Gold_price_prediction_ML.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6ba90720",
   "metadata": {},
   "source": [
    "# IMPORTING NECESSARY LIBRARIES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f6ff8903",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn import metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22e978b2",
   "metadata": {},
   "source": [
    "# READING THE FILE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ca20f30b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>SPX</th>\n",
       "      <th>GLD</th>\n",
       "      <th>USO</th>\n",
       "      <th>SLV</th>\n",
       "      <th>EUR/USD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/2/2008</td>\n",
       "      <td>1447.160034</td>\n",
       "      <td>84.860001</td>\n",
       "      <td>78.470001</td>\n",
       "      <td>15.1800</td>\n",
       "      <td>1.471692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/3/2008</td>\n",
       "      <td>1447.160034</td>\n",
       "      <td>85.570000</td>\n",
       "      <td>78.370003</td>\n",
       "      <td>15.2850</td>\n",
       "      <td>1.474491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/4/2008</td>\n",
       "      <td>1411.630005</td>\n",
       "      <td>85.129997</td>\n",
       "      <td>77.309998</td>\n",
       "      <td>15.1670</td>\n",
       "      <td>1.475492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/7/2008</td>\n",
       "      <td>1416.180054</td>\n",
       "      <td>84.769997</td>\n",
       "      <td>75.500000</td>\n",
       "      <td>15.0530</td>\n",
       "      <td>1.468299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/8/2008</td>\n",
       "      <td>1390.189941</td>\n",
       "      <td>86.779999</td>\n",
       "      <td>76.059998</td>\n",
       "      <td>15.5900</td>\n",
       "      <td>1.557099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2285</th>\n",
       "      <td>5/8/2018</td>\n",
       "      <td>2671.919922</td>\n",
       "      <td>124.589996</td>\n",
       "      <td>14.060000</td>\n",
       "      <td>15.5100</td>\n",
       "      <td>1.186789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2286</th>\n",
       "      <td>5/9/2018</td>\n",
       "      <td>2697.790039</td>\n",
       "      <td>124.330002</td>\n",
       "      <td>14.370000</td>\n",
       "      <td>15.5300</td>\n",
       "      <td>1.184722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2287</th>\n",
       "      <td>5/10/2018</td>\n",
       "      <td>2723.070068</td>\n",
       "      <td>125.180000</td>\n",
       "      <td>14.410000</td>\n",
       "      <td>15.7400</td>\n",
       "      <td>1.191753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2288</th>\n",
       "      <td>5/14/2018</td>\n",
       "      <td>2730.129883</td>\n",
       "      <td>124.489998</td>\n",
       "      <td>14.380000</td>\n",
       "      <td>15.5600</td>\n",
       "      <td>1.193118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2289</th>\n",
       "      <td>5/16/2018</td>\n",
       "      <td>2725.780029</td>\n",
       "      <td>122.543800</td>\n",
       "      <td>14.405800</td>\n",
       "      <td>15.4542</td>\n",
       "      <td>1.182033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2290 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date          SPX         GLD        USO      SLV   EUR/USD\n",
       "0      1/2/2008  1447.160034   84.860001  78.470001  15.1800  1.471692\n",
       "1      1/3/2008  1447.160034   85.570000  78.370003  15.2850  1.474491\n",
       "2      1/4/2008  1411.630005   85.129997  77.309998  15.1670  1.475492\n",
       "3      1/7/2008  1416.180054   84.769997  75.500000  15.0530  1.468299\n",
       "4      1/8/2008  1390.189941   86.779999  76.059998  15.5900  1.557099\n",
       "...         ...          ...         ...        ...      ...       ...\n",
       "2285   5/8/2018  2671.919922  124.589996  14.060000  15.5100  1.186789\n",
       "2286   5/9/2018  2697.790039  124.330002  14.370000  15.5300  1.184722\n",
       "2287  5/10/2018  2723.070068  125.180000  14.410000  15.7400  1.191753\n",
       "2288  5/14/2018  2730.129883  124.489998  14.380000  15.5600  1.193118\n",
       "2289  5/16/2018  2725.780029  122.543800  14.405800  15.4542  1.182033\n",
       "\n",
       "[2290 rows x 6 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv('E:\\DA_PROJECTS\\SAMPLE_PRO\\gold.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4704c3ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>SPX</th>\n",
       "      <th>GLD</th>\n",
       "      <th>USO</th>\n",
       "      <th>SLV</th>\n",
       "      <th>EUR/USD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/2/2008</td>\n",
       "      <td>1447.160034</td>\n",
       "      <td>84.860001</td>\n",
       "      <td>78.470001</td>\n",
       "      <td>15.180</td>\n",
       "      <td>1.471692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/3/2008</td>\n",
       "      <td>1447.160034</td>\n",
       "      <td>85.570000</td>\n",
       "      <td>78.370003</td>\n",
       "      <td>15.285</td>\n",
       "      <td>1.474491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/4/2008</td>\n",
       "      <td>1411.630005</td>\n",
       "      <td>85.129997</td>\n",
       "      <td>77.309998</td>\n",
       "      <td>15.167</td>\n",
       "      <td>1.475492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/7/2008</td>\n",
       "      <td>1416.180054</td>\n",
       "      <td>84.769997</td>\n",
       "      <td>75.500000</td>\n",
       "      <td>15.053</td>\n",
       "      <td>1.468299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/8/2008</td>\n",
       "      <td>1390.189941</td>\n",
       "      <td>86.779999</td>\n",
       "      <td>76.059998</td>\n",
       "      <td>15.590</td>\n",
       "      <td>1.557099</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "       Date          SPX        GLD        USO     SLV   EUR/USD\n",
       "0  1/2/2008  1447.160034  84.860001  78.470001  15.180  1.471692\n",
       "1  1/3/2008  1447.160034  85.570000  78.370003  15.285  1.474491\n",
       "2  1/4/2008  1411.630005  85.129997  77.309998  15.167  1.475492\n",
       "3  1/7/2008  1416.180054  84.769997  75.500000  15.053  1.468299\n",
       "4  1/8/2008  1390.189941  86.779999  76.059998  15.590  1.557099"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#DISPLAYING FIRST 5 ENTRIES\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "bced0ec2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>SPX</th>\n",
       "      <th>GLD</th>\n",
       "      <th>USO</th>\n",
       "      <th>SLV</th>\n",
       "      <th>EUR/USD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2285</th>\n",
       "      <td>5/8/2018</td>\n",
       "      <td>2671.919922</td>\n",
       "      <td>124.589996</td>\n",
       "      <td>14.0600</td>\n",
