+kFmSBIHF3budL740q5AK6XD7kmSYul2lrzb+wKhaLBdaVSicrKyibbX9/W0l6n06Gurq7Z/nQ6nU19XCs+Ph7bt2/HwYMHsXLlSgQGBmLWrFlt6qMtZDIBAQFerbbz9XWdEQ5nyKVUa35P+3T3b/X9cYZ82sLX1xOTR/fBln1noSmvRV5JDYb2D5E6rHZzpffHlXIBXC8fci2SFkseHuY1IHq93vpnANDpdPD0bPwPx8PDo8mF3zqdDiqVCkql0trf9Y9b+mutj2uFhYUhLCwMkZGRyMnJwfr16zFr1qw29dEWJpMIrbb5O+rkchl8fT2h1dbCaDS1+3UcgbPkIoqi9Vw4TzcB5eXVTbZzlnxsdX0+o6LU2JeZj69+yEbP4NYLekfjSu+PK+UCuFY+tvyyS85J0mLJMpWl0WjQo0cP63WNRoPIyMhG7dVqNfbu3dvgml6vR0VFBUJDQ+Hv7w+VSgWNpuF5VhqNxjo111of9fX1+OGHHxAVFdVgqq1///74/PPPberjRhgMrX9YGI0mm9o5A0fPpaJKh3qDCYIA+KoUrcbq6Pm0lSWfcTFdsS8zH4fOFKOkohb+3kqpQ2sXV3p/XCkXwPXyIdci6SRxZGQkvL29rXeZAYBWq8XJkycRFxfXqH18fDwKCwsb7MNkeW5sbCwEQUBsbCzS0tIaPC81NRXDhw+3qQ+5XI4XXngB//rXvxr0ceTIEfTt29emPsh1WBZ3B/p4wO0mXlPRPcQbEd18YTSJ+JE7ehPRTUbST3+FQoGkpCSsXLkS+/btQ1ZWFpYsWQK1Wo3ExEQYjUYUFxdb1yLFxMQgNjYWS5YswdGjR5GSkoJly5Zh+vTp1hGdOXPmYOfOndi4cSOys7Px9ttv49SpU5g9e7ZNfchkMsydOxebNm3Czp07kZOTgw8//BA7duzAwoULbY6DXEOJdY+lm2/bgOvdOrQbAPPhutzRm4huJpJvR7xo0SIYDAa8+OKLqKurQ3x8PNavXw+FQoH8/HxMmjQJK1aswMyZMyEIAtasWYPly5dj9uzZUCqVmDx5Mp5//nlrf2PGjMGbb76J5ORkrFq1Cn379sXatWutt/nb0se8efOgVCrx/vvvo6CgAH369MFf//pXTJo0yeY+yDVYtw24yTakbEp8ZAi27DuLUm0djmaXYmi/LlKHRETUKQRRFPkrooMwGk0oK2t6ATFg3lYgIMAL5eXVTj+37yy5rN95EgeOFWLGuD6YdkuvZts5Sz62ai6ff313Dl+nXcSgXgF4+oFhEkbYNq70/rhSLoBr5RMc7CN1CNRBbt5FGEQ2sB51chMdoNuSibHdIAjAyZxyXCppvrAnInIlLJaIWmA56oTTcGZd/D0xrF8wAGBfZr7E0RARdQ4WS0TNqDeYUH51Q8qb7RDdltw2PBwA8PPxAlTX1UscDRFRx2OxRNSMMm0dRAAKdxl8Ve5Sh+MwBvTwR3iwF/T1Jvx4hNsIEJHrY7FE1IxrD9AVnPA8tI4iCAJui+sOAPjuUD63ESAil8diiagZxZVc3N2chEGh8PJwQ0llHX45VyJ1OEREHYrFElEzSrjHUrMU7nKMv7pJ5d6MPImjISLqWCyWiJphmYbj4u6mTRjWDTJBQNbFCuRrqqQOh4iow7BYImoGp+FaFuTngdj+5l2893IbASJyYSyWiJrBabjWWRZ6HzxRiKpabiNARK6JxRJRE2p1BlTXGQAAXTiy1Kx+4X7oEeqNeoMJ3x++JHU4REQdgsUSURNKr07BeXm4wVMp+XnTDksQBNwxogcA847e9QajxBEREdkfiyWiJpRozcVSkC9HlVoTHxmCAB8ltNV6HDxRJHU4RER2x2KJqAmWkaUgTsG1yk0uQ+LVtUvfpF2ESeQmlUTkWlgsETWhlCNLbTJ+aFd4KuUoKK3BsexSqcMhIrIrFktETeDIUtt4Kt0wPsa8SeU3aRcljoaIyL5YLBE1gSNLbXdbXDjkMvMmlRcKtFKHQ0RkNyyWiJrAkaW2C/T1wIiBoQA4ukREroXFEtF16g0mVFbrAXBkqa3uGGFe6J2epbFu6klE5OxYLBFdp+yKeVRJ4SaDj8pd4micS49QH0T1CoAoAt/ygF0ichEsloiuY5mCC/T1gCAIEkfjfO4Yad6k8scjBaiu4xEoROT8WCwRXYfrlW5MVK9AhAd7Q1dvxPeHeAQKETk/FktE1+GdcDdGEATcmWAeXdqTkQd9PY9AISLnxmKJ6DocWbpxIwaGoIufB67U1OOnYwVSh0NEdENYLBFdxzKy1IUjS+0ml8msB+x+nXoRRpNJ4oiIiNqPxRLRdUo4smQXY4aEwUfljpLKOqSf0kgdDhFRu7FYIrqGySSi/IoOANcs3Siluxy3DQ8HAOxKyYXIA3aJyEmxWCK6RkWVDkaTCJkgwN9HIXU4Tm/i8HAoFXLkF1fj2HkesEtEzonFEtE1LOuVAnyUkMv4z+NGeXm449ahXQEAuw7mShwNEVH78KcB0TV4J5z93R7fA3KZgDP5lTibXyF1OEREbcZiiega3GPJ/gJ8lLhlsBoAsDuFB+wSkfNhsUR0DY4sdYzJI3tAAPDLuRLkF1dJHQ4RUZuwWCK6RolljyUWS3YVFuSF2AHBAMz7LhERORMWS0TXKNNy24COMiWhJwAg9WQRSiprJY6GiMh2LJaIrhJF0ToNF+irlDga19M7zBcDewbAaBLxbVqe1OEQEdmMxRLRVdV1BuiuHvrKkaWOMWWUeXRp/5HLuFKjlzgaIiLbsFgiusoyquSrcofCXS5xNK5pUM8A9FT7QG8wYV9mvtThEBHZhMUS0VU8E67jCYKAqVfXLu3LzEed3iBxRERErWOxRHQV91jqHLH9gxEa4InqOgP2/3JZ6nCIiFrFYonoKu6x1DlkMgF3Xh1d+iY9DwajSeKIiIhaxmKJ6CqOLHWeUVFq+HkrUH5Fh4MnCqUOh4ioRZIXSyaTCatXr8bYsWMRExODuXPnIje3+QM3y8vL8dRTTyE+Ph7x8fF46aWXUFNT06DN7t27MWXKFERHR2PatGnYv39/m/owmUz4xz/+gTvuuANDhw7F1KlT8e9//7tBH1988QUGDBjQ6Kul2MmxcWSp87i7yXBHfA8A5iNQTKIocURERM2TvFhKTk7Gli1b8Prrr2Pr1q0QBAHz5s2DXt/0bcWLFi1CXl4eNm3ahNWrV+PAgQNYvny59fGUlBQ888wzmDVrFrZv344xY8ZgwYIFyM7OtrmPv//97/jwww+xePFifPXVV5g9ezaWL1+OL774wtrm9OnTGDFiBH766acGX+Hh4R3wXaLOwJGlzjV+aFeolG4oLKvB4TPFUodDRNQsSYslvV6PDRs2YOHChRg/fjwiIyOxatUqFBUVYc+ePY3aHz58GGlpaVixYgWioqIwatQovPrqq/jyyy9RVFQEAFi3bh0SExORlJSEiIgILF26FFFRUdi8ebPNfWzZsgVz587FnXfeiR49euD+++/HPffcg//85z/WWM6cOYPIyEgEBwc3+JLLecu5M9LpjaiqrQfAo046i6fSDROHdwMA7DyYC5GjS0TkoCQtlrKyslBdXY2EhATrNV9fXwwaNAjp6emN2mdkZCA4OBgRERHWayNGjIAgCMjMzITJZMKhQ4ca9AcAI0eOREZGhs19/PnPf8b06dMbvX5lZaX1z6dPn0bfvn3bnTs5FsuZcJ5KOVQe7hJHc/O4La47FG4y5BRewcnccqnDISJqkpuUL15YaF7YGRYW1uB6SEgICgoKGrUvKipq1FahUMDf3x8FBQXQarWoqamBWq1utr/W+pDJZBg1alSDx/Pz87Fz50488MADAICysjKUlJQgPT0dH3/8MSoqKhATE4Onn34avXv3bsd34ldubs3Xr3K5rMF/nZmj5VJRZT4TroufZ4vvQXMcLZ8b1Vn5BPp64NZh3fBteh52p+Qipm+XDnkdV3p/XCkXwPXyIdckabFUW2s+TFOhUDS4rlQqG4ziXNv++raW9jqdDnV1dc32p9PpbOrjesXFxZg/fz6CgoLwxBNPADBPwQGAXC7HW2+9hZqaGiQnJ2PWrFnYsWMHunRp3we+TCYgIMCr1Xa+vp7t6t8ROUoutfUaAIC6i5dN70FzHCUfe+mMfH57RyT2ZebjZE45NFodBvQM7LDXcqX3x5VyAVwvH3ItkhZLHh7mtSF6vd76ZwDQ6XTw9Gz8D8fDw6PJhd86nQ4qlQpKpdLa3/WPW/prrY9rnT9/HvPnz0d9fT0+/vhj+Pn5AQASEhKQlpZm/X8A+OCDDzBhwgRs27YN8+fPtyn/65lMIrTammYfl8tl8PX1hFZbC6OT703jaLlcLNACAPxU7igvr27z8x0tnxvVmfm4A7glWo0fjxTg06+zsPj+GLu/hiu9P66UC+Ba+dzIL1rk2CQtlizTYRqNBj169LBe12g0iIyMbNRerVZj7969Da7p9XpUVFQgNDQU/v7+UKlU0Gg0DdpoNBrr1FxrfVhkZmbiiSeeQHBwMD7++ONGU3fXFkoAoFKpEB4ebl0k3l4GQ+sfFkajyaZ2zsBRcimuMI9yBvgobygeR8nHXjorn8kjeuCnIwU4dKYYOQVahAd7d8jruNL740q5AK6XD7kWSSeJIyMj4e3tjdTUVOs1rVaLkydPIi4urlH7+Ph4FBYWNtjLyPLc2NhYCIKA2NhYpKWlNXheamoqhg8fblMfAHD06FE89thj6NevHz799NNGhdKnn36KkSNHWqf9AKCqqgo5OTlc9O2kuG2AtMKCvDB8QDAAYHcK9yojIsciabGkUCiQlJSElStXYt++fcjKysKSJUugVquRmJgIo9GI4uJia1ESExOD2NhYLFmyBEePHkVKSgqWLVuG6dOnW0eF5syZg507d2Ljxo3Izs7G22+/jVOnTmH27Nk29WEwGPD0008jKCgIf/7zn6HX61FcXIzi4mKUlZUBACZMmABRFPHss8/i7NmzOHbsGBYuXIjAwEDMmDFDmm8m3RDrhpQsliQzdVQvAEDqSY11pI+IyBFIfvvBokWLcO+99+LFF1/Egw8+CLlcjvXr10OhUKCgoABjxozBrl27AJhPLF+zZg3Cw8Mxe/ZsLF68GOPGjcMrr7xi7W/MmDF488038dlnn2HGjBlISUnB2rVrrVsFtNbH0aNHkZubi7y8PNx2220YM2aM9evee+8FYJ4+3Lx5M6qrq/Hggw/ikUcegY+PDz766KMGa6/IORiMJuvdcNy9Wzo91T4Y3DsQJlHE16kXpQ6HiMhKELkTnMMwGk0oK2t+cbGbmwwBAV4oL692+rl9R8qluKIWS9cehJtcwNqnb4VMENrchyPlYw9S5XP6Yjne+vQw3OQyvPPEKPh5K+3Sryu9P66UC+Ba+QQH+0gdAnUQyUeWiKRmmYIL9PVoV6FE9tO/uz/6dvODwWjCt+l5UodDRASAxRIRF3c7EEEQMGVUTwDAd4cvobquXuKIiIjaWSx98MEHTe6wTeSMrIu7uV7JIcREBCE82Bs6vRHfZeZLHQ4RUfuKpc2bN2PSpEmYM2cOduzY0eTO10TOwnIuXBeOLDkE8+iSed+1PRn50OmNEkdERDe7dhVLP/30E1auXAl3d3c899xzGD16NF5++WUcPnzY3vERdTiOLDme+MgQhPh7oqq2HvuPXJY6HCK6ybWrWFIoFJgyZQo+/PBDfP/993j88cdx4sQJzJo1C3feeSfWrVuH0tJSe8dK1CG4ZsnxyGUyTE4wjy59nXYRBic/BoOInNsNL/AOCQnB7373Ozz++OOIi4vDhQsX8N5772H8+PF46aWXUFVVZY84iTqESRRRpuXIkiMaPTgMft4KlF/R4eDxQqnDIaKb2A0VS2lpaXjhhRdwyy234P/+7//g7u6O9957DxkZGXj77bexZ88eLFmyxF6xEtmdtloPg1GEIJjPhSPH4e4mwx3x5tGlXSm5MJm4JRwRSaNdB+muWrUKO3bsQEFBAcLCwvDII49g5syZ6Nq1q7XNlClTcPr0aXz00Ud2C5bI3izrlfy9lXCTcycNR3PrsK7YeTAHReW1yDxTjPjIEKlDIqKbULuKpY0bN+K2227Da6+9hltuuQVCMxv5RUdHY/HixTcSH1GHKuUUnEPzULhh0vBwfHUgBzt/zkHcgOBmP2+IiDpKu4qlH3/8EX5+figuLrZ+cFVWVqKgoACRkZHWdrfddpt9oiTqIJaRJW4b4Lhui+uOb9LycFFTheMXyhDdJ0jqkIjoJtOueQeZTIY5c+bg4Ycftl47cuQIpk+fjieffBK1tTwxnJwDR5Ycn7enO8YPNU/x7/w5R9pgiOim1K5i6Z133sHZs2fxxz/+0XotISEBycnJOH78OFavXm23AIk6knWPJY4sObQ7RvSAm1zAmfxKnMmrkDocIrrJtKtY+u6777B06VLcfvvt1msKhQITJ07EH//4R+zevdtuARJ1JMvIUiCLJYcW4KPELYPDAJjvjCMi6kztKpaqq6vh6+vb5GNBQUEoLy+/oaCIOgun4ZzHnQk9IAjA0exSXCy6InU4RHQTaVexFBUVhc8//7zJx7Zt24YBAwbcUFBEnaGmrh61OvO5Y1zg7fhCA1TWrQM4ukREnaldd8M98cQTmDdvHmbOnInExEQEBQWhrKwM+/btw4kTJ7B27Vp7x0lkdyVX1yt5e7pDqZBLHA3ZYuqoXkg7pUF6lgYzxtYgNFAldUhEdBNo18jS6NGj8be//Q2CIGD16tV4+eWX8f7778NoNCI5ORnjxo2zd5xEdscz4ZxP9xBvDIkIgigCu1M5ukREnaNdI0sAMH78eIwfPx46nQ4VFRXw8fGBSsXf8sh5WO+E43olp3LXqF44ml2KA8cKcc+YPjymhog63A2d71BZWYny8nIYjUZUVFTg8uXL1i8iR8eRJefUN9wP/bv7w2gS8U3aRanDIaKbQLtGlnJycvDcc8/hyJEjzbY5depUu4Mi6gwcWXJed43qiffyKvC/Xy7hrlt6wdvTXeqQiMiFtatYeu2115CTk4M//OEPUKvVkMl4ACk5H44sOa+o3oHoEeqNi0VV2JuRh+lj+0gdEhG5sHYVSxkZGXjjjTdw11132Tseok5jPReOI0tORxAE3DWqF5K3H8e+zHzcMaIHPJXtXoJJRNSidg0JeXt7w8/Pz96xEHUafb0R2pp6AJyGc1ax/YMRGqhCdZ0BP/zCdZJE1HHaVSzdc889+OSTTyCKor3jIeoUlik4pbscXh4ckXBGMpmAKQk9AADfpF9EvcEocURE5Kra9VPC09MTmZmZSExMRHR0NDw8Gv5mLggC3nzzTbsESNQRrj3mRBAEiaOh9hoVpcb2Hy+g/IoOB44V4tZh3aQOiYhcULuKpS+++AI+Pj4wmUxN3hHHHz7k6Mq0OgBc3O3s3OQyTB7ZA5/tPYvdqbkYGxMGOW84ISI7a1ex9N1339k7DqJOVcJtA1zGuJiu2HEgB8UVdUg/pUFClFrqkIjIxdzQr2AmkwlZWVnYv38/qqqqUFFRYaewiDqWdY8lX+7+7OyU7nIkxoUDAHam5MLEtZREZGftLpa+/PJL3HrrrZg+fTp+//vfIzc3F8899xwWLlwIvV5vzxiJ7I57LLmWicPD4aGQ41JxNY6eK5U6HCJyMe0qlnbt2oWlS5ciISEBq1atst4Vd/vtt2P//v1ITk62a5BE9sbdu12Ll4c7Jlxd3L3zYA7v1CUiu2pXsbR27Vo88MADePvtt3H77bdbr8+cORN/+MMfsHPnTrsFSGRvRpMJ5Ve4wNvV3B7fHW5yGbIva3H6YoXU4RCRC2lXsXThwgUkJiY2+VhMTAyKiopuKCiijlRxRQ+TKEIuE+DvzTVLrsLPW4mxQ8IAmNcuERHZS7uKpaCgIGRnZzf5WHZ2NoKCgm4oKKKOZFmvFOCjhEzGbS5cyeSRPSATBJy4UIacQq3U4RCRi2hXsTRlyhSsXr0aX3/9tXUxtyAIOH78OJKTkzF58mS7BklkTzwTznUF+3ti5KAQAMDOgxxdIiL7aNc+S4sXL8aZM2ewePFiyK5uAPfwww+jpqYGcXFx+L//+z+7BklkTyW8E86lTUnoiYMninDodDEKSqsRFuQldUhE5OTaVSwpFAr84x//wIEDB3Dw4EFUVlbCx8cHI0aMwPjx47mDNzk03gnn2roFe2NYvy44fLYEu1Jy8ejUQVKHRERO7oZOEB09ejRGjx5tr1iIOgX3WHJ9U0b1xOGzJUg5UYTpY/ogNEgldUhE5MTaVSytWbOm1TZ/+MMf2tM1UYfjyJLri+jqh8ge/si6WIFv0i7id3dGSh0SETkxuxdL3t7eCAkJYbFEDkkURZRpWSzdDKaO6oWsi79g/5HLmD6uDwICuHaJiNqnXXfDZWVlNfo6dOgQ1q1bBz8/P7z00ks292UymbB69WqMHTsWMTExmDt3LnJzm7+Lpby8HE899RTi4+MRHx+Pl156CTU1NQ3a7N69G1OmTEF0dDSmTZuG/fv3t6kPk8mEf/zjH7jjjjswdOhQTJ06Ff/+97/bHAc5nis19dAbTACAQB8WS65sUK8A9FT7QG8w4dv0PKnDISIndkMH6V5LpVJh7NixWLBgAd5++22bn5ecnIwtW7bg9ddfx9atWyEIAubNm9fs+XKLFi1CXl4eNm3ahNWrV+PAgQNYvny59fGUlBQ888wzmDVrFrZv344xY8ZgwYIFDfaFaq2Pv//97/jwww+xePFifPXVV5g9ezaWL1+OL774wuY+yDFZ1iv5eyvg7ma3v/7kgARBwNSEngCAvRl5qKmrlzgiInJWdv9pERYW1uyGldfT6/XYsGEDFi5ciPHjxyMyMhKrVq1CUVER9uzZ06j94cOHkZaWhhUrViAqKgqjRo3Cq6++ii+//NK6a/i6deuQmJiIpKQkREREYOnSpYiKisLmzZtt7mPLli2YO3cu7rzzTvTo0QP3338/7rnnHvznP/+xuQ9yTCVcr3RTiR0QDHWgCjV1Bnx9MEfqcIjISdmtWBJFEZcvX8a6devQrVs3m56TlZWF6upqJCQkWK/5+vpi0KBBSE9Pb9Q+IyMDwcHBiIiIsF4bMWIEBEFAZmYmTCYTDh061KA/ABg5ciQyMjJs7uPPf/4zpk+f3uj1KysrbeqDHNevG1J6ShwJdQaZIODOhB4AgO0/ZENvMEocERE5o3Yt8I6MjGx2LyVRFG2ehissLARgHo26VkhICAoKChq1LyoqatRWoVDA398fBQUF0Gq1qKmpgVqtbra/1vqQyWQYNWpUg8fz8/Oxc+dOPPDAAzb1cSPcWpgakstlDf7rzKTKpeyKuVgK8fds8XvdVq703gCulc/YmK748qcLKNPq8POxQtw6zLZf5hyVK703gOvlQ66pXcXSggULmiyWvL29ceutt6JXr1429VNbWwvAXGhcS6lUWkdxrm9/fVtLe51Oh7q6umb70+l0NvVxveLiYsyfPx9BQUF44okn2tWHrWQywaY7dnx9XWdUpLNzqag2r1vp3tWvQ+6OcqX3BnCdfH4zoR/WfXkcu1Jycff4vi7xg9lV3hsLV8uHXEu7iqWFCxfa5cU9PMzrRvR6vfXPAKDT6eDp2fgfjoeHR5MLv3U6HVQqFZRKpbW/6x+39NdaH9c6f/485s+fj/r6enz88cfw8/Nrcx9tYTKJ0Gqbv6NOLpfB19cTWm0tjEZTu1/HEUiVS2FJFQBA5S5DeXm13fp1pfcGcL18EgaFYMseBQpLa/DtwQtIiFK3/iQH5WrvjSvlw+0pXFe7iqXLly+3qX3Xrl2bvG6ZytJoNOjRo4f1ukajQWRk403k1Go19u7d2+CaXq9HRUUFQkND4e/vD5VKBY1G06CNRqOxTs211odFZmYmnnjiCQQHB+Pjjz9uMO1max/tYTC0/mFhNJpsaucMOjMXURRRfHXNUoC3okNe15XeG8B18nF3k2Ha2D749Jss7DiQg+H9g53+WCZXeW8sXC0fci3tKpYmTpzYpg+aU6dONXk9MjIS3t7eSE1NtRZLWq0WJ0+eRFJSUqP28fHxWLlyJXJzc9Gzp/mW4NTUVABAbGwsBEFAbGws0tLScN9991mfl5qaiuHDh9vUBwAcPXoUjz32GAYNGoTk5GTriJKtcZBjqq4zQKc3L/DlUSc3n7vG9Ma2788iT1OFY+dLMSSii9QhEZGTaFex9Je//AXLli1DVFQU7r77boSGhqK8vBzfffcddu/ejSeeeMKmO+IUCgWSkpKwcuVKBAYGolu3bnjnnXegVquRmJgIo9GIsrIy+Pj4wMPDAzExMYiNjcWSJUvwyiuvoKamBsuWLcP06dOtIzpz5szB/PnzMWjQIIwbNw6ff/45Tp06hTfeeAMAWu3DYDDg6aefRlBQEP785z9Dr9ejuLgYACCXyxEYGGhTHOR4SirNa+R8vRRQuMsljoY6m49KgQmx3bA75SJ2HsxlsURENmtXsbR9+3ZMnDgRK1asaHB9ypQpCAoKwqFDh2w+7mTRokUwGAx48cUXUVdXh/j4eKxfvx4KhQL5+fmYNGkSVqxYgZkzZ0IQBKxZswbLly/H7NmzoVQqMXnyZDz//PPW/saMGYM333wTycnJWLVqFfr27Yu1a9dab/NvrY+jR49adxC/7bbbGsTarVs3fPfddzbFQY7n120DOKp0s5o8sif2pOfhbH4lzuRVoH93f6lDIiInIIiiKLb1SUOHDsUHH3yA0aNHN3rswIEDePLJJ3HkyBG7BHgzMRpNKCtrftGxm5sMAQFeKC+vdvq5fSly+SbtIrZ+dw4jBobg8XsG27VvV3pvANfO5x87TmL/kcsYEhGExffFSB1am7nye+Ps+QQH+0gdAnWQdt0/GxAQgF9++aXJxw4cOMCpKHJI1t27uV7ppnZnQg8IAnA0uxQXi65IHQ4ROYF2TcPde++9+Nvf/oba2lpMnDgRgYGBKCkpwa5du7Blyxa8/PLL9o6T6IZxGo4AIDRAhfjIEKSd0mBXSq7dRxmJyPW0q1h68sknceXKFWzatAnr168HYL4t29PTE3/84x+tO10TOZJfz4Xj5nc3uykJPZF2SoP0LA1mjKtBaED790cjItfXrmJJEAQ899xzePLJJ/HLL7+gsrISAQEBGDp0KLy9ve0dI5FdlGrNd8NxZIl6hPoguk8Qjp0vxdepFzF7cuN93YjIPnbs2IF//vOfOHPmDACgT58+uO+++2weWNm2bRuef/55nD59uiPDbFG7iiULb29vhISEADAv+jYYDHYJisjeaurqUavjHkv0q6mjeuLY+VIcOFaAu0f3RoCPUuqQiFzOf/7zH7z++uv405/+hPj4eIiiiIMHD+KNN95ASUmJzXfOS63dxdKXX36Jd999F8XFxRAEAf/+97/x17/+Fe7u7nj33XebPDuNSCqWKTgflTuUCu6xRED/7v7oG+6Hc/mV2JORh/sn9JU6JCKX8+mnn+Lee+/F/fffb73Wp08fFBYW4qOPPnKaYqldd8Pt2rULS5cuRUJCAt577z2YTObbPW+//Xbs378fycnJdg2S6EaVcHE3NWHKSPMO/D/8cgm1Oo6Mk2MTRRF1OoMkX+3YZQgAIJPJcOjQIVRWVja4Pm/ePGzduhUAUFhYiKeffhq33HILoqKiMH78eKxatcpaW1xPr9fjnXfewdixYzFs2DDcf//9+Omnn6yPG41GvPPOOxg/fjwGDx6MyZMn47PPPmtX/BbtGllau3YtHnjgAbzyyiswGo3W6zNnzkRpaSn+9a9/YfHixTcUGJE9cXE3NWVI3yCEBalQUFqDH365jMkje7T+JCIJiKKIpWt+wqmcMklef2CvQLz1hzFtPlNx3rx5WLx4McaNG4eRI0ciLi4OCQkJiI6Ohq+vLwDg97//PYKCgrB+/Xp4e3vjf//7H15//XVER0c32hwaAJ5//nmcPXvWeuLH999/j8cffxxr1qzBrbfeik8//RRff/01Vq1ahdDQUHz//fd45ZVX0K9fP8TFxbUr/3aNLF24cAGJiYlNPhYTE4OioqJ2BUPUUazbBnC9El1DJgiYPMJcIO3JyIPByU+9J3I0d9xxB7Zu3Yrbb78dx44dw7vvvov77rsPkydPRmZmJurq6nDPPffgtddew8CBA9G9e3c8/PDDCAkJaXJBd25uLv773//ijTfeQEJCAnr16oU5c+Zg6tSp1rvzL168CJVKhe7du6Nbt25ISkrCxo0b0bt373bn0a6RpaCgIGRnZze5g3d2djaCgoLaHRBRR7CcCxfEaTi6TkKUGtt+PI/yKzqknizC6OgwqUMiakQQBLz1hzHWw8A7m1Ihb/OoksWQIUPwzjvvQBRFnDlzBj/88AM++ugjzJs3D3v27EFSUhK+/vprbN68Gbm5ucjKyoJGo2lyGu7kyZMAgN/97ncNrtfX11tHqh566CHs3bsX48aNw+DBgzF69GjceeedN1SbtKtYmjJlClavXo2QkBCMHz8egPmNPH78OJKTk3HXXXe1OyCijsANKak57m4yJMZ1x3/+l42vUy/ilsHqdv9QIOpIgiDAQ3lDN7F3qsLCQqxbtw7z589HaGgoBEHAgAEDMGDAAEyaNAlTpkzBjz/+iI8++gi1tbW48847cc899+Cll17CQw891GSflrVTn3zyCby8vBo8JpOZJ8t69eqFb7/9FmlpaThw4AD27duHtWvXYsWKFZgxY0a7cmnXd33x4sU4c+YMFi9ebA3u4YcfRk1NDeLi4vB///d/7QqGqKOUai1rllgsUWO3Du2KHT/n4FJJNY6dL8WQiC5Sh0Tk9BQKBbZu3Qq1Wo158+Y1eMyyJ2N+fj5OnDiBAwcOoEsX87+7iooKlJaWNrmovF+/fgAAjUaDW2+91Xp91apVEAQBixcvxkcffYSgoCBMnToVo0ePxrPPPos5c+Zg165dnVssKRQK/OMf/8CBAweQkpKCiooK+Pj4YMSIERg/fjx/KyOHUlNnQHWd+U4n7rFETVF5uOPWoV3xTVoevk69yGKJyA4CAwPx2GOP4S9/+QuqqqowefJkeHt749y5c0hOTsbIkSMxbtw4/PWvf8VXX32FO+64AwUFBXjvvfdQX18PvV7fqM9+/fphwoQJWLZsGV5++WX0798f3377Lf7+97/jjTfeAACUlpbigw8+gIeHByIjI5GdnY2TJ09i9uzZ7c6lXcXS448/jt/97ncYPXp0k+uWiByJZVTJ29Mdnk40hE2dKzGuO/Zm5CPrYgUuFGjRO8xX6pCInN7ixYvRq1cv/Otf/8Inn3yCuro6hIWFYcqUKfj9738PlUqF559/Hps2bcJf/vIXhIaGYsqUKQgLC8ORI0ea7HPVqlVYtWoVli1bhsrKSnTv3h2vvfYafvOb3wAA/vCHP8BgMOC1115DSUkJgoODMWvWLPz+979vdx6C2I7NE4YPH26tCsl+jEYTysqqm33czU2GgAAvlJdXw2Bw7rt2OjOXw2eL8dfPj6Gn2gfLHonvkNdwpfcGuHnz+cd/T+Ln44WIiwzBk9Md84Ddm/W9cQbBwT5Sh0AdpF1bB4wePRr//ve/odPp7B0Pkd1x2wCylWUbgczTGmjKaySOhogcRbvmJJRKJXbv3o09e/YgPDy80e14giBg8+bNdgmQ6Eb9uiEliyVqWXiINwb3CcTx82X4Jj0PD98+QOqQiMgBtGtkqbCwEMOGDcOQIUMQGBgIURQbfDW3RTmRFLhtALXFnVePQDlwtADamsYLTIno5mPzyNKOHTswduxY+Pv74+OPP+7ImIjsqoTbBlAbRPbwR0+1D3ILr+C7zHxMH9tH6pCISGI2jyw9++yzuHjxYoNra9euRUlJid2DIrKnX0eWeC4ctU4QBNx59Yy47w5dgq5emh2Tichx2FwsXX/TnNFoxPvvv89z4Mih1ekNqKqtB8A9lsh2wwcEo4ufB6pq6/Hz8UKpwyEiibVrzZJFO3YdIOpUllElLw83qDy4xxLZRi6TITG+OwBgT3oeTPysI7qp3VCxROTorHfCcVSJ2mhMdBg8lW4oLKvBsexSqcMhIgmxWCKXxm0DqL08lW4YH9MVAPBtep7E0RCRlG64WOI5cOTIuLibbsSk4eGQCQJO5ZbjYtEVqcMhIom0aRHHggULoFAoGlx7/PHH4e7u3uCaIAjYu3fvjUdHdIMs2wZwjyVqjyA/D8RFBiPtlAZ70vPw6F2DpA6JiCRgc7E0Y8aMjoyDqEOUVtYC4DQctd/t8T2QdkqDlJNF+M2tEfD3VkodEhF1MpuLpRUrVnRkHEQdooS7d9MN6tPVF33D/XAuvxLfHbqEmeO4SSXRzYYLvMll6eqNuFJj3mOJxRLdiDuubiPwv8PcpJLoZsRiiVyWZVTJUymHysO9ldZEzRvW79dNKg9yk0qimw6LJXJZJRXm9UrBvBOObpBMJiAx7uomlRncpJLoZsNiiVxWsaVY8mexRDduzJAweCrlKCitwfHz3KSS6GbCYolcVnGFeRqOxRLZg3mTym4AgG/SuEkl0c2ExRK5rF9Hlri4m+zj2k0q8zRVUodDRJ2ExRK5rOJKTsORfVk2qQSAb9MvShwNEXUWFkvkkkRR5Jol6hC3x/cAAKSeLEJllU7iaIioM7BYIpekramHvt4EAdy9m+zLskmlwSjiu0OXpA6HiDoBiyVySZZRpUBfJdzk/GtO9nX71W0Evj98CXpuUknk8vhThFwSp+CoI8X2/3WTyp9PcJNKIlfHYolckqVY6sJiiTqATCbgNssmlel5ELlJJZFLY7FELokjS9TRxg4Jg4fCvEnliQtlUodDRB1I8mLJZDJh9erVGDt2LGJiYjB37lzk5uY22768vBxPPfUU4uPjER8fj5deegk1NTUN2uzevRtTpkxBdHQ0pk2bhv3797e5D4v09HQMHDiw0fUvvvgCAwYMaPTVUuzUeX7dkJKLu6ljeCrdMC6mKwDg23RuUknkyiQvlpKTk7Flyxa8/vrr2Lp1KwRBwLx586DX65tsv2jRIuTl5WHTpk1YvXo1Dhw4gOXLl1sfT0lJwTPPPINZs2Zh+/btGDNmDBYsWIDs7Gyb+7BITU3Fk08+CZPJ1Oix06dPY8SIEfjpp58afIWHh9vhu0I3iiNL1BkmDQ+HIADHL5ThUkm11OEQUQeRtFjS6/XYsGEDFi5ciPHjxyMyMhKrVq1CUVER9uzZ06j94cOHkZaWhhUrViAqKgqjRo3Cq6++ii+//BJFRUUAgHXr1iExMRFJSUmIiIjA0qVLERUVhc2bN9vch8FgwOuvv465c+eie/fuTcZ+5swZREZGIjg4uMGXXC7voO8W2areYETFFfP+NyyWqCMF+3sitp95k8p9GRxdInJVkhZLWVlZqK6uRkJCgvWar68vBg0ahPT09EbtMzIyEBwcjIiICOu1ESNGQBAEZGZmwmQy4dChQw36A4CRI0ciIyPDpj4AoKamBsePH8eGDRuQlJTUZOynT59G37592588dZiSyjqIAJQKOXw83aUOh1xcYrz5F6qfjxeiqrZe4miIqCO4SfnihYXmW27DwsIaXA8JCUFBQUGj9kVFRY3aKhQK+Pv7o6CgAFqtFjU1NVCr1c3211ofgLlg27JlCwBg27ZtjeIoKytDSUkJ0tPT8fHHH6OiogIxMTF4+umn0bt377Z8Cxpxc2u+fpVf3S9I7gL7BnVkLuVXd1UO8feEu3vnjPS50nsDMJ+2GNgrAL3UPsgpvIIfj17GtNE39hnQGr43RJ1P0mKptta8rkShUDS4rlQqUVlZ2WT769ta2ut0OtTV1TXbn06ns6kPW5w5cwYAIJfL8dZbb6GmpgbJycmYNWsWduzYgS5dutjUz/VkMgEBAV6ttvP1dZ2ppY7IpUqnAQB0C/G26ftpT6703gDMx1YzJ/bDe58ewr7MS3hw8iC4t/BLj73wvSHqPJIWSx4e5juV9Hq99c8AoNPp4OnZ+B+Oh4dHkwu/dTodVCoVlEqltb/rH7f011oftkhISEBaWhr8/Pys1z744ANMmDAB27Ztw/z5823q53omkwittum78gDzb16+vp7QamthNDZedO5MOjKX3MsVAAB/LwXKyztn0a0rvTcA82mrwT394e+tQJm2Dt8evIBbBqtbf1I78b1xXJ39yxl1HkmLJct0mEajQY8ePazXNRoNIiMjG7VXq9XYu3dvg2t6vR4VFRUIDQ2Fv78/VCoVNBpNgzYajcY6NddaH7a6tlACAJVKhfDwcOsi8fYyGFr/sDAaTTa1cwYdkUtRmXnEMsjXo9O/T6703gDMpy0mxIbji/3n8XVKLuIHBEMQhA55HQu+N0SdR9JJ4sjISHh7eyM1NdV6TavV4uTJk4iLi2vUPj4+HoWFhQ32MrI8NzY2FoIgIDY2FmlpaQ2el5qaiuHDh9vUhy0+/fRTjBw50jrtBwBVVVXIycnhom8HwG0DSArjh3aFu5sMOYVXcO5S42UEROS8JC2WFAoFkpKSsHLlSuzbtw9ZWVlYsmQJ1Go1EhMTYTQaUVxcbC1KYmJiEBsbiyVLluDo0aNISUnBsmXLMH36dOuo0Jw5c7Bz505s3LgR2dnZePvtt3Hq1CnMnj3b5j5aM2HCBIiiiGeffRZnz57FsWPHsHDhQgQGBmLGjBkd880im4iieE2xxA0pqfP4qhQYFWX+DNnDTSqJXIrktx8sWrQI9957L1588UU8+OCDkMvlWL9+PRQKBQoKCjBmzBjs2rULACAIAtasWYPw8HDMnj0bixcvxrhx4/DKK69Y+xszZgzefPNNfPbZZ5gxYwZSUlKwdu1a61YBtvTRmrCwMGzevBnV1dV48MEH8cgjj8DHxwcfffRRg7VX1PmqautRpzefAt/Fj+8Fda7Eq+fFZZ4pRsnVop2InJ8g8gRIh2E0mlBW1vyCZDc3GQICvFBeXu30c/sdlcv5y1q8/lEGAnyUeHfBaLv12xpXem8A5nMj3t1yGCdyynHHiO747cR+du+f743jCg72kToE6iCSjywR2ZN1Co6jSiSRxHjzzSr7j1xGrc4gcTREZA8slsilcHE3SW1wn0CoA1Wo1Rlx4FjjzXWJyPmwWCKXoim/WiwFsFgiacgEAYlx5gO192bkw2TiSgciZ8diiVxKUbl5U8/QANs2GCXqCLcMDoOXhxs0FbU4kl0idThEdINYLJFLKbo6shQayJElko5SIce4oV0BcBsBIlfAYolcRq3OAG21+SibEH+OLJG0JsWGQyYIyLpYgYtFV6QOh4huAIslchmW9Uo+KneoPCQ9yYcIgb4eiIsMBgDsyeDoEpEzY7FELoPrlcjR3H51G4HUk0WorNJJHA0RtReLJXIZlvVKIbwTjhxEn66+iOjmC4NRxPeHL0kdDhG1E4slchmaMsvIEoslchyWI1C+P3wJ9QajxNEQUXuwWCKXUVRhuROO03DkOIYPCEagrxJXauqRcrJI6nCIqB1YLJHL+HVkicUSOQ65TIZJw82bVO5JzweP4yRyPiyWyCXU6gzQ1tQD4JolcjzjYrpC6S5HfnEVsnLLpQ6HiNqIxRK5BMudcL4qd3gquW0AORYvD3eMjlYDAPZk5EscDRG1FYslcglFZVfvhON6JXJQt11d6H3kXAmKrk4ZE5FzYLFELkFTzjvhyLGpA1WIiQiCCPMBu0TkPFgskUv4dY8ljiyR40qMN48u/XSsADV19RJHQ0S2YrFELqGII0vkBAb2DEB4sBd09UbsP1IgdThEZCMWS+QSLGuWuG0AOTJBEKybVO7LzIPRZJI4IiKyBYslcno1dfWoquW2AeQcEqJC4aNyR6lWh0NnSqQOh4hswGKJnJ5lvZKvl4LbBpDDc3eTY8KwbgCAPel5EkdDRLZgsUROj+uVyNlMGNYNbnIB5y5V4vxlrdThEFErWCyR09NwvRI5GT9vJUYODAUA7Mng6BKRo2OxRE7PMrLE9UrkTCzbCGRkaVCmrZM4GiJqCYslcnqaq2uWQrl7NzmRHqE+iOzhD6NJxHeHLkkdDhG1gMUSOTVRFFFYxjVL5Jws2wj88Msl6OqNEkdDRM1hsURO7UptParrDBDAkSVyPjF9uyDY3wPVdQb8fLxQ6nCIqBkslsipFZRUAwCC/DygdJdLHA1R28hkgvWA3b0ZeTCJosQREVFTWCyRUyu4OgWnDuKoEjmnMdFh8FTKUVBag+Pny6QOh4iawGKJnFpBiblY6hrkJXEkRO3jqXTD2CFdAXAbASJHxWKJnFpBqXkaLowjS+TEJg0PhyAAJy6U4VJxldThENF1WCyRUysoNY8shXFkiZxYsL8nYvsFAwD2ZORLHA0RXY/FEjktnd6I0qub+XFkiZydZZPKgycKcaVGL3E0RHQtFkvktCz7K3l7usNHpZA4GqIb0y/cDz3VPqg3mPC/Xy5LHQ4RXYPFEjktrlciVyIIAm6/Orr03aF8GIwmiSMiIgsWS+S0LnO9ErmY+MgQ+HkrUFmlR/opjdThENFVLJbIaRVyZIlcjJtchkmx4QCAb9PzIHKTSiKHwGKJnBbvhCNXNH5oV7i7yZBbdAVn8yulDoeIwGKJnJTRZEJRuaVY4sgSuQ4flQKjotQAgD3p3KSSyBGwWCKnVFJRB4NRhMJNhiA/D6nDIbIryzYCh84Wo7iiVuJoiIjFEjmly1fXK6kDVZAJgsTRENlXty5eiOodCFEE9mVyk0oiqUleLJlMJqxevRpjx45FTEwM5s6di9zc3Gbbl5eX46mnnkJ8fDzi4+Px0ksvoaampkGb3bt3Y8qUKYiOjsa0adOwf//+NvdhkZ6ejoEDB7YrDuo4haU8QJdcm2Ubgf1HLqNWZ5A4GqKbm+TFUnJyMrZs2YLXX38dW7duhSAImDdvHvT6pnewXbRoEfLy8rBp0yasXr0aBw4cwPLly62Pp6Sk4JlnnsGsWbOwfft2jBkzBgsWLEB2drbNfVikpqbiySefhMnUeL8TW/ugjmEZWeIBuuSqonoHIixIhTq9ET8dLZA6HKKbmqTFkl6vx4YNG7Bw4UKMHz8ekZGRWLVqFYqKirBnz55G7Q8fPoy0tDSsWLECUVFRGDVqFF599VV8+eWXKCoqAgCsW7cOiYmJSEpKQkREBJYuXYqoqChs3rzZ5j4MBgNef/11zJ07F927d29XHNSxOLJErk4mCLgtzvz5sycjDyYTtxEgkoqkxVJWVhaqq6uRkJBgvebr64tBgwYhPT29UfuMjAwEBwcjIiLCem3EiBEQBAGZmZkwmUw4dOhQg/4AYOTIkcjIyLCpDwCoqanB8ePHsWHDBiQlJbU5DupYoihaN6TkyBK5slsGq+Hl4YaSyjocOlMsdThENy03KV+8sLAQABAWFtbgekhICAoKGg87FxUVNWqrUCjg7++PgoICaLVa1NTUQK1WN9tfa30A5oJty5YtAIBt27a1OY4b4ebWfP0ql8sa/NeZ3UguFVU61OoMEASga4hXi9+zzuJK7w3AfByFm5sMk+K646ufLuDbjDwkDFY7bS7NcbV8yDVJWizV1ppviVUoGh6CqlQqUVnZeDO22traRm0t7XU6Herq6prtT6fT2dSHrXHfaB9NkckEBAS0PlLi6+vZ7tdwNO3JJc8yBRfohdBgX3uHdENc6b0BmI8juHdSf+w6mItz+ZUorNBhYO9AAM6ZS0tcLR9yLZIWSx4e5v1x9Hq99c8AoNPp4OnZ+B+Oh4dHkwu/dTodVCoVlEqltb/rH7f011oftsZ9o300xWQSodU2f0edXC6Dr68ntNpaGJ38kM0byeVUdgkA82aU5eXVHRFem7nSewMwH0czOlqNH365jH/tzcKS3w5z6lyu5+zvzbVs+WWXnJOkxZJlKkuj0aBHjx7W6xqNBpGRkY3aq9Vq7N27t8E1vV6PiooKhIaGwt/fHyqVChpNwwMoNRqNdWqutT5sYY8+mmMwtP5hYTSabGrnDNqTS27hFQDmvWgc7fvgSu8NwHwcxW1x3fHDL5eRmVWMy8VV8PX1dNpcmuNq+ZBrkXSSODIyEt7e3khNTbVe02q1OHnyJOLi4hq1j4+PR2FhYYN9mCzPjY2NhSAIiI2NRVpaWoPnpaamYvjw4Tb1YQt79EHtl19cBQDoHuItcSREnaNbFy9E9wmCCOCbtItSh0N005G0WFIoFEhKSsLKlSuxb98+ZGVlYcmSJVCr1UhMTITRaERxcbF1LVJMTAxiY2OxZMkSHD16FCkpKVi2bBmmT59uHdGZM2cOdu7ciY0bNyI7Oxtvv/02Tp06hdmzZ9vcR2vs0Qe1j8kk4lKxeeqtWzCHvOnmMXnEr5tUXqlpeh86IuoYkt9+sGjRItx777148cUX8eCDD0Iul2P9+vVQKBQoKCjAmDFjsGvXLgCAIAhYs2YNwsPDMXv2bCxevBjjxo3DK6+8Yu1vzJgxePPNN/HZZ59hxowZSElJwdq1a623+dvSR2vs0Qe1T3FFLfQGE9zdZAgN4B5LdPOI7BmAHiHe0NebsPvnHKnDIbqpCKIocqczB2E0mlBW1vyCZTc3GQICvFBeXu30c/vtzSUjS4Pk7cfRS+2Dlx+J78AI28aV3huA+Tiqg8cLse6/JxHgo8TKBaPhCqciusp7AwDBwT5Sh0AdRPKRJaK2sKxXCud6JboJxQ8MQYCPEuVXdDh4vFDqcIhuGiyWyKnkX12vFB7MYoluPm5yGW6/unZpd2ouODFA1DlYLJFTyddcvROOi7vpJnXrsG7wVMpxqbgaxy+USR0O0U2BxRI5jTq9AZoK867v3TgNRzcpLw933D6yFwBuI0DUWVgskdOwbBng562Ar6rxcTNEN4u7x/aBTBBwMqccF4uuSB0OkctjsUROw7q4m+uV6CYXEqhC/MAQAMA3aXkSR0Pk+lgskdPI15hHlrqzWCLCnQk9AQBpp4pQpq2TOBoi18ZiiZxGnnXbAC7uJurT1Rf9u/vDaBKxLzNf6nCIXBqLJXIKoijiEqfhiBq44+o2Av/75TJqdQaJoyFyXSyWyCmUX9Ghus4AmSAgLIgjS0QAENO3C0IDVajVGfDT0QKpwyFyWSyWyClYFneHBang7sa/tkQAIBME3BFvHl36Nj0PRpNzHxdC5Kj4U4ecQp6Gx5wQNeWWwWp4e7qjVFuHzNPFUodD5JJYLJFT+PWYE07BEV1L4S7HxNhuAMybVPIIFCL7Y7FETiGn0LzxXo9QnupNdL2JseFwk8twoeAKzuZXSh0OkcthsUQOr1ZnQFFZDQCgp5rFEtH1fL0UGB2tBsAjUIg6AoslcniW4xwCfZU85oSoGbdfXej9y9kSFF795YKI7IPFEjm83KtTcD05BUfUrLAgL8REBEGE+c44IrIfFkvk8HKvjixxCo6oZZNH9gAAHDhWAG2NXuJoiFwHiyVyeDkcWSKySf/u/uip9kG9wYT/HbokdThELoPFEjm0Or0BhaXm9Re9OLJE1CJBEKxHoHx3KB/1BqPEERG5BhZL5NDyNFUQAfh7K+DnrZQ6HCKHFzcgBEG+Smhr6nHwRJHU4RC5BBZL5NAuFHAKjqgt3OQy3BZnHl36Ju0iTNykkuiGsVgih3ahQAsA6NPVV+JIiJzHuJiu8FTKUVBag2PZpVKHQ+T0WCyRQzt/2bwbcZ+ufhJHQuQ8PJVuGB/z6xEoRHRjWCyRw7pSo0dxRR0AoHcYp+GI2uK2uHDIZQKyLlZYR2iJqH1YLJHDsnzAqwNVUHm4SxwNkXMJ9PXAiIEhAIDdqRxdIroRLJbIYZ2/zPVKRDfizpE9AQCZpzUoKucRKETtxWKJHJblTrjeYSyWiNojPMQbQyKCIIrANxxdImo3FkvkkERR5J1wRHZw59UjUH46VojKah6BQtQeLJbIIRWW1aCqth7ubjJ0D/GWOhwip9W/uz/6dPWFwWjC3gwesEvUHiyWyCGdyzdvGdBb7QM3Of+aErWXIAjWtUvfH7qEWp1B4oiInA9/CpFDOnfJXCz1DfeXNhAiFzCsfxeoA1Wo0Rnwwy+XpQ6HyOmwWCKH9GuxxM0oiW6UTBAw+erapT0ZeTAYTRJHRORcWCyRw6mqrUdBqfk2577dWCwR2cOoKDX8vBUov6JDCg/YJWoTFkvkcCzrlcKCVPD25GaURPbg7ibD7VcP2N2dmssDdonagMUSOZyzlyoAcFSJyN7GD+1mPWD3yLkSqcMhchoslsjhnM3jeiWijqDycMOtw8wH7O5O4SaVRLZisUQORac3WjejjOwRIHE0RK4nMa473OQCzl2qxNn8CqnDIXIKLJbIoZy7VAmjSUSQrxJd/DykDofI5fh7K3HLYDUAYNfBXImjIXIOLJbIoWRdLAcADOgRAEEQJI6GyDVNHtkTAoAj2aW4WHRF6nCIHB6LJXIop/MqAAADevhLGgeRK1MHqhA/MAQA8N+fc6QNhsgJSF4smUwmrF69GmPHjkVMTAzmzp2L3Nzmh4bLy8vx1FNPIT4+HvHx8XjppZdQU1PToM3u3bsxZcoUREdHY9q0adi/f7/d+/jiiy8wYMCARl8txU4t0+mNuHCZ65WIOsNdt/QCAGSeLsalkmppgyFycJIXS8nJydiyZQtef/11bN26FYIgYN68edDrmz4de9GiRcjLy8OmTZuwevVqHDhwAMuXL7c+npKSgmeeeQazZs3C9u3bMWbMGCxYsADZ2dl27eP06dMYMWIEfvrppwZf4eHhHfBdujmcu8z1SkSdJTzYG8P7B0MEsJOjS0QtkrRY0uv12LBhAxYuXIjx48cjMjISq1atQlFREfbs2dOo/eHDh5GWloYVK1YgKioKo0aNwquvvoovv/wSRUXmHWnXrVuHxMREJCUlISIiAkuXLkVUVBQ2b95stz4A4MyZM4iMjERwcHCDL7lc3gnfOdd0MqcMANcrEXUWy+hS6qkiFJXVtNyY6CYmabGUlZWF6upqJCQkWK/5+vpi0KBBSE9Pb9Q+IyMDwcHBiIiIsF4bMWIEBEFAZmYmTCYTDh061KA/ABg5ciQyMjLs1gdgHlnq27fvjX0DqIETF8zFUlTvQIkjIbo59FT7ICYiCKII/PdgjtThEDksNylfvLCwEAAQFhbW4HpISAgKCgoatS8qKmrUVqFQwN/fHwUFBdBqtaipqYFarW