From 6e9a8853253566ec131c4163dffca2dc3c79ba4f Mon Sep 17 00:00:00 2001
From: Daria Gavrilova <dariaironhack@gmail.com>
Date: Sun, 6 Dec 2020 15:23:05 +0100
Subject: [PATCH] lab completed

---
 your-code/lab_boston_housing.ipynb | 1160 +++++++++++++++++++++++++++-
 your-code/lab_overfitting.ipynb    |  102 ++-
 2 files changed, 1220 insertions(+), 42 deletions(-)

diff --git a/your-code/lab_boston_housing.ipynb b/your-code/lab_boston_housing.ipynb
index 4a25b49..67f9c0d 100644
--- a/your-code/lab_boston_housing.ipynb
+++ b/your-code/lab_boston_housing.ipynb
@@ -35,11 +35,760 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here"
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "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>crim</th>\n",
+       "      <th>zn</th>\n",
+       "      <th>indus</th>\n",
+       "      <th>chas</th>\n",
+       "      <th>nox</th>\n",
+       "      <th>rm</th>\n",
+       "      <th>age</th>\n",
+       "      <th>dis</th>\n",
+       "      <th>rad</th>\n",
+       "      <th>tax</th>\n",
+       "      <th>ptratio</th>\n",
+       "      <th>black</th>\n",
+       "      <th>lstat</th>\n",
+       "      <th>medv</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.15876</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10.81</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.413</td>\n",
+       "      <td>5.961</td>\n",
+       "      <td>17.5</td>\n",
+       "      <td>5.2873</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>305.0</td>\n",
+       "      <td>19.2</td>\n",
+       "      <td>376.94</td>\n",
+       "      <td>9.88</td>\n",
+       "      <td>21.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.10328</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>5.13</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.453</td>\n",
+       "      <td>5.927</td>\n",
+       "      <td>47.2</td>\n",
+       "      <td>6.9320</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>284.0</td>\n",
+       "      <td>19.7</td>\n",
+       "      <td>396.90</td>\n",
+       "      <td>9.22</td>\n",
+       "      <td>19.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.34940</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>9.90</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.544</td>\n",
+       "      <td>5.972</td>\n",
+       "      <td>76.7</td>\n",
+       "      <td>3.1025</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>304.0</td>\n",
+       "      <td>18.4</td>\n",
+       "      <td>396.24</td>\n",
+       "      <td>9.97</td>\n",
+       "      <td>20.3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2.73397</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>19.58</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.871</td>\n",
+       "      <td>5.597</td>\n",
+       "      <td>94.9</td>\n",
+       "      <td>1.5257</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>403.0</td>\n",
+       "      <td>14.7</td>\n",
+       "      <td>351.85</td>\n",
+       "      <td>21.45</td>\n",
+       "      <td>15.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.04337</td>\n",
+       "      <td>21.0</td>\n",
+       "      <td>5.64</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.439</td>\n",
+       "      <td>6.115</td>\n",
+       "      <td>63.0</td>\n",
+       "      <td>6.8147</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>243.0</td>\n",
+       "      <td>16.8</td>\n",
+       "      <td>393.97</td>\n",
+       "      <td>9.43</td>\n",
+       "      <td>20.5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      crim    zn  indus  chas    nox     rm   age     dis  rad    tax  \\\n",
+       "0  0.15876   0.0  10.81   0.0  0.413  5.961  17.5  5.2873  4.0  305.0   \n",
+       "1  0.10328  25.0   5.13   0.0  0.453  5.927  47.2  6.9320  8.0  284.0   \n",
+       "2  0.34940   0.0   9.90   0.0  0.544  5.972  76.7  3.1025  4.0  304.0   \n",
+       "3  2.73397   0.0  19.58   0.0  0.871  5.597  94.9  1.5257  5.0  403.0   \n",
+       "4  0.04337  21.0   5.64   0.0  0.439  6.115  63.0  6.8147  4.0  243.0   \n",
+       "\n",
+       "   ptratio   black  lstat  medv  \n",
+       "0     19.2  376.94   9.88  21.7  \n",
+       "1     19.7  396.90   9.22  19.6  \n",
+       "2     18.4  396.24   9.97  20.3  \n",
+       "3     14.7  351.85  21.45  15.4  \n",
+       "4     16.8  393.97   9.43  20.5  "
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "data=pd.read_csv('../data/boston_data.csv')\n",
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 404 entries, 0 to 403\n",
+      "Data columns (total 14 columns):\n",
+      " #   Column   Non-Null Count  Dtype  \n",
+      "---  ------   --------------  -----  \n",
+      " 0   crim     404 non-null    float64\n",
+      " 1   zn       404 non-null    float64\n",
+      " 2   indus    404 non-null    float64\n",
+      " 3   chas     404 non-null    float64\n",
+      " 4   nox      404 non-null    float64\n",
+      " 5   rm       404 non-null    float64\n",