       "      <td>15.5100</td>\n",
       "      <td>1.186789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2286</th>\n",
       "      <td>5/9/2018</td>\n",
       "      <td>2697.790039</td>\n",
       "      <td>124.330002</td>\n",
       "      <td>14.3700</td>\n",
       "      <td>15.5300</td>\n",
       "      <td>1.184722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2287</th>\n",
       "      <td>5/10/2018</td>\n",
       "      <td>2723.070068</td>\n",
       "      <td>125.180000</td>\n",
       "      <td>14.4100</td>\n",
       "      <td>15.7400</td>\n",
       "      <td>1.191753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2288</th>\n",
       "      <td>5/14/2018</td>\n",
       "      <td>2730.129883</td>\n",
       "      <td>124.489998</td>\n",
       "      <td>14.3800</td>\n",
       "      <td>15.5600</td>\n",
       "      <td>1.193118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2289</th>\n",
       "      <td>5/16/2018</td>\n",
       "      <td>2725.780029</td>\n",
       "      <td>122.543800</td>\n",
       "      <td>14.4058</td>\n",
       "      <td>15.4542</td>\n",
       "      <td>1.182033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "           Date          SPX         GLD      USO      SLV   EUR/USD\n",
       "2285   5/8/2018  2671.919922  124.589996  14.0600  15.5100  1.186789\n",
       "2286   5/9/2018  2697.790039  124.330002  14.3700  15.5300  1.184722\n",
       "2287  5/10/2018  2723.070068  125.180000  14.4100  15.7400  1.191753\n",
       "2288  5/14/2018  2730.129883  124.489998  14.3800  15.5600  1.193118\n",
       "2289  5/16/2018  2725.780029  122.543800  14.4058  15.4542  1.182033"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#DISPLAYING LAST 5 ENTRIES\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "01ed58cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2290"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#SHOWING TOTAL NUMBER OF ENTRIES\n",
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ea9a65e7",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2290 entries, 0 to 2289\n",
      "Data columns (total 6 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   Date     2290 non-null   object \n",
      " 1   SPX      2290 non-null   float64\n",
      " 2   GLD      2290 non-null   float64\n",
      " 3   USO      2290 non-null   float64\n",
      " 4   SLV      2290 non-null   float64\n",
      " 5   EUR/USD  2290 non-null   float64\n",
      "dtypes: float64(5), object(1)\n",
      "memory usage: 107.5+ KB\n"
     ]
    }
   ],
   "source": [
    "#DISPLAYING THE INFORMATION ABOUT TABLE DATA\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0c93bd52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2290, 6)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#DISPLAIYNG NUMBER OF ROWS AND COLUMNS\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ddd2e683",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date       0\n",
       "SPX        0\n",
       "GLD        0\n",
       "USO        0\n",
       "SLV        0\n",
       "EUR/USD    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#CHECKING ON PRESENCE OF NULL VALUE\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e89e39a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SPX</th>\n",
       "      <td>2290.0</td>\n",
       "      <td>1654.315776</td>\n",
       "      <td>519.111540</td>\n",
       "      <td>676.530029</td>\n",
       "      <td>1239.874969</td>\n",
       "      <td>1551.434998</td>\n",
       "      <td>2073.010070</td>\n",
       "      <td>2872.870117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GLD</th>\n",
       "      <td>2290.0</td>\n",
       "      <td>122.732875</td>\n",
       "      <td>23.283346</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>109.725000</td>\n",
       "      <td>120.580002</td>\n",
       "      <td>132.840004</td>\n",
       "      <td>184.589996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USO</th>\n",
       "      <td>2290.0</td>\n",
       "      <td>31.842221</td>\n",
       "      <td>19.523517</td>\n",
       "      <td>7.960000</td>\n",
       "      <td>14.380000</td>\n",
       "      <td>33.869999</td>\n",
       "      <td>37.827501</td>\n",
       "      <td>117.480003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SLV</th>\n",
       "      <td>2290.0</td>\n",
       "      <td>20.084997</td>\n",
       "      <td>7.092566</td>\n",
       "      <td>8.850000</td>\n",
       "      <td>15.570000</td>\n",
       "      <td>17.268500</td>\n",
       "      <td>22.882500</td>\n",
       "      <td>47.259998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EUR/USD</th>\n",
       "      <td>2290.0</td>\n",
       "      <td>1.283653</td>\n",
       "      <td>0.131547</td>\n",
       "      <td>1.039047</td>\n",
       "      <td>1.171313</td>\n",
       "      <td>1.303297</td>\n",
       "      <td>1.369971</td>\n",
       "      <td>1.598798</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          count         mean         std         min          25%  \\\n",
       "SPX      2290.0  1654.315776  519.111540  676.530029  1239.874969   \n",
       "GLD      2290.0   122.732875   23.283346   70.000000   109.725000   \n",
       "USO      2290.0    31.842221   19.523517    7.960000    14.380000   \n",
       "SLV      2290.0    20.084997    7.092566    8.850000    15.570000   \n",
       "EUR/USD  2290.0     1.283653    0.131547    1.039047     1.171313   \n",
       "\n",
       "                 50%          75%          max  \n",
       "SPX      1551.434998  2073.010070  2872.870117  \n",
       "GLD       120.580002   132.840004   184.589996  \n",
       "USO        33.869999    37.827501   117.480003  \n",
       "SLV        17.268500    22.882500    47.259998  \n",
       "EUR/USD     1.303297     1.369971     1.598798  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#STATISTICAL DESCRIPTION OF THE DATA\n",
    "df.describe().transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0e10586",
   "metadata": {},
   "source": [
    "# CREATING CORRELATION BETWEEN PARAMETERS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cff82b42",
   "metadata": {},
   "outputs": [],
   "source": [