62P3v0UVZWhpKSEqSnp+Pjjz9GRUUFYmJi8PTTT6N3797t+E78ys2t+fpVLpc1+K8zuz4XbbUeF4uqAABDIoJa/D44Ild6bwDm48jsncv0cX1wJLsUB48XYeb4CAT7e9qlX1u50ntDrkvSYqm2thaAuVi5llKpRGVlZZPtr29raa/T6VBXV9dsfzqdzm59nDlzBgAgl8vx1ltvoaamBsnJyZg1axZ27NiBLl26tJ58E2QyAQEBXq228/Xt3A+zjmTJ5egF85YBvbv6old35x1ZcqX3BmA+jsxeucQFeGFo/2D8cqYYezIvYcG9MXbpt61c6b0h1yNpseThYV7Eq9frrX8GAJ1OB0/Pxv9wPDw8mlz4rdPpoFKpoFQqrf1d/7ilP3v0kZCQgLS0NPj5/XocxwcffIAJEyZg27ZtmD9/fuvJN8FkEqHVNr9uQC6XwdfXE1ptLYxGU7tew1Fcn0vqscsAgIE9A1Be7nx35rjSewMwH0fWEblMTeiBX84UY29aLibHhyPQt/NusHCl98aWX3bJOUlaLFmmwzQaDXr06GG9rtFoEBkZ2ai9Wq3G3r17G1zT6/WoqKhAaGgo/P39oVKpoNFoGrTRaDTWaTV79AGgQaEEACqVCuHh4dZF4u1lMLT+YWE0mmxq5wyMRhPq6404dr4UgLlYcubcXOm9AZiPI7NnLhFd/TCguz9O51Vgx4EcPJTY3y79toUrvTfkeiSdJI6MjIS3tzdSU1Ot17RaLU6ePIm4uLhG7ePj41FYWNhgLyPLc2NjYyEIAmJjY5GWltbgeampqRg+fLjd+vj0008xcuRI65QdAFRVVSEnJ4eLvtshv7gaFVV6uLvJ0J+H5xJJYtroXgCAH365jDJtXcuNiW4ykhZLCoUCSUlJWLlyJfbt24esrCwsWbIEarUaiYmJMBqNKC4uthYlMTExiI2NxZIlS3D06FGkpKRg2bJlmD59OkJDQwEAc+bMwc6dO7Fx40ZkZ2fj7bffxqlTpzB79my79TFhwgSIoohnn30WZ8+exbFjx7Bw4UIEBgZixowZEnwnndsv50oAAIN6BsDdjVsvEElhYM8A9O/uD4PRhP/yzDiiBiS//WDRokW499578eKLL+LBBx+EXC7H+vXroVAoUFBQgDFjxmDXrl0AAEEQsGbNGoSHh2P27NlYvHgxxo0bh1deecXa35gxY/Dmm2/is88+w4wZM5CSkoK1a9datwqwRx9hYWHYvHkzqqur8eCDD+KRRx6Bj48PPvroowZrr8g2R68WSzH92rcwnohunCAImDmuDwDgxyOXUVxRK3FERI5DEEVRlDoIMjMaTSgra35xs5ubDAEBXigvr3b6uX1LLrn55Vi4aj9EAO8uGI0AH6XUobWLK703APNxZB2dy3tbf8HxC2UYPViNR+8aZPf+r+dK701wsI/UIVAHkXxkiW5uR86VQATQM9THaQslIlcy4+ro0s8nClFQ6nx3phJ1BBZLJKnDZ4sBADF9gySOhIgAoHeYL4b16wJRBL786YLU4RA5BBZLJJk6nQFHs81bBgzrFyxxNERkMX1sHwgA0k5pcLHoitThEEmOxRJJJjNLA329CV38PNAj1FvqcIjoqu4h3hgxyHx38L+/PydxNETSY7FEkjlw1Lxrd1xkCARBkDgaIrrWzHF94CYXcCKnHMevbhpLdLNisUSS0NcbkX7SfJBy3IAQiaMhousF+3tiYmw4AOBf35+DycQbp+nmxWKJJHHsfCnq9EYE+XqgdxhvtyVyRHfd0gsqpRvyi6tx4HiB1OEQSYbFEkni5+PmUaURgzgFR+SovD3dcdctvQAAX+w/D129UdqAiCTCYok6XU1dPX45Y961+5bBYRJHQ0QtmTQ8HF38PFBRpcc3aRelDodIEiyWqNNlnC5GvdGEnmof3gVH5ODc3WS491bzUU+7DuaitJKH7NLNh8USdTrLFNyE4d05BUfkBOIjQzCguz/0BhO2fHdW6nCIOh2LJepUmopanMmrgABg/NU7bYjIsQmCgIcS+0MmCMg8XYwTF8qkDomoU7FYok61/xfz3kpRfQLRxd9T4miIyFbhId6YOLwbAOCTPWdgMDr3obdEbcFiiTqNwWjCT1c3opzAUSUipzN9TB/4qtxRWFaDPel5UodD1GlYLFGnOXy2BNqaevh5KTCsXxepwyGiNlJ5uOG+CX0BAF8euIDiilqJIyLqHCyWqNP87/AlAMDYmDC4yflXj8gZjRqsRv/u/tDXm7BpdxZEkTt7k+vjTyzqFBeLruBUbjlkgoDxMd2kDoeI2kkmCJgzJRIKNxlO5Zbjx6Pc2ZtcH4sl6hTfpJnXN8RFBiPIz0PiaIjoRoQGqDBjXB8AwNbvzqJMy72XyLWxWKIOV35Fh7RTRQCAO0b0kDgaIrKHxLju6NPVF7U6Iz765jSn48ilsViiDvdt+kUYTSL6h/uhd5iv1OEQkR3IZALmTBkIN7mAo9mlnI4jl8ZiiTpUZbUe3x8yL+yeMqqnxNEQkT116+KFGWPN03Gf7jmDSyXVEkdE1DFYLFGH2p2SC73BhD5dfRHdJ0jqcIjIzu4Y2QNRvQKgN5iw9svj0NcbpQ6JyO5YLFGHqajSWbcLuGdMb54DR+SCZIKAx6ZFwddLgUvF1diyj2fHkethsUQdZtsP56E3mBDRzReDewdKHQ4RdRA/LwXm3TUIAoD//XLZekMHkatgsUQdIrfwCg4cMy/4fGBiP44qEbm4qN6B1nWJG3adQm7hFYkjIrIfFktkd6Io4rN9ZyECGDkoFBHd/KQOiYg6wfSxvc3rl+pNWP35UVRU6aQOicguWCyR3f14tABn8iqgcJfhN+P7SB0OEXUSuUyGJ6YPRliQCuVXdPjr58e44JtcAoslsqvKKh3+9d05AOYTyrv4eUocERF1JpWHOxbdOwReHm64UKDF+p2nYOKGleTkWCyR3YiiiM1fn0aNzoCeoT5IjA+XOiQikkBogAoLZkRDLhOQnqXBR19nsWAip8Ziiezmu0OX8Mu5ErjJzQdtymX860V0s4rsGYDH7hoEQQD2HynAJ3vO8EgUclr8aUZ2kVt4BVuvTr/dd2tf9Aj1kTgiIpLayEGhmDtlIAQA3x+6ZL7xgwUTOSEWS3TDKqv1WP35URiMJgyJCMJtcZx+IyKz0dFhmH1nJABgb0Y+Pv7mNIwmk8RREbUNiyW6ITq9EWs+P4ryKzqoA1WYP20Q91QiogbGxXTF7+4YYN208v3/HEWtziB1WEQ2Y7FE7VZvMGHNtqPIvqyFSumGRfcOgcrDXeqwiMgB3TqsGxbMjIbCTYbj58uw4p+HUKatkzosIpuwWKJ20dUbsWbbMZzIKYfSXY4l98dAHaiSOiwicmCx/YOx9KFY+HopkF9cheWb0nH4bLHUYRG1isUStVlVbT3e3foLjp0vhcJNhoW/ieYu3URkk95hvnjxd8PRPcQbV2rqsWrrEazddpSbV5JDY7FEbXKx6Ape3ZSOc/mV8FS64akHhmJQLx6SS0S26+LniRd/F4fb47sDAHYeuIBl69OQlVsucWRETXOTOgByDiZRxL6MfPz7f9kwGE0I9vfAwt8MQXiwt9ShEZETcneT4YFJ/TCkbxf8478ncamkGm9/dhhxA4Jx/8S+3P2fHAqLJWpVnqYKn3x7GmfyKwEA0X2CMG/aIHh7cjE3Ed2YIRFB+OCZidjw5TF8dygfGaeLcSS7FOOHdsUd8T0Q5OchdYhELJaoeZqKWuz46QJ+PlEIUQQU7jLcP6EvJgzrxu0BiMhufL0UmH1nJMbFdMVne88g62IF9mbk4/tDlzBiYChuj++OHqHe/NwhyUi+ZslkMmH16tUYO3YsYmJiMHfuXOTm5jbbvry8HE899RTi4+MRHx+Pl156CTU1NQ3a7N69G1OmTEF0dDSmTZuG/fv3S9KHMzIYTTh+vhQfbDuG5/9+EAeOmwuluAHBeHNeAibGhvMDi4g6RPcQbzzz4DD88bcxGNgzAEaTiIMnCrF8UzpeXp+GnQdzUFrJ7Qao8wmixHvPr1mzBp9++ilWrFiB0NBQvPPOO8jLy8N///tfKBSKRu0ffvhh6HQ6LFu2DFqtFi+88ALi4+Px1ltvAQBSUlLw2GOP4bnnnsOoUaPwn//8B//85z+xfft2REREdFof7WE0mlBWVt3s425uMgQEeKG8vBoGg/12wNXVG3HuUiUyTxcjI0uDqtp662ODewdi+tg+6NPV126vB3RcLlJhPo7NlfJxpVyAlvPJKdTim7Q8ZJ4uhsH462PhwV4Y3DsIUb0D0bebH5QKeWeH3aTgYB7z5KokLZb0ej0SEhLwzDPP4MEHHwQAaLVajB07Fm+++SamTp3aoP3hw4fxwAMPYNeuXdai5aeffsJjjz2GH374AaGhoXj00Ufh6+uLVatWWZ/3wAMPoH///nj11Vc7rY/26IxiyWA0obCsBpeKq3FRcwVn8ypxoUALo+nXvwY+KnfERYZgwrBuHbaA+2b6wHdGzMdxuVIugG351NQZkHFag4PHC3EmrwLX/tASBKBrFy/0Vvuip9oH6kAV1IEqBPgqIevkUXAWS65L0jVLWVlZqK6uRkJCgvWar68vBg0ahPT09EbFUkZGBoKDg60FCgCMGDECgiAgMzMTkydPxqFDh/Dcc881eN7IkSOxZ8+eTutjypQpN/idaR9ttR6FZTWorqtHVW09qmsNqK6rR/kVHcq0dSjT6lCqrWtQGFkE+CgR1TsQIweGIrKnP+QyyWdoiYgAACoPN4yL6YpxMV1xpUaPkznlOHGhDCdzy1Cm1eFScTUuFVfjp2MF1ue4u8kQ4K2Ev48S/t4K+Hsr4e+thMrDDR4KOTyVbvBUuMFDKYenwg2+Xu5wd3OMESpyPJIWS4WFhQCAsLCwBtdDQkJQUFDQqH1RUVGjtgqFAv7+/igoKIBWq0VNTQ3UanWz/XVGH+0lkwkIDPRq9nHLL0l+fp64fjzQaBJhlMkQ4dP6nSOCALjJZZDLZHB3M3/JZZ37G1hLuTgj5uPYXCkfV8oFaHs+gYFe6BkegDvH9AFg3tbEYDCh3miCwSjCaDQ1+Qth63EI8JdgNIqcg6TFUm1tLQA0WpukVCpRWVnZZPum1jEplUrodDrU1dU1259Op+u0PtpLEATI5a3/Q5U1MeojlwPqoOYLLUfVVC7OjPk4NlfKx5VyAdqfjxyAu5sc3JWJOpKk/9o8PMyjIHq9vsF1nU4HT8/Gf/U9PDwatbW0V6lUUCqVrfbXGX0QERGR65C0WLJMZWk0mgbXNRpNo2kwAFCr1Y3a6vV6VFRUIDQ0FP7+/lCpVC321xl9EBERkeuQtFiKjIyEt7c3UlNTrde0Wi1OnjyJuLi4Ru3j4+NRWFjYYB8my3NjY2MhCAJiY2ORlpbW4HmpqakYPnx4p/VBRERErkPSYkmhUCApKQkrV67Evn37kJWVhSVLlkCtViMxMRFGoxHFxcXWdUQxMTGIjY3FkiVLcPToUaSkpGDZsmWYPn26dURnzpw52LlzJzZu3Ijs7Gy8/fbbOHXqFGbPnt2pfRAREZFrkHxTSqPRiPfeew/btm1DXV0d4uPj8fLLLyM8PBz5+fmYNGkSVqxYgZkzZwIASktLsXz5cvz4449QKpWYPHkynn/+eetaIwDYvn07kpOTUVhYiL59++KZZ57BqFGjrI93Vh9ERETk/CQvloiIiIgcmWvde0pERERkZyyWiIiIiFrAYomIiIioBSyWiIiIiFrAYomIiIioBSyWiIiIiFrAYomIiIioBSyWnIDJZMLq1asxduxYxMTEYO7cuQ2OWnEUycnJePjhhxtcO3XqFJKSkjB06FDceuutWL9+fYPHbcmttT7spaKiAi+//DLGjRuH2NhYPPjgg8jIyHDKXADzxqnPPPMMEhISMGzYMMyfPx/nzp1z2nyudeHCBQwbNgzbtm1z2nwuXbqEAQMGNPr697//7ZT5AObNfKdMmYLo6GhMnToVu3fvtjkWR8yHyEokh/fXv/5VHDVqlPi///1PPHXqlDh37lwxMTFR1Ol0UodmtXHjRnHAgAFiUlKS9VpZWZk4cuRI8YUXXhDPnTsn/uc//xGjo6PF//znP9Y2reVmSx/2MmfOHPHuu+8W09PTxezsbPG1114ThwwZIp47d87pchFFUbzvvvvE3/72t+LRo0fFc+fOiQsXLhRHjx4t1tTUOGU+Fnq9Xpw5c6bYv39/8fPPP7c5FkfLZ9++fWJ0dLRYVFQkajQa61dtba1T5rN9+3Zx4MCB4qZNm8ScnBxxzZo1YmRkpHjo0CGnzIfoWiyWHJxOpxOHDRsmfvrpp9ZrlZWV4pAhQ8T//ve/EkZmVlhYKD766KPi0KFDxcmTJzcoltauXSuOHTtWrK+vt1579913xTvuuEMURdtya60Pe8nJyRH79+8vZmZmWq+ZTCYxMTFR/Mtf/uJUuYii+QfLkiVLxDNnzlivnTp1Suzfv7945MgRp8vnWu+++6748MMPNyiWnDGfv/3tb+Ldd9/d5GPOlo/JZBInTJgg/vnPf25wfe7cueLatWudLh+i63EazsFlZWWhuroaCQkJ1mu+vr4YNGgQ0tPTJYzM7MSJE/Dz88NXX32FmJiYBo9lZGQgPj4ebm5u1msJCQm4cOECSktLbcqttT7sJSAgAB9++CEGDx5svSYIAkRRRGVlpVPlYsnnvffeQ79+/QAAJSUlWL9+PdRqNfr27et0+Vikp6dj69ateOuttxpcd8Z8Tp8+jb59+zb5mLPlc/78eVy6dAnTpk1rcH39+vX4/e9/73T5EF2PxZKDKywsBACEhYU1uB4SEoKCggIpQmpg4sSJePfdd9G9e/dGjxUWFkKtVje4FhISAgC4fPmyTbm11oe9+Pr6Yvz48VAoFNZru3fvxsWLFzFmzBinyuV6L730EkaPHo2vv/4ab7zxBlQqlVPmo9Vq8eyzz+LFF19sFJcz5nPmzBmUlpZi1qxZuOWWW/Dggw/ixx9/dMp8cnJyAAA1NTV49NFHMWrUKNx333347rvvnDIfouuxWHJwtbW1ANDghzgAKJVK6HQ6KUKyWV1dXZNxA4BOp7Mpt9b66CiZmZn405/+hEmTJmHixIlOncvs2bPx+eef4+6778aCBQtw4sQJp8znlVdewdChQxuNXtgSi6Plo9frkZOTg6qqKixevBgffvghoqOjMW/ePBw8eNDp8qmqqgIALF26FHfddRc2bNiA0aNH48knn3TKfIiu59Z6E5KSh4cHAPOHq+XPgPnDwdPTU6qwbOLh4QG9Xt/gmuVDTaVS2ZRba310hL179+Lpp59GTEwM3nvvPafOBYB1que1117DL7/8gn/+859Ol8/27duRkZGBHTt2NPm4s+WjUCiQnp4ONzc3awEwePBgZGdnY/369U6Xj7u7OwDg0UcfxYwZMwAAAwcOxMmTJ7Fx40any4foehxZcnCWYWmNRtPgukajaTQk7WjUanWTcQNAaGioTbm11oe9/fOf/8TChQsxbtw4rFu3zvrB7Wy5lJaW4r///S+MRqP1mkwmQ0REhDUmZ8rn888/R2lpKW699VYMGzYMw4YNAwAsW7YMU6dOdbp8APMP+OtHSvr374+ioiKny8fymv37929wvW/fvsjPz3e6fIiux2LJwUVGRsLb2xupqanWa1qtFidPnkRcXJyEkbUuPj4emZmZDX5gHzx4EL1790ZQUJBNubXWhz19+umneO211/DQQw/hL3/5S4MfZM6Wi0ajwVNPPYW0tDTrtfr6epw8eRIRERFOl8/KlSuxa9cubN++3foFAIsWLcKHH37odPlkZWVh2LBhDfbxAoDjx4+jb9++TpfPoEGD4OXlhSNHjjS4fubMGfTo0cPp8iFqROrb8ah17733njhixAhx79691v1Hbr/9dofaZ0kURXHp0qUNtg4oKSkR4+PjxaVLl4pnz54VP//8czE6Olrctm2btU1rudnShz2cP39ejIqKEhcsWNBgzxuNRiNqtVqnykUUzbdyz507V7zjjjvE9PR08fTp0+KSJUvE+Ph48dKlS06XT1Ou3TrA2fIxGo3ifffdJ951111ienq6eO7cOfHNN98UBw8eLGZlZTldPqIoih988IE4bNgwcceOHWJubq6YnJwsRkZGiikpKU6ZD9G1WCw5AYPBIL799ttiQkKCOHToUHHevHliXl6e1GE1cn2xJIqieOTIEfH+++8XBw8eLE6YMEH8+OOPGzxuS26t9WEPf/vb38T+/fs3+bV06VKnysVCq9WKy5YtE0ePHi0OGTJEnDt3boN9l5wtn+tdWyzZEouj5VNaWio+//zz4ujRo8Xo6Gjxt7/9rZienu60+YiiKG7YsEGcOHGiGBUVJd59993inj17nDofIgtBFEVR6tEtIiIiIkfFNUtERERELWCxRERERNQCFktERERELWCxRERERNQCFktERERELWCxRERERNQCFktERERELWCxRERERNQCFktE1OG2bduGAQMGID8/X+pQiIjajMUSERERUQtYLBERERG1gMUSEbXqxIkTmD17NoYPH45hw4bhkUcewZEjR6yP//vf/8bMmTMxdOhQDBkyBPfccw927drVYp8ZGRlISkpCTEwMRowYgaVLl6KsrMz6uMlkwvvvv4+JEydi8ODBmDhxIt577z3U19d3WJ5ERE1hsURELaqqqsJjjz2GgIAArF69GqtWrUJtbS0effRRXLlyBZ988glefvllTJo0CX//+9/xzjvvwN3dHc888wwuX77cZJ/p6el45JFH4OHhgb/85S/405/+hLS0NPzud79DXV0dAGDdunX45JNPsGDBAmzYsAEPPvgg/vGPf2Dt2rWdmT4REdykDoCIHNu5c+dQVlaGhx9+GMOHDwcA9OnTB1u2bEFVVRXy8vIwd+5cLFiwwPqc8PBwzJw5E4cOHULXrl0b9fnuu++id+/e+Pvf/w65XA4AiImJwdSpU/H555/joYceQlpaGqKiovCb3/wGADBixAh4enrC29u7E7ImIvoViyUialG/fv0QGBiIJ554AnfeeSfGjx+PUaNG4dlnnwUAPPfccwCAK1euICcnBzk5OTh48CAANDllVltbiyNHjuDRRx+FKIowGAwAgO7duyMiIgIHDhzAQw89hJEjR+Ldd9/FrFmzkJiYiHHjxiEpKamTsiYi+hWLJSJqkZeXFz755BP87W9/w65du7BlyxZ4enri7rvvxgsvvICioiK8/PLLSElJgZubG/r06YMBAwYAAERRbNSfVquFyWTCunXrsG7dukaPK5VKAMBjjz0GLy8vfP7553jrrbfw5z//Gf3798ef/vQnjBo1qmOTJiK6BoslImpVnz598M4778BoNOLo0aP48ssv8dlnnyE8PBzbtm2Du7s7/vWvf2HQoEFwc3PDuXPn8NVXXzXZl5eXFwRBwCOPPIKpU6c2etzT0xMAIJPJ8NBDD+Ghhx5CaWkpfvjhB6xduxYLFy7Ezz//DIVC0aE5ExFZcIE3EbXo66+/RkJCAoqLiyGXyzFs2DC88sor8PX1xeXLl3HhwgXce++9GDJkCNzczL9/7d+/H4D5jrbreXt7Y9CgQTh//jyio6OtX/369cOaNWuQmpoKAHjggQfw+uuvAwCCgoIwc+ZMPPTQQ7hy5Qqqqqo6KXsiIo4sEVErYmNjYTKZsGDBAsyfPx9eXl7YvXs3rly5gsmTJ2P//v345JNPoFar4evri59++gmbN28GYF6f1JQ//vGPmD9/Pp566incfffdMBqN2LBhA44cOYInnngCABAfH48NGzagS5cuGDZsGIqKirBx40aMGDECgYGBnZY/EZEgNrWogIjoGkePHsX777+P48ePo7a2Fv369cPjjz+OxMREZGVl4Y033sDx48ehUCjQt29fPP7443jzzTfRv39/vP/++9i2bRuef/557Nu3D+Hh4QCAgwcPYs2aNTh+/Djc3d0RFRWFhQsXIi4uDgBgMBjwt7/9DV999RUKCwvh4+ODiRMn4qmnnkJAQICU3w4iusmwWCIiIiJqAdcsEREREbWAxRIRERFRC1gsEREREbWAxRIRERFRC1gsEREREbWAxRIRERFRC1gsEREREbWAxRIRERFRC1gsEREREbWAxRIRERFRC1gsEREREbXg/wHwfcR7L3ESNgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 593.375x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#hdisplot for sales\n",
    "sns.displot(data, kind=\"kde\")\n",
    "plt.xlabel('sales')\n",
    "plt.ylabel('Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c2f9a31",
   "metadata": {},
   "source": [
    "<h3>Observations:</h3>\n",
    "There is an showing nearly Normal distribution in graph<br>\n",
    "sales between 1000 to 5000 the variance is high <br>\n",
    "At sales value 2300 the frequency is high"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c771929f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1734.82699966, 2244.96099854, 2533.80499268, 2154.96299744,\n",
       "       1547.81899643, 2104.41199493, 2014.36299896, 1991.74699783,\n",
       "       1869.04999924, 2313.63199615, 2128.31999969, 2026.82899857,\n",
       "       1910.60399628, 2331.16499329, 2206.54999542, 2173.96799469,\n",
       "       2148.27799988, 2739.30799866, 2792.7539978 , 2556.00999451,\n",
       "       2480.97399902, 3039.522995  , 3172.11599731, 2879.00099945,\n",
       "       2772.        , 3550.        , 3508.        , 3243.85999298,\n",
       "       3056.        , 3899.        , 3629.        , 3373.        ,\n",
       "       3352.        , 4342.        , 4461.        , 4017.        ,\n",
       "       3854.        , 4936.        , 4895.        , 4333.        ,\n",