+      " 6   age      404 non-null    float64\n",
+      " 7   dis      404 non-null    float64\n",
+      " 8   rad      404 non-null    float64\n",
+      " 9   tax      404 non-null    float64\n",
+      " 10  ptratio  404 non-null    float64\n",
+      " 11  black    404 non-null    float64\n",
+      " 12  lstat    404 non-null    float64\n",
+      " 13  medv     404 non-null    float64\n",
+      "dtypes: float64(14)\n",
+      "memory usage: 44.3 KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "data.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\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>crim</th>\n",
+       "      <th>zn</th>\n",
+       "      <th>indus</th>\n",
+       "      <th>chas</th>\n",
+       "      <th>nox</th>\n",
+       "      <th>rm</th>\n",
+       "      <th>age</th>\n",
+       "      <th>dis</th>\n",
+       "      <th>rad</th>\n",
+       "      <th>tax</th>\n",
+       "      <th>ptratio</th>\n",
+       "      <th>black</th>\n",
+       "      <th>lstat</th>\n",
+       "      <th>medv</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>crim</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.194770</td>\n",
+       "      <td>0.404249</td>\n",
+       "      <td>-0.060688</td>\n",
+       "      <td>0.405290</td>\n",
+       "      <td>-0.172226</td>\n",
+       "      <td>0.349288</td>\n",
+       "      <td>-0.376493</td>\n",
+       "      <td>0.603044</td>\n",
+       "      <td>0.565047</td>\n",
+       "      <td>0.292092</td>\n",
+       "      <td>-0.377436</td>\n",
+       "      <td>0.428940</td>\n",
+       "      <td>-0.400956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>zn</th>\n",
+       "      <td>-0.194770</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.532268</td>\n",
+       "      <td>-0.037290</td>\n",
+       "      <td>-0.497114</td>\n",
+       "      <td>0.302404</td>\n",
+       "      <td>-0.546587</td>\n",
+       "      <td>0.659018</td>\n",
+       "      <td>-0.311313</td>\n",
+       "      <td>-0.289332</td>\n",
+       "      <td>-0.371315</td>\n",
+       "      <td>0.176350</td>\n",
+       "      <td>-0.412075</td>\n",
+       "      <td>0.355608</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>indus</th>\n",
+       "      <td>0.404249</td>\n",
+       "      <td>-0.532268</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.059928</td>\n",
+       "      <td>0.760913</td>\n",
+       "      <td>-0.353589</td>\n",
+       "      <td>0.630048</td>\n",
+       "      <td>-0.702583</td>\n",
+       "      <td>0.616375</td>\n",
+       "      <td>0.722828</td>\n",
+       "      <td>0.356549</td>\n",
+       "      <td>-0.378189</td>\n",
+       "      <td>0.608309</td>\n",
+       "      <td>-0.501698</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>chas</th>\n",
+       "      <td>-0.060688</td>\n",
+       "      <td>-0.037290</td>\n",
+       "      <td>0.059928</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.100650</td>\n",
+       "      <td>0.090146</td>\n",
+       "      <td>0.084852</td>\n",
+       "      <td>-0.103124</td>\n",
+       "      <td>-0.022561</td>\n",
+       "      <td>-0.043708</td>\n",
+       "      <td>-0.121835</td>\n",
+       "      <td>0.042580</td>\n",
+       "      <td>-0.041061</td>\n",
+       "      <td>0.141400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>nox</th>\n",
+       "      <td>0.405290</td>\n",
+       "      <td>-0.497114</td>\n",
+       "      <td>0.760913</td>\n",
+       "      <td>0.100650</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.266114</td>\n",
+       "      <td>0.728882</td>\n",
+       "      <td>-0.762469</td>\n",
+       "      <td>0.612115</td>\n",
+       "      <td>0.660607</td>\n",
+       "      <td>0.166715</td>\n",
+       "      <td>-0.393876</td>\n",
+       "      <td>0.587573</td>\n",
+       "      <td>-0.439225</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>rm</th>\n",
+       "      <td>-0.172226</td>\n",
+       "      <td>0.302404</td>\n",
+       "      <td>-0.353589</td>\n",
+       "      <td>0.090146</td>\n",
+       "      <td>-0.266114</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.210589</td>\n",
+       "      <td>0.178700</td>\n",
+       "      <td>-0.173222</td>\n",
+       "      <td>-0.241733</td>\n",
+       "      <td>-0.323330</td>\n",
+       "      <td>0.128410</td>\n",
+       "      <td>-0.578025</td>\n",
+       "      <td>0.683541</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>age</th>\n",
+       "      <td>0.349288</td>\n",
+       "      <td>-0.546587</td>\n",
+       "      <td>0.630048</td>\n",
+       "      <td>0.084852</td>\n",
+       "      <td>0.728882</td>\n",
+       "      <td>-0.210589</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.734915</td>\n",
+       "      <td>0.467341</td>\n",
+       "      <td>0.503830</td>\n",
+       "      <td>0.231820</td>\n",
+       "      <td>-0.276469</td>\n",