    "correlation=df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b1388a5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AX4i/KB8/b/N2ft5m3cgXzl2Qt1+hPI01v/p++Uo9+0QvPftEL/26dbvizsZlT0FlGIbOxp5VYFBgjv2CSgaqQeP68g/wl8lkUtgj7bX/9/15HX6+s/GHTQrvM0bhfcbo9x37lXjuvDIzsgayGYahhLhE+QXcugfHs6CnQto01qbVW/Mi5HxrxbIVeqpbdz3Vrbu2btmW43cjNuasAoOCbrr/T6t/UvkK5XMdeALYikUJ4dGjR9W3b9/sxz179lR6erpiY2MtOml4eLiSk5PNFpX3uf2ODuKbjSvVrXmY/Itkdc0M6vSc/rdumZ2jyl+8fL1UvHxxHdp4WJJ0bNtx+fh7m3UXS1KFJuV0fPsJXUq6JMMwtD8ySpWa8SFrDY906aiFXy/Qwq8XqHf/nqparYpWffejJGlN5FqVLBWUo7tYktq2b6Oo36N04UJW1/2WX7aqcpXKeRp7ftSyQ3NFzBuniHnj1Pm5jipXuax+Wb1FkvTrup3yC/TLtbv47Ol/kpW/q4NlK5bO0Q537vrBIf0G9FW16lX1/YqVkrKSvZKlSt6yu3jpt8uoDt4hF5PJbkt+YzKMO+9Ec3FxUWxsrPz9/bPX+fj4aO/evapQocK9BdLOMT6Apr/8trqGtFdgsRKKT07UhbRLqtynhWYN/4+Wb1mtFVsiJUkDOjyjEd0Hy8XFpDV7NuvF98OVkekYE3j/d/Kr9g7hjiSdSdLaDzco/cJlFfByV+shrVSsTFGtn7lBwQ2DVa5hsCQp6qc/tWfZPhmGoVK1gtRiQAu5ujnGRfP9q/e3dwh37MSxExr377eVnJysQoUKaczEN1WxUtbnwttj3tGDD7XUg61bSsqqLi6Y87lcXV3l719C4WNGKiDQ/1aHt7tDyVH2DsEiZ6Jj9PHEObqQfEFehTw1aPQAla6QNe3MrP+bq/ot6qpBi3pa990G/bAoUi4uJmVmXlPNBtX19OCn5O5xf1+7VqtYPXuHcMeOHzuuN0e9paSkZHl7F9KEdyaoUuWsL6Zj3xynh1q30kMPPyRJOhl9Uk891kM/rV+tQoUcozfD07Wg3c5ddHRTu537/MT8VUm3OCF8++235e39T7fciBEj9MYbb8jP759vnq+88orlgThIQugMHCUhdAaOlBDmd46WEOZ3jpQQ5nf2TAiL/TvEbudOfHuL3c5tCxaNMi5btqxmzZplti4wMFCfffZZ9mOTyXRXCSEAAADsw6KE8Pjx4zYKAwAAwDLM4mE9Fl1ItW3bNv3www9m6xYsWKDy5cvL399fzz//vNLT060aIAAAAGzLooRwzJgx2rdvX/bj3377Tf3791fbtm01cuRIrVixQhEREVYPEgAAALZjUUK4d+9etWnTJvvx//73PzVp0kSzZs3S8OHDNW3aNH311VdWDxIAAOBGJpP9lvzGooTw/PnzCggIyH68fv16hYWFZT9u1KiRTp48ab3oAAAAYHMWJYQBAQE6duyYJOnKlSvatWuXQkL+GfKdmprKfRcBAECeMJlMdlvyG4sSwrCwMI0cOVIbN25UeHi4ChYsqJYtW2Zv37dvnypW5C4QAAAAjsSiaWfefvttPfbYY2rVqpW8vb01f/58ubu7Z2+fM2eOQkNDrR4kAAAAbMeihLBEiRLauHGjkpOT5e3tLVdXV7PtixcvNruLCQAAgK3kx65be7EoIfybr69vruuLFSt2T8EAAAAg791VQggAAGBvVAitx6JBJQAAAMh/SAgBAACcHF3GAADAIdFlbD1UCAEAAJwcFUIAAOCQKBBaDxVCAAAAJ0eFEAAAOCSuIbQeKoQAAABOjoQQAADAydFlDAAAHBJdxtZDhRAAAMDJUSEEAAAOyYUKodVQIQQAAHByJIQAAABOji5jAADgkOgxth4qhAAAAE6OCiEAAHBITDtjPVQIAQAAbGzGjBkqX768PD091aBBA23cuPGW7dPT0zV69GgFBwfLw8NDFStW1Jw5c2wWHxVCAADgkExyjArhokWLNHToUM2YMUPNmzfXxx9/rA4dOmj//v0qW7Zsrvs89dRTOnv2rGbPnq1KlSopLi5OGRkZNouRhBAAAMCGpkyZov79+2vAgAGSpKlTp+rHH3/URx99pIiIiBztV61apfXr1+vo0aMqVqyYJKlcuXI2jZEuYwAAAAulp6crJSXFbElPT8/R7sqVK9q5c6dCQ0PN1oeGhmrz5s25Hnv58uVq2LChJk2apFKlSqlKlSp6/fXXlZaWZpPnIpEQAgAAB2Uymey2REREyNfX12zJrdoXHx+vzMxMBQQEmK0PCAhQbGxsrs/r6NGj+uWXX/T7779ryZIlmjp1qr7++msNGTLEJq+jRJcxAACAxcLDwzV8+HCzdR4eHjdtf+OIaMMwbjpK+tq1azKZTFq4cKF8fX0lZXU7P/HEE/rwww/l5eV1j9HnREIIAAAckj2nnfHw8LhlAvg3Pz8/ubq65qgGxsXF5aga/i0oKEilSpXKTgYlqXr16jIMQ6dOnVLlypXvLfhc0GUMAABgI+7u7mrQoIEiIyPN1kdGRqpZs2a57tO8eXOdOXNGFy5cyF538OBBubi4qHTp0jaJk4QQAADAhoYPH65PP/1Uc+bMUVRUlIYNG6bo6GgNGjRIUlb3c69evbLbP/PMMypevLj69u2r/fv3a8OGDXrjjTfUr18/m3QXS3QZAwAAB+UoNyrp3r27EhISNH78eMXExKhWrVpauXKlgoODJUkxMTGKjo7Obu/t7a3IyEi9/PLLatiwoYoXL66nnnpKb7/9ts1iJCEEAACwscGDB2vw4MG5bps3b16OddWqVcvRzWxLJIQAAMAhcS9j6+EaQgAAACdHhRAAADgkKoTWQ4UQAADAyZEQAgAAOLn7psv4v5NftXcI+Mtrr79v7xDwlzrzatg7BPyl3ajht2+EPPNp+DB7h4C/9K82yG7npsvYeqgQAgAAOLn7pkIIAABgCQqE1kOFEAAAwMmREAIAADg5uowBAIBDYlCJ9VAhBAAAcHJUCAEAgEOiQmg9VAgBAACcHBVCAADgkKgQWg8VQgAAACdHQggAAODk6DIGAAAOiR5j66FCCAAA4OSoEAIAAIfEoBLroUIIAADg5EgIAQAAnBxdxgAAwCHRZWw9VAgBAACcHBVCAADgkKgQWg8VQgAAACdHhRAAADgkCoTWQ4UQAADAyZEQAgAAODm6jAEAgENiUIn1UCEEAABwclQIAQCAY6JCaDVUCAEAAJwcCSEAAICTo8sYAAA4JAaVWA8VQgAAACdHhRAAADgkCoTWQ4UQAADAyVEhBAAADolrCK2HCiEAAICTIyEEAABwcnQZAwAAh0SXsfVQIQQAAHByd1UhNAxDO3fu1PHjx2UymVS+fHnVq1ePTB0AAOQZ8g7rsTghXLt2rfr3768TJ07IMAxJyk4K58yZowcffNDqQQIAAMB2LOoyPnz4sDp16qRy5crp22+/VVRUlPbv36/FixerdOnS6tixo44ePWqrWAEAAGADFlUIp06dqqZNm+rnn382W1+tWjV169ZNbdu21XvvvacPPvjAqkECAADciB5j67GoQrhu3ToNHTo0120mk0lDhw7V2rVrrREXAAAA8ohFFcLo6GjVrl37pttr1aqlEydO3HNQAAAAt8OgEuuxqEJ44cIFFSxY8KbbCxYsqEuXLt1zUAAAAMg7Fo8y3r9/v2JjY3PdFh8ff88B3e+SY5K19sP1upx6We4FPdR6yIMqWrpojnZ/rjmg3Uv3SoahkrVKquWA5nJxZdpHa3p/8Hh1CWmncoFlVGtgG/1x/ECu7fqF9dDIHkPkYjLp592bNHjaKGVey8zjaPO/uFPntOD/vtTFlIvyKuSpniOeVlC5wBztDuw6pGWffq/0tHSZTCbVaV5Lnft14Ju+FVUKCNb8gf8nP5+iSrqUqj6zRirqzBGzNiaTSZO6v6Gw2i3l5uKmTYd26cX5Y3U186qdos6/Es+c18qpPyotNU0ehTzU8ZX28itbPNe2+yJ/19ZvtkuGobJ1yih0UBv+diBPWPxT1qZNG9WtWzfHUq9ePbVt29YWMd5XNnzyi6q3raYe7z+lul3raN1HG3O0SYlL1fZFO9V1fCf1mPaU0pLS9Oea3JMV3L2vN36vFsMe0/HYkzdtUy6wjCb0eV0thnZTpd4tFFishPp36JGHUTqPL6csVvNOTTVmQbja9nhYCycvyrVdQR8v9ft3T705d4RGzBymQ3uPaMeaXXkcbf72cZ/x+mTdV6o6IkyTvv9Us/tPzNGm/4NPqE6Zqqr/1mOqHt5BkvRqaK+8DtUprJ7xsx5oX1sDP+qrJt0aatX0yFzbJZ1N1saFm/Xs/z2lgTP76uL5S9oX+XseR+tYTCaT3Zb8xqKE8NixYzp69KiOHTuWY/l7fX6ediYtOU3xxxJUuWUlSVL5JuWUGpeq1LhUs3ZHtx5TuUbBKlikoEwmk2q0q67Dm47kdkjcg42/bdPp+Jhbtnmi5SNasmmV4pKyqtczv/tcT7d+NA+icy6p51N18tApNW7XQJJU78E6io9JVEJsYo62ZSqXll/JrOpIAfcCKl2xpOLP5GyHu1PCp5jqB9fQ55uXS5K+2fGjyvuVVrBfKbN2D5Stpp/+2JJdEVy5b716Nu+a5/HmdxeTLuns0TjVfKi6JKlKs8pKPpus5LPJOdoe2HRIVZpWUqEihWQymVQ3rI6iNlJMQN6wKCEMDg6+5VK4cGGtX7/eVrHa3YWEiypYtGB2+d5kMsnbz1up8RfM28VfkE8J7+zHPv7euhB/MU9jRZay/qV04uzp7MfHY0+qrH9JO0aUP50/lyRfP1+5urpKyvrdKOZfRIlnz99yv+TEFO3esE81m1TPizCdQpniQTqTFGd2WUR0YozKFg8ya7f96G/qWr+NvD0LqYBrAfVo8ojK3ZA04t6lxqfKu2ghs78bPiV8lBKfmmvbwv4+2Y99/Qsr5VxKnsXqiKgQWo9VL0yIjo5W3759b9suPT1dKSkpZkvGlQxrhmIzOX8GjNs2NG7SBHnDuO4NyI+/xPer2/3Yp128rJmjZ6tdj9YqW6V0nsTkLIwbXn2Tcv7cL9i0VD/+9os2jPpca0bO1x+nD3H9oK3c+PLf8pfj+sb88UDeuat7Gd+riIgIjRs3zmxd6Att1f7FUHuEc8e8ixfSxYSLupZ5TS6uLjIMQxfiL8rHz9u8nZ+3WTfyhXMX5O1XKK/DhaTouNMqF/hPshEcUFrRcWfsGFH+sW31dv28OKtHoOHD9ZQUn6zMzEy5urrKMAydj0tSsYCcA64k6fKly/pwxCeq06ym2jz5UB5Gnf+dTIhR6aKBcnVxza4SlikWqOiEnJdXTFj2oSYs+1CS1L1JR+0/zaUt1vD7mv3asTzrutjqLasqNeGC2d+N1PhUFfbzybGfj5+PUuL+qQgmx6WqcInCeRa3I+JLvvXYZehSeHi4kpOTzZY2/R+2RygW8fL1UvHyxXVo42FJ0rFtx+Xj7y0ff/Nf7ApNyun49hO6lHRJhmFof2SUKjWraI+Qnd43G1eqW/Mw+RfxkyQN6vSc/rdumZ2jyh+ahDbSqFmva9Ss1xX6dBuVqVRKv0bulCTt3rBPxQOLqnhgsRz7XU5L14cjPlH1RlXVoef9/SXQEZ1LTdTuE/v1XLMukqTHG7bX8fjTOhF/2qydRwF3+RbM+uwq7l1UIx95XpNWfprn8eZHtR6uoT5Tn1Ofqc+pyeONFFDBX3+si5IkHdx8SIX9C8s3wDfHflWbVdLBrYd1MemiDMPQnlX7VK1FlbwOH07KLhVCDw8PeXh4mAfibpdQLPbg8y209sMN2r1kjwp4uav1kFaSpPUzNyi4YbDKNQxW4YDCavhkfS178zsZhqFStYJU9eGqdo48/5n+8tvqGtJegcVK6Kd3v9SFtEuq3KeFZg3/j5ZvWa0VWyJ1LDZaY+ZP0aapS+XiYtKaPZs1+4f/2Tv0fOnpYU/qs0lfavUXP8uzoId6jngme9vCyYtUO6Sm6jSvpXXfbNDxP6OVfvmK9v7ymySpfqsHFPZcO3uFnu+8MG+M5g2M0KjOLygl7aJ6zxohSZrV720t371GK3avka+Xj9aHf65MI1OuJldNXT1f3+3hTlO2EPpiG/0wbbW2fv2r3L3c9cjQ9tnbfvggUpUaV1DlJhVVJLCIWjwTooUjFskwDJWtXVZ12tWyY+RwJibDuPMr3KZNm3bL7adPn9bkyZOVmWn5HG9T9v7H4n1gG6+9/r69Q8BfIud9bO8Q8Jd2o4bbOwRc59PwYfYOAX/pX22Q3c7d/HP7TSO26bn8VVywqCz33nvv3bZN2bJl7zoYAAAA5D2LEsJjx47ZKg4AAACLMKjEeixKCC9fvqyffvpJnTp1kpQ1OCQ9Pf2fg7m5afz48fL09LRulAAAALAZixLC+fPn67vvvstOCKdPn66aNWvKy8tLkvTnn38qMDBQw4dzrQ0AAICjsGjamYULF6pfv35m67744gutXbtWa9eu1X/+8x8tXrzYqgECAADkxpHuVDJjxgyVL19enp6eatCggTZu3HhH+23atElubm6qW7euxee0hEUJ4cGDB1Wlyj9zInl6esrF5Z9DNG7cWPv377dedAAAAA5u0aJFGjp0qEaPHq3du3erZcuW6tChg6Kjo2+5X3Jysnr16qU2bdrYPEaLEsLk5GS5uf3Ty3zu3DmVK1cu+/G1a9fMrikEAACwFUepEE6ZMkX9+/fXgAEDVL16dU2dOlVlypTRRx99dMv9XnjhBT3zzDMKCQm5l5fpjliUEJYuXVq///77Tbfv27dPpUtzT1IAAJC/paenKyUlxWzJrSh25coV7dy5U6Gh5ndmCg0N1ebNm296/Llz5+rIkSMaM2aM1WPPjUUJYceOHfXWW2/p8uXLObalpaVp3LhxeuSRR6wWHAAAwM2YTPZbIiIi5Ovra7ZERETkiDE+Pl6ZmZkKCAgwWx8QEKDY2Nhcn9ehQ4c0cuRILVy40Kxn1pYsOsuoUaP01VdfqWrVqnrppZdUpUoVmUwm/fnnn5o+fboyMjI0atQoW8UKAABwXwgPD88xq8qNt+W93o3dzIZh5Nr1nJmZqWeeeUbjxo0zG7dhaxYlhAEBAdq8ebNefPFFjRw5Un/f9c5kMqldu3aaMWNGjgwYAAAgv/Hw8LhlAvg3Pz8/ubq65qgGxsXF5ZozpaamaseOHdq9e7deeuklSVljNAzDkJubm1avXq2HH37YOk/iOhbXIcuXL69Vq1YpMTFRhw8fliRVqlRJxYoVs3pwAAAAN+MIdypxd3dXgwYNFBkZqW7dumWvj4yMVNeuXXO0L1y4sH777TezdTNmzNCaNWv09ddfq3z58jaJ8647posVK6bGjRtbMxYAAIB8Z/jw4erZs6caNmyokJAQffLJJ4qOjtagQYMkZXU/nz59WgsWLJCLi4tq1apltr+/v788PT1zrLemvLlSEQAAwNocoEIoSd27d1dCQoLGjx+vmJgY1apVSytXrlRwcLAkKSYm5rZzEtoaCSEAAICNDR48WIMHD85127x5826579ixYzV27FjrB3Udi6adAQAAQP5DhRAAADgkRxhU4iioEAIAADg5KoQAAMAhuVAgtBoqhAAAAE6OCiEAAHBIXENoPVQIAQAAnBwJIQAAgJOjyxgAADgkF7qMrYYKIQAAgJOjQggAABwSg0qshwohAACAkyMhBAAAcHJ0GQMAAIdEVct6eC0BAACcHBVCAADgkJh2xnqoEAIAADg5KoQAAMAhMe2M9VAhBAAAcHIkhAAAAE6OLmMAAOCQGFRiPVQIAQAAnBwVQgAA4JAYVGI9VAgBAACcHAkhAACAk6PLGAAAOCSqWtbDawkAAODkqBACAACHxLQz1kOFEAAAwMlRIQQAAA6JaWes575JCPtX72/vEPCXOvNq2DsE/KVdnxfsHQL+8trYZ+0dAq4zYMo0e4eAv/T/ZJC9Q4AV0GUMAADg5O6bCiEAAIAlGFRiPVQIAQAAnBwVQgAA4JCoD1oPFUIAAAAnR0IIAADg5OgyBgAADolBJdZDhRAAAMDJUSEEAAAOiQqh9VAhBAAAcHIkhAAAAE6OLmMAAOCQTHQZWw0VQgAAACdHhRAAADgkBpVYDxVCAAAAJ0eFEAAAOCTqg9ZDhRAAAMDJkRACAAA4ObqMAQCAQ2JQifVQIQQAAHByVAgBAIBDokJoPVQIAQAAnBwJIQAAgJOjyxgAADgk7mVsPVQIAQAAnBwVQgAA4JAYVGI9VAgBAACcHBVCAADgkKgPWg8VQgAAACdHQggAAODk6DIGAAAOiUEl1kOFEAAAwMmREAIAAIfkYjLZbbHUjBkzVL58eXl6eqpBgwbauHHjTdt+++23ateunUqUKKHChQsrJCREP/744728VLdFQggAAGBDixYt0tChQzV69Gjt3r1bLVu2VIcOHRQdHZ1r+w0bNqhdu3ZauXKldu7cqdatW6tz587avXu3zWIkIQQAALChKVOmqH///howYICqV6+uqVOnqkyZMvroo49ybT916lT961//UqNGjVS5cmW98847qly5slasWGGzGBlUAgAAHJI972Wcnp6u9PR0s3UeHh7y8PAwW3flyhXt3LlTI0eONFsfGhqqzZs339G5rl27ptTUVBUrVuzegr4FKoQAAAAWioiIkK+vr9kSERGRo118fLwyMzMVEBBgtj4gIECxsbF3dK7//ve/unjxop566imrxJ6be6oQxsfHy2QyqXjx4taKBwAA4I7Ys6oVHh6u4cOHm627sTp4vRurmYZh3FGF88svv9TYsWO1bNky+fv7312wd8Di1zIpKUlDhgyRn5+fAgIC5O/vLz8/P7300ktKSkqyQYgAAAD3Fw8PDxUuXNhsyS0h9PPzk6ura45qYFxcXI6q4Y0WLVqk/v3766uvvlLbtm2tGv+NLKoQJiYmKiQkRKdPn9azzz6r6tWryzAMRUVFad68efr555+1efNmFS1a1FbxAgAASLLvNYR3yt3dXQ0aNFBkZKS6deuWvT4yMlJdu3a96X5ffvml+vXrpy+//FKPPPKIzeO0KCEcP3683N3ddeTIkRxZ7fjx4xUaGqrx48frvffes2qQAAAAjmr48OHq2bOnGjZsqJCQEH3yySeKjo7WoEGDJGV1P58+fVoLFiyQlJUM9urVS++//76aNm2aXV308vKSr6+vTWK0qMt46dKlmjx5cq4lzsDAQE2aNElLliyxWnAAAACOrnv37po6darGjx+vunXrasOGDVq5cqWCg4MlSTExMWZzEn788cfKyMjQkCFDFBQUlL28+uqrNovRogphTEyMatasedPttWrVuuMRMwAAAPfCke5lPHjwYA0ePDjXbfPmzTN7vG7dOtsHdAOLKoR+fn46fvz4TbcfO3aMEccAAAAOxqIKYVhYmEaPHq3IyEi5u7ubbUtPT9ebb76psLAwqwZ4P4o+cVLjRo9XUlKyfHy89dbbb6pCxfK5tj188LAmR0xRYkKirhmGhrz6olq3fShvA87H4k6d04L/+1IXUy7Kq5Cneo54WkHlAnO0O7DrkJZ9+r3S09JlMplUp3ktde7XwSEuSHYE7w8ery4h7VQusIxqDWyjP44fyLVdv7AeGtljiFxMJv28e5MGTxulzGuZeRxt/nfh7AXt+XSXrlxIV4GCBVS3X335lCps1iY+6pyivt6vjMsZMrlIAXWDVO2x6vxOWFkl/2DN7/uO/LyLKulSivrMG62omCM52k16/HV1rP2gMq9lKuFikgYuGKMj53K/rRn+4UgVwvudRQnhuHHj1LBhQ1WuXFlDhgxRtWrVJEn79+/XjBkzlJ6ers8++8wmgd5PIsa/q25PPKpOjz6in1ev0dtvvaM5C2flaHc57bLeeHWkxkx8U3XrP6CMjAylpqTaIeL868spi9W8U1OFhDXWrvV7tXDyIr0+Pec1FgV9vNTv3z3lV7K4rl65qmmvz9SONbvUqE0DO0Sd/3y98XtN+uoj/fLetzdtUy6wjCb0eV31BoUpLiley8bPUf8OPfTJ9wvzMFLnsG/+HgW3ClaZFsE6s+O09s7brRajW5m1KVCwgOq/0FCF/Asp82qmtvxnk05vO6XSTcvYKer86ePnxuiTDYs1f8tSPV4/VLN7TVCzd58xa9PlgYf1YJWGqjvhMWVkZmh0xxf0Treh6v7J8JscFbA+i7qMS5curS1btqhGjRoKDw/Xo48+qkcffVSjR49WjRo1tGnTJpUpk78/TBITEnUg6oDCOrWXJD3crrXOnD6jM6djcrRdtXK1aj9QS3XrPyBJcnNzU9FiTMljLannU3Xy0Ck1bpeV1NV7sI7iYxKVEJuYo22ZyqXlVzLrcoYC7gVUumJJxZ/J2Q53Z+Nv23Q6PufvwPWeaPmIlmxapbikeEnSzO8+19OtH82D6JxLekq6kk8kqVRI1mdxUIOSunTuki7FXzRr5xtcRIX8C0mSXAu4yresry6du5Tn8eZnJXyKqX7ZGvp8W9b9Z7/ZtVrl/UoruHjJHG093Nzl6ZbV81bYy1unznM9PvKWxXcqKV++vH744QedP39ehw4dkiRVqlTJpvfXu5+cjY1TiRJ+cnPLeulMJpMCgwIUGxOrkqWCzNoeO3JM7h7uGjbkNcWdPadKVSpq6OuvkBRayflzSfL185Wrq6ukrPeimH8RJZ49r+KBN/95TE5M0e4N+zQ4YmBehQpJZf1L6cTZ09mPj8eeVFn/nH8YcW/SEtPkWcRLLq5Z3/dNJpO8inspLSFNBf0K5brP5eTLitlxRo2HheRlqPlemaKBOpN0zuyyiOjEMypbLEgnEs5kr1uxb60eqtpIsZM3KPXyJZ1OOqtWk3vbI2SHwyUO1nPXd30pWrSoGjdurMaNGys1NVX79+/XtWvX7mjf9PR0paSkmC033iD6vpbj9jO5N8vIyNDWTdsU/tYIfb54vgICAzRp4uQ8CNB53eStyJZ28bJmjp6tdj1aq2yV0nkSE/5hXPfLwge5Dd3w0t7sM0qSrqZd1a/vb1XFDpVVJLiITcNyRsYNn0q5/dzXL1tD1QIrqNS/Wqvkv1rp5z+3avrTo/MqRECShQnh/PnzNXXqVLN1zz//vCpUqKDatWurVq1aOnny5G2Pk9sNoadMmnrb/ezl++Ur9ewTvfTsE73069btijsbp4yMDElZf+DOxp5VYFDOgQxBJQPVoHF9+Qf4y2QyKeyR9tr/+/68Dj9f2bZ6u94ZOFnvDJysP3ceVFJ8sjIzs759G4ah83FJKhaQewX28qXL+nDEJ6rTrKbaPPlQHkYNSYqOO61ygf8k4cEBpRUdd+YWe+BueBXz0uXzabqWmfUF3TAMXU5Mk1dxrxxtM9KuatuULQqsG6iK7Svldaj53snzsSpdNECuLq7Z68oUDVJ0ovnlFX2aPaq1B7YpOS1VhmFo/uZlal21SV6H65BcZLLbkt9YlBDOnDnTbIbsVatWae7cuVqwYIG2b9+uIkWKaNy4cbc9Tnh4uJKTk82W4f8aanHweeWRLh218OsFWvj1AvXu31NVq1XRqu9+lCStiVyrkqWCcnQXS1Lb9m0U9XuULlzIunZnyy9bVblK5TyNPb9pEtpIo2a9rlGzXlfo021UplIp/Rq5U5K0e8M+FQ8smmt38eW0dH044hNVb1RVHXqG5nXYkPTNxpXq1jxM/kX8JEmDOj2n/61bZueo8h+Pwh7yLeur01uyvpzH7DwjL7+CObqLMy5naOt7W1Silr+qdKlmj1DzvXOpidodHaXnmnSWJD1eP1THE06bdRdL0tFzp9SmWlO5uWZditT5gYf0+5lDeR4vnJtF1xAePHhQDRs2zH68bNkydenSRc8++6wk6Z133lHfvn1vexwPD48cN4A2rmRYEopdhb81QuP+/bbmfjpfhQoV0piJb2Zve3vMO3rwoZZ6sHVLBQYFqveAXur/3EC5urrK37+EwseMtGPk+c/Tw57UZ5O+1OovfpZnQQ/1HPHP6L2FkxepdkhN1WleS+u+2aDjf0Yr/fIV7f3lN0lS/VYPKOy5dvYKPV+Z/vLb6hrSXoHFSuind7/UhbRLqtynhWYN/4+Wb1mtFVsidSw2WmPmT9GmqUvl4mLSmj2bNfuH/9k79HypTq+62jNnlw59f1BungVUb0B9SdLeubsVUDdQgfWCdDTyiJKOnVdmeoZid2UlKEENS6lK56r2DD3feeHzsZrX5x2N6vi8UtIuqPfcUZKkWT3Ha/m+tVqxd60+XPeFqgdV0G9jlupKxlXFJJ/TC5+PtW/gDoJLT6zHZBi3urrEXMGCBRUVFZV9q5UHHnhA/fr1y76VSnR0tKpWraq0tDSLA0m+wojP+8X2c1vsHQL+0q7PC/YOAX95beyz9g4B1/nv/BX2DgF/MT6x36VQIzaH2+3c7zaLsNu5bcGiLuPg4GDt3JnVPRcfH68//vhDLVq0yN4eGxtrs5suAwAAwDYs6jLu1auXhgwZoj/++ENr1qxRtWrV1KDBPxP7bt68WbVq1bJ6kAAAADfiTiXWY1FCOGLECF26dEnffvutAgMDtXjxYrPtmzZt0tNPP23VAAEAAGBbFiWELi4umjBhgiZMmJDr9hsTRAAAAFsx5cPpX+zFomsIXVxc5OrqmmMpWrSomjZtqm+/vfl9TAEAAHB/sqhCuGTJklzXJyUl6ddff9Vzzz2n+fPn68knn7RKcAAAALA9ixLCrl273nRb7969VaNGDU2ePJmEEAAA2BzzEFrPXd/LODehoaE6ePCgNQ8JAAAAG7OoQng7aWlp8vT0tOYhAQAAcsW0M9Zj1QrhrFmzVK9ePWseEgAAADZmUYVw+PDhua5PTk7Wjh07dOTIEW3cuNEqgQEAANyKybp1LadmUUK4e/fuXNcXLlxYYWFhGjx4cPZ9jgEAAOAYLEoI165da6s4AAAAYCdWHVQCAACQVxhUYj10vgMAADg5KoQAAMAhMTG19VAhBAAAcHIkhAAAAE6OLmMAAOCQTKLL2FqoEAIAADg5KoQAAMAhMe2M9VAhBAAAcHJUCAEAgENi2hnroUIIAADg5EgIAQAAnBxdxgAAwCG5UNeyGl5JAAAAJ0eFEAAAOCQGlVgPFUIAAAAnR0IIAADg5OgyBgAADokuY+uhQggAAODkqBACAACH5CIqhNZChRAAAMDJUSEEAAAOiWsIrYcKIQAAgJMjIQQAAHBydBkDAACH5EKXsdVQIQQAAHByVAgBAIBDMjHtjNVQIQQAAHByJIQAAABOji5jAADgkFxM1LWshVcSAADAyVEhBAAADok7lVgPFUIAAAAnd99UCA8lR9k7BPyl3ajh9g4Bf3lt7LP2DgF/+e/YhfYOAdfp/HKYvUMA8pX7JiEEAACwBPMQWg9dxgAAAE6OCiEAAHBI3MvYeqgQAgAAODkqhAAAwCFxDaH1UCEEAACwsRkzZqh8+fLy9PRUgwYNtHHjxlu2X79+vRo0aCBPT09VqFBBM2fOtGl8JIQAAAA2tGjRIg0dOlSjR4/W7t271bJlS3Xo0EHR0dG5tj927Jg6duyoli1bavfu3Ro1apReeeUVffPNNzaLkYQQAAA4JBeTyW6LJaZMmaL+/ftrwIABql69uqZOnaoyZcroo48+yrX9zJkzVbZsWU2dOlXVq1fXgAED1K9fP02ePNkaL1uuSAgBAAAslJ6erpSUFLMlPT09R7srV65o586dCg0NNVsfGhqqzZs353rsLVu25Gjfvn177dixQ1evXrXek7gOCSEAAHBIJpOL3ZaIiAj5+vqaLRERETlijI+PV2ZmpgICAszWBwQEKDY2NtfnFRsbm2v7jIwMxcfHW+8FvA6jjAEAACwUHh6u4cPNb/Xq4eFx0/amG7qZDcPIse527XNbby0khAAAABby8PC4ZQL4Nz8/P7m6uuaoBsbFxeWoAv4tMDAw1/Zubm4qXrz43Qd9C3QZAwAAh2Sy47875e7urgYNGigyMtJsfWRkpJo1a5brPiEhITnar169Wg0bNlSBAgUsf6HuAAkhAACADQ0fPlyffvqp5syZo6ioKA0bNkzR0dEaNGiQpKzu5169emW3HzRokE6cOKHhw4crKipKc+bM0ezZs/X666/bLEa6jAEAgENylHsZd+/eXQkJCRo/frxiYmJUq1YtrVy5UsHBwZKkmJgYszkJy5cvr5UrV2rYsGH68MMPVbJkSU2bNk2PP/64zWIkIQQAALCxwYMHa/DgwblumzdvXo51rVq10q5du2wc1T9ICAEAgEOy1YhbZ8Q1hAAAAE6OhBAAAMDJ0WUMAAAckosF07/g1qgQAgAAODkqhAAAwCExqMR6qBACAAA4ORJCAAAAJ0eXMQAAcEgmE3Uta+GVBAAAcHJUCAEAgENi2hnroUIIAADg5KgQAgAAh8S0M9ZDhRAAAMDJkRACAAA4ObqMAQCAQzIxqMRqqBACAAA4OSqEAADAITGoxHqoEAIAADg5EkIAAAAnR5