       "       4194.        , 5253.        ])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array(data[\"Sales\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "33be23fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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A7mAbBSIKTAxURAHqTFOgSvfDW81cjmmjeyEqQg1DrRmbcs/LXQ4RUYcwUBEFIGODDTUXGk/39e0WGO0SLiVMo8SvJqQBADb89wxq660yV0REdPkYqIgC0PmmzujJsbqAPd13sTGDk9EnRQ+rzYlPtp2SuxwiosvGQEUUgJoDVc8AXYz+U2LTff4A4Lsjpe6rF4mIAgUDFVGAsdgcqKgxAwB6JgVOM8/2pKVGYUxmEgDg/zaxjQIRBRYGKqIAU2RogAQgJlKDiDCV3OX41K+uTodaJaKguA67j5XLXQ4RkccYqIgCTPPpvh6JwXG672IxkRpMH90LAPDR1kJYbU6ZKyIi8gwDFVEAcThdKK1qABCcgQoArh3ZE3F6LWouWLFx91m5yyEi8ggDFVEAKasyweGUoNMqEavXyF1Op1CrFLh1UjoAYOPuc6iqs8hcERFR+xioiAJIcWXj0anuCeEQBEHmajrPiAEJ6N8jGnaHCx99WyB3OURE7WKgIgoQkiShuKIxUKUmBOfpvmaCIOCOyf0gANhzzIAT52vlLomI6GcxUBEFCGODHfVmO0RBQHKsTu5yOl2v5EiMy+oGoLGNgottFIjIjzFQEQWI4srGq/sSY8OgUobGt+7M8X0RplHgbPkF7DxcKnc5RESXFBo/lYmCgPt0X3y4zJV0HX24GjOu7AMAWLetECaLXeaKiIjaxkBFFAAcThfKm7qjpyaETqACgGtGdEdyrA5Gkx3rd5yWuxwiojYxUBEFgLIqE1wuCeFaJaLC1XKX06WUChF3TekPANi8vwjnyi/IXBERUWsMVEQBoKSy+eq+4G6XcCmZfWIxIiMRkgS8980J3uePiPwOAxVRACitMgEAuoXQ+qmfun1S033+iurw36NlcpdDRNQCAxWRn2uw2FHXYIMAICkE2iVcSqxeixuualyg/tHWAi5QJyK/wkBF5OfKmo5OxUVpoVEpZK5GXr/I6eFeoP4pF6gTkR9hoCLyc83rp1LiQvfoVDOlQsRdv2hcoL6FC9SJyI8wUBH5MUmS3OunUuJCd/3UxTJ7xyKnaYH63/99HC4XF6gTkfwYqIj8WG29DRabEwpRQEKMVu5y/Mbtk/shTKPA6VIjtuwvkrscIiIGKiJ/VlrVeLovKTYMCpHfrs1iIjX41YQ0AMC67adQbbTIXBERhTr+hCbyYzzdd2kThqciPTUKVpsT7/2HvamISF4MVER+yuWSUF7dHKi4IP2nREHA7KkDoBAFHCyoxP4TFXKXREQhjIGKyE9VGS1wOCWoVSJiIjVyl+OXUhMicN3oXgAaO6ibLA6ZKyKiUMVAReSnypqOTiXH6kLydjOemnFlLyTFhKGu3oaPtxXKXQ4RhSgGKiI/1dzQMymGp/t+jkqpwOypGQCAbw8UI/9sjcwVEVEoYqAi8kMul4SKWjMAIJnrp9qV0SsGE4Z1AwCs+eoYLDae+iOirsVAReSHKusa109pVApER6jlLicg3DoxHXF6LSrrLPhgc4Hc5RBRiGGgIvJDzeunkmLDuH7KQ2EaJeZMazz1t3lfEQ7xqj8i6kIMVER+qPyiBenkuUG9YzFxeCoA4H8/PACzlaf+iKhrMFAR+RmnS4Khpmn9FAPVZbtlYhrio7SoqDFj7aaTcpdDRCGCgYrIz1TVWeB0Na6fiuL6qcumVSsxb8YgAMDWA8U4eqpK5oqIKBTIHqhcLhdWrlyJcePGISsrC3PnzsXZs2cvuX9NTQ0efvhh5OTkICcnB08++SRMJlOLfTZu3Ihp06ZhyJAhmDFjBrZv335ZYzidTqxcuRITJ07E0KFDMXPmTGzZssW3L5zoEgw1XD/lrYG9Y3H92D4AgNVfHcMFk03miogo2MkeqFatWoW1a9fi+eefxwcffABBEDBv3jzYbG3/AFy4cCHOnz+Pd999FytXrsTOnTuxdOlS9+O7du3Co48+ijvvvBPr16/H2LFjMX/+fBQWFno8xooVK7B27VosXboUX375JaZMmYLf/e53OHLkSOdNBFGT5tN9idFhMlcS2GZPH4Ru8eGoq7fh3Y35vNcfEXUqWQOVzWbDmjVrsGDBAkyYMAEZGRlYsWIFysvL8c0337Ta/8CBA9izZw+WLVuGzMxMjBkzBs8++yw+++wzlJeXAwDefvttTJkyBbNmzUJaWhoWL16MzMxM/P3vf/d4DIfDgSeeeALjx49Hjx49cP/99yM8PBy7d+/uusmhkCRJEgxN/acSYxmovKFVK3H/TYOhEAUcOFmJbYdK5C6JiIKYrIEqPz8fDQ0NGD16tHubXq/HoEGDsHfv3lb75+bmIiEhAWlpae5tI0eOhCAI2LdvH1wuF/bv399iPAAYNWoUcnNzPRoDAB5//HFMnz4dAGA2m/Huu+/CbDZj1KhRvnvxRG2orbfBZndBqRAQG6mVu5yA1ys5EjdPaPxeX7vpJEqrGmSuiIiClVLOJy8rKwMApKSktNiemJiI0tLSVvuXl5e32letViM6OhqlpaUwGo0wmUxITk6+5HjtjXGxDRs24LHHHoMkSViwYAGGDBnSsRd6EaWy/QyrUIgt/qVG/jovggAIogBF04c3KpuOTiVEh0HlwXtFFMWL/nV59dwAoBAFCKIApVKAJAXu+q2L3yvTruyFH85U44fT1Xjr8zw8PScHSj97D3UFf/3+kRvnpTXOScfIGqjM5sZfHmp1yyuZNBoN6urq2tz/p/s272+1WmGxWC45ntVq9WiMi+Xk5GD9+vX4/vvvsXz5csTGxuLOO++8jFfYkigKiIkJ93h/vZ6nfNrij/Nic5kQFqaGUuVdqKk0Nr4HuydGQqfTePx5Wq3Kq+dtplKKCNOqER0dHO0amt8rj949AguWb8XZsgv44vtzmDMjU+bK5OOP3z/+gPPSGufk8sgaqLTaxlMaNpvN/X8AsFqtCAtr/YXUarVtLla3Wq3Q6XTQaDTu8X76ePN47Y1xsZSUFKSkpCAjIwNnzpzB6tWrvQpULpcEo9HU7n4KhQi9PgxGoxlOp/dHHYKFv86LIABmix1msw02u9OrsUoq6gEAsZFqmEzWdvZuPDKl1apgsdjhcnk/J2qVAmaLDbW1EgJ5DfdP3ysigDnTBmLlx4fxybcF6JsSiaFpcXKX2aX89ftHbpyX1jgnLen1YR4drZM1UDWfejMYDOjZs6d7u8FgQEZGRqv9k5OTsWnTphbbbDYbamtrkZSUhOjoaOh0OhgMhhb7GAwG92nA9saw2+3Ytm0bMjMzW5wa7N+/P9atW+fdCwbgcHj+5nQ6XZe1f6jwt3kRBAGSS4Kz6aOj6s12NFgcEAQgVq/1cKzGeXC5XF49dzOnS4LkkuBwSEFxVdzF75Vh6fG4engqvj1QjDfXH8Uzc3IQqw+9dWr+9v3jLzgvrXFOLo+sJ0gzMjIQERHR4uo5o9GIvLw8jBgxotX+OTk5KCsra9Gnqvlzs7OzIQgCsrOzsWfPnhaft3v3blxxxRUejaFQKPDEE0/gww8/bDHGoUOHkJ6e7uUrJrq05nYJsXqtR+un6PLdMTkdPZMiUG+2468bfoDTB0f1iIgAmQOVWq3GrFmzsHz5cmzevBn5+flYtGgRkpOTMWXKFDidTlRUVLjXRmVlZSE7OxuLFi3C4cOHsWvXLjz99NO46aabkJSUBACYM2cOvvzyS7zzzjsoLCzEyy+/jGPHjmH27NkejSGKIubOnYt3330XX375Jc6cOYO33noLn3/+ORYsWCDbXFHwczf0jOG6hc6iUipw/02DoVUrcLKoDp9uPy13SUQUJGQ95Qc0Ntl0OBz4wx/+AIvFgpycHKxevRpqtRpFRUWYPHkyli1bhpkzZ0IQBLz22mtYunQpZs+eDY1Gg6lTp2LJkiXu8caOHYsXX3wRq1atwooVK5Ceno4333zT3SbBkzHmzZsHjUaD//3f/0VpaSn69u2LV199FZMnT+7y+aHQ4W7oyUDVqZJidJg7bSBWrT+Kr3adRf8eURiaFi93WUQU4AQpGBZKBAin04Xq6vb74CiVImJiwlFT08Dz1xfx13kRBAH1FjsOFVR2eFG61ebEB1sKAAC3TkqDVu3Z3zoKUYBOp4HJZPXJGiq1SoGs9HhEaFUBvYbKk/fKv/5zApv3FyFcq8TSuSODfj2Vv37/yI3z0hrnpKXY2HCPFqVzoQaRH2jujq4PV3scpsg7t05KR+/kSDRYHFi1/ijs/MVBRF5goCLyA/50uk8Qmj+EAP748bU0/tt6H7VKgQd+OQThWiVOlRjx/qYTflD3z38Qkf/in8JEfsBfFqQrFAJEUcQFswNA4J7yE0QBNpcJFqsdKqUCVou9zf3CtErMnpaBNz49im0HS5ASF46rhqa0ua8/0GqUUMhdBBG1iYGKSGYOpwtVdY1Xssp9hEohCjDbHCg8Xwebw7smpXJSiALCwtQQJBe6J0W2+3pGZCRi7zEDPtxyEg0WO5Ji/a9TvEopYlDv2IBf30YUrBioiGRWWWeBSwLCNApEhPnmFjLesjtcXnd9l5NCFKBUuSBIjeui2ns9GT2jYag24Wx5PTblnsf0Mb2h0/LHIxF5jmuoiGT24/opHdfJyEQQBFw5JAXREWqYrU5sO1jik6smiSh0MFARyayiOVBFy78gPZSplCKuHp4KlVJERa0ZufmG9j+JiKgJAxWRjCRJQkVdY6BK8IMr/EKdPlyNcU2L0o+fq0VBUZ3MFRFRoGCgIpKRscEGm90FhSggJlIjdzkEoHtiBIalxwEAduWVo7KpRxgR0c9hoCKSUUVt49V9cVFaKESun/IXQ9Li0CMxAi6XhK0HitFwibYLRETNGKiIZFTRdPQjITq4b3sSaARBwNihPy5S37q/mJ3UiehnMVARyejHQMX1U/5GpRQxKbs7tGoFqo1W7DxSyv5PRHRJDFREMrE7XKittwEA4qMYqPxRhE6Fq4d3gygIOFdej4MFVXKXRER+ioGKSCaVTVf3hWuVbCLpxxJjdBgzOAkAcKSwCqdKjDJXRET+iIGKSCbNC9J5us//paVGIbNPLADgv0fL3KdqiYiaMVARyYTrpwJLdv/4H6/821+MejOv/COiHzFQEclAkiRUuo9Q8Qq/QNB85V9MpAYWG6/8I6KWGKiIZHDBZIfV7oQoCojRM1AFCpVSxMTsVGjVCtRcsOK7w7zyj4gaMVARyaD5dF+cXsOGngEmIkyFicNTIQoCzhvqceBkpdwlEZEf6FCgKikp8XUdRCGF66cCW0JMGK4c0njl39FT1Sgs5j3/iEJdhwLV5MmTMWfOHHz++eewWq2+roko6PEKv8DXt1sUBvdtvPLv+6NlKK82yVwREcmpQ4Fq+fLlUCqVePzxx3HVVVfhqaeewsGDB31cGlFwsjtcqL3Q+IcIF6QHtuH94tErKQIuCdh6oBjGBpvcJRGRTDoUqKZPn463334b3377Le677z7s378ft99+O6ZOnYq33noL5eXlvq6TKGhU1VkgAdBpldBpVXKXQ14QBAFXDU1BfJQWNrsLm/cVwWJzyl0WEcnAq0XpCQkJmDdvHr744gt8+umnSExMxIoVKzBp0iTcf//92Ldvn6/qJAoaXD8VXJSKxiv/wrVKXDDZse1AMZwutlMgCjVeX+WXm5uLJ598Er/5zW+Qm5uLq666Cv/zP/8Dh8OBWbNm4Z133vFFnURB48dAxdN9wSJMo8SkK7pDpRRRXmPG90fL2U6BKMR06AZiZ8+exWeffYYNGzaguLgYqamp+PWvf42bb74ZycnJAIC77roLjzzyCN544w3MmTPHp0UTBSpJkrggPUjFRGowYVg3bN5XhFMlRujD1RiaFid3WUTURToUqK699lpoNBpcc801eO655zBmzJg29+vbty/OnDnjTX1EQcXd0FMQEKvXyF0O+Vi3+HCMGpiEXXnlOHiyEpFhKvTpppe7LCLqAh0KVE8++SRuuOEGREZG/ux+DzzwAB544IEOFUYUjCrrGk/3xeo1UIjsqxuM+veMhtFkQ96ZGuw8WobwMBUSY3g0kijYdegn+tdffw2DwdDmY/n5+ZgxY4ZXRREFK57uCw3ZAxJa3Ej5gontFIiCncdHqHJzc92LLPfs2YO9e/eiurq61X5bt27F+fPnfVchURBxL0jnEYugJjbdSPnrPedQbbRiy75iTB3dExqVQu7SiKiTeByoPv74Y6xfvx6CIEAQBCxdurTVPs2B6/rrr/ddhURBwu5woaa5oWcUr/ALdiqliEnZ3fHVrrOoa7Bh24ESTB7RnfduJApSHgeqJ554AjNnzoQkSZg9ezaeeuoppKent9hHFEXo9Xr069fP54USBboqowWSBOg0SoSHsaFnKNBplZiUnYp/7z6HsmoTdueVY0xmEgSBoYoo2HgcqCIjIzFy5EgAwD/+8Q9kZmYiPDy80wojCjbsPxWaYvVajM/qhq37i1FQVAe9ToXBfdlOgSjYeByo1q9fjwkTJiAmJgYlJSUoKSn52f1vuukmb2sjCiqVTQvS47kgPeR0T4zAiIGJ2HvMgP0nKhGpU6NX8s9fJU1EgcXjQPX444/jww8/RExMDB5//PGf3VcQBAYqoos0NvTkLWdC2cBeMbjQYEP+uVp8d7gU4VolwzVREPE4UG3evBkJCQnu/xOR5+rNdlhsTogCEMeGniFrxMBEXDDbUVzRgC37izFtTC9EcD0dUVDwOFClpqa2+f9mDocD9fX1iI6O9klhRMGkuf9UrF4LhYINPUOVKAgYn9UN/959DjUXrNiyrwhTR/WEmu0UiAJeh36yOxwOvPbaa9iwYQMA4Pvvv8eVV16JMWPGYPbs2airq/NpkUSBrrLpdF88F6SHvMZ2CqkI0yhQW2/D9kMlcLl4I2WiQNehQPXqq6/ijTfewIULFwAAL774ImJiYrBkyRKcO3cOr7zyik+LJAp0FXVNHdKjuGaGgPAwFSZld4dSIaCk0oQ9x8rdffyIKDB1KFB98cUX+P3vf4+77roLp06dwsmTJ3H//ffj17/+NRYtWoQtW7b4uk6igOV0ulBjbL7Cj0eoqFFclBZjh6YAAE6cr8OxszUyV0RE3uhQoDIYDMjKygIAbN++HaIoYvz48QCA5ORk95ErIgKqjVa4JECrVnABMrXQMykSIwY0XuyTm1+Bc+X82UkUqDoUqBITE1FUVAQA+OabbzBw4EDExsYCAA4cOIDk5GTfVUgU4CrqmtZPRWnZIZtaGdg7Bv17RAEAvjtciqqm08NEFFg6FKhuuOEGLFu2DPfccw/27duHm2++GQDwwgsv4NVXX8WMGTN8WiRRIGtu6Mn+U9QWQRAwcmASUuJ0cDglbNlfjAaLXe6yiOgydShQLVy4EHPnzoUgCHj44Ydx5513AgCOHDmCuXPn4v777/dpkUSBrIJX+FE7RFHAhGHdEB2hhtnqwJZ9xbA7XHKXRUSXweM+VBcTBAH33Xcf7rvvvhbb165d65OiiIKF2epAg8UBoHERMtGlqFUKTMrujq92nUXNBSu2HyrBxOGpEEWeJiYKBB0KVABw4cIF7Nq1CyaTqc3LfXnrGaIfj05FR6ihVrJ5I/28CJ0Kk7JT8fWe8yiuaMDefANGDUqSuywi8kCHAtW2bdvw0EMPwWw2t/k47+VH1Ig3RKbLFR8dhrFDU7DtYAmOn6uFXqfGwN4xcpdFRO3oUKD685//jL59+2LJkiVISkqCKPJWGkRtab7CL4Gn++gy9EqORHb/eOw/UYncfAMidSr0TY2Suywi+hkdClSnTp3CqlWrMGLECF/XQxQ0XJLkvgSeR6jocmX2iYXRZEdBUR22HyqBPkItd0lE9DM6dGipW7duqK+v93UtREGlrt4Kh1OCSiEiir8M6TIJgoDRg35sp/CfPedRc8Eqd1lEdAkdClT33XcfXn/9dXdzTyJqraJp/VRclBYiG3pSBzS3U4iKUMNkceCtz47CYnPIXRYRtaFDp/w+//xzlJeXY8qUKYiNjYVW23J9iCAI2LRpk08KJApUPzb05Pop6ji1SoHJTe0Uiioa8OZnR7Hw5qzLbqfQnOkFAX7TsZ83hKZg0qFAlZyczNvLELXDfcsZrp8iL0XoVJg6uie+/O9ZHCqowj++zsevJqZf1hiCKMDmMsFssUNy+UeQ0WqUYDMRChYdClTLli3zdR1EQcVmd6Ku3gag8R5+RN7qFh+OO6b0xz825mPbwRLYHC5k9on1+PMVooCwMDXMZhucfhCoVEoRg3rHIkKr4pEqCgodbuwJAIWFhdi5cycMBgPuvvtunD9/HhkZGYiIiPBVfUQBqbLp6r6IMBXCNF59mxG5ZfWLR86ZROw9ZsCuo2UIUyvQPdGzn7cKUYBS5YLN7vSLQEUUbDr0k97pdOLpp5/GunXrIEkSBEHAddddh9dffx3nz5/He++9x1OCFNIq3e0SeHSKfCsrLR41F6zudgpTR/VErJ7vMyK5degqvzfeeAOff/45nn/+eezcudN9uHbx4sVwuVxYsWKFT4skCjTNt5xJiOL6KfKt5nYKyU3tFDbvK4bJYpe7LKKQ16FAtW7dOixcuBA333wzoqOj3dszMjKwcOFC7Ny501f1EQUcSZIuuuUMjxyQ74migKub2imYrQ5s2V8Mu8Mld1lEIa1DgaqyshIDBw5s87GkpCQYjUaviiIKZPVmO6x2J0RBQKxeI3c5FKTUKgUmZadCq1ag2mjFjkMlcHFxN5FsOhSoevXqhW3btrX52J49e9CrVy+viiIKZM0NPWP1Gih4n0vqRJE6NSZmp0IhCiiqaEBuvkHukohCVocWpc+ePRtPPfUU7HY7Jk6cCEEQcPbsWezevRtr1qzB448/7us6iQJGZfP6Kfafoi6QEB2Gq4amYPvBEuSfrYVep0ZGrxi5yyIKOR0KVLfccguqq6vx5ptv4v333wcA/P73v4dKpcJvf/tb3HHHHT4tkiiQVPAKP+pivZMjcaF/PA6cqMTeYwZEhKk8bqdARL7R4QY58+bNw4wZM7Bnzx4olUpERkYiKyurxSJ1olDjdLpQY2wKVGzoSV1ocJ9YXDDZ2U6BSCaXHai++OILrF27FocOHYLD0XiTTq1Wi+zsbNxxxx245pprfF4kUaCoNlrhkgCtWoGIMJXc5VAIaW6nUG+2o6zKhC37ijFtTE/otHwfEnUFjwOVy+XCI488gq+++gqJiYmYNm0a4uPjAQDl5eXYs2cPFixYgBtvvBEvvfRSpxVM5M8uvn+fv9yAlkJHczuFjbvOoa7Bhi37i3HtyJ5QKXlxBFFn8zhQvf/++/j3v/+Nxx9/HL/+9a8h/uTqJZfLhf/7v//Diy++iHHjxmH69Ok+L5bI3zX3n0rg6T6SiVqlwKQrUrFx1zl3O4Wrs1OhAAM+UWfy+M+WTz75BLfddht+85vftApTACCKIu666y7ceuut+PDDD31aJFGgaO6QzgXpJKdInRoTh6dCbGqnsC+/Qu6SiIKex4HqzJkzmDBhQrv7jRs3DqdOnfK4AJfLhZUrV2LcuHHIysrC3Llzcfbs2UvuX1NTg4cffhg5OTnIycnBk08+CZPJ1GKfjRs3Ytq0aRgyZAhmzJiB7du3X9YYLpcLf/vb33Dttddi2LBhmD59Oj766COPXxOFJpPFgQZL47rCeN5yhmSWEBOGsUMa76l67GwNjp2pkbkiouDmcaAym82Iiopqd7+YmBhUV1d7XMCqVauwdu1aPP/88/jggw8gCALmzZsHm83W5v4LFy7E+fPn8e6772LlypXYuXMnli5d6n58165dePTRR3HnnXdi/fr1GDt2LObPn4/CwkKPx/jrX/+Kt956Cw899BA2bNiA2bNnY+nSpfj00089fl0UepqPTkVHqLlmhfxC7xQ9hvdrXOu6O68cZ0p5FwuizuLxT31JkqBQKNofUBThcnl2TymbzYY1a9ZgwYIFmDBhAjIyMrBixQqUl5fjm2++abX/gQMHsGfPHixbtgyZmZkYM2YMnn32WXz22WcoLy8HALz99tuYMmUKZs2ahbS0NCxevBiZmZn4+9//7vEYa9euxdy5c3HdddehZ8+euPXWW3HjjTfi448/9nS6KAQZahqPcsazoSf5kcF9Y5GeGgUJwH92n0V1U1sPIvItWf+Mzs/PR0NDA0aPHu3eptfrMWjQIOzdu7fV/rm5uUhISEBaWpp728iRIyEIAvbt2weXy4X9+/e3GA8ARo0ahdzcXI/HeOmll3DTTTe1ev66ujpvXzIFMUNNc4d0rp8i/yEIAkZlJiE5Tge7w4Vvcotgajo1TUS+c1l9qJ555hlERPx89936+nqPxysrKwMApKSktNiemJiI0tLSVvuXl5e32letViM6OhqlpaUwGo0wmUxITk6+5HjtjSGKIsaMGdPi8aKiInz55Ze4/fbbPX5tl6L04FSQQiG2+Jca+eu8CAIg4cd7+CXF6KAQu+aKquYLRBr/9ezI8M+OJwgQBAGiAlA4A/eqsB/nJTheD+Dd10YhCrjmih748vszqLlgxdb9RbhudC9ZT00rRAGCKECpFCBJ8n1t/PXnipw4Jx3jcaDKyckB0Hjq7+eEh4djxIgRHo1pNjf+Ra9Wq1ts12g0bR4NMpvNrfZt3t9qtcJisVxyPKvV6tEYP1VRUYF7770XcXFxuP/++z16XZciigJiYsI93l+v56mjtvjjvBSW1sPhdEGlFJGSGAmxi3tQaX3UvDFMq4RSqUCYVg2l0vuAJjeNRhU0r8cXX5vpV/XBuq0FqDJa8d2RMlx3Ze8uf682UylFhGnViI7WyfL8P+WPP1fkxjm5PB4Hqn/+858+f3KttvHUiM1mc/8fAKxWK8LCWn8htVptm4vVrVYrdDodNBqNe7yfPt48XntjXOzUqVO49957Ybfb8c9//tOjRfk/x+WSYDSa2t1PoRCh14fBaDTD6QzsXwK+5K/zIghA/tkqAI23m7GY276gojOIogitVgWLxe7x2sWfI0guOBxOmC022GxOH1Qoj+Z5sVrtQfF6AO+/NqIoIipCg8kjumPj92dxptSIbfvOY9SgpE6otn1qlQJmiw21tRLa+Tu9U/nrzxU5cU5a0uvDPDpa1+F7+flC86k3g8GAnj17urcbDAZkZGS02j85ORmbNm1qsc1ms6G2thZJSUmIjo6GTqeDwWBosY/BYHCfBmxvjGb79u3D/fffj4SEBPzzn/9sdZqwoxwOz9+cTqfrsvYPFf42L4Ig4ExJ49VT8VFaOF1d+duhcR5cLpdPntclSZAkCS4nuvh1+FrzvATL6/HF16ZxThKitLhySDJ2HCpF3pkaROhUyOgZ49tiPeB0SZBcEhwOqd0zH11Sj5/9XPEHnJPLI+sJ0oyMDERERGD37t3ubUajEXl5eW2eNszJyUFZWVmLPlXNn5udnQ1BEJCdnY09e/a0+Lzdu3fjiiuu8GgMADh8+DB++9vfol+/fnj//fd9FqYoeJ0pvQCAV/hRYOhzUTuFvXkGFFV4vvaViNoma6BSq9WYNWsWli9fjs2bNyM/Px+LFi1CcnIypkyZAqfTiYqKCvfaqKysLGRnZ2PRokU4fPgwdu3ahaeffho33XST++jSnDlz8OWXX+Kdd95BYWEhXn75ZRw7dgyzZ8/2aAyHw4FHHnkEcXFxeOmll2Cz2VBRUYGKiorL6q9FocNkcaC8uqllAm85QwFicN9YpKXqIQHYfrCE7RSIvCTrKT+gscmmw+HAH/7wB1gsFuTk5GD16tVQq9UoKirC5MmTsWzZMsycOROCIOC1117D0qVLMXv2bGg0GkydOhVLlixxjzd27Fi8+OKLWLVqFVasWIH09HS8+eab7jYJ7Y1x+PBh99Gra665pkWtqamp2LJlSxfNDAWK06VGSAAidSqEaWT/liLyiCAIGJ2ZjAazA2XVJmzZX4xpo3tBp+V7mKgjBMkfTl6HCKfTherqhnb3UypFxMSEo6amgeevL+Kv8/L5zjP4dMcp9O2mx9ihXXt6WCEK0Ok0MJmsPlkjFKFTIa17NPJP18BqD9xeRc3zIkgu9EmNCvjXA3j/tbnUe8Vqd2LjrnMwNtgQq9fg2pE9u6SdglqlQFZ6PCK0KlnXUPnrzxU5cU5aio0N92hROptMEHmpoLixxUdSrH9c/k10OTQqBSZfkQqNSoFqoxXfHS6Fi39nE102BioiL7gkCYUlTYEqhgvSKTBF6tSYmJ0KURRw3lCPffkVcpdEFHAYqIi8UFplgsnigFopIlbPBekUuBJjwnDVkMb2MsfO1uD4uRqZKyIKLAxURF4obDrd1ys5EmIX3W6GqLP0SdFjWFM7hT15BhSznQKRxxioiLxQUNQYqPp008tcCZFvDOkbi7Ruje0Uth0sQc0FtlMg8gQDFZEXmhek90lhoKLgIAgCRg9ORlJsGBxOCZv3FcNkCewrJIm6AgMVUQddMNlQ1tTQk4GKgolCFHD1sFTow9UwWRzYur8IDt7TjehnMVARdVBh0/37UuJ0CA9TyVwNkW9p1D+2U6gyWvHfI2V+cc89In/FQEXUQc0L0tNTo2SuhKhzROrUuHp4NwgCcKbsAo6e4u23iC6FgYqog5oXpKd3j5a3EKJOlBSrw6iBjfdKPXCyEucNvPKPqC0MVEQd4HC6cLq08ZRfv+48QkXBrX/PaAzoGQ0A2HGoBLUXrPIWROSHGKiIOuC8oR42hwvhWiVvOUMhIScj0X3l39YDxbDanHKXRORXGKiIOqC5XUJaahREgQ09KfiJooAJw7ohIkyFCyY7th0qgcsHN+QmChYMVEQdwAXpFIq0aiUmZqdCqRBQVmVC7nGD3CUR+Q0GKqIOKGCgohAVE6nB2KEpAID8s7U4WVQrb0FEfoKBiugyVRstqDZaIQoCG3pSSOqZFIms9DgAwO4fymGoMclcEZH8GKiILlPz0akeSRHQqBUyV0Mkj6FpceiVFAGXBHx7oAT1ZrvcJRHJioGK6DLxdB9R4z3/rhySgphIDSw2J749UMzb01BIY6AiukxckE7USKUUMTE7FVq1AtVGK74/ytvTUOhioCK6DFa7E+fKGztFp6Vy/RRRRJgK47Mab09zuvQC8s/Wyl0SkSwYqIguw6niOjhdEmL1GsTptXKXQ+QXkuN0GDEgEQCQe9yAsiouUqfQw0BFdBmOn68FAPTvHg2BDT2J3DJ6RaNvNz0kCdh+iIvUKfQwUBFdhhPNgapHtKx1EPkbQRAwOjMJsfrGRerbDpTAyUXqFEIYqIg85HC6cKqk6YbIDFRErSgVIq4elgqNSoEqowW78sq5SJ1CBgMVkYfOlF2AzeFCRJgK3eJ4Q2SitkToVBiXlQIBQGGx0X2anCjYMVAReehk0y+Gft2juH6K6Gd0iw9H9oAEAMDeYwaUs5M6hQAGKiIPNf+lPYCn+4jaNah3DHonR0KSgG0HSmCycJE6BTcGKiIPuFwSThY1NvTk+imi9gmCgDGDkxEdoW7qpF4Cp4uL1Cl4MVAReaCooh5mqwMatQI9kyLkLocoIDR3UlcrRVTWWbAnzyB3SUSdhoGKyAPNR6fSU6OgEPltQ+SpSJ0a47K6AWj8PjrBReoUpPibgcgDx9l/iqjDUhPCMbxfPABgT145KmrMMldE5HsMVETtkCTJfYVf/+68ITJRRwzuG4ueSRFwScC3B4u5SJ2CDgMVUTsMNWbUNdigVAjo2403RCbqCEEQcNWQFERFqGG2OrE5twgOdlKnIMJARdSO5tN9fVL0UCkV8hZDFMBUShETh6dCpRRRXmPGJ9tOyV0Skc8wUBG14yTXTxH5jD5cjbFDUwAAOw6V4LvDpTJXROQbDFRE7eCCdCLf6pEYgeH9Gxep//3f+ThTZpS5IiLvMVAR/YxqowWVdRYIQmPLBCLyjez+CRjcJxYOpwuvf3IERpNN7pKIvMJARfQzThTVAgB6JkYiTKOUtxiiICIIAu6emoGkmDBUGa3462c/sJM6BTQGKqKfceJcLQCgXw8enSLyNZ1WiQU3D4VGpcCxszVY9y0XqVPgYqAi+hnHztYAAAb2ipG5EqLglJoQgbnTBwIA/r3nHPYcK5e5IqKOYaAiuoRqowXlNWYIAjCgBwMVUWfJyUjEdaN6AgDWfHUMRYZ6mSsiunwMVESX0Hx0qneyHjot108RdaaZE/piUO8Y2OwuvPbJETSwkzoFGAYqokvIO9MYqAb15tEpos6mEEX8vxsHI06vhaHWjLc/z4NLkuQui8hjDFREbZAkCfnnGgNVBtdPEXWJiDAVfjdzCFRKEYcLq/DZjtNyl0TkMQYqojaUVZtQc8EKpUJEP/afIuoyvZIjMXvqAADA5/89gwMnKmSuiMgzDFREbchvWj+VnqqHWsX79xF1pSsHp2DyFd0BAG9/kYfSqgaZKyJqHwMVURvy2C6BSFa3TUpH/+5RsNiceO2TIzBbHXKXRPSzGKiIfsIlSe4jVAN7x8pcDVFoUipE3H/TYERHqFFaZcKaL49B4iJ18mMMVEQ/cb68Hg0WB7RqBfqkRMpdDlHIiorQYP4vh0AhCth3ogJf7Tord0lEl8RARfQTzf2n+veIhkLktwiRnNJSo3DXL/oDAD7ZdgpHT1XJXBFR2/jbgugnmgPVIK6fIvILVw9LxfisFEgA/rrhBxhqzXKXRNQKAxXRRRxOF06crwXA/lNE/uSuKQPQJ0WPBosDr39yBFa7U+6SiFpgoCK6yOlSI6x2JyLCVOieGCF3OUTURKUUMf+Xg6HXqXDeUI+/b8znInXyKwxURBc5dubHdgmiIMhcDRFdLFavxf03DYYoCNiVV45vcovkLonIjYGK6CLH2H+KyK8N6BmD2yalAwA+3FLgbnFCJDcGKqImVrsThSV1AICBvCEykd+6ZkR3jM5MgkuS8MZnR1FttMhdEhEDFVGz4+dq4HBKiNNrkRgdJnc5RHQJgiBg9tQM9EyMwAWTHa9/egR2Bxepk7wYqIiaHD1VDQAY0jcWAtdPEfk1jUqB+TOHIFyrxOnSC3jvPye4SJ1kxUBF1OTI6cZAldknTuZKiMgTCdFhuO/GTAgCsONwKbYdLJG7JAphDFREACpqzSivNkEhClyQThRABveJw8zxfQEA//rmBAqK62SuiEIVAxURgKNNR6fSuumh0yplroaILse00b1wxYAEOF0SVn16BLX1VrlLohDEQEUEuO8PNrgvT/cRBRpBEDB32kB0iw9Hbb2taZG6S+6yKMQwUFHIczhd7v5Tg/vGylwNEXVEmEaJBTOHQKdRorDYiPf+c5yL1KlLMVBRyCssroPF5kSkToWeSZFyl0NEHZQUq8P/u2iR+pb9xXKXRCGEgYpC3uHCptN9fWJ5uxmiADe4bxxuubqxk/r/bTrJTurUZRioKOQdagpUWenxMldCRL5w7cge7k7qq9YfRWWtWe6SKATIHqhcLhdWrlyJcePGISsrC3PnzsXZs2cvuX9NTQ0efvhh5OTkICcnB08++SRMJlOLfTZu3Ihp06ZhyJAhmDFjBrZv337ZYzTbu3cvBg4c6P0LJb9UUWtGSWUDREHA4D5cP0UUDARBwG+mZqBXciTqzXa8+skRWG3spE6dS/ZAtWrVKqxduxbPP/88PvjgAwiCgHnz5sFms7W5/8KFC3H+/Hm8++67WLlyJXbu3ImlS5e6H9+1axceffRR3HnnnVi/fj3Gjh2L+fPno7Cw0OMxmu3evRsPPPAAXC5eLRKsmk/39eseBZ1WJXM1ROQrapUCC2YOgV6nwnlDPVZ/dYyL1KlTyRqobDYb1qxZgwULFmDChAnIyMjAihUrUF5ejm+++abV/gcOHMCePXuwbNkyZGZmYsyYMXj22Wfx2Wefoby8HADw9ttvY8qUKZg1axbS0tKwePFiZGZm4u9//7vHYzgcDjz//POYO3cuevTo0XUTQl3uUEElAJ7uIwpGsXotHvjlEChEAbn5Bny169JnP4i8JWugys/PR0NDA0aPHu3eptfrMWjQIOzdu7fV/rm5uUhISEBaWpp728iRIyEIAvbt2weXy4X9+/e3GA8ARo0ahdzcXI/GAACTyYSjR49izZo1mDVrlk9fM/kPi82B/HONC1aHprH/FFEw6t8jGnf9oj8A4JNtp3Cw6Y8oIl+TtSV0WVkZACAlJaXF9sTERJSWlrbav7y8vNW+arUa0dHRKC0thdFohMlkQnJy8iXHa28MoDHUrV27FgDwySefePEKW1Mq28+wCoXY4l9q5Ot5OV5YC4dTQmJ0GHokRXT4hsiCAAiiAEXTR1cSRfGif70/NS0KAgRBgKgAFM7AveLxx3kJjtcDeP+18fV7xVsKUYAgClAqBUhS535trhnRA0UVDdiyrwhvbfgBz8wdiW7x4Y118OdtK5yTjpE1UJnNjVdeqNXqFts1Gg3q6lrfj8lsNrfat3l/q9UKi8VyyfGsVqtHY3QmURQQExPu8f56fVgnVhO4fDUveWdrAQAjBycjNjbCq7FsLhPCwtRQquT5RaX10fqvMK0SSqUCYVo1lEr5f+l6S6NRBc3r8dXXxlfvFW+plCLCtGpER+u65Pl+d+twlNeY8cOpKry67jCWPzgBEWE/zgV/3rbGObk8sgYqrVYLoHEtVfP/AcBqtSIsrPUXUqvVtrlY3Wq1QqfTQaPRuMf76ePN47U3RmdyuSQYjW1fTXgxhUKEXh8Go9EMpzOwfwn4ki/nxeWSsOto4xHJzF4xqKlp6PBYggCYLXaYzTbY7F17JZEoitBqVbBY7D65eEKQXHA4nDBbbLAF8FVRzfNitdqD4vUA3n9tfP1e8ZZapYDZYkNtrYSuWit+/42ZeGr1bhRXNGDZO7vx+9uGQaVS8OftT/B3UEt6fZhHR+tkDVTNp94MBgN69uzp3m4wGJCRkdFq/+TkZGzatKnFNpvNhtraWiQlJSE6Oho6nQ4Gg6HFPgaDwX0asL0xOpvjMu4v5XS6Lmv/UOGLeTlxvhYXTHboNEqkddN7NZ4gCJBcEpxNH12rsW6Xy+WT53ZJEiRJgssJGV6LLzXPS7C8Hl98bXz7XvGW0yUBkgSns+sCVbhWhQU3D8Wyf+7D4cIqfLi1AHdc0w9A07w4O15IMF5ByN9Bl0fWE6QZGRmIiIjA7t273duMRiPy8vIwYsSIVvvn5OSgrKysRZ+q5s/Nzs6GIAjIzs7Gnj17Wnze7t27ccUVV3g0BoWGAycrAABZ6XFQcp0AUZdTKASIoogLZgfqLfYu+4iPDsMdUxoXqX/1/Vls3lcMQ7UJdSbvxg3s45/kC7IeoVKr1Zg1axaWL1+O2NhYpKam4k9/+hOSk5MxZcoUOJ1OVFdXIzIyElqtFllZWcjOzsaiRYvwzDPPwGQy4emnn8ZNN93kPro0Z84c3HvvvRg0aBDGjx+PdevW4dixY3jhhRcAwKMxKLhJkoT9JxoD1fB+CTJXQxSaFKIAs82BwvN1sDm6No6olCKGpsfhcEEV3vs6HzanC5FaZYeP3KmUIgb1jkWEVhWUR6rIM7IGKqCxyabD4cAf/vAHWCwW5OTkYPXq1VCr1SgqKsLkyZOxbNkyzJw5E4Ig4LXXXsPSpUsxe/ZsaDQaTJ06FUuWLHGPN3bsWLz44otYtWoVVqxYgfT0dLz55pvuNgmejEHBrbiiARW1FigVIgb3ZXd0IjnZHa4uX3sINLZKqaq1oLiyARt2nML1Y3pBrVJ0eR0UPASJcbrLOJ0uVFe3v/hZqRQRExOOmpoGnr++iK/mZcPO01i/4zSGpcdj4a+Gel2XIAiot9hxqKCyy38xKEQBOp0GJpPVJ+tiInQqpHWPRv7pGljtDh9UKI/meREkF/qkRgX86wG8/9r4+r3iLX94r9nsTnz1/VkYTXYkxYZhyogeEDvQ+kStUiArPT5ojlDxd1BLsbHhHi1K5+IRCjk/nu5jd3SiUKZWKTB5RHeolSLKq83Ym29o/5OILoGBikKKocaEc+X1EAQgi4GKKORFR2gwZWQvAMDxc7U4cb5W3oIoYDFQUUhp/gt0YK8Y6HWtG7wSUejp3U2P7P6Nf2DtySuHoab9foFEP8VARSGlOVDlZCTKXAkR+ZOhaXHolRwJlwR8e6AEDWa73CVRgGGgopBR3nS6TxQEZPdnuwQi+pEgCLhycDJiIjWw2Jz49kAxHOwSTpeBgYpCRq77dF80Inm6j4h+QqUUMXF4KjQqBaqMVvz3aFlQXLVHXYOBikKG+3TfQDZwJaK2RehUmDCsGwQBOFN6AUdPVctdEgUIBioKCeXVP57uY7sEIvo5yXE6jGz6w+vAyUqcN9TLXBEFAgYqCgnf/1AGABjUJ4an+4ioXQN6RmNAz2gAwI5DJai5YJW3IPJ7DFQU9CRJwq4fygEAYzKTZa6GiAJFTkYikmN1cDglbN1fDIstsLvtU+dioKKgd6rECEOtGRqVAtm8GTIReUgUBYwf1g2ROhXqzXZsO1DiF7ftIf/EQEVBr/noVHb/eGjUvPkpEXlOq1ZgYnYqVAoR5TVm7D1Wziv/qE0MVBTUHE4Xdh9rDFSjebqPiDogOkKDcVkpAIAT5+tw/FytvAWRX2KgoqD2w+lq1Jvt0OtUGNQ7Ru5yiChAdU+McN+eZm++AaVVDTJXRP6GgYqC2neHSwEAowYlQyHy7U5EHZfZJxZ9u+khScC2gyUwNtjkLon8CH/DUNAymmw4WFAJABg3NEXmaogo0AmCgDGZSYiP0sJmd2Hr/mLY7E65yyI/wUBFQev7o2VwuiT0SYlE98QIucshoiCgUIi4engqwjRK1DXYsONwKVxcpE5goKIgJUkSdjSd7hs3tJvM1RBRMNFplZiYnQqFKKC4ogF7jxnkLon8AAMVBaVTJUaUVDZArRTdt5AgIvKV+CgtrhzceOXwkcIq7M4rl7kikhsDFQWlHYdLAABXDEiETquUuRoiCkZ9uukxpG8sAGDtphMoLK6TuSKSEwMVBR2TxY5dTX8tjs/iYnQi6jzD+sWjV1IkHE4JK9cdRrXRIndJJBMGKgo63x0pg83uQmpCOPr3iJa7HCIKYoIgYEJ2N6TE6WBssOHVdUdgtfHKv1DEQEVBxSVJ2Lq/CAAwKbs7BEGQuSIiCnZqpQL33piJiDAVzpZfwFuf/wAX7/kXchioKKgcO1OD8hozwjQKjMnkYnQi6hrxUWFY+KuhUCpEHDhZiQ+3FshdEnUxBioKKluajk5dOTgFWjUXoxNR1+nXPRr3TB8IAPjP3vPYeqBY5oqoKzFQUdAw1JjcndEnDk+VuRoiCkWjBiXhl+P6AAD+9Z8TOHqqSuaKqKswUFHQ+GZvESQJGNI3Dt3iw+Uuh4hC1PVX9saVg5PhkiSsWn8URRX1cpdEXYCBioJCvdmOHUcae09NHdlD5mqIKJQJgoDZUzPQv0c0LDYn/vejQ6irt8pdFnUyBioKClsPFMNmd6FnYgQyesXIXQ4RhTiVUsTvZg5BUkwYqoxWrFx3GFbeSDmoMVBRwLM7nNi8r3Ex+rWjerJVAhH5hYgwFR66JQvhWiVOl17AWxvYTiGYMVBRwNtxuBTGBhtiIjXIyUiUuxwiIrekWB0W3PxjO4X3/nMcksRQFYwYqCig2R0ufPn9WQDAtNG9oFTwLU1E/qV/j2jcO2MQBADfHizBhp1n5C6JOgF/+1BA23m0FDUXrIiKUPO+fUTkt0ZkJGLWL/oDAD777jS+ZY+qoMNARQHL4XThy/82HZ0a1QsqpULmioiILm1idnfMuLI3AOCf/zmO/Scq5C2IfIqBigLWf4+WocpoQVS4GhOGdZO7HCKidt00rg/GZ3WDJAFvfvYDTpyvlbsk8hEGKgpIVrsT63ecAgBcN7oX1CoenSIi/ycIAu6+tj+GpcfD4XRh5ceH2fgzSDBQUUDalHsetfU2xEdpeZsZIgooClHE/7sxE+ndo2CyOrDiw0OorDPLXRZ5iYGKAs4Fkw1f7WpcO/XL8X2hUvJtTESBRa1SYOHNQ9EtPhw1F6xY/n8HUXOB3dQDGX8TUcDZ8N1pmK1O9EiMwKhBSXKXQ0TUIRFhKvz+1izER2lhqDVj+doDMDbY5C6LOoiBigLKuTIjNuU2dkW/ZWIaRHZFJ6IAFqvX4rE7hiMmUoPSKhOWrz2IerNd7rKoAxioKGBIkoS/fnoETpeE4f3iMbhPnNwlERF5LT46DI/dMRxR4WoUVdTjlQ8OwmRxyF0WXSYGKgoYe48ZcLigEiqliNsn95O7HCIin0mK1eGRO4YjIkyFs2UXsOIjhqpAw0BFAcFsdeD9b04AAK6/sjcSosNkroiIyLdS48PxyO3DEK5VorDYiOVrD/D0XwBhoKKA8NHWAlRfsCI5TofpY3rJXQ4RUafomRSJR25vPFJ1puwC/vR/B2A0caF6IGCgIr937Ew1vj1YAgBYeOtwNvEkoqDWKzkSi+8cDn24GucN9fjjv/ajtp4tFfwdAxX5NYvNgXc25gMAJl3RHUPS42WuiIio86UmRODxu7LdV/+99K/9qKqzyF0W/QwGKvJr739zEpV1FsTpNbhtUrrc5RARdZnkWB0W35Xd2KeqxowX/pmL8wbepsZfMVCR39qVV4bvjpRCEIDfXj8IYRql3CUREXWpxOgwPH5XNrrFh6O23oaX/rUPeWeq5S6L2sBARX7JUGPCP/59HAAw48reGNAzRuaKiIjkEavXYsmsbPTvEQ2z1YkVHx7C90fL5C6LfoKBivyOxebAa58chcXmRP/uUZhxVW+5SyIiklW4VoWHbxuGkQMT4XRJePuLPHzx3zOQJEnu0qgJAxX5FUmSsPrLYyiqqEdUuBr33pAJhci3KRGRSini3hsyce3IHgCAT7afwl83/ACrzSlzZQQwUJGf2bDzDPYdr4BSIWD+zCGI1WvlLomIyG+IgoDbJvXDrF/0h0IUsOeYAS/8MxeGWrPcpYU8BiryG9sOFuOz704DAGb9YgDSU6NkroiIyD9Nyu6OR+9o7FVVVNGA597di6OnquQuK6QxUJFf2He8Av/4unER+vQxvTA+q5vMFRER+bf+PaLx9G9y0LebHg0WB1Z8eAjrd5yC0+WSu7SQxEBFsjtYUIm/bjgKSQLGZ6Vg5vi+cpdERBQQYiI1WHxnNsZndYOExmUTy97bj/Iak9ylhRwGKpLV/hMVeP2TI3A4JVwxIAF3XzsAgiDIXRYRUcBQKUX85roM3HtDY7++UyVGPLNmL7YfKuFVgF2IgYpks/NIKd5YfxROl4ScjETcxyv6iIg6bPSgZDw7dyQG9IiG1e7Euxvz8donR1BzgfcB7Ar87UVdTpIkrN9xCqu/PAanS8KYzCTce8MgKBV8OxIReSMuSotH7xiOW65Og0IUcOBkJf7n7V34es85rq3qZLyXB3Ups7XxZse5+QYAjQvQfzm+L0Se5iMi8glRFHDd6F4Y3DcO//g6H4XFRnywpQA7j5Th19cOQHp3XkHdGRioqMucN9Rj1fqjKK82QSEKuPvaAbyaj4iok/RIjMCSWVfgu8Ol+GhrAYoq6vHie/swOjMJN47tg6QYndwlBhUGKup0TpcL/959Dp99dxoOp4RYvQb33zgYaewzRUTUqURBwPisbhjeLx4ff1uIHYdLseuHcuzJM2Ds0BTccFVvNlD2EQYq6lSnS4147z/Hcbr0AgAgKy0Oc6cPRKROLXNlREShI1KnxpxpAzEpuzs+3XEKhwursP1QCf57tAxXD+uGKTk9kBAdJneZAY2BijpFzQUr1u84he8Ol0ICEKZR4s5r+uHKwclsi0BEJJNeyZF46JYsnCyqxbptp3DifC027SvC5v1FGN4vAVNGdMegPrFylxmQGKjIp2rrrfj37nPYsr8YDmfjFSVjMpPxq6vTEBOpkbk6IiICgH7do7H4zuHIO1ODf+8+ix/O1GD/iQrsP1GBnkkRuH5sX2T2ikaYmjHBU5wp8omzZRewKfc8duWVw+lqbCTXr3sUfnV1Gvp1j5a3OCIiakUQBGT2iUVmn1gUV9Rj074ifH+0DOfK67Fq3WEoRAFD+sZhdGYShqXHQ61SyF2yX2Ogog6rrDPjwIlK7DxSinOGevf29O5RuOHK3sjsE8vTe0REASA1IQKzp2bg5glp+P6HMuzOM+BUSR0OFlTiYEElNCoFBvWOwZC+cRjSNw5xUVzI/lOyByqXy4XXXnsNH330EYxGI6644go8/fTT6NWrV5v719TU4Pnnn8f27dsBAFOnTsWSJUug0/14+efGjRvx6quv4vz58+jduzceffRRjB8/3qdjhCKXJOF8eT0OnKzAgZOVOH9RiFIqBGT3T8CUnB5I68ar94iIAlFEmArXje6FO68bhCMnyrGz6arAKqMFB05W4sDJSgBAanw4MnrFID01CumpUQxY8INAtWrVKqxduxbLli1DUlIS/vSnP2HevHn44osvoFa3vhJs4cKFsFqtePfdd2E0GvHEE09g6dKl+OMf/wgA2LVrFx599FE8/vjjGDNmDD7++GPMnz8f69evR1pams/GCAVmqwOnS40oKK5DYbERp0rq0GBxuB8XBKBfahRGZCRidGYyIsJUMlZLRES+1D0hAjdPSMMvx/fF+fJ6HD5VhSOFVSgsqUNxZQOKKxuweV8RgMabNKd106N7YgS6J0Sge0I44qPDQqppsyDJeOdEm82G0aNH49FHH8Udd9wBADAajRg3bhxefPFFTJ8+vcX+Bw4cwO23346vvvrKHWy+++47/Pa3v8W2bduQlJSEe+65B3q9HitWrHB/3u23347+/fvj2Wef9ckYHeV0ulBd3dDufkqliJiYcNTUNMDh6NxbBVhtTlRfsKDaaEVFrRklVQ0orTKhtKoB1cbW939Sq0QM7hOH4f3iMTQtrkvbH3TlvFwOQRBQb7HjUEElbHZnlz63QhSg02lgMlnda9e8EaFTIa17NPJP18Bqd7T/CX6qeV4EyYU+qVEB/3oA7782vn6veMtf3mu+mBe1SoGs9HhEaFVBcTPi9n7W1pvtyDtTjYKiOhQU1+FceT1cbbxujUqBpJgwJEQ3f2gRFxWG6Ag1osLViNCpAuL+rbGx4VB4cGs0WY9Q5efno6GhAaNHj3Zv0+v1GDRoEPbu3dsqUOXm5iIhIaHFUaKRI0dCEATs27cPU6dOxf79+/H444+3+LxRo0bhm2++8dkY/kSSJBgbbLA6XLDZnbDZXbDanY3/d7hgtjpQb7ajwWxHg8WOerMDDWY76i121F6wtjji1JY4vRZpqXqkp0YhLTUKPRIjeM89IqIQFhGmwsiBSRg5MAlA4x/mZ8qMOFVqRHFFA4oq6lFSaYLV7sQ5Q32LNbYXEwBE6lTQhzcGrEidGlqNEmEaBcLUSoRd9H+1WgGVQoRKedGHQoSy6V+VUoRCFGRdtytroCorKwMApKSktNiemJiI0tLSVvuXl5e32letViM6OhqlpaUwGo0wmUxITk6+5Hi+GKOjRFFAbGx4u/s1vx+iosLQ3h87xgYbIhQKRHhRlyA0dtNViCIUCgFKReP/lQp535w/dTnz0tWiJAmJ8RFdXpcgAAIESJB88tyi0PjXafckvd/N8eVonhcIjev7Av31AN5/bXz9XvGWv7zXfDEvggColGLQnN7qyM/alGQ9xgxruc3pkuB0uhr/bfpwNX90whddoRQRHeH79jyi6NnXVdZAZTabAaDVWimNRoO6uro2929rXZVGo4HVaoXFYrnkeFar1WdjdJQgCFAoPP+GEz04FBoTgrcM8GReupoCgEoZPJcUB9NrAYLr9QTTawGC7/UEE29/1ioUAEKo1YKsv5m02sYwYLPZWmy3Wq0IC2vdAl+r1bbat3l/nU4HjUbT7ni+GIOIiIjoYrIGquZTbwaDocV2g8HQ6pQbACQnJ7fa12azoba2FklJSYiOjoZOp/vZ8XwxBhEREdHFZA1UGRkZiIiIwO7du93bjEYj8vLyMGLEiFb75+TkoKysDGfPnnVva/7c7OxsCIKA7Oxs7Nmzp8Xn7d69G1dccYXPxiAiIiK6mKyBSq1WY9asWVi+fDk2b96M/Px8LFq0CMnJyZgyZQqcTicqKirc65qysrKQnZ2NRYsW4fDhw9i1axeefvpp3HTTTUhKarzaYM6cOfjyyy/xzjvvoLCwEC+//DKOHTuG2bNn+2wMIiIioovJ2ocKAJxOJ/785z/jk08+gcViQU5ODp566il0794dRUVFmDx5MpYtW4aZM2cCAKqqqrB06VLs2LEDGo3G3eW8ee0TAKxfvx6rVq1CWVkZ0tPT8eijj2LMmDHux30xBhEREVEz2QMVERERUaDzv+vPiYiIiAIMAxURERGRlxioiIiIiLzEQEVERETkJQYqIiIiIi8xUBERERF5iYGKiIiIyEsMVH7E5XJh5cqVGDduHLKysjB37twWt8gJNqtWrcLdd9/dYtuxY8cwa9YsDBs2DFdffTVWr17d4nFP5qi9MfxRbW0tnnrqKYwfPx7Z2dm44447kJub6348FOelqqoKjz76KEaPHo3hw4fj3nvvRUFBgfvxUJyTnzp9+jSGDx+OTz75xL0tFOeluLgYAwYMaPXx0UcfAQjNOWm2fv16TJs2DUOGDMH06dOxceNG92OhPC+dQiK/8eqrr0pjxoyRvv32W+nYsWPS3LlzpSlTpkhWq1Xu0nzunXfekQYMGCDNmjXLva26uloaNWqU9MQTT0gFBQXSxx9/LA0ZMkT6+OOP3fu0N0eejOGP5syZI91www3S3r17pcLCQum5556Thg4dKhUUFITsvNxyyy3SbbfdJh0+fFgqKCiQFixYIF111VWSyWQK2Tm5mM1mk2bOnCn1799fWrdunSRJofs9tHnzZmnIkCFSeXm5ZDAY3B9mszlk50SSJGn9+vXSwIEDpXfffVc6c+aM9Nprr0kZGRnS/v37Q3peOgsDlZ+wWq3S8OHDpffff9+9ra6uTho6dKj0xRdfyFiZb5WVlUn33HOPNGzYMGnq1KktAtWbb74pjRs3TrLb7e5tr7zyinTttddKkuTZHLU3hj86c+aM1L9/f2nfvn3ubS6XS5oyZYr0l7/8JSTnpbq6Wlq0aJF04sQJ97Zjx45J/fv3lw4dOhSSc/JTr7zyinT33Xe3CFShOi9vvPGGdMMNN7T5WKjOicvlkiZOnCi99NJLLbbPnTtXevPNN0N2XjoTT/n5ifz8fDQ0NGD06NHubXq9HoMGDcLevXtlrMy3fvjhB0RFRWHDhg3Iyspq8Vhubi5ycnKgVCrd20aPHo3Tp0+jqqrKozlqbwx/FBMTg7feeguDBw92bxMEAZIkoa6uLiTnJSYmBn/+85/Rr18/AEBlZSVWr16N5ORkpKenh+ScXGzv3r344IMP8Mc//rHF9lCdl+PHjyM9Pb3Nx0J1Tk6dOoXi4mLMmDGjxfbVq1fjvvvuC9l56UwMVH6irKwMAJCSktJie2JiIkpLS+UoqVNMmjQJr7zyCnr06NHqsbKyMiQnJ7fYlpiYCAAoKSnxaI7aG8Mf6fV6TJgwAWq12r1t48aNOHfuHMaOHRuy89LsySefxFVXXYV///vfeOGFF6DT6UJ6ToxGIx577DH84Q9/aPX6QnVeTpw4gaqqKtx555248sorcccdd2DHjh0AQndOzpw5AwAwmUy45557MGbMGNxyyy3YsmULgNCdl87EQOUnzGYzALT4pQoAGo0GVqtVjpK6nMViafP1A4DVavVojtobIxDs27cP//M//4PJkydj0qRJIT8vs2fPxrp163DDDTdg/vz5+OGHH0J6Tp555hkMGzas1ZEHIDS/h2w2G86cOYP6+no89NBDeOuttzBkyBDMmzcP33//fUjOCQDU19cDABYvXozrr78ea9aswVVXXYUHHnggpOelMynb34W6glarBdD4w6H5/0DjmzIsLEyusrqUVquFzWZrsa35m1Kn03k0R+2N4e82bdqERx55BFlZWfjzn/8MgPPSfCrnueeew8GDB/Hee++F7JysX78eubm5+Pzzz9t8PBTnRa1WY+/evVAqle5f7oMHD0ZhYSFWr14dknMCACqVCgBwzz334Je//CUAYODAgcjLy8M777wTsvPSmXiEyk80H1Y1GAwtthsMhlaHVINVcnJym68fAJKSkjyao/bG8GfvvfceFixYgPHjx+Ptt992/xALxXmpqqrCF198AafT6d4miiLS0tLcryvU5gQA1q1bh6qqKlx99dUYPnw4hg8fDgB4+umnMX369JCdF51O1+pISf/+/VFeXh6yc9Jce//+/VtsT09PR1FRUcjOS2dioPITGRkZiIiIwO7du93bjEYj8vLyMGLECBkr6zo5OTnYt29fi1+i33//Pfr06YO4uDiP5qi9MfzV+++/j+eeew533XUX/vKXv7T45RCK82IwGPDwww9jz5497m12ux15eXlIS0sLyTkBgOXLl+Orr77C+vXr3R8AsHDhQrz11lshOS/5+fkYPnx4i75tAHD06FGkp6eH5JwAwKBBgxAeHo5Dhw612H7ixAn07NkzZOelU8l9mSH96M9//rM0cuRIadOmTe6eH7/4xS+Csg+VJEnS4sWLW7RNqKyslHJycqTFixdLJ0+elNatWycNGTJE+uSTT9z7tDdHnozhb06dOiVlZmZK8+fPb9FDx2AwSEajMSTnxeVySXPnzpWuvfZaae/evdLx48elRYsWSTk5OVJxcXFIzsmlXNw2IRTnxel0Srfccot0/fXXS3v37pUKCgqkF198URo8eLCUn58fknPS7PXXX5eGDx8uff7559LZs2elVatWSRkZGdKuXbtCel46CwOVH3E4HNLLL78sjR49Who2bJg0b9486fz583KX1Wl+GqgkSZIOHTok3XrrrdLgwYOliRMnSv/85z9bPO7JHLU3hr954403pP79+7f5sXjxYkmSQnNejEaj9PTTT0tXXXWVNHToUGnu3Lkt+lKF4py05eJAJUmhOS9VVVXSkiVLpKuuukoaMmSIdNttt0l79+51Px6Kc9JszZo10qRJk6TMzEzphhtukL755hv3Y6E8L51BkCRJkvsoGREREVEg4xoqIiIiIi8xUBERERF5iYGKiIiIyEsMVEREREReYqAiIiIi8hIDFREREZGXGKiIiIiIvMRARUQh7cSJE1i0aBGuuuoqDB48GGPHjsVDDz2EvLy8yxrn1VdfxYABAzqpSiLydwxURBSyTp48idtuuw3V1dV44oknsGbNGjz22GMoKSnBbbfdhoMHD8pdIhEFCKXcBRARyeWdd95BdHQ0/va3v0GlUrm3X3PNNbjuuuuwatUqvPXWWzJWSESBgoGKiEJWZWUlAOCnd+DS6XRYsmQJzGYzAMDpdGL16tXYsGEDzp07B1EUkZGRgQcffBBjxoy55PibNm3CqlWrcPLkSej1elx33XX4/e9/D51OBwCwWq146aWXsHnzZlRXV6N79+649dZbMXfu3E56xUTUWRioiChkXX311di2bRtuv/123HzzzRg9ejT69u0LQRAwdepU937Lly/H+++/j0ceeQQDBgxAWVkZXn/9dTz44IP49ttv3QHpYp9//jkeeeQRzJgxAw899BCKi4uxYsUKFBQU4J133oEgCHjhhRfw3XffYfHixYiPj8f27dvxxz/+EdHR0Zg5c2ZXTgUReYmBiohC1p133omKigqsXr0azz77LAAgJiYGY8eOxd13342srCwAgMFgwKJFi3D33Xe7P1er1WLBggU4fvw4hg8f3mJcSZKwfPlyjBs3DsuXL3dv7927N37zm99g27ZtuPrqq7Fnzx5ceeWVmD59OgBg1KhR0Ol0iImJ6eyXTkQ+xkBFRCHtwQcfxG9+8xvs2LED33//PXbv3o3PP/8cX3zxBZYsWYLZs2fjlVdeAQBUV1fj7NmzOH36NLZs2QIAsNvtrcY8deoUysrKcN9998HhcLi35+TkICIiAjt37sTVV1+NUaNGYe3atSgvL8fEiRMxYcIEzJ8/v2teOBH5FAMVEYW8qKgoXH/99bj++usBAHl5eXjsscewfPly3HDDDSgqKsLSpUtx5MgRaLVapKenIzU1FUDr9VcAUFtbCwBYunQpli5d2upxg8EAAHjiiSeQnJyMDRs2uPcbPnw4nnrqKQwaNKgzXioRdRIGKiIKSeXl5bj55pvx4IMP4pZbbmnx2KBBg/DQQw9h/vz5KCgowO9+9zsMGDAAX3zxBdLS0iCKIrZt24avv/66zbH1ej0A4LHHHsPIkSNbPR4VFQUAUKvVuP/++3H//fejpKQEW7duxapVq/Dwww9j48aNPn7FRNSZ2IeKiEJSfHw8lEol3n//fVit1laPnzp1ChqNBmq1GrW1tfj1r3+Nfv36QRQbf2xu374dAOByuVp9bt++fREXF4eioiIMGTLE/ZGcnIxXXnkFeXl5sFgsuPbaa7FmzRoAQLdu3XDXXXdh+vTpKCsr68RXTkSdgUeoiCgkKRQKPPPMM5g/fz5uvvlm3HXXXUhLS4PZbMbOnTvxr3/9Cw8++CD69u2LiIgIvPnmm1AqlVAqlfj666/x8ccfA4C7tcJPx160aBGeeuopKBQKTJw4EUajEatWrUJ5eTkyMzOh1WqRmZmJ1157DSqVCgMGDMDp06fx6aef4tprr+3q6SAiLwlSWwsAiIhCxA8//IDVq1dj3759qK6uhlqtxqBBg3D33XfjF7/4BQBg9+7dePnll1FQUIDw8HAMHDgQDzzwAObNm4fbb78djz32GF599VW89tprOH78uHvsr776Cn/7299w8uRJ6HQ6ZGdn46GHHnLfoqa+vh5/+ctfsHnzZlRUVCAuLg7Tpk3Dgw8+CK1WK8t8EFHHMFAREREReYlrqIiIiIi8xEBFRERE5CUGKiIiIiIvMVAREREReYmBioiIiMhLDFREREREXmKgIiIiIvISAxURERGRlxioiIiIiLzEQEVERETkJQYqIiIiIi8xUBERERF56f8DxSzMPkFDsKgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_theme()\n",
    "rk= sns.distplot(data['Sales'],kde=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9f3a3c35",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='y(t)', ylabel='y(t + 1)'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.plotting import lag_plot\n",
    "lag_plot(data['Sales'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e94e705",
   "metadata": {},
   "source": [
    "<h3>Observations:</h3>\n",
    "The lag_plot graph shows the time series is random <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "49ce95d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "42"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a5d82bcf",
   "metadata": {},
   "outputs": [],
   "source": [
    "data['quarter'] = 0\n",
    "for i in range(42):\n",
    "    p=data['Quarter'][i]\n",
    "    data['quarter'][i]=p[0:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0350f000",
   "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>Quarter</th>\n",
       "      <th>Sales</th>\n",
       "      <th>quarter</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Q1_86</td>\n",
       "      <td>1734.827000</td>\n",
       "      <td>Q1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Q2_86</td>\n",
       "      <td>2244.960999</td>\n",
       "      <td>Q2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q3_86</td>\n",
       "      <td>2533.804993</td>\n",
       "      <td>Q3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Q4_86</td>\n",
       "      <td>2154.962997</td>\n",
       "      <td>Q4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Q1_87</td>\n",
       "      <td>1547.818996</td>\n",
       "      <td>Q1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Quarter        Sales quarter\n",
       "0   Q1_86  1734.827000      Q1\n",
       "1   Q2_86  2244.960999      Q2\n",
       "2   Q3_86  2533.804993      Q3\n",
       "3   Q4_86  2154.962997      Q4\n",
       "4   Q1_87  1547.818996      Q1"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "074d8df6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Q1    11\n",
       "Q2    11\n",
       "Q3    10\n",
       "Q4    10\n",
       "Name: quarter, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['quarter'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a60bbfce",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_dummies=pd.DataFrame(pd.get_dummies(data['quarter']),columns=['Q1','Q2','Q3','Q4'])\n",
    "cc=pd.concat([data,df_dummies],axis= 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "53983638",
   "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>Quarter</th>\n",
       "      <th>Sales</th>\n",
       "      <th>quarter</th>\n",
       "      <th>Q1</th>\n",
       "      <th>Q2</th>\n",
       "      <th>Q3</th>\n",
       "      <th>Q4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Q1_86</td>\n",
       "      <td>1734.827000</td>\n",
       "      <td>Q1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Q2_86</td>\n",
       "      <td>2244.960999</td>\n",
       "      <td>Q2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q3_86</td>\n",
       "      <td>2533.804993</td>\n",
       "      <td>Q3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Q4_86</td>\n",
       "      <td>2154.962997</td>\n",
       "      <td>Q4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Q1_87</td>\n",
       "      <td>1547.818996</td>\n",
       "      <td>Q1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Quarter        Sales quarter  Q1  Q2  Q3  Q4\n",
       "0   Q1_86  1734.827000      Q1   1   0   0   0\n",
       "1   Q2_86  2244.960999      Q2   0   1   0   0\n",
       "2   Q3_86  2533.804993      Q3   0   0   1   0\n",
       "3   Q4_86  2154.962997      Q4   0   0   0   1\n",
       "4   Q1_87  1547.818996      Q1   1   0   0   0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cc.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e6f6de57",
   "metadata": {},
   "outputs": [],
   "source": [
    "#adding columns t,t_squared and sales_log\n",
    "cc['t'] = np.arange(1,43)\n",
    "cc['t_squared'] = cc['t']**2\n",
    "cc[\"Sales_log\"] =np.log(data['Sales'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "04bc5ebb",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Quarter</th>\n",
       "      <th>Sales</th>\n",
       "      <th>quarter</th>\n",
       "      <th>Q1</th>\n",
       "      <th>Q2</th>\n",
       "      <th>Q3</th>\n",
       "      <th>Q4</th>\n",
       "      <th>t</th>\n",
       "      <th>t_squared</th>\n",
       "      <th>Sales_log</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Q1_86</td>\n",
       "      <td>1734.827000</td>\n",
       "      <td>Q1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>7.458663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Q2_86</td>\n",
       "      <td>2244.960999</td>\n",
       "      <td>Q2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>7.716443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q3_86</td>\n",
       "      <td>2533.804993</td>\n",
       "      <td>Q3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>7.837477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Q4_86</td>\n",
       "      <td>2154.962997</td>\n",
       "      <td>Q4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>7.675529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Q1_87</td>\n",