+       "      <td>0.602001</td>\n",
+       "      <td>-0.390863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dis</th>\n",
+       "      <td>-0.376493</td>\n",
+       "      <td>0.659018</td>\n",
+       "      <td>-0.702583</td>\n",
+       "      <td>-0.103124</td>\n",
+       "      <td>-0.762469</td>\n",
+       "      <td>0.178700</td>\n",
+       "      <td>-0.734915</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.503471</td>\n",
+       "      <td>-0.526938</td>\n",
+       "      <td>-0.206016</td>\n",
+       "      <td>0.306445</td>\n",
+       "      <td>-0.500912</td>\n",
+       "      <td>0.264876</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>rad</th>\n",
+       "      <td>0.603044</td>\n",
+       "      <td>-0.311313</td>\n",
+       "      <td>0.616375</td>\n",
+       "      <td>-0.022561</td>\n",
+       "      <td>0.612115</td>\n",
+       "      <td>-0.173222</td>\n",
+       "      <td>0.467341</td>\n",
+       "      <td>-0.503471</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.917344</td>\n",
+       "      <td>0.487733</td>\n",
+       "      <td>-0.468700</td>\n",
+       "      <td>0.499279</td>\n",
+       "      <td>-0.423508</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tax</th>\n",
+       "      <td>0.565047</td>\n",
+       "      <td>-0.289332</td>\n",
+       "      <td>0.722828</td>\n",
+       "      <td>-0.043708</td>\n",
+       "      <td>0.660607</td>\n",
+       "      <td>-0.241733</td>\n",
+       "      <td>0.503830</td>\n",
+       "      <td>-0.526938</td>\n",
+       "      <td>0.917344</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.465997</td>\n",
+       "      <td>-0.462250</td>\n",
+       "      <td>0.542732</td>\n",
+       "      <td>-0.495792</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ptratio</th>\n",
+       "      <td>0.292092</td>\n",
+       "      <td>-0.371315</td>\n",
+       "      <td>0.356549</td>\n",
+       "      <td>-0.121835</td>\n",
+       "      <td>0.166715</td>\n",
+       "      <td>-0.323330</td>\n",
+       "      <td>0.231820</td>\n",
+       "      <td>-0.206016</td>\n",
+       "      <td>0.487733</td>\n",
+       "      <td>0.465997</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.194891</td>\n",
+       "      <td>0.351408</td>\n",
+       "      <td>-0.506313</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>black</th>\n",
+       "      <td>-0.377436</td>\n",
+       "      <td>0.176350</td>\n",
+       "      <td>-0.378189</td>\n",
+       "      <td>0.042580</td>\n",
+       "      <td>-0.393876</td>\n",
+       "      <td>0.128410</td>\n",
+       "      <td>-0.276469</td>\n",
+       "      <td>0.306445</td>\n",
+       "      <td>-0.468700</td>\n",
+       "      <td>-0.462250</td>\n",
+       "      <td>-0.194891</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.388913</td>\n",
+       "      <td>0.360071</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>lstat</th>\n",
+       "      <td>0.428940</td>\n",
+       "      <td>-0.412075</td>\n",
+       "      <td>0.608309</td>\n",
+       "      <td>-0.041061</td>\n",
+       "      <td>0.587573</td>\n",
+       "      <td>-0.578025</td>\n",
+       "      <td>0.602001</td>\n",
+       "      <td>-0.500912</td>\n",
+       "      <td>0.499279</td>\n",
+       "      <td>0.542732</td>\n",
+       "      <td>0.351408</td>\n",
+       "      <td>-0.388913</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.742695</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>medv</th>\n",
+       "      <td>-0.400956</td>\n",
+       "      <td>0.355608</td>\n",
+       "      <td>-0.501698</td>\n",
+       "      <td>0.141400</td>\n",
+       "      <td>-0.439225</td>\n",
+       "      <td>0.683541</td>\n",
+       "      <td>-0.390863</td>\n",
+       "      <td>0.264876</td>\n",
+       "      <td>-0.423508</td>\n",
+       "      <td>-0.495792</td>\n",
+       "      <td>-0.506313</td>\n",
+       "      <td>0.360071</td>\n",
+       "      <td>-0.742695</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             crim        zn     indus      chas       nox        rm       age  \\\n",
+       "crim     1.000000 -0.194770  0.404249 -0.060688  0.405290 -0.172226  0.349288   \n",
+       "zn      -0.194770  1.000000 -0.532268 -0.037290 -0.497114  0.302404 -0.546587   \n",
+       "indus    0.404249 -0.532268  1.000000  0.059928  0.760913 -0.353589  0.630048   \n",
+       "chas    -0.060688 -0.037290  0.059928  1.000000  0.100650  0.090146  0.084852   \n",
+       "nox      0.405290 -0.497114  0.760913  0.100650  1.000000 -0.266114  0.728882   \n",
+       "rm      -0.172226  0.302404 -0.353589  0.090146 -0.266114  1.000000 -0.210589   \n",
+       "age      0.349288 -0.546587  0.630048  0.084852  0.728882 -0.210589  1.000000   \n",
+       "dis     -0.376493  0.659018 -0.702583 -0.103124 -0.762469  0.178700 -0.734915   \n",
+       "rad      0.603044 -0.311313  0.616375 -0.022561  0.612115 -0.173222  0.467341   \n",