cxAABwSNypxHqoEAIAADg5ixLCPXv22CgMAAAAy5hMLnZb8huLnlH9+vXVoEEDffTRR0pOTrZVTAAAAMhDFiWEmzZtUv369TVy5EgFBQXpueee09q1a20VGwAAwE2Z7Pgvv7EoIQwJCdGsWbMUGxurjz76SKdOnVLbtm1VsWJFTZw4UadOnbJVnAAAALCRu+oE9/LyUu/evbVu3TodPHhQTz/9tD7++GOVL19eHTt2tHaMAAAAsKF7nnamYsWKGjlypMqUKaNRo0bpxx9/tEZcAAAAt8SdSqznnhLC9evXa86cOfrmm2/k6uqqp556Sv3797dWbPet2JNnNXPip0pNuqCCPgX1wqh+Kl2+VI52h34/rDmTP5MkZWZkqmqdyuo19BkVcC+Q1yHnS5UCgjV/4P/Jz6eoki6lqs+skYo6c8Ssjclk0qTubyisdku5ubhp06FdenH+WF3NvGqnqPOvC2cvaM+nu3TlQroKFCyguv3qy6dUYbM28VHnFPX1fmVczpDJRQqoG6Rqj1XnQ92K3h88Xl1C2qlcYBnVGthGfxw/kGu7fmE9NLLHELmYTPp59yYNnjZKmdcy8zja/C+okL+G1uunwu7eung1Te/vnqOTF2LM2lQtWkEv1nlOkuRmctX+xMP65PcvlXEtwx4hw0lZ3GV88uRJTZgwQRUrVlTr1q115MgRffDBBzpz5oxmzZqlpk2b2iLO+8rs/8xX6y6t9N//RajTMx006//m5dqubKUymvDpm4qYN07/t2C8UpJS9fOydXkaa372cZ/x+mTdV6o6IkyTvv9Us/tPzNGm/4NPqE6Zqqr/1mOqHt5BkvRqaK+8DtUp7Ju/R8GtgvVwRDtV7FBZe+ftztGmQMECqv9CQ7We2EYt33pICQfidXob1x5b09cbv1eLYY/peOzJm7YpF1hGE/q8rhZDu6lS7xYKLFZC/Tv0yMMonceQOj3144kNenHNv/Xt4VV6uW6fHG2OpZzSaxsmauj68Xp53Vj5evgoLLhV3gfrgBhUYj0WJYTt2rVT+fLlNWPGDD3xxBOKiorSL7/8or59+6pQoUI6f/68FixYYKtY7wvJ51N0/OAJtQgNkSQ1fqiBzsWc07mY+BxtPTw95OaWVYTNuJqpK+lX5OKS/+YusocSPsVUP7iGPt+8XJL0zY4fVd6vtIL9zCu1D5Stpp/+2JJdEVy5b716Nu+a5/Hmd+kp6Uo+kaRSIWUkSUENSurSuUu6FH/RrJ1vcBEV8i8kSXIt4Crfsr66dO5Snsebn238bZtOx8fcss0TLR/Rkk2rFJeU9bk187vP9XTrR/MgOufi6+6jCkWCte7UVknS5pidCijoJ3+v4mbtrmReUaaRVZ11c3GVu0sBGca1PI8Xzs2i7MTLy0vffPONTp06pXfffVdVq1Y12x4dHa2+ffve9jjp6elKSUkxW66kX7EscjtJPJuoIn5F5OrmKimrS7J4QHHFn03Itf25mHiF9xmjQZ1ekVchLz3chW991lCmeJDOJMWZdXFFJ8aobPEgs3bbj/6mrvXbyNuzkAq4FlCPJo+onF/O7n3cm7TENHkW8ZKLa9ZHislkkldxL6UlpN10n8vJlxWz44z86wTkVZj4S1n/Ujpx9nT24+OxJ1XWv6QdI8qf/LyKKfFykq5dl9ydS0tUCa9iOdr6exXX1FZv6fOwqbqUcVk/ntiQl6ECliWEy5cvV9euXeXq6npPJ42IiJCvr6/ZMu/9z+7pmHkpR6nYMG7atkSQnyLmjdOMZe8p42qGtq/faePonIch89c9txL+gk1L9eNvv2jDqM+1ZuR8/XH6ENcP2sqd/1roatpV/fr+VlXsUFlFgovYNCzkzrjuDeIaThsybvycyl1cWoKGrh+v3j++pgIubgoJqm/72PIBk8lktyW/uedRxncjPDxcw4cPN1v3e8r9myht/GGTVi5aLUlq1raJEs+dV2ZGplzdXGUYhhLiEuUXUPyWx/As6KmQNo21afVWhbRtkhdh52snE2JUumigXF1cs6uEZYoFKjohZ1fZhGUfasKyDyVJ3Zt01P7TR3K0wb3xKualy+fTdC3zmlxcXWQYhi4npsmruFeOthlpV7VtyhYF1g1UxfaV7BAtouNOq1xg6ezHwQGlFR13xo4R5U/xaYkq7lVULiaX7Cqhn1cxnUtLvOk+lzPTtfH0r2pVuqk2ntmeV6ECdzcP4b3y8PBQ4cKFzRZ3D3d7hHJHWnZoroh54xQxb5w6P9dR5SqX1S+rt0iSfl23U36BfioR5Jdjv7On45SRkTVK7O/qYNmKpXO0g+XOpSZq94n9eq5ZF0nS4w3b63j8aZ2IP23WzqOAu3wL+kiSinsX1chHnteklZ/mebz5nUdhD/mW9dXpLVkDGWJ2npGXX0EV9Ctk1i7jcoa2vrdFJWr5q0qXavYIFZK+2bhS3ZqHyb9I1ufWoE7P6X/rltk5qvwn+Uqqjiaf1EOlswZbNgtqoLhL8YpLM7/EKLBgCbmasnre3EyuCgmqr+MpDLa6Ey4y2W3JbyyqEE6bNu2W20+fPn3L7flFv3/10scT52j5gu/lVchTg0YPyN426//mqn6LumrQop6idv+pHxZFysXFpMzMa6rZoLoe7dPFjpHnLy/MG6N5AyM0qvMLSkm7qN6zRkiSZvV7W8t3r9GK3Wvk6+Wj9eGfK9PIlKvJVVNXz9d3e7jdoi3U6VVXe+bs0qHvD8rNs4DqDcjq8to7d7cC6gYqsF6QjkYeUdKx88pMz1DsrqyKVFDDUqrSueqtDg0LTH/5bXUNaa/AYiX007tf6kLaJVXu00Kzhv9Hy7es1ootkToWG60x86do09SlcnExac2ezZr9w//sHXq+NGPvAr1ar5+erNxRlzIua+ruOZKklx7orV9j9+jXs3tV26+qulRop2vGNbmaXLQv/k8tOrjCzpHD2ZgM41ZX+pgrX778HbU7duyYxYHsOLfJ4n1gG41e72fvEPCX155/1N4h4C//HbvQ3iHgOp1fDrN3CPjL8i7263VZenyR3c79aLnudju3LVhUIbybRA8AAAD3N4uuIdy2bZt++OEHs3ULFixQ+fLl5e/vr+eff17p6elWDRAAAAC2ZVFCOGbMGO3bty/78W+//ab+/furbdu2GjlypFasWKGIiAirBwkAAHAj+w0pyX83mbDoGe3du1dt2rTJfvy///1PTZo00axZszR8+HBNmzZNX331ldWDBAAAgO1YdA3h+fPnFRDwz10F1q9fr7Cwfy7sbdSokU6evPn9MwEAAKwlP04QbS8WVQgDAgKyB5ZcuXJFu3btUkhISPb21NRUFShQwLoRAgAAwKYsSgjDwsI0cuRIbdy4UeHh4SpYsKBatmyZvX3fvn2qWLGi1YMEAACA7VjUZfz222/rscceU6tWreTt7a358+fL3f2fO4zMmTNHoaGhVg8SAADgRrndwx53x6KEsESJEtq4caOSk5Pl7e0tV1dXs+2LFy+Wt7e3VQMEAACAbVmUEP7N19c31/XFihW7p2AAAADulAuDSqwm/02kAwAAAIvcVYUQAADA3riG0HqoEAIAADg5EkIAAAAnR5cxAABwSNypxHqoEAIAADg5KoQAAMAhmahrWQ2vJAAAgJMjIQQAAHBydBkDAACHxKAS66FCCAAA4OSoEAIAAIfkwp1KrIYKIQAAgJMjIQQAAHBydBkDAACHxKAS66FCCAAA4ORICAEAgEMy2fGfrZw/f149e/aUr6+vfH191bNnTyUlJd20/dWrVzVixAjVrl1bhQoVUsmSJdWrVy+dOXPGovOSEAIAANwnnnnmGe3Zs0erVq3SqlWrtGfPHvXs2fOm7S9duqRdu3bpzTff1K5du/Ttt9/q4MGD6tKli0Xn5RpCAADgkPLbNYRRUVFatWqVtm7dqiZNmkiSZs2apZCQEB04cEBVq1bNsY+vr68iIyPN1n3wwQdq3LixoqOjVbZs2Ts6NwkhAACAhdLT05Wenm62zsPDQx4eHnd9zC1btsjX1zc7GZSkpk2bytfXV5s3b841IcxNcnKyTCaTihQpcsfnpssYAADAQhEREdnX+f29RERE3NMxY2Nj5e/vn2O9v7+/YmNj7+gYly9f1siRI/XMM8+ocOHCd3xuEkIAAOCQTHKx2xIeHq7k5GSzJTw8PNc4x44dK5PJdMtlx44dWc8pl25wwzDuqHv86tWr6tGjh65du6YZM2ZY9FrSZQwAAGAhS7qHX3rpJfXo0eOWbcqVK6d9+/bp7NmzObadO3dOAQEBt9z/6tWreuqpp3Ts2DGtWbPGouqgREIIAAAclIuDDCrx8/OTn5/fbduFhIQoOTlZv/76qxo3bixJ2rZtm5KTk9WsWbOb7vd3Mnjo0CGtXbtWxYsXtzhGuowBAADuA9WrV1dYWJgGDhyorVu3auvWrRo4cKA6depkNqCkWrVqWrJkiSQpIyNDTzzxhHbs2KGFCxcqMzNTsbGxio2N1ZUrV+743CSEAAAA94mFCxeqdu3aCg0NVWhoqOrUqaPPPvvMrM2BAweUnJwsSTp16pSWL1+uU6dOqW7dugoKCspeNm/efMfnpcsYAAA4JFveMcReihUrps8///yWbQzDyP5/uXLlzB7fLSqEAAAATo4KIQAAcEj57U4l9kSFEAAAwMlRIQQAAA4pP15DaC9UCAEAAJwcCSEAAICTo8sYAAA4JAaVWA8VQgAAACd331QIaxWrZ+8Q8JdPw4fZOwT8ZcCUafYOAX/p/HKYvUPAdVZ8sMreIeBvXex3ahfqWlbDKwkAAODkSAgBAACc3H3TZQwAAGAJBpVYDxVCAAAAJ0eFEAAAOCTuVGI9VAgBAACcHBVCAADgkLiG0HqoEAIAADg5EkIAAAAnR5cxAABwSAwqsR4qhAAAAE6OCiEAAHBIVAithwohAACAkyMhBAAAcHJ0GQMAAMfEPIRWQ4UQAADAyVEhBAAADolBJdZDhRAAAMDJUSEEAAAOiXsZWw8VQgAAACd3TxXC+Ph4HT9+XCaTSeXKlVPx4sWtFRcAAADyyF1VCP/44w89+OCDCggIUJMmTdS4cWP5+/vr4Ycf1oEDB6wdIwAAQA4mO/7LbyyuEMbGxqpVq1YqUaKEpkyZomrVqskwDO3fv1+zZs1Sy5Yt9fvvv8vf398W8QIAAMDKLE4I33vvPQUHB2vTpk3y9PTMXh8WFqYXX3xRLVq00HvvvaeIiAirBgoAAHC9/FipsxeLu4wjIyM1YsQIs2Twb15eXnrjjTf0448/WiU4AAAA2J7FCeHRo0dVv379m25v2LChjh49ek9BAQAAIO9Y3GWcmpqqwoUL33S7j4+PLly4cE9BAQAA3A7zEFrPXU07k5qammuXsSSlpKTIMIx7CgoAAAB5x+KE0DAMValS5ZbbydgBAICtMajEeixOCNeuXWuLOAAAAGAnFieErVq1skUcAAAAFqFCaD0WJ4TXrl3TtWvX5Ob2z65nz57VzJkzdfHiRXXp0kUtWrSwapAAAACwHYsTwv79+6tAgQL65JNPJGUNMGnUqJEuX76soKAgvffee1q2bJk6duxo9WABAABgfRbPQ7hp0yY98cQT2Y8XLFigjIwMHTp0SHv37tXw4cP1n//8x6pBAgAA3MhkMtltyW8sTghPnz6typUrZz/++eef9fjjj8vX11eS1Lt3b/3xxx/WixAAAAA2ZXFC6OnpqbS0tOzHW7duVdOmTc22MzE1AACwNZMd/+U3FieEDzzwgD777DNJ0saNG3X27Fk9/PDD2duPHDmikiVLWi9CAAAA2JTFg0refPNNdezYUV999ZViYmLUp08fBQUFZW9fsmSJmjdvbtUgAQAAYDsWJ4StW7fWjh079NNPPykwMFBPPvmk2fa6deuqcePGVgsQAAAgN/lxcIe93NW9jGvWrKmaNWvmuu3555+/p4AAAACQtyxOCBcsWJDrel9fX1WtWlXVqlW756AAAABuJz8O7rAXixPCV199Ndf1Fy5c0LVr19SxY0d98cUX8vHxuefgAAAAYHsWjzI+f/58rkt6erq2bt2q6OhojRs3zhaxAgAAwAYsTghveiAXFzVq1Ej//e9/tWLFCmsdFgAAIFfMQ2g9dzWo5FYqVaqkU6dOWfuw95UTx0/ozVFv6fz5JPkU9tGEieNUsVLFHO1WLFuhz+Z9nv347Nk41W9YX+9N+29ehpuvJZ45r5VTf1Raapo8Cnmo4yvt5Ve2eK5t90X+rq3fbJcMQ2XrlFHooDZycbXadyKnV8k/WPP7viM/76JKupSiPvNGKyrmSI52kx5/XR1rP6jMa5lKuJikgQvG6Mi5aDtEnH8FFfLX0Hr9VNjdWxevpun93XN08kKMWZuqRSvoxTrPSZLcTK7an3hYn/z+pTKuZdgj5Hzp/cHj1SWkncoFllGtgW30x/EDubbrF9ZDI3sMkYvJpJ93b9LgaaOUeS0zj6OFs7P6X8MjR46odOnS1j7sfWXCuIl6/MnHteKHZerbr7fGvpl7F3nnrp311ZJF2YtfCT890qlDHkebv62e8bMeaF9bAz/qqybdGmrV9Mhc2yWdTdbGhZv17P89pYEz++ri+UvaF/l7Hkebv3383Bh9smGxqr7ZUZN+nKPZvSbkaNPlgYf1YJWGqjvhMT0wvpt+jtqqd7oNzftg87khdXrqxxMb9OKaf+vbw6v0ct0+OdocSzml1zZM1ND14/XyurHy9fBRWHCrvA82H/t64/dqMewxHY89edM25QLLaEKf19ViaDdV6t1CgcVKqH+HHnkYpWPjXsbWY7WE0DAM7dq1S6+99po6d+5srcPedxISEvXn/ig90rmjJKltaFudPnVGp0+fueV+v+37XQkJCWrVmg9ca7mYdElnj8ap5kPVJUlVmlVW8tlkJZ9NztH2wKZDqtK0kgoVKSSTyaS6YXUUtTH3b+uwXAmfYqpftoY+35Z1ucg3u1arvF9pBRfPedciDzd3ebq5