       "      <td>1547.818996</td>\n",
       "      <td>Q1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "      <td>7.344602</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Quarter        Sales quarter  Q1  Q2  Q3  Q4  t  t_squared  Sales_log\n",
       "0   Q1_86  1734.827000      Q1   1   0   0   0  1          1   7.458663\n",
       "1   Q2_86  2244.960999      Q2   0   1   0   0  2          4   7.716443\n",
       "2   Q3_86  2533.804993      Q3   0   0   1   0  3          9   7.837477\n",
       "3   Q4_86  2154.962997      Q4   0   0   0   1  4         16   7.675529\n",
       "4   Q1_87  1547.818996      Q1   1   0   0   0  5         25   7.344602"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cc.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "4aa686dd",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cc['t_squared'].plot()\n",
    "plt.title('Quterwise Sales',fontdict={'fontsize': 16,'color': 'black'})\n",
    "plt.xlabel('Quaters')\n",
    "plt.ylabel('Sales')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55acfe44",
   "metadata": {},
   "source": [
    "<h3>Observations:</h3>\n",
    "as we saw in first there was an trend and multiplicative seasonality <br>\n",
    "now we have defined new column t_squared and plotted the graph<br>\n",
    "so there we got the upward trend but the seasonality has reduced<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "dc589afb",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='quarter'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,8))\n",
    "heatmap_y_month = pd.pivot_table(data=data,values=\"Sales\",columns=\"quarter\",aggfunc=\"mean\",fill_value=0)\n",
    "sns.heatmap(heatmap_y_month,annot=True,fmt=\"g\") #fmt is format of the grid values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3d9de5e",
   "metadata": {},
   "source": [
    "<h3>Observations:</h3>\n",
    "The Quarter 2 has highest mean<br>\n",
    "Most of the Sales has occurred in Quarter 2.So, these quarter is benificial for oue future analysis <br> \n",
    "while Quarter 1 has low mean<br>\n",
    "which means less sales took place in Quarter 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "862af4c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Boxplot for ever\n",
    "plt.figure(figsize=(20,15))\n",
    "plt.subplot(211)\n",
    "sns.boxplot(x=\"quarter\",y=\"Sales\",data=data)\n",
    "plt.title('Boxplot of Quterwise Sales',fontdict={'fontsize': 30})\n",
    "plt.xlabel('Quarters')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "2e70683b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,3))\n",
    "sns.lineplot(x=\"quarter\",y=\"Sales\",data=data)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bbd20bd",
   "metadata": {},
   "source": [
    "<h3>Observations:</h3>\n",
    "From Quarter 1 the sales was in upward trend<br>\n",
    "then from Quarter 2 the sales got drastic downward<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90728536",
   "metadata": {},
   "source": [
    "## Splitting of data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "fb80880e",
   "metadata": {},
   "outputs": [],
   "source": [
    "train =cc.head(32)\n",
    "test =cc.tail(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4858752d",
   "metadata": {},
   "source": [
    "## Moving Average"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "074f3856",
   "metadata": {},
   "source": [
    "A moving average is a technique that calculates the overall trend in a data set. In operations management, the data set is sales volume from historical data of the company. This technique is very useful for forecasting short-term trends. It is simply the average of a select set of time periods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "1d8fe372",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,4))\n",
    "data['Sales'].plot(label=\"org\")\n",
    "for i in range(2,20,4):\n",
    "    data['Sales'].rolling(i).mean().plot(label=str(i))\n",
    "plt.legend(loc='best')\n",
    "plt.title('Moving Average of Dataset')\n",
    "plt.xlabel('Quarters')\n",
    "plt.ylabel('Sales')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e62ec6ac",
   "metadata": {},
   "source": [
    "<h3>Observations:</h3>\n",
    "The original sales according to quarters have trend and seasonality<br>\n",
    "but as we increase the number range the seasonality getting vanished<br>\n",
    "and at the end the best fitted line getting which fits maximum numbers od data points on a line"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "818010d2",
   "metadata": {},
   "source": [
    "## Time series decomposition plot "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3599b260",
   "metadata": {},
   "source": [
    "Time series decomposition is usually presented as an analysis step to be performed before generating predictions, but it can also be used as a forecasting method in and of itself if you know what the structure of your time series will look like beforehand"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "f9ab59ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "decompose_ts_add = seasonal_decompose(data['Sales'],period=12)\n",
    "decompose_ts_add.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fef6733",
   "metadata": {},
   "source": [
    "<h3>Observations:</h3>\n",
    "By seasonal_decompose we have got the forecasting components<br>\n",
    "In trend component we got Upward trend<br>\n",
    "In seasonal component we got additive seasonality <br>\n",
    "And Resid part covers less numbers of datapoints on the line"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e906ba7e",
   "metadata": {},
   "source": [
    "## ACF plots and PACF plots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b061e748",
   "metadata": {},
   "source": [
    "An ACF measures and plots the average correlation between data points in time series and previous values of the series measured for different lag lengths. A PACF is similar to an ACF except that each partial correlation controls for any correlation between observations of a shorter lag length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "0a53d4b8",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import statsmodels.graphics.tsaplots as tsa_plots\n",
    "tsa_plots.plot_acf(data['Sales'],lags=12)\n",
    "tsa_plots.plot_pacf(data['Sales'],lags=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b458161a",
   "metadata": {},
   "source": [
    "<h3>Observations:</h3>\n",
    "The autocorrelation graph shows that lags getting gradually decresing<br>\n",
    "so we can see that data is non-Stationary<br>\n",
    "In ACF there are four significant spikes <br>\n",
    "In PACF there are five significant spikes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e56d5261",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sales_diff = data['Sales'].diff(periods = 1)\n",
    "tsa_plots.plot_acf(sales_diff[1:])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d40b87a9",
   "metadata": {},
   "source": [
    "<h3>Observations:</h3>\n",
    "The data has been converted into Stationary<br>\n",
    "In ACF there are only three significant spikes <br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bdd195c6",
   "metadata": {},
   "source": [
    "## Evaluation Metric MAPE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "4a28c8a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def MAPE(pred,org):\n",
    "    temp = np.abs((pred-org)/org)*100\n",
    "    return np.mean(temp)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57bb350f",
   "metadata": {},
   "source": [
    "### Simple Exponential Method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "640442e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22.724051812293908"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ses_model = SimpleExpSmoothing(train[\"Sales\"]).fit(smoothing_level=0.2)\n",
    "pred_ses = ses_model.predict(start = test.index[0],end = test.index[-1])\n",
    "MAPE(pred_ses,test.Sales)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6442e237",
   "metadata": {},
   "source": [
    "### Holt method "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "0e250e3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16.720651186614823"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Holt method \n",
    "hw_model = Holt(train[\"Sales\"]).fit(smoothing_level=0.8, smoothing_slope=0.2)\n",
    "pred_hw = hw_model.predict(start = test.index[0],end = test.index[-1])\n",
    "MAPE(pred_hw,test.Sales) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3014eef8",
   "metadata": {},
   "source": [
    "### Holts winter exponential smoothing with additive seasonality and additive trend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "d6e43621",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12.18419752082701"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hwe_model_add_add = ExponentialSmoothing(train[\"Sales\"],seasonal=\"add\",trend=\"add\",seasonal_periods=12).fit() #add the trend to the model\n",
    "pred_hwe_add_add = hwe_model_add_add.predict(start = test.index[0],end = test.index[-1])\n",
    "MAPE(pred_hwe_add_add,test.Sales) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6527f66b",
   "metadata": {},
   "source": [
    "### Holts winter exponential smoothing with multiplicative seasonality and additive trend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "f88279ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12.781002162867637"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hwe_model_mul_add = ExponentialSmoothing(train[\"Sales\"],seasonal=\"mul\",trend=\"add\",seasonal_periods=12).fit() \n",
    "pred_hwe_mul_add = hwe_model_mul_add.predict(start = test.index[0],end = test.index[-1])\n",
    "MAPE(pred_hwe_mul_add,test.Sales)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14fb9385",
   "metadata": {},
   "source": [
    "## Final Model by combining train and test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "8b0afe00",
   "metadata": {},
   "outputs": [],
   "source": [
    "hwe_model_add_add = ExponentialSmoothing(data[\"Sales\"],seasonal=\"add\",trend=\"add\",seasonal_periods=12).fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "3e4d2c4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "42    5055.537501\n",
       "43    4927.723652\n",
       "44    4883.395386\n",
       "45    5555.315269\n",
       "46    5589.336941\n",
       "47    5335.210947\n",
       "48    5233.944437\n",
       "49    5969.869343\n",
       "50    6031.388558\n",
       "51    5756.189471\n",
       "52    5561.316463\n",
       "53    6362.887311\n",
       "dtype: float64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Forecasting for next 10 time periods\n",
    "hwe_model_add_add.forecast(12)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b7e0f74",
   "metadata": {},
   "source": [
    "## Buliding Models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "90a5b458",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import mean_squared_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "5948fef4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "752.9233932767121"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Linear Model\n",
    "\n",
    "linear_model =smf.ols(\"Sales~t\",data =train).fit()\n",
    "linear_pred = pd.Series(linear_model.predict(test['t']))\n",