+       "tax      0.565047 -0.289332  0.722828 -0.043708  0.660607 -0.241733  0.503830   \n",
+       "ptratio  0.292092 -0.371315  0.356549 -0.121835  0.166715 -0.323330  0.231820   \n",
+       "black   -0.377436  0.176350 -0.378189  0.042580 -0.393876  0.128410 -0.276469   \n",
+       "lstat    0.428940 -0.412075  0.608309 -0.041061  0.587573 -0.578025  0.602001   \n",
+       "medv    -0.400956  0.355608 -0.501698  0.141400 -0.439225  0.683541 -0.390863   \n",
+       "\n",
+       "              dis       rad       tax   ptratio     black     lstat      medv  \n",
+       "crim    -0.376493  0.603044  0.565047  0.292092 -0.377436  0.428940 -0.400956  \n",
+       "zn       0.659018 -0.311313 -0.289332 -0.371315  0.176350 -0.412075  0.355608  \n",
+       "indus   -0.702583  0.616375  0.722828  0.356549 -0.378189  0.608309 -0.501698  \n",
+       "chas    -0.103124 -0.022561 -0.043708 -0.121835  0.042580 -0.041061  0.141400  \n",
+       "nox     -0.762469  0.612115  0.660607  0.166715 -0.393876  0.587573 -0.439225  \n",
+       "rm       0.178700 -0.173222 -0.241733 -0.323330  0.128410 -0.578025  0.683541  \n",
+       "age     -0.734915  0.467341  0.503830  0.231820 -0.276469  0.602001 -0.390863  \n",
+       "dis      1.000000 -0.503471 -0.526938 -0.206016  0.306445 -0.500912  0.264876  \n",
+       "rad     -0.503471  1.000000  0.917344  0.487733 -0.468700  0.499279 -0.423508  \n",
+       "tax     -0.526938  0.917344  1.000000  0.465997 -0.462250  0.542732 -0.495792  \n",
+       "ptratio -0.206016  0.487733  0.465997  1.000000 -0.194891  0.351408 -0.506313  \n",
+       "black    0.306445 -0.468700 -0.462250 -0.194891  1.000000 -0.388913  0.360071  \n",
+       "lstat   -0.500912  0.499279  0.542732  0.351408 -0.388913  1.000000 -0.742695  \n",
+       "medv     0.264876 -0.423508 -0.495792 -0.506313  0.360071 -0.742695  1.000000  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.corr()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "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>crim</th>\n",
+       "      <th>zn</th>\n",
+       "      <th>indus</th>\n",
+       "      <th>chas</th>\n",
+       "      <th>nox</th>\n",
+       "      <th>rm</th>\n",
+       "      <th>age</th>\n",
+       "      <th>dis</th>\n",
+       "      <th>rad</th>\n",
+       "      <th>tax</th>\n",
+       "      <th>ptratio</th>\n",
+       "      <th>black</th>\n",
+       "      <th>lstat</th>\n",
+       "      <th>medv</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>404.000000</td>\n",
+       "      <td>404.000000</td>\n",
+       "      <td>404.000000</td>\n",
+       "      <td>404.000000</td>\n",
+       "      <td>404.000000</td>\n",
+       "      <td>404.00000</td>\n",
+       "      <td>404.000000</td>\n",
+       "      <td>404.000000</td>\n",
+       "      <td>404.000000</td>\n",
+       "      <td>404.000000</td>\n",
+       "      <td>404.000000</td>\n",
+       "      <td>404.000000</td>\n",
+       "      <td>404.000000</td>\n",
+       "      <td>404.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>3.730912</td>\n",
+       "      <td>10.509901</td>\n",
+       "      <td>11.189901</td>\n",
+       "      <td>0.069307</td>\n",
+       "      <td>0.556710</td>\n",
+       "      <td>6.30145</td>\n",
+       "      <td>68.601733</td>\n",
+       "      <td>3.799666</td>\n",
+       "      <td>9.836634</td>\n",
+       "      <td>411.688119</td>\n",
+       "      <td>18.444554</td>\n",
+       "      <td>355.068243</td>\n",
+       "      <td>12.598936</td>\n",
+       "      <td>22.312376</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>8.943922</td>\n",
+       "      <td>22.053733</td>\n",
+       "      <td>6.814909</td>\n",
+       "      <td>0.254290</td>\n",
+       "      <td>0.117321</td>\n",
+       "      <td>0.67583</td>\n",
+       "      <td>28.066143</td>\n",
+       "      <td>2.109916</td>\n",
+       "      <td>8.834741</td>\n",
+       "      <td>171.073553</td>\n",
+       "      <td>2.150295</td>\n",
+       "      <td>94.489572</td>\n",
+       "      <td>6.925173</td>\n",
+       "      <td>8.837019</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>0.006320</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.460000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.392000</td>\n",
+       "      <td>3.56100</td>\n",
+       "      <td>2.900000</td>\n",
+       "      <td>1.169100</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>187.000000</td>\n",
+       "      <td>12.600000</td>\n",
+       "      <td>0.320000</td>\n",
+       "      <td>1.730000</td>\n",
+       "      <td>5.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>0.082382</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>5.190000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.453000</td>\n",
+       "      <td>5.90275</td>\n",
+       "      <td>45.800000</td>\n",
+       "      <td>2.087875</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>281.000000</td>\n",