S5IKe3nr1PnYPI01v/N191GFIsFad2qrJGlzzE4FFPSTv5d55fxK5hVlGllVKDcXV7m7FJBhXMvzePOzjb9t0+n4mFu2eaLlI1qyaZXikuIlSTO/+1xPt340D6IDzFncZVy0aNFcM+MLFy4oMzNTYWFhGjt27C2PkZ6ervT0dLN1hlumPDw8LA0nz52NjVWJEiXk5pb10plMJgWWDFRsTIxKlbr5LfuWfLNUnTo/ogIFCuRVqPleanyqvIsWyu72NZlM8inho5T4VPkG+OZoW9j/n5Hvvv6FlXIuJU/jzc/KFA3UmaRzZt1c0YlnVLZYkE4k/PNlacW+tXqoaiPFTt6g1MuXdDrprFpN7m2PkPMtP69iSrycpGvXJXfn0hJVwquY4tISzNr6exXXqMZDFFTIXzvO/qYfT2zI63CdXln/Ujpx9nT24+OxJ1XWn9u/3qn8eC2fvVicEE6dOjXX9YULF1a1atVUvXr12x4jIiIix0jk0W+O0r/HjLY0HPu4MSE2jFs2T0tL0+pVP2r+wnm2i8lZ3fhZcMu34vrGt37PYDnjhtc0ty+O9cvWULXACir1r9ZKuXxB//fYcE1/erT6znOQ331HccNn0s3+ZMalJWjo+vHydPXQ8PoDFBJUXxvPbLd9fDBjXPd+5ceuSDgGixPCoKAgtW7d+p4qXeHh4Ro+fLjZOsPt/r2A9vrBIWGPhCnubJwyMjLk5uYmwzAUG3NWgdfdz/lGP63+SeUrlM914Aks8/ua/dqxfJckqXrLqkpNuKBrmdfk4uoiwzCyKoF+OefA9PHzUUrcPxXB5LhUFS5ROM/izu9Ono9V6aIBcnVxza4SlikapOhE8+6yPs0e1doD25SclipJmr95mVa+MjPP483P4tMSVdyrqFxMLtlVQj+vYjqXlnjTfS5npmvj6V/VqnRTEsI8Fh13WuUC/7nuPjigtKLjbn0JEmALFl9DOGjQIJUoUULdu3fXF198oaSkJItP6uHhocKFC5st93N38fWDQ/oN6Ktq1avq+xUrJWUleyVLlbxld/HSb5ep2+OP5lG0+Vuth2uoz9Tn1Gfqc2ryeCMFVPDXH+uiJEkHNx9SYf/CObqLJalqs0o6uPWwLiZdlGEY2rNqn6q1qJLX4edb51ITtTs6Ss81ybp++PH6oTqecNqsu1iSjp47pTbVmsrNNeu7aOcHHtLvZw7lebz5WfKVVB1NPqmHSjeVJDULaqC4S/E5uosDC5aQq8lVUtYo45Cg+jqekr9niLgffbNxpbo1D5N/ET9J0qBOz+l/65bZOSrHwbQz1mMyjNv0d+Zi3759Wr58uZYvX659+/apefPm6tq1q7p06aJy5crdVSCXMy/d1X72cPzYcb056i0lJSXL27uQJrwzQZUqZ1X/xr45Tg+1bqWHHn5IknQy+qSeeqyHflq/WoUKFbJj1Hdu4aHcb094P0o4lagfpq1WWmqa3L3c9cjQ9vIrm/XB+sMHkarUuIIqN8l6b/au/k3bvtkuwzBUtnZZhb74sFzdXO0Z/m0NmDLN3iHcsSoB5TSvzzsq7l1EKWkX1HvuKO2POaxZPcdr+b61WrF3rdzdCmj60/9Wy8oNdCXjqmKSz+mFz8fmSBzvR507NbN3CHesVKEAvVqvn3zcC+lSxmVN3T1HJ1PP6KUHeuvX2D369exetSvbQl0qtNM145pcTS7aF/+n5u5frKsOMu3Mig9W2TuE25r+8tvqGtJegcVKKD45URfSLqlynxaaNfw/Wr5ltVZsyZoVYUCHZzSi+2C5uJi0Zs9mvfh+uDIyHeN9kCQj0n5fJA4l/2G3c1f2rWm3c9vCXSWE1ztz5kx2crh27VpVqVIlOzls2LDhHR/HkRLC/M6REsL8zpESwvzOkRJCZ+AICaGzsGdCeDhlv93OXalwDbud2xbuedqZkiVLatCgQVq5cqXi4+P15ptv6vjx4woLC9M777xjjRgBAABgQ1admLpQoUJ64oknFBERobi4OA0cONCahwcAAMjXzp8/r549e8rX11e+vr7q2bOnReM1XnjhBZlMppvOCnMzVk0IY2Nj9fLLL6tSpUpycXFRiRIlrHl4AACA65jsuNjGM888oz179mjVqlVatWqV9uzZo549e97RvkuXLtW2bdtUsqTlc1lanBAmJSXp2WefVYkSJVSyZElNmzZN165d01tvvaUKFSpo69atmjNnjsWBAAAAOLOoqCitWrVKn376qUJCQhQSEqJZs2bpu+++04EDt7671unTp/XSSy9p4cKFdzU1oMXzEI4aNUobNmxQ7969tWrVKg0bNkyrVq3S5cuX9cMPP6hVK27NBgAAbM+eE3nndtc1Dw+Pe5pGb8uWLfL19VWTJk2y1zVt2lS+vr7avHmzqlatmut+165dU8+ePfXGG2+oZs27G/1scYXw+++/19y5czV58mQtX75chmGoSpUqWrNmDckgAABwChEREdnX+f29RERE3NMxY2Nj5e/vn2O9v7+/YmNvft/3d999V25ubnrllVfu+twWVwjPnDmjGjWyhlpXqFBBnp6eGjBgwF0HAAAAcDfsOUF0bnddu1l1cOzYsTlu2Xuj7duz7hKUW9XTMIybVkN37typ999/X7t27bqniqnFCeG1a9fM+qZdXV0dZsJlAAAAa7Cke/ill15Sjx49btmmXLly2rdvn86ePZtj27lz5xQQEJDrfhs3blRcXJzKli2bvS4zM1Ovvfaapk6dquPHj99RjBYnhIZhqE+fPtkvwuXLlzVo0KAcSeG3335r6aEBAADyHT8/P/n5+d22XUhIiJKTk/Xrr7+qcePGkqRt27YpOTlZzZrlPjl+z5491bZtW7N17du3V8+ePdW3b987jtHihLB3795mj5977jlLDwEAAHDP8ts9hatXr66wsDANHDhQH3/8sSTp+eefV6dOncwGlFSrVk0RERHq1q2bihcvruLFi5sdp0CBAgoMDLzpIJTcWJwQzp0719JdAAAAcAcWLlyoV155RaGhoZKkLl26aPr06WZtDhw4oOTkZKue1+KEEAAA4H5gz2lnbKVYsWL6/PPPb9nGMIxbbr/T6wavZ3FC2Lp161zfAF9fX1WtWlVDhgxRmTJlLA4EAAAA9mFxQli3bt1c1yclJWnlypWaPn26fvnll5u2AwAAwP3F4oTwvffeu+X2IUOGaNSoUVq5cuVdBwUAAHA7+W1QiT1ZfKeS23nhhRe0e/duax8WAAAANmL1QSVeXl66fPmytQ8LAABghgqh9Vi9Qrh69WpVqVLF2ocFAACAjVhcIVy+fHmu65OTk7V9+3bNnj1b8+bNu9e4AAAAbik/TjtjLxYnhI8++miu6318fFStWjXNmzdPTz755L3GBQAAgDxicUJ47do1W8QBAAAAO7H4GsKOHTua3S5l4sSJSkpKyn6ckJCgGjVqWCU4AACAmzHZ8V9+Y3FCuGrVKqWnp2c/fvfdd5WYmJj9OCMjQwcOHLBOdAAAALC5e5525nb30wMAALAFBpVYj9WnnQEAAIBjsTghNJlMOTJyMnQAAADHZXGXsWEY6tOnjzw8PCRJly9f1qBBg1SoUCFJMru+EAAAwFby4+AOe7E4Iezdu7fZ4+eeey5Hm169et19RAAAAMhTFieEc+fOtUUcAAAAFqJCaC0MKgEAAHBy9zztDAAAgD1QH7QeKoQAAABOjoQQAADAydFlDAAAHBLzIFsPFUIAAAAnR4UQAAA4KCqE1kKFEAAAwMmREAIAADg5uowBAIBDosPYeqgQAgAAODkqhAAAwEFRI7QWKoQAAABOjgohAABwSExMbT1UCAEAAJwcCSEAAICTMxmGYdg7iPwgPT1dERERCg8Pl4eHh73DcXq8H/cP3ov7B+/F/YP3wjriLp+x27n9PUva7dy2QEJoJSkpKfL19VVycrIKFy5s73CcHu/H/YP34v7Be3H/4L2wDhJC62FQCQAAcEgmpp2xGq4hBAAAcHIkhAAAAE6OLmMr8fDw0JgxY7g4+D7B+3H/4L24f/Be3D94L6yDLmPrYVAJAABwSPGXY+12bj/PQLud2xboMgYAAHByJIQAAABOjmsIAQCAQ+JextZDhRAAAMDJkRDeRlxcnF544QWVLVtWHh4eCgwMVPv27bVlyxZJUrly5WQymWQymVSwYEHVqlVLH3/8cfb+//rXv1SuXDmlpqaaHbdz58568MEHde3atTx9Po4sNjZWr776qipVqiRPT08FBASoRYsWmjlzpi5duiQp6/2YOnVqrvsfP348+70ymUzy8fFRzZo1NWTIEB06dCgPn4njeuihhzR06NAc65cuXZr9TT0zM1MRERGqVq2avLy8VKxYMTVt2lRz58412+fkyZPq37+/SpYsKXd3dwUHB+vVV19VQkJCXjyVfOdOPqtu/N3o3Lmz2rZtm+vxtmzZIpPJpF27dtk6dAD3ARLC23j88ce1d+9ezZ8/XwcPHtTy5cv10EMPKTExMbvN+PHjFRMTo3379unRRx/VoEGDtGjRIknShAkT5O3treHDh2e3nzNnjtauXau5c+fKxYW34E4cPXpU9erV0+rVq/XOO+9o9+7d+umnnzRs2DCtWLFCP/300x0f66efflJMTIz27t2rd955R1FRUXrggQf0888/2/AZOI+xY8dq6tSpmjBhgvbv36+1a9dq4MCBOn/+fHabo0ePqmHDhjp48KC+/PJLHT58WDNnztTPP/+skJAQs98v3Jk7+ay6Uf/+/bVmzRqdOHEix7Y5c+aobt26ql+/vi3Dvi/06dPH7Mvi30tYWJikrG7JpUuX5thv6NCheuihh3I9jpubm8qWLasXX3zR7Gf/euXLl9eqVas0b948FSlSJNc2RYoU0bx587Ifr127Vq1bt1axYsVUsGBBVa5cWb1791ZGRoYkad26ddkxuLi4yNfXV/Xq1dO//vUvxcTE3NXrA+fANYS3kJSUpF9++UXr1q1Tq1atJEnBwcFq3LixWTsfHx8FBmYNP3/77bf11VdfaenSperevbs8PDw0f/58hYSE6PHHH1eNGjU0bNgwTZo0SRUrVszz5+SoBg8eLDc3N+3YsUOFChXKXl+7dm09/vjjsmT2pOLFi2e/XxUqVFDnzp3Vpk0b9e/fX0eOHJGrq6vV43cmK1as0ODBg/Xkk09mr3vggQfM2gwZMkTu7u5avXq1vLy8JElly5ZVvXr1VLFiRY0ePVofffRRnsbtyO70s+pGnTp1kr+/v+bNm6cxY8Zkr7906ZIWLVqkd955x6Zx30/CwsJyVLHvZo7Av4+TkZGh/fv3q1+/fkpKStKXX35p1m7fvn1KSEhQ69atc2y7mT/++EMdOnTQK6+8og8++EBeXl46dOiQvv766xy9TQcOHFDhwoWVkpKiXbt2adKkSZo9e7bWrVun2rVrW/y8kP9RnroFb29veXt7a+nSpUpPT7/j/Tw9PXX16tXsxw0aNFB4eLgGDBignj17qlGjRnrxxRdtEXK+lJCQoNWrV2vIkCFmyeD17uXCYhcXF7366qs6ceKEdu7cedfHQZbAwECtWbNG586dy3V7YmKifvzxRw0ePDg7Gbx+32effVaLFi2yKMl3dnf7WeXm5qZevXpp3rx5Zq/34sWLdeXKFT377LO2CPe+9Hc3+/VL0aJF7/o4pUuXVmhoqLp3767Vq1fnaLds2TK1b9/eoqQzMjJSQUFBmjRpkmrVqqWKFSsqLCxMn376qdzd3c3a+vv7KzAwUFWqVFGPHj20adMmlShRIt/97THZ8V9+Q0J4C25ubpo3b57mz5+vIkWKqHnz5ho1apT27duXa/uMjAzNmzdPv/32m9q0aWO27d///rdcXFy0bds2zZkzh5FRFjh8+LAMw1DVqlXN1vv5+WX/IRwxYsQ9naNatWqSsq4zxL2ZMmWKzp07p8DAQNWpU0eDBg3SDz/8kL390KFDMgxD1atXz3X/6tWr6/z58zdNKJGTpZ9V1+vXr5+OHz+udevWZa+bM2eOHnvssbtKiPCPo0ePatWqVSpQoECObcuXL1fXrl0tOl5gYKBiYmK0YcMGi2Px8vLSoEGDtGnTJsXFxVm8P/I/EsLbePzxx3XmzBktX75c7du317p161S/fn2zazpGjBghb29veXl5aciQIXrjjTf0wgsvmB0nMjJSMTExMgxD27dvz+NnkT/cmET/+uuv2rNnj2rWrGlRVSQ3f1dHSNTvXY0aNfT7779r69at6tu3r86ePavOnTtrwIABd7Q/78XduZPPqtxUq1ZNzZo105w5cyRJR44c0caNG9WvX788iPr+8d1332V/wfx7mTBhwl0fx8vLSxUrVtT+/ftzfGE9ffq09u7dq44dO1p07CeffFJPP/20WrVqpaCgIHXr1k3Tp09XSkrKHe3PF1/cCgnhHfD09FS7du301ltvafPmzerTp4/Z9TZvvPGG9uzZoxMnTujChQuaNGmS2WCR8+fPa+DAgRo1apTefPNNDR48WPHx8fZ4Kg6pUqVKMplM+vPPP83WV6hQQZUqVcrR7Xg3oqKiJGVd5I2bK1y4sJKTk3OsT0pKUuHChbMfu7i4qFGjRho2bJiWLFmiefPmafbs2Tp27Fj2+7l///5cz/Hnn3+qaNGi8vPzs9nzyK9u91l1M/3799c333yjlJQUzZ07V8HBwTl6OfK71q1ba8+ePWbLkCFD7vo427Zt08svv6z27dvr5ZdfNmuzfPlyNW/eXMWKFbPo2K6urpo7d65OnTqlSZMmqWTJkpo4caJq1qx5RwNG8ueXLZMdl/yFhPAu1KhRQxcvXsx+7Ofnp0qVKqlkyZK5/qK9/PLL8vf317///W+NHDlSZcqU0UsvvZSXITu04sWLq127dpo+fbrZ624t165d07Rp01S+fHnVq1fP6sfPT6pVq6YdO3bkWL99+/YcXfrXq1GjhiTp4sWL2e/njBkzlJaWZtYuNjZWCxcuVPfu3fPZHy37uPGz6