    "linear_rmse =np.sqrt(mean_squared_error(np.array(test['Sales']),np.array(linear_pred)))\n",
    "linear_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "d139551c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "457.7357355407437"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Quadratic Model\n",
    "\n",
    "quad_model =smf.ols(\"Sales~t+t_squared\",data=train).fit()\n",
    "quad_pred = pd.Series(quad_model.predict(test[['t','t_squared']]))\n",
    "quad_rmse =np.sqrt(mean_squared_error(np.array(test['Sales']),np.array(quad_pred)))\n",
    "quad_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "b7f95584",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4387.940544839098"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exponential model\n",
    "\n",
    "exp_model  =smf.ols(\"Sales_log~t\",data=train).fit()\n",
    "exp_pred =pd.Series(exp_model.predict(test['t']))\n",
    "exp_rmse =np.sqrt(mean_squared_error(np.array(test['Sales']),np.array(exp_pred)))\n",
    "exp_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "67ea9342",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1850.4665461858358"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Additive seasonality model\n",
    "\n",
    "add_sea = smf.ols('Sales~Q1+Q2+Q3+Q4',data=train).fit()\n",
    "pred_add_sea = pd.Series(add_sea.predict(test[['Q1','Q2','Q3','Q4']]))\n",
    "rmse_add_sea = np.sqrt(np.mean((np.array(test['Sales'])-np.array(pred_add_sea))**2))\n",
    "rmse_add_sea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "b6bb99de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "277.3510771128639"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Additive Seasonality Quadratic model\n",
    "\n",
    "add_sea_Quad = smf.ols('Sales~t+t_squared+Q1+Q2+Q3+Q4',data=train).fit()\n",
    "pred_add_sea_quad = pd.Series(add_sea_Quad.predict(test[['Q1','Q2','Q3','Q4','t','t_squared']]))\n",
    "rmse_add_sea_quad = np.sqrt(np.mean((np.array(test['Sales'])-np.array(pred_add_sea_quad))**2))\n",
    "rmse_add_sea_quad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "d55d8a02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1908.250394836118"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##Multiplicative Seasonality model\n",
    "\n",
    "Mul_sea = smf.ols('Sales_log~Q1+Q2+Q3+Q4',data = train).fit()\n",
    "pred_Mult_sea = pd.Series(Mul_sea.predict(test))\n",
    "rmse_Mult_sea = np.sqrt(np.mean((np.array(test['Sales'])-np.array(np.exp(pred_Mult_sea)))**2))\n",
    "rmse_Mult_sea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "a7ee04f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "448.8678182692097"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Multiplicative Additive Seasonality model\n",
    "\n",
    "Mul_Add_sea = smf.ols('Sales_log~t+Q1+Q2+Q3+Q4',data = train).fit()\n",
    "pred_Mult_add_sea = pd.Series(Mul_Add_sea.predict(test))\n",
    "rmse_Mult_add_sea = np.sqrt(np.mean((np.array(test['Sales'])-np.array(np.exp(pred_Mult_add_sea)))**2))\n",
    "rmse_Mult_add_sea "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "306fe606",
   "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>MODEL</th>\n",
       "      <th>RMSE_Values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>rmse_add_sea_quad</td>\n",
       "      <td>277.351077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rmse_Mult_add_sea</td>\n",
       "      <td>448.867818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>rmse_Quad</td>\n",
       "      <td>457.735736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>rmse_linear</td>\n",
       "      <td>752.923393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>rmse_add_sea</td>\n",
       "      <td>1850.466546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>rmse_Mult_sea</td>\n",
       "      <td>1908.250395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rmse_Exp</td>\n",
       "      <td>4387.940545</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               MODEL  RMSE_Values\n",
       "4  rmse_add_sea_quad   277.351077\n",
       "6  rmse_Mult_add_sea   448.867818\n",
       "1          rmse_Quad   457.735736\n",
       "0        rmse_linear   752.923393\n",
       "3       rmse_add_sea  1850.466546\n",
       "5      rmse_Mult_sea  1908.250395\n",
       "2           rmse_Exp  4387.940545"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Compare the results \n",
    "\n",
    "data = {\"MODEL\":pd.Series([\"rmse_linear\",\"rmse_Quad\",\"rmse_Exp\",\"rmse_add_sea\",\"rmse_add_sea_quad\",\n",
    "                           \"rmse_Mult_sea\",\"rmse_Mult_add_sea\"]),\n",
    "        \"RMSE_Values\":pd.Series([linear_rmse,quad_rmse,exp_rmse,rmse_add_sea,\n",
    "                                 rmse_add_sea_quad,rmse_Mult_sea,rmse_Mult_add_sea])}\n",
    "\n",
    "table_rmse=pd.DataFrame(data)\n",
    "table_rmse.sort_values(['RMSE_Values'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9445db59",
   "metadata": {},
   "source": [
    "## ARIMA model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "b6b16ba6",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_excel(\"CocaCola_Sales_Rawdata.xlsx\",header=0,index_col=0, parse_dates=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "eeb17ab1",
   "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>Sales</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Quarter</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Q1_86</th>\n",
       "      <td>1734.827000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q2_86</th>\n",
       "      <td>2244.960999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q3_86</th>\n",
       "      <td>2533.804993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q4_86</th>\n",
       "      <td>2154.962997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q1_87</th>\n",
       "      <td>1547.818996</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Sales\n",
       "Quarter             \n",
       "Q1_86    1734.827000\n",
       "Q2_86    2244.960999\n",
       "Q3_86    2533.804993\n",
       "Q4_86    2154.962997\n",
       "Q1_87    1547.818996"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "9eeaaadc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset_cc 32, Validation_cc 10\n"
     ]
    }
   ],
   "source": [
    "#separate out a validation dataset\n",
    "split_point = len(data) - 10\n",
    "dataset_cc, validation_cc = data[0:split_point], data[split_point:]\n",
    "print('Dataset_cc %d, Validation_cc %d' % (len(dataset_cc), len(validation_cc)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "61b78fd6",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset_cc.to_csv('dataset_cc.csv', header=False)\n",
    "validation_cc.to_csv('validation_cc.csv', header=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "74203acd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas import read_csv\n",
    "from math import sqrt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "d5b2c1d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0\n",
       "Q1_86    1734.827000\n",
       "Q2_86    2244.960999\n",
       "Q3_86    2533.804993\n",
       "Q4_86    2154.962997\n",
       "Q1_87    1547.818996\n",
       "Name: 1, dtype: float64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train = read_csv('dataset_cc.csv', header=None, index_col=0, parse_dates=True, squeeze=True)\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "3aa684e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = train.values\n",
    "X = X.astype('float32')\n",
    "train_size = int(len(X) * 0.50)\n",
    "train, test = X[0:train_size], X[train_size:]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d9bb7c6",
   "metadata": {},
   "source": [
    "## Validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "eddf4d29",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">Predicted=2173.968, Expected=2148.278\n",
      ">Predicted=2148.278, Expected=2739.308\n",
      ">Predicted=2739.308, Expected=2792.754\n",
      ">Predicted=2792.754, Expected=2556.010\n",
      ">Predicted=2556.010, Expected=2480.974\n",
      ">Predicted=2480.974, Expected=3039.523\n",
      ">Predicted=3039.523, Expected=3172.116\n",
      ">Predicted=3172.116, Expected=2879.001\n",
      ">Predicted=2879.001, Expected=2772.000\n",
      ">Predicted=2772.000, Expected=3550.000\n",
      ">Predicted=3550.000, Expected=3508.000\n",
      ">Predicted=3508.000, Expected=3243.860\n",
      ">Predicted=3243.860, Expected=3056.000\n",
      ">Predicted=3056.000, Expected=3899.000\n",
      ">Predicted=3899.000, Expected=3629.000\n",
      ">Predicted=3629.000, Expected=3373.000\n",
      "RMSE: 387.510\n"
     ]
    }
   ],
   "source": [
    "history = [x for x in train]\n",
    "predictions = list()\n",
    "for i in range(len(test)):\n",
    "    yhat = history[-1]\n",
    "    predictions.append(yhat)\n",
    "# observation\n",
    "    obs = test[i]\n",
    "    history.append(obs)\n",
    "    print('>Predicted=%.3f, Expected=%.3f' % (yhat, obs))\n",
    "# report performance\n",
    "rmse = sqrt(mean_squared_error(test, predictions))\n",
    "print('RMSE: %.3f' % rmse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "06df87d1",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MODEL</th>\n",
       "      <th>RMSE_Values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>rmse_add_sea_quad</td>\n",
       "      <td>277.351077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>RMSE_ARIMA</td>\n",
       "      <td>387.510403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rmse_Mult_add_sea</td>\n",
       "      <td>448.867818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>rmse_Quad</td>\n",
       "      <td>457.735736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>rmse_linear</td>\n",
       "      <td>752.923393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>rmse_add_sea</td>\n",
       "      <td>1850.466546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>rmse_Mult_sea</td>\n",
       "      <td>1908.250395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>rmse_Exp</td>\n",
       "      <td>4387.940545</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               MODEL  RMSE_Values\n",
       "4  rmse_add_sea_quad   277.351077\n",
       "7         RMSE_ARIMA   387.510403\n",
       "6  rmse_Mult_add_sea   448.867818\n",
       "1          rmse_Quad   457.735736\n",
       "0        rmse_linear   752.923393\n",
       "3       rmse_add_sea  1850.466546\n",
       "5      rmse_Mult_sea  1908.250395\n",
       "2           rmse_Exp  4387.940545"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Compare the results \n",
    "\n",
    "data = {\"MODEL\":pd.Series([\"rmse_linear\",\"rmse_Quad\",\"rmse_Exp\",\"rmse_add_sea\",\"rmse_add_sea_quad\",\n",
    "                           \"rmse_Mult_sea\",\"rmse_Mult_add_sea\",\"RMSE_ARIMA\"]),\n",
    "        \"RMSE_Values\":pd.Series([linear_rmse,quad_rmse,exp_rmse,rmse_add_sea,\n",
    "                                 rmse_add_sea_quad,rmse_Mult_sea,rmse_Mult_add_sea,rmse])}\n",
    "\n",
    "table_rmse=pd.DataFrame(data)\n",
    "table_rmse.sort_values(['RMSE_Values'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c97cf4d",
   "metadata": {},
   "source": [
    "<h3>Insights:</h3>\n",
    "    The least RMSE values has the rmse_add_sea_quad (Additive Seasonality Quadratic) model and we can final this model and forecast the future predictions."
   ]
  }
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