+       "      <td>17.375000</td>\n",
+       "      <td>374.710000</td>\n",
+       "      <td>7.135000</td>\n",
+       "      <td>17.100000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>0.253715</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>9.795000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.538000</td>\n",
+       "      <td>6.23050</td>\n",
+       "      <td>76.600000</td>\n",
+       "      <td>3.207450</td>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>330.000000</td>\n",
+       "      <td>19.000000</td>\n",
+       "      <td>391.065000</td>\n",
+       "      <td>11.265000</td>\n",
+       "      <td>21.400000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>4.053158</td>\n",
+       "      <td>12.500000</td>\n",
+       "      <td>18.100000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.631000</td>\n",
+       "      <td>6.62925</td>\n",
+       "      <td>94.150000</td>\n",
+       "      <td>5.222125</td>\n",
+       "      <td>24.000000</td>\n",
+       "      <td>666.000000</td>\n",
+       "      <td>20.200000</td>\n",
+       "      <td>396.007500</td>\n",
+       "      <td>16.910000</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>88.976200</td>\n",
+       "      <td>95.000000</td>\n",
+       "      <td>27.740000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.871000</td>\n",
+       "      <td>8.78000</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>12.126500</td>\n",
+       "      <td>24.000000</td>\n",
+       "      <td>711.000000</td>\n",
+       "      <td>22.000000</td>\n",
+       "      <td>396.900000</td>\n",
+       "      <td>34.370000</td>\n",
+       "      <td>50.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             crim          zn       indus        chas         nox         rm  \\\n",
+       "count  404.000000  404.000000  404.000000  404.000000  404.000000  404.00000   \n",
+       "mean     3.730912   10.509901   11.189901    0.069307    0.556710    6.30145   \n",
+       "std      8.943922   22.053733    6.814909    0.254290    0.117321    0.67583   \n",
+       "min      0.006320    0.000000    0.460000    0.000000    0.392000    3.56100   \n",
+       "25%      0.082382    0.000000    5.190000    0.000000    0.453000    5.90275   \n",
+       "50%      0.253715    0.000000    9.795000    0.000000    0.538000    6.23050   \n",
+       "75%      4.053158   12.500000   18.100000    0.000000    0.631000    6.62925   \n",
+       "max     88.976200   95.000000   27.740000    1.000000    0.871000    8.78000   \n",
+       "\n",
+       "              age         dis         rad         tax     ptratio       black  \\\n",
+       "count  404.000000  404.000000  404.000000  404.000000  404.000000  404.000000   \n",
+       "mean    68.601733    3.799666    9.836634  411.688119   18.444554  355.068243   \n",
+       "std     28.066143    2.109916    8.834741  171.073553    2.150295   94.489572   \n",
+       "min      2.900000    1.169100    1.000000  187.000000   12.600000    0.320000   \n",
+       "25%     45.800000    2.087875    4.000000  281.000000   17.375000  374.710000   \n",
+       "50%     76.600000    3.207450    5.000000  330.000000   19.000000  391.065000   \n",
+       "75%     94.150000    5.222125   24.000000  666.000000   20.200000  396.007500   \n",
+       "max    100.000000   12.126500   24.000000  711.000000   22.000000  396.900000   \n",
+       "\n",
+       "            lstat        medv  \n",
+       "count  404.000000  404.000000  \n",
+       "mean    12.598936   22.312376  \n",
+       "std      6.925173    8.837019  \n",
+       "min      1.730000    5.000000  \n",
+       "25%      7.135000   17.100000  \n",
+       "50%     11.265000   21.400000  \n",
+       "75%     16.910000   25.000000  \n",
+       "max     34.370000   50.000000  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.describe()"
    ]
   },
   {
@@ -52,11 +801,246 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['crim', 'zn', 'indus', 'chas', 'nox', 'rm', 'age', 'dis', 'rad', 'tax',\n",
+       "       'ptratio', 'black', 'lstat', 'medv'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Your plots here\n",
+    "import matplotlib.pyplot as plt\n",
+    "fig, ax = plt.subplots(figsize=(10, 10)) \n",
+    "data.boxplot(column=['crim', 'zn', 'indus','chas', 'nox', 'rm', 'age', 'dis', 'rad', 'tax',\n",
+    "       'ptratio', 'black', 'lstat', 'medv'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your plots here"
+    "data.drop('chas', inplace=True, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "crim      -0.400956\n",
+       "zn         0.355608\n",
+       "indus     -0.501698\n",
+       "chas       0.141400\n",
+       "nox       -0.439225\n",
+       "rm         0.683541\n",
+       "age       -0.390863\n",
+       "dis        0.264876\n",
+       "rad       -0.423508\n",
+       "tax       -0.495792\n",
+       "ptratio   -0.506313\n",
+       "black      0.360071\n",
+       "lstat     -0.742695\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.corrwith(data['medv'])[:-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "mdev and crim: correlation -0.4009558757372439\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "mdev and rm: correlation 0.683540993926214\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "mdev and ptratio: correlation -0.5063125552383495\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "mdev and lstat: correlation -0.7426954940642158\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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HD/fz4OF+RhK54vFYyOJ1O7vZc0UPO7pjc2YuRYMWLRGrbPU+F7ff89iMFX8qZxMwhFTerWuyr6SGCrUbmGrXWy4RvMW8nxbw02gWl5elcSjguIonTo6y91A/P3lppCwOsa2riVt39fC6S9fSOi3wPB1P58iiORzANGY3KAX57VLDo5Ti+GCCje2RGUajuzlcs5to39FB/ui+Z0lkbRxXYRpCLGTxV7dduaAdTT1aULVOzJXuN5nOey7AnFPXBK93URrN4nPBp7KahmAZlYdsGsL129bwZ2++nH+683p+d/dFbFnjBZR7h5L87SMv8ba7D/CJfz3CEyerB7HLCusmM2TylYvRoHog23UVfeNpjvZ7MhfxTL7u7KdP732e8VQe5YIpgnJhPJXn03ufn/Pc+abmzldZdfr9HFcxlspzcjRVt0LrUqUVazSa+lhVxsEyhM1roqxrjcy6sm+LBvm1azbypXdfy+ff8Sp++ZXriAZN8o5i37EhPvTtg/zHL/6Uf/j3k/RPZCpeQylFImtzfjzN2bEUE+k87jSDUkkyYiKdB/GkuE1fOO/sWJpjA3EG49mqXeamc2Ik5VVTG4KIYBiCId7xuZhLgrwa852Yp99vKJ715EFcVfcEP9+xazSaxWVVZSsViARNIkETpYKk8w6JrE0q6+BOc5GJCJeua+HSdS387u6L2H9siL1+EHswnuWrj53iq4+d4urNbezZtY4bt68hFDB5vHeUbzxxhr7JNOtaIrz91Zu4blsHY8kcTSU1E7t3dvMJKIsVBE0DyxBGkjmUC67yurwBvKIjvCQNeqYzlwR5NeZb7zH9fjnHRfDkQeq5zkLGrtFoFpdVaRwKFFal0aCFiimSOYdExiaddyiNpUyf7P/oDRdzfiLNvx0eYCSZ4+nT4zx9epxYyGLX+hZeHEoQCZi0hK2iltMH2cF12zqIZ/Kemyho0hoJzEhNvfGuh+mMhQhZJsOJLKmcN1GKQEskCHjxh7sePDqrb39bZxPHBxMo18VxFYVNy6b2cNXnUYgXFCQ42qMBOmOhmlNz5zsxT08FNsXbMXXGQnVdp9K1dLGfRtMYVpVbaTZEvIBtT2uYzR1R1sRChP1dwOcePs5IMluc7L/++GleuaGNb9xxPf/9rbu4cXsnpiEksjaPnRhlOJFjMJ5lPJUv7gS+8cSZsvulc05RGbbU5VSIQ7REAmzrimGZUgyuFrAdl2ODiVl9+x+6ZSdNIc8VVmgKZIo3yVZyS5XGCwoSHGOpPP0T6ZoL5uarrDq9uG9rZxNt0QCWKXUrtGoBP41mZbDk2Uoisgn4KrAWTz/uHqXU50SkA/gmsAWvE9zblFJjs13r2muvVU8++WRd9//1uw8wMJkhZJnF3UQl4b6xVI4v/+gE//dQf/n4gaaQScA0+KffuQGjSkpsoWbiZ6fH+MT3ni8ahBcHE9iuYkNbhBbfZXN8IA4CO7qnWrpVyma65bOPcnI0heMqgqZBZyyEZUrFrKdqabX1ZEhB5ZTa+UzMi3UdjUazcOaTrbQcbiUb+EOl1NMi0gw8JSIPAb8J/FAp9WkR+TDwYeBDi33zc+PpYrqpqxSuq4gEzBnCfcf7Ezx9ZpyACa7r9VJQyrNmiawDOPzHL/6UWy7v4U27euhpKXfvuL5C6rauGH/w+h3c+/gZzk+k2drZxFAiW1xFp/MOededoQ1VySefyDls74pVSJWNc/s9j3FmLEXMV589NpggbHkGpGCE5hPIrVTBPR8W6zorHV2ToblQWY42oX1An/99XESeBzYAbwF2+2/7CrCPJTAOpX50QwTDFHKOzSs6mmiJBEj6dQTfeOIMliF0xbygsYWgUCi8NNmcoxiYzPKVA6f46gE/iH3FOm7c3jlD0O+Vm9p45aY2Qn7c4skTo9zzoxPFVXTAEPLTMp8q+eQrxQBGklniGZvBeAZT4MWhJACWeIHg8xOe0WuJBOoO5OqJrj6mt4FdjmQDjWa5WNYiOBHZAuwHdgGnlVJt/nEBxgqvp51zB3AHwObNm685depUXfespagqlbN53f98lFjIQoBE1mYslSPvuIgIn3zzLta1hdl7qJ+HjnhB7AKxkMXrLu3m1l097FjbXHEMpiE0hwO0hC0s05gxpuFElrFUnuawRVcs5KXR5hyaQxZDiSytkUBx7GfH0rRHA3Q1h+kdSmA7XkBC8BoIKTwXVE9ruK7iMV18Vj+L5crTaJaaFV0hLSIx4FHgU0qpfxaR8VJjICJjSqn22a4xn5gD1Ob/vv2exxiYTBMOWJ77SSnSuZmxCcdVPH7Cq8Q+0Fteib29O8aeXT28/tLusp4NpTSFLFrCAX7aO+JlFg1MEs86dDQFCJoG58a9uosNbWEs0yhWGidz3i7g2MAk61ojiAhH+ycxxbMMjh/XGJzMkHUU123pqGvlrye62in8Pj1+cnSGK083YNKsRFZqzAERCQDfBr6ulPpn//CAiKxTSvWJyDpg7sqweVKL/7uQQpm1PfnsVM5BAe++4RWISDGYbRrCDRet4YaL1jCazPHQkQH2Hurn9GiKFwcT/H8Pv8jfP/oSv7Cjiz27enjV5rayIHYya5PM2mxfG+Pu37iGO77yJEOJLI6rOD2aKmYmDUxmizuR9qYQD/6+N0GXTuJB0/B2Dng1BYXCwPlM6EvZ0+JConSHFTJlwa48jWalsuTGwXcZfQl4Xin1mZIf3Q+8G/i0/+93l3oss1GpoK2w8nZcr1o6mbXL5DQ6moL8+qs38bZrN3L4/CQPHurnkReGSOcdHj46yMNHB1nbEqoYxM7ZLsPxLCdHkliGMDCZLRoGBWRsl3jGa1RUOkGX1gF0xoLeTkNBT0uIoXiGsVSeiXSePX+9v+ieqiV+sFqLz5Y7TlJaRd7dEub8eAaFYthPOtA1GZoLheVIZb0R+BFwEC8JCOBPgJ8C3wI2A6fwUllHZ7vWfN1Ki0necUlmbeIZm7zjzvh5Ouew79gQDx7q4+C5yeJxAa5+RTu37urhNSVB7D/45rMc6ZtAAbajir2iRSAaMOlpDc/YCZS6yQq9sofimVndU7Wowi5WzGG5JuxGxEmmiy3GM/l5u/I0muViRcccFoOVYBxKydpeRXYy62C7Mw3F6dEUDx7q5/tHBhgtCWI3hz058VuvWMdoIsef/MtBTPFSZ+1p/ztClsH7dl/EB15/8axjKXU39Q55tRUosExhW1espvhBpdjMc2fH+eKPT5DMOTQFTd5741ZeubGt6uS/nBN2I+IkOjajWY1o49BA0jmn6HqarvHkuIqfnhhh70EviF2axbq9O8ZYMstkJu/VVShwSn7e3RzE9aUoCi6inpYgPzw6VDZhf+ups8UV7dH+SU+UUIGjFDt7WuYVKP2bHxzjcw+/6AkAipcN5biKWNCkqyVcNvnfdvUGDvSO8vTpMQToaQ0Xg/JLNXlWk0xfyoCwzurSrEZWbED6QmE2d0lBDLAzFiTlG4pUztN4Mg3h5y/q5Ocv6mQ0meP7h/vZe6ifM2NpXhxMFK8fDZrYjguuwhChu8XTJupPZIhnbbZ1xni+b5wDvQ6meLuCZNbmMz84jiEwHM/S0xr2AtX+zqEgfjef+MEXf3wCQyjKpBsCecchkXN4hb9yjgYthhMZPr/vJTa2R3CVQoDz4xnWt0FzOFAW2F6Iy2n6ubGgNzkvZ5xkttiURnMhoY1DjdRa8CQiNIUsmkIWrqtI5LzdRDrnBbI7moK8/brN/PqrN3H4/CR7D/XzyAuDZPIuKf89AkRDJkHToH8yU5S/dlzFRNp7j6tAKSnuUpSiKA/eFDRJ+tdSCoYTGQKmWXegNJlzsCqob01vhTGRyuO4qjyDSjzp7ubwVAbPQorGKp07mc4XYzTLKdL3cqn+1ry80cahRkqzVMBbMadyNnfv7606URiG0BIO0BIOYDsuyaxDImeTzTuICLs2tLJrQyvvf+129r0wyN5D/Rw6P4kC4hkv6C14K/aA6blOCpOhwguOl742xXNJTWRsgqYgeK9Hk3net3tz3RNaU9AkmbVROCjlBcnxx1MgnsmTynvKs71DCaJBk/F0HlGQtd0y0b35PMPZnj9ANu8wFM+Wudj0xK3RLBxtHGpkoXUAlmnQGjVojQaKGU+JrE3OdokETfZcsY49V6zje8+e5+79vV5HOV/byVHg2Ipz41N6UIWU11JyJdlO61qnhP5SOZsDvaN8gPrcOq/b2cV3nukrvi6EUsKWQSpnYztuMSvKEC/bajydpy0SIJ61EeXVXBTu8dHvHqrpGVYaY6XnbzsufZMZtqxpYrO/c7jv6XO8cmObNhAazQLRxqFGZqsDqHXCrfS+n9/eWQxk5x2XX75yPWPJHP/n8dNknfLpv+Aqqkbpu0+NpgiZwrq2SLFWol63Tv9kjvaoxUTaxlWeAWiNWKxtDtPeFOLJknarjgLXcTENiGftilLbtdRSVBtjc8iaEV8YiGcJGMa8diIajWZ2Lph+DktNtV4HN2zrqKnvcrX+zD95cZiOpiCbOqKsb4tw6OwEDx4ZQAkEDCr6/GHmrqESWUdxfjzDSDLLxvZozW1A9x0d5PZ7HuPxk6PkbMWm9ihXbGjl8vWtbGiLksw53HnTNhzl7VQKXiYF2C44VbJ3aukXUW2MSqmK565tCZXdQ1d1azSLgzYONVKtCc2B3tGaJtxaJuZwwOTeJ84QCRi4rvKDzN7PBE95VYBrNrcTDtT2v85VLiOJHHf8wtaa+jOXGrGQKWRsh9OjKQ6fn6B3KFFmaIqIF48oGIlI0Ky4cq+lkU+1MSZzzoxzL+6OYZnlz2E1VHVrNKsB7Vaqg0pZKrX60WeLWZS6m4biWXpavDajqRI3kmJqt/DcuXF2rm2hJWLx+MlR8k71fUTANAhbBtu6Y/S0hBlNZmkKTY1j+mRaasSawwFS8WzxZznHZTCe4/qtQR44NFDMWppeKqOUW+w3Md3NNlemz2yup+nnFgyZbimq0Sw+euewQAptQUup1puh0vtiIYuP3X+YE8MJxpI5srbL6dG0VzE97V5+hiiuqxhP5+gdTvLO6zbPaBxUwPCrrjN5l7fdfYBRXxp8Mp1jPJXl+ECckyNJxpLZohusdOWeyNpYhpf1pPyaiZawyQOHBsp2CgUE7xcq51B0n50cSXDnPz7FNZ/8Prff81jFFqel1NOqVLcU1WiWDl0hvUBqrZit9r5owGA8nWckmcPAq1uY3ggIPLeNCZh+T+s1TUEG4hmUgsvWtfKqTa08cKiPgXhuxrngyXBEgyau8jrhDcY9objuWIigZWC78Ik3X87d+3uLK/dCpbVyp2Q4XhqMk3M8efCz4+liQFrwFGsLRX9eaq1guwoR6uoxUUnGA9CNiDSaeaLlMxpErf2SK73vo989xFgyh+0oDEOwHXeGcSjsIixDAKEtYjGWzvsNfhSbO6JMpPO4ygtgxzM2WdsLFhdkLwoIXv1FRzQwJT0hXk1CT0uY3/3Fi4pGrG88XRzLej819kjfBGHLZFtXjMl0nv7JDDnbq7fY2Bbm/EQGyxAMQ8jmp+owBOiMBYlnbZSCqze31zzBa8kKjWZhaPmMBlBP3UAlf/um/VH6/QkVPC0k8CZ10xA2tEXon8iQdVwMEXpaw/RNZIoKroXJP5l1QOCirhidMYWr4PhgnKDptT6dyOSJZ2yvbsJVDCVyjKfytES8DnVBUzg1kuSSdc38yZ6dfOXAKSbS3jnt0QDNYS9N1DIMmsPer01LJEBLJFDUTgIYjGfJOwpVIQ4ylMhh+sHr2dJopz/TsWR23sVzGo1mfuiYwwKolp46l1+9lDtv2oZpiJ8WqoqrfNOQYgOf7d0x1jQF6W4Jk8k7ZP2VesGVc348Q85xcXxNJss0CFoGIb+/QCRk0tMS5qLOJtqjgWKFc95VjCRznBhJcWY0TdgymUjlubinmf9x2yv5wR/8In/3jqvZ2hkr+vTft/sigpZZMSZwbGDSMwwVPmfhmAuELHPWNNrpz/T4UMLTnCpBp6xqNEtLTcZBRL5Wy7GXG7XWDczG7p3dvG/3RRgi5B3X3zGAIHQ1ezn86bzDju5mPvHmy8v0lwKmgWUYiB94No3yEHFbUxDLNLAdF9MQ8q5LOGDy7utfQWcsSHPIwlflIGO7nBxN8ba7D/D5R17khf5JRpM5tnbH+NztV/HQH/wi995xPR94/cVVg8DpnFu1/qJYC+Erux7tn6R/IsPxgcmy91V8pobBQEnWVOGZ6JRVjWbpqNWtdHnpCxExgWtqOVFEvgz8MjColNrlH/s48NvAkP+2P1FKPVDjWFYM9UpqVHNBfeD1Fxd7JJT2lI6FrLJiu7v395LMOQQNcClkESmU8oK+hfcX/PIB0+TWXR1l8t6/9Zot/Kcbt7FrQytfe+w0J4fjpG2F7bg4CiYzNt9++hzffvocl/Q0s2dXDzfv7CaRsQkFTJrDFr94SVdFd06h+VElaY9SlPKC1TnHxXYV+44OFq9X6ZmubQlxdjyjU1Y1mmVkVuMgIh/B69oWEZHCEk+AHHBPjff4B+Bvga9OO/5ZpdRf1T7UlUc9rTXnkq4ojUdMD1zfsK2D+54+R8AUwpZBznFRrkJ8d5RpCBd3NvHhPZdWPK+rOVTUHvrnn53nqk3t/IdrN3F6NMWRvglsRxVb9BU2H66CF/rjvNAf5+/2vcRNF3s9sa/c2MqYaRALeXUQhY52+44OYhcUYis8q57WEH0TWS/mYHgGQhA6mgJlsYNKz9QyDS7ujtEWDWqZbI1mmZjVOCil/gL4CxH5C6XUR+ZzA6XUfhHZMp9zVzql/ZznWtHWo0g6PXB9+z2PFc/tjIU4P5HGMARDYEN7lLyj+PCeS2c9b/o9Af5+fy+Kqd6tQDHjqbMpSN5VpHMOGdvloSMDPHRkgPVtYfbs6uGNl/XQ1RzimdPj/P2jL/HiUGKGVTCgGDRPZh0/u8oT6AtZBl3NoVl7ZJc+0z/9pZ0161XNFeBeTYZlNY9ds7qpya2klPqIiLQDO4BwyfH9C7j3+0XkN4AngT9USo0t4FoNoVrjF2BGhfBCVF1Lzy0orQ4nsmRst0z1dLbzpt/z7v292K6LKTLjPNuFwUQOAXatb2VHd4znByZ5vi/O+fEMX/rxSf73v59kR3eMgXiWZCaPKZ6RKUtSEogFTcIBk5ZIAMdV5By3GE9pDnuZTqU7rXqa6dQiJLiQHhKNZjWPXbP6qanOQUTeC3wQ2Ag8A1wPHFBK1dSL0d85fK8k5rAWGMZbWH4SWKeU+q0q594B3AGwefPma06dOlXLLRtGtZz8pqBJznHn1Xt4vn2LZzvvzFiK0USWdL56EBlgbUsQUww+cPMOulpCxZ7YE+l82fsKqbeuq4oKrpZpsK2zqfi5+yfSDCdyxUyrntYQAdOsWq8w16r59nse48RwgnjGJue4fnaXxdbOWPG5rOaez6t57JqVxXzqHGpNZf0g8GrglFLqtcCrgPH6hjeFUmpAKeUopVzgC8B1s7z3HqXUtUqpa7u6uuZ7y2WjXlXRWoKq9UhK1HrepvYordHArIYhYAqJjEMkaPKdZ85x9eZ2PvC6HXzrzuv5+JsvK8YbwHMX5R3PMIh4PaQvW9fCmbEULw0lOXhugqESw6CA4UQO13H46HcPFaU1Coqw13zy+/z2157kqVOj9E+k+dnpMf74vmfL0oSPDUwy4hcQmiLYjpeaW5oBVYvY4EplNY9ds/qpNVspo5TKiAgiElJKHRWRS+Z7UxFZp5QqdJF5K3BovtdaaVRz5Uyk83zyLbvm1Xt4vn2L5zrvY/cfJmgKuQoFa4UaipzjEgmYnB9P094UpL0pSCbvsCYW4rs/O0//ZIZk1mYyYwO+QKCCc+OZYiOg6SjwDSYMp/Js74oxGM/wx/c9iwJaIwESWacoKBg0PTmOsVSeux48Whx/4eeGH0UX8XSnSj9PPUkDlWikz3+hY9doFkKtxuGsiLQB/wI8JCJjQE3+HRG5F9gNdIrIWeC/AbtF5Cq8eeIkcGc9g17J1KMqWg/zPbfaeQXDcdeDRzk2mPDSYaHYfS5gGkWxvekTUjjgxRE+cPN2/vT+w7RHAzQFDQbjOSrYmYrkHe9+tqs4MZykMxYinrFBvC52OXsqLdZ2vQC2EkXvcLJ4jaBlkM45uH4qr/Kla0t3NPUkDUyn0T7/hYxdo1kotQak3+p/+3EReQRoBfbWeO7tFQ5/qbbhrT4a+Qdd7yq3YDj2HR0sGglLvLRWhUK50NIUqDr+1166lj8Xr+jv2IAn0ieuwq7RQBTelrddzk+kcRyFaU4LkBcm/Qrs6G7m5EiCsWSebN4zJgFT6IpNNQCa764L5tc3fDFZyNg1moVSk3EQka8ppd4FoJR6tHAMeNcSjm1V0qg/6IWsckuNRKEQL+cogpbBljWxmsafyDoYIjgFfe8asQTEF4hyAVzFkb7JouEoXKoQ6N7eObWDufOmbXzwmz8jU7LL8HSjsmWFdfPddS20b/hisJDdpkazEJa8QvrlyHL+QRcm9KdPj/kZQOFiILzeVe50I3Fmjknwb35wjM/vewnHVb6uU7kCbC3YChx7KmPKLQQtpqFQtEUDfHjPpWXHk1l7qiLb33QUJEwW+v9gOXz+uo5Bs1JZjgppzRJRultw/ZjB+fEM69ugORyY1yq31tqBT+99nqMDCQACRUXZqcK3alj+G7zJXHDcykJ907FdRTbv8IFv/IygZbCju5mxZBYQQpZ40uN4EuYTqTxnjYWv7pfaRdjomIZGMxuzprIqpf5CKdUM/KVSqsX/alZKrZlvxbRm8Sj1iQdNA0EQgSFfpK7SKreQKnrjXQ9X7Mw2l5hgYUI7OepNvoWAcUH0b3bDIFy6rpX1bWEUsKE1xPQQQzVc5X2eZM5mOJHjpydGfOOkyjYaIpB13EVZ3S91p7nFEG7UaJaKWt1K3xORJqVUUkTeCVwNfE4ptbIr0i5wSn3iBVkNUV7jnkq1ELWsVEuvOZnOM5zIknNczo6liy6QgOmt+EvndVcpAoYUmwMJnjFw1JQMue0qeocStEQsLu6O0d4U4vRY5XTXSrjulNSHKl4THFxM1yu6c5TCMoxFW90vpYtwJcQ0NJpq1FoE93dASkSuBP4QeImZQnqaZaa0L3VLJMD61giGIZiGUXGVW8tKtXDNyXSe8xNpbD/lVPDqIo4NTBIJmARNo0wi3PWr20KWQUvYwhDPGEyPQSRzDgOTWW69Yh333nE9IcuoffdQ8r2a9r2jIGd7DZHet/uiVeGWqbX/uEbTCGo1DrbydDbeAvytUurzQPPSDUtTC9MroC1T6G4Oc/c7r+HOm7Zx9/7eMvfRmbEUtuPSO5TgaP8kvX4TnenCd3lHMRDPeDsD/z89rWECfvOgdN6hMxby+lr7/aLBE9QLml7faEdVdzEpBXsP9QPQHDJrro2YDRGIhS3ufuc1fOD1Fy/8gsvAfCvfNZrloFbjEPeD0+8E/q+IGEBgjnM0S0w1nzhQsUMdrsu58UyZ3MS58QxNQXPGNZXyXEWWIaxvCxcD3EHLIO94hmh9axjL9NRhA6awtiXEK9Y0zejaNh0FvDiYYN/RQUZT+arvEyAgc/+SmgLrW8NEAwZXbW6b8/4rhaWOaWg0C6HWmMOvA+8A3qOU6heRzcBfLt2wNLVSySdeTaq7L+FJXBT9RACKYqZP6TWv3txeMY1zR3czN2zr4Is/PlFsINQVCxG0DKJBi3gmX5S1mA3bVdy9v7dqSYQAuza0Al7so38yTc6unNnkKDg7niFkGXz+kRd542Vr2dTRRCxs0RQ0Z3y+lUTh/10hnbXg4tMGQtNoato5KKX6lVKfUUr9yH99WimlYw4rlGqCbVnbpSMaIO+4ZPIuecd7ncjaM65RzeVR2kDo0p5muppDnJ/IYDsu8Uye81X0lKajgMd6R4qTvcjUV4HJdJ7eoQTnJ9JYhsGapgB/8PodZTGK0mk/a7t84Ucn+PV7HuP3v/kM//zUWV4aTDCcyJK1y337K4XF6EOu0SwFc9U5xKnsOvY7VKqWJRmVZkFUK94KWQajqTwBc6rv9Ggqz47u0IxrVKr0ntox2IQts9iTIWAKA5NZTz5DPF2mXA2unaIeEoXOcFO/bAo4O57GEgHlBbKTOYfP/uA4AVPoiARI5RyytoNpCJ1NIX7uojX84MgAkxmbA70jHOgdoT0a4A2XreXWXevYvjZGczhAc8gqivU1mlolOnSxnGa5masTnA46r0KqFW91RCz647nyGRivD3Ulprcu9a7pYBle0LlQcLe2OcTZ8TR510tfFcT/V5GfxUaICCaqGJAu7iL87x1XIYbngiqggJyjGEvl6Yh6Ya+s7TCUyPLai7v4z7+4nS//uJd/fa6PeNZmLJXnW0+e5VtPniVgCj0tYd5741b2XLHOi6MEy3dYy00t6ay6WE7TCGoNSGtWEVUD1YbBhjYviOz42U0b2sIkc3O7XAor3JBlgBIMmSq4s0yDHV0xmoIWjot/3Qg717ViGr67iCkXUOHfsGWwqSNKsOS3MGwZbO6IFtNkSw1D6VrfdhWDiRxZ29N0MgzhL79/jAcOnmf/i8NEggahafN+3lGcGUvz8X89wu/+49M8dKSfU8NJxpI58g0KYteSzqqL5TSNoNaAtGaVUSlQvWm/527a1hUrHit0FpuLwgq3MxbizFgK5Xir+Cwwkc7zV7ddCVDWBS+Vs7EMg0jAIJlzMPD6QxQa/nTGPLdURyzEQDyLZUjRKIQtg7zjlvVmqLS/8TT3FCEgZzt88ccnaAqZjKdswNu9FM6LBAwyfue7p06P8dTpMTa1R7ye2Jf3sL4tQnPYoim4fG6nWiQ6dLGcphFo4/Ayoh6toOk+7ljQLFvhlk7UhVV3pTjFW65cz31PnyMccIhnbK+iWUFrxKI5bDEUzzCUyBX1mbz02rSnwlrHZ8s6iv7JrH8NFxEwxCDvlK/Kt3U2MZnJM5bKY7veTuKeH53giz8+wfXb1rBnVw83bFtDSzRAc2jp3U61qPjqpj+aRlBTD+mVwrXXXquefPLJRg9jVVOY9GeTE6/UB3synSebd4hnnTLDUOjotqM7xodu2VkxaFroF9E7nPTUWylUNU9VUBcW6qYhNaXCzoYAoYCnNZW1nWJPa9MQLlnbTCJr0x4N8p93X8TeQ/384PmBYic7gPZogDdetpY9u9axrSvmpcSGTEJWY+IT1fqS65oITa3Mp4f0khsHEfky8MvAoFJql3+sA/gmsAWvE9zblFJjc11LG4fZWayMlkqN7YcTGYYTuRkTd9D0pnqloNVPi3V8Ib5YyCpzN8UzOcZTdvX0N8ozlgoSHbbr1mUwRLzAuFfo52Irr1AuZBm0RgOMJvM0BQ22d7fw9ldv4rL1LfzkpWEeONjPU6fGysa3a30Le3b1sPuSblqjAWIhi1jIwjKXN1xXi1HXaKqxUo3DTUAC+GqJcfgfwKhS6tMi8mGgXSn1obmupY1DdRZzdXnjXQ/TFgmUFY+9NBgn56iixLb4s7jnvin4/qcE9wzxgt7bu5pobwpxciRB/0S2eO70X7vC9UoPC1MTvasUbdEg8YyNq9SsxiIaNIs9JkKWQcAU0nmXkGWQtV3ao17spPCMPvZLl3LVK9pJZGz6JtL82+F+Hjw0QP/kVM1GJGDy2ku6uGVXD5evbyHqG4knTozyhR+d0CmmmhXNijQOACKyBfheiXF4AditlOoTkXXAPqXUJXNdRxuH6lRa7ReCzffecf2Cr3Wkb4KwZWI7Ltk5VvGCV+sAChGhqznEaCJLys9rrWQcKl6nxGCYBjQFLeKZyjuPUlrCFu+9cWtZFfd7b9zKgd7R4ucqKM5mbZdo0ORv3v4qbrq4i3jWJp7Jk8k7PHN6nL2H+tl/fKjMGIUsg5sv6ebqzW18+ScnCZpCU9AiYzvYLjMMsq5R0DSKwu/etz96ey43eGJmQdMsNMo4jCul2vzvBRgrvK5w7h3AHQCbN2++5tQprRJeiUqrfaUUE+k8P/rQzXVdq9Iu5OxYmvZogJBletlKswjrgbebsAyvCc/Vm9t5/OSIr9c0zw8INAUNUjl3zvs2BQ3am8Jl459I5xlP5VF4LUenX6MrFuQvb7uyOGln/DhLMufwyPOD/PUPjxV3GqUE/XJtx/XaqsZCFu3RAGtiYc6MpWgOWQwlsrRGAhdsvEAbv5VJ6d/xjz797lRu6FRTPec3vM7BV3ut+veulLpHKXWtUurarq6uZRzZ6mIx5Z8r1Um8b/dFBC0TyxQ2tUcIBWb/1XEVRTfUWDKLIVJPa+mKpHIusyWYhkyhuzmEo4TByQynR1OcGE4S9w1DwdU0fRgCjKXy3PXg0eKxcMCkuyXM5o4oDxzqoy0aYOuaJja3R2iLBIoB9JyjvM+pIJt3GU7kODaY5Nx4iljIoncowXgq70mfX4A1Clr+Y+Uyvfq+XhqVyjogIutK3Er6N2mBLHZLy0p1Eq/c2FYMim7piHJsMDHrDsLACwS/OJREqdnbgRri1TakqpRUlwaqAyVNhArFdZetb2E4kWUkORU0L8iHDyVyzBU/NgR6h5MzjpuG0D/pTXyugqghhAMma2IBXhpKlY2rdOTZvEveyRVdcKdHU2zuiNASCV5QNQq1yn9olp9K9TH10Kidw/3Au/3v3w18t0HjuGBYDvnn3Tu7ufeO6/nRh26mvSlE0DSwTCmrfi5gGVLsBWHVUFDmKqoaBvAmaUPKU2ANgbaoRSxs0T+RZiyVLxtL3lFF41UImAfN8rHUUupW2JWZhhAwDQKWge2CJZ7xswxmGJ+BeJa+iWzxtcLr7z2WypHM2RdMjUI1kccLxfitZip5E+phyXcOInIvsBvoFJGzwH8DPg18S0TeA5wC3rbU43g5UG9Ly4X4is+MpVjbEqJvIotlej73gtsoFjJQyusXUag0XohHqZC15PoTfCFuIQKTGYcP3ry9GGw+PZrCMiDvFnSYpgxOyDL8dNmpXUwhfdZVsL1z5oS97+gg46kcJ0dSXs+K5hCWaaAUbO+OMZbKMZmxyTsuYcur0VBUjq04SjEwkaazOcyvvmoDY8kcsbDlB+/L77lafPi6QG/lUupNmA9LvnNQSt2ulFqnlAoopTYqpb6klBpRSr1OKbVDKfV6pdToUo9DU85CfcWb2qNYpsH6tnCxHiFsGVza08wVG9rJ2l6VsuOqYiFarQiF+gmPaNBkTVOwqNFUCHaHLZPu5iAHekc5Phinb9xra1ptAxIJGriuYvpGJmAKbdEAH95zacVnlHNcNraFQXlKsQFD+MSbL+fDey4lFLBY1xpmR3cz3S1hWiIBWiOB4jhLcZVntDqiQXKOy3Aiy5nRFH0TaSYzeVxXrTofvu5mt3Ip9SYgRt0bAV0h/TJloamvs9VVANz5j09hO27RKNT7WxYOGORstxhXaA5749zcEUVEiGfyDMW9Pg2CFP1DAmV6TCIQMAxiIRPbzyjK2S5KuYgYBC2DHd3NFVfntTyj6cVp/+nnt5DK2fzXfzlEJu8UM5hyjiKeyZcZyTVNQd54+VpuubyHTf7n+qNvPctoKkuTL7JX6Z4rDV2gt/KZT52D1lZ6mTIfMbfp7o7brt7Agd7RipPC+3ZfxGd/cLzotjGFunpFZ/zlf0H2Iue4OK5iJJklZJmcH8/4BXhe0BkXDL/4rtQUhUyDntYwsZBVd1pvLc+omiuvORzgY/cfxjQ8d1Ym7xIJGFyytpmnTo+TyNqMJHPc+/gZ7n38DFdsaGHPrnWcGUvSGgmQc1wM8aq8F+rDX2o3VeEZFO7z0e8eYtN+bSRWO9o4vEyp11c8vafAyZEET58eIxYyuXhty4yJ4AOvv5ivHDhJJu+Sc1yCpkFT0GQwkat4/ZKupRgy5bN3FZgKlAuOoxhO5DCL1XFSNAPFwPg0V05Pq6c4++JgAoW3Gyi4POaaMBfiT3/dZWsxDeHvH33Jj8+EuXJDKw8eGfArtD0Zj2TWxlFw8NwkB89NYggksw4dTUHCloErQsZ2WNsSJpN3CAfq03da6l4QBYNwfDBOPGMXq891z4nVT8PrHDSNoV5fcWnKYiJrM5LI4ypFJu9W9YtfvLaFntYwO3ta2NYVIxK0ii0+g6Zglfz2WaYQDhj0tIS4fH1rWe8Hx0+DVXgZSFnHxXYVedfbTYCn5ppzFBm7POBwZjTFmdEUtqvoafEmrT++71n+6L5n5/TrF57RcCLDS4NxjvRNcHYszQ3bOuZ8vkVXy3iazR1NfODmHRzpixP03XBB06SnJcy61jAXdTbx2ku6CJiC63e9OzOW5sUhr14ik3e57eqNnB9Pc2Y0xWgyV3Pb06XsBVEaH0llPVmTkWSOeMZesnqOfUcHuf2ex7jxroe5/Z7HVmws5kJAG4eXKfWmvpamLA7Fs4iAKZ67p9pEMN0ADcQziHgZP16r0qkg9vFP3cqaWIjO2LQKf38XkS/pAxEwvEnUwAtcK8+rNCOuUXBlOb7