maeeuopubq66osvvtD8+fPVt29fp3v9CxUqpEqVKpktfydsPj4+N/0i5Ovrm+tx6tSpo2nTpik9PV3jxo0za3Njd3HhwoV14cIFZWZmmrXLzMzUhQsXcpyjVKlS6tmzpz788EPt379fly9f1syZM2/7HP/+4luuXLnbtoXzISG8hYSEBD388MP6/PPPtW/fPh07dkyLFy/WpEmT7vjajyVLlmjx4sWaP3++ChQokH2tz5IlS/TNN9/Y+BnkHzNmzFBGRoYaNmyoRYsWKSoqSgcOHNDnn3+uP//802xk8OnTp3N8079+6o2EhATFxsbq6NGjWr58udq2batff/1Vs2fPZoTxbQwePFhHjhzRkCFDtHfvXh08eFAffvihZs+erTfeeEOS9MQTT+i9997Ttm3bdOLECa1bt05DhgxRlSpVsruspk+frvT0dLVv314bNmzQyZMntWrVKrVr106lSpXSxIkT7fk0Hc6dflbd7HfD29tb3bt316hRo3TmzBn16dPHfk/mPlStWrUcl/oYhqGdO3fe8ouQJI0ZM0aTJ0/WmTNnJEkXLlzQ2rVr1aVLF7PjZ2Zmavfu3Wb77tq1S5mZmbc8R9GiRRUUFHTbxD8tLU2ffPKJHnzwQZUoUeKWbR0J9UErMnBTly9fNkaOHGnUr1/f8PX1NQoWLGhUrVrV+Pe//21cunTJMAzDCA4ONt57771c9z937pzh7+9vTJw4Mce2iRMnGv7+/sa5c+ds+RTylTNnzhgvvfSSUb58eaNAgQKGt7e30bhxY+M///mPcfHiRcMwst4PSTmWuXPnGseOHTNbV7BgQaN69erG4MGDjUOHDtn52TmOHTt2GO3btzf8/f2NwoULGw0bNjS+/PLL7O2ffPKJ0bp1a6NEiRKGu7u7UbZsWaNPnz7G8ePHzY5z/Phxo0+fPkZgYKBRoEABo0yZMsbLL79sxMfH5/VTcnh3+ll1s98NwzCMzZs3G5KM0NBQOz4T++jdu7cRFhZmxMTEmC1/fz4vWrTI8PT0ND744APjwIEDxp49e4zBgwcbXl5eZj/XvXv3Nrp27Zrj+A0aNDCGDBliGIZhLF682KhVq1aONh06dDBq165tREZGGkePHjUiIyON2rVrGx06dMhuM3PmTGPQoEHGjz/+aBw+fNj4/fffjX/961+Gi4uLsW7dOsMwDGPt2rWGJOPAgQNGTEyMcfDgQePLL7806tWrZxQvXtz4448/rPnS2V3i5Ti7LfmNyTCY2wEA4Lz69Omj+fPn51hftWrV7GuXFy1apMmTJ+vgwYPy9PRUvXr1NHHiRDVo0MDsOElJSTkmsf7iiy/Ut29fHT58WKNGjVJwcLDefvttszYpKSkaO3asVqxYoVOnTql06dLq1KmTxo4dm91lvHv3bk2ZMkWbNm3SmTNn5O3trZo1a+r1119X586dJWVNTN26dWtJWdcKent7q0KFCgoNDdXw4cOz52DNL86n2282gqIe+afSKkkkhAAA5IHMzEz5+/vrhx9+uO2k4bgzSVfsN0CziHv+GvjGNYQAAOSBhIQEDRs2TI0aNbJ3KEAOVAgBAIBDSrqSYLdzF3Evbrdz2wIVQgAAACfnZu8AAAAA7ka+nP7FTqgQAgAAODkSQgAAACdHQggAABxU/rtXyfnz59WzZ0/5+vrK19dXPXv2VFJS0m33i4qKUpcuXeTr6ysfHx81bdpU0dHRd3xeEkIAAID7xDPPPKM9e/Zo1apVWrVqlfbs2aOePXvecp8jR46oRYsWqlatmtatW6e9e/fqzTfflKen5x2fl2lnAACAQ0q5et5u5y5coKjVjxkVFaUaNWpo69atatKkiSRp69atCgkJ0Z9//nnT+1r36NFDBQoU0GeffXbX56ZCCAAAYKH09HSlpKSYLenp6fd0zC1btsjX1zc7GZSkpk2bytfXV5s3b851n2vXrun7779XlSpV1L59e/n7+6tJkyY5bqF4OySEAAAAFoqIiMi+zu/vJSIi4p6OGRsbK39//xzr/f39FRsbm+s+cXFxunDhgv7v//5PYWFhWr16tbp166bHHntM69evv+NzMw8hAACAhcLDwzV8+HCzdR4eHrm2HTt2rMaNG3fL423fvl2SZDLlHLBiGEau66WsCqEkde3aVcOGDZMk1a1bV5s3b9bMmTPVqlWrWz+Rv5AQAgAAWMjDw+OmCeCNXnrpJfXo0eOWbcqVK6d9+/bp7NmzObadO3dOAQEBue7n5+cnNzc31ahRw2x99erV9csvv9xRfBIJIQAAcFAmB7lXiZ+fn/z8/G7bLiQkRMnJyfr111/VuHFjSdK2bduUnJysZs2a5bqPu7u7GjVqpAMHDpitP3jwoIKDg+84Rq4hBAAAuA9Ur15dYWFhGjhwoLZu3aqtW7dq4MCB6tSpk9kI42rVqmnJkiXZj9944w0tWrRIs2bN0uHDhzV9+nStWLFCgwcPvuNzkxACAAAHlf8mpl64cKFq166t0NBQhYaGqk6dOjmmkzlw4ICSk5OzH3fr1k0zZ87UpEmTVLt2bX366af65ptv1KJFizs+L/MQAgAAh5R6Nfn2jWzEp4Cv3c5tC1QIAQAAnByDSgAAgENyjCEljoEKIQAAgJOjQggAABzSzSZrhuWoEAIAADg5EkIAAAAnR5cxAABwUHQZWwsVQgAAACdHhRAAADgk6oPWQ4UQAADAyVEhBAAADooaobVQIQQAAHByJIQAAABOji5jAADgkLhTifVQIQQAAHByJIQAAABOjoQQAADAyZEQAgAAODkGlQAAAIdkYh5Cq6FCCAAA4ORMhmEY9g4CAAAA9kOFEAAAwMmREAIAADg5EkIAAAAnR0IIAADg5EgIAQAAnBwJIQAAgJMjIQQAAHByJIQAAABOjoQQAADAyf0/j66pc6VMXaIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#PLOTTING THE CORRELATION\n",
    "plt.figure(figsize= (8,8))\n",
    "sns.heatmap(correlation, cbar=True,square=True, fmt='.1f',annot=True,annot_kws={'size':8},cmap='Greens')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "78efc5dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SPX        0.049345\n",
      "GLD        1.000000\n",
      "USO       -0.186360\n",
      "SLV        0.866632\n",
      "EUR/USD   -0.024375\n",
      "Name: GLD, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "#PRINTING THE CORRELATION OF 'GOLD' WITH RESPECT TO OTHER PARAMETERS\n",
    "print(correlation['GLD'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78e35434",
   "metadata": {},
   "source": [
    "# VISUALIZATION OF DATA USING SEABORN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "62988828",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x2173a887370>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#PLOTTING THE PRICE OF GOLD\n",
    "sns.displot(df['GLD'],color='Blue')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c8e9362a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E:\\ANACONDA\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='GLD', ylabel='Density'>"
      ]
     },
     "execution_count": 14,
     "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": [
    "#PLOTTING GOLD PRICE WITH RESPECT TO IT'S DENSITY\n",
    "sns.distplot(df['GLD'],color='Blue')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b1674280",
   "metadata": {},
   "outputs": [],
   "source": [
    "#EXTRACTING THE REQUIRED COLUMNS\n",
    "x=df.drop(['Date','GLD'],axis=1)\n",
    "y=df['GLD']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e13e98cc",
   "metadata": {},
   "source": [
    "# SPLITTING OF TEST AND TRAINING DATASET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "85215a40",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test,y_train,y_test= train_test_split(x,y,test_size=0.2,random_state=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "edf8016a",
   "metadata": {},
   "source": [
    "# RANDOM FOREST REGRESSOR MODEL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e065bd1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "regressor=RandomForestRegressor(n_estimators=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c0d987b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor()"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#TRAINING MODEL DATA\n",
    "regressor.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2bfaf78b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#PREDICTION ON TEST DATA\n",
    "test_data_prediction=regressor.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4306afdb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[168.29239932  81.94169967 116.43610031 127.64070065 120.8402012\n",
      " 154.73449705 150.48799877 125.95150048 117.42259871 126.05410054\n",
      " 116.60540112 171.60550093 141.51659845 167.68049773 114.97830034\n",
      " 117.91690056 137.9091034  170.10470099 159.03540263 158.89509909\n",
      " 155.0329002  125.04080029 175.43159921 157.00430348 125.13930055\n",
      "  93.83349981  77.45630004 120.91330009 119.18179977 167.55150037\n",
      "  88.11040045 125.40810005  90.96020068 117.82050002 121.12469966\n",
      " 136.39200077 115.53060159 115.00260092 147.86270007 107.43520095\n",
      " 104.71400251  87.0714979  126.4598007  117.9535001  152.56709921\n",
      " 119.68630037 108.45079963 108.37759869  93.25510043 127.12489747\n",
      "  75.06800029 113.63909924 121.2445999  111.16169894 118.9084991\n",
      " 120.63499934 158.69650014 168.73040087 147.01949672  85.80009847\n",
      "  94.33180038  86.79369874  90.54280043 119.17820061 126.37210088\n",
      " 127.46540029 168.51550028 122.22419939 117.34849884  98.46700017\n",
      " 168.03720056 143.06279806 132.26650222 121.23900214 121.22339965\n",
      " 119.85180043 114.48860114 118.17100052 107.1875011  127.89280129\n",
      " 113.8407994  107.57940021 116.7961007  119.48859881  89.16700058\n",
      "  88.29669876 146.12650116 127.13479937 113.26640021 110.35499822\n",
      " 108.25389904  77.46319929 169.06620128 114.0689991  121.69929895\n",
      " 127.9531021  154.92469774  91.91859936 134.75660097 159.0790035\n",
      " 125.65370074 125.23500054 130.33390219 114.83390102 119.70669977\n",
      "  92.17889984 110.45939879 166.40909896 158.07259888 114.15029952\n",
      " 106.86300133  79.98419934 113.35250041 125.90300083 106.82289954\n",
      " 119.10040091 155.62870288 160.07879931 120.2861998  134.00810267\n",
      " 101.47849972 117.50839798 119.2720004  112.92400064 102.83659928\n",
      " 160.24289827  99.16140037 147.95029899 125.56990098 170.26139914\n",
      " 125.97919861 127.32879725 127.52220229 113.84909942 113.20160082\n",
      " 123.60339919 102.1904992   89.2869001  124.22670001 101.77909919\n",
      " 107.18449883 113.4166006  117.35020076  99.17459978 121.52910022\n",
      " 163.68969975  87.44969862 106.81380016 117.32950048 127.7495018\n",
      " 124.13900043  80.65199908 120.34440061 157.22129774  88.18449977\n",
      " 110.03239976 118.76799887 172.68059899 103.003699   105.8011004\n",
      " 122.09660028 157.88709729  87.77719819  93.38750031 112.75760023\n",
      " 177.37100012 114.40429987 119.27370033  94.83500101 126.02990035\n",
      " 166.24780118 114.72670082 116.81920114  88.33019863 148.89030025\n",
      " 120.34439947  89.68489952 112.4536001  117.39580053 118.76140116\n",
      "  88.20909928  94.19979994 117.16180017 118.66000174 120.32680055\n",
      " 126.95369836 121.90679969 151.7940994  165.22680068 118.58329959\n",
      " 120.42320126 150.29409997 118.6272992  172.81749928 105.75339981\n",
      " 104.98530106 148.93630032 113.63990078 124.91230116 147.34589956\n",
      " 119.65480121 115.25470051 112.57330003 113.56150214 141.05550118\n",
      " 117.79459782 102.96100032 115.86800107 103.50910187  98.71170013\n",
      " 117.54020054  90.68280023  91.62330086 153.74889927 102.72529963\n",
      " 154.73230109 114.32350167 138.22460131  90.19479819 115.50809932\n",
      " 114.00709947 123.03460037 121.94910039 165.35210112  92.8771994\n",
      " 135.63180133 121.35209939 120.72050078 104.62120019 142.80030234\n",
      " 121.72279949 116.59720027 113.67640081 127.41789741 122.77129965\n",
      " 125.82959938 121.22260032  86.75049922 132.47940058 144.90460205\n",
      "  92.72429955 159.78679987 159.16910251 126.46849897 164.86699965\n",
      " 108.89529996 109.88910067 103.56419816  94.23380028 128.15230339\n",
      " 107.08070067 162.93749982 121.50910007 132.06540033 130.4408016\n",
      " 160.70089959  90.19319879 175.43130149 127.03960062 127.08099835\n",
      "  86.34749898 124.47759927 150.1003974   89.76509968 107.03400003\n",
      " 109.07539992  84.01029886 136.32099968 155.05730192 138.86540313\n",
      "  74.21230028 152.51400089 126.38910032 126.78239999 127.43379865\n",
      " 108.80889961 156.34859981 114.50450054 117.02530129 125.31339955\n",
      " 154.19740137 121.14529971 156.28649906  92.94740046 125.41760109\n",
      " 125.47660057  88.27890101  92.21369949 126.21309966 128.24880322\n",
      " 113.2736004  117.8961974  120.82900023 127.28269812 119.60070097\n",
      " 136.12610093  93.82109961 119.84900037 113.05300106  94.35729948\n",
      " 108.82659974  87.26229915 109.24419968  89.64969999  92.45820016\n",
      " 131.54490341 162.31510092  89.43050023 119.47920083 133.52740159\n",
      " 123.8716001  128.24860168 102.00769864  88.98959856 131.73590017\n",
      " 119.85600054 108.64329992 169.58600116 115.29210026  86.59359878\n",
      " 118.87070057  91.17189946 161.61000089 116.38720027 121.36819996\n",
      " 160.18799831 120.0064992  112.92499914 108.46679864 126.81749996\n",
      "  75.60950043 103.0405998  127.91600278 121.67039957  92.54559999\n",
      " 131.91790064 118.23780108 116.16179979 154.53150274 159.70030014\n",
      " 110.11089968 153.37789835 119.30360074 160.71560048 118.51320022\n",
      " 158.12039893 115.07279931 116.57740026 148.69779877 114.73720061\n",
      " 125.91539896 166.45829941 117.67800006 125.02239917 153.33860304\n",
      " 153.45670257 132.2482997  114.61340035 121.29960182 124.87300072\n",
      "  89.71330042 123.49199988 154.6105014  111.7181005  106.74350015\n",
      " 161.7311008  118.64119991 165.63689969 134.05060151 115.22739977\n",
      " 152.92509869 168.47390001 114.90769981 113.95980154 157.8792987\n",
      "  85.43559852 127.04550109 127.87060089 129.0679994  124.29410078\n",
      " 123.85890075  90.73840075 152.9925007   97.20509982 137.67250016\n",
      "  89.47279921 107.51030017 115.0603004  112.83070094 124.29449933\n",
      "  91.46549867 125.33100097 162.16799874 120.02029882 164.93810072\n",
      " 126.95399842 112.3235003  127.63239918  95.04589878  90.93620018\n",
      " 103.45949908 120.79500017  83.27599933 126.23190007 159.90080471\n",
      " 117.48900085 118.44639993 120.0708     122.77909979 120.1213014\n",
      " 121.51620024 118.07380067 106.95670001 148.13699988 126.3285982\n",
      " 115.8168011   73.86320015 127.74430063 153.46430123 122.70399963\n",
      " 125.52960063  88.93620018 104.31509868 124.7558006  120.29030023\n",
      "  73.49610084 152.06970014 120.98070052 104.56880006  86.53269772\n",
      " 115.20319917 172.15649831 119.89330022 159.91069741 113.19289981\n",
      " 121.40320032 118.51640107  95.95539981 118.71929998 125.84020021\n",
      " 118.66829959  95.88290045 153.78470204 122.10379984 147.26769954\n",
      " 159.3450026  113.9525003  122.55569943 148.8690984  127.25330035\n",
      " 165.81120061 135.91390018 119.97079923 166.81379766 108.30849975\n",
      " 121.70799877 138.26240128 105.89999863]\n"
     ]
    }
   ],
   "source": [
    "print(test_data_prediction)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "456624bd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ERROR PERCENTAGE =  0.9890733318194944\n"
     ]
    }
   ],
   "source": [
    "#R squared error\n",
    "error_score=metrics.r2_score(y_test,test_data_prediction)\n",
    "print(\"ERROR PERCENTAGE = \",error_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e8bd4d9",
   "metadata": {},
   "source": [
    "# COMPARING ACTUAL AND PREDICTED VALUES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "5da49057",
   "metadata": {},
   "outputs": [],
   "source": [
    "#CONVERTING DATA INTO LIST TYPE\n",
    "y_test=list(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "44bf6b76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#VISUALIZATION OF ACTUAL AND PREDICTED  GOLD PRICE\n",
    "plt.plot(y_test,color='black',label='Actual value')\n",
    "plt.plot(test_data_prediction,color='yellow',label='Predicted value')\n",
    "plt.title('ACTUAL PRICE VS PREDICTED PRICE')\n",
    "plt.xlabel('Number of values')\n",
    "plt.ylabel('Gold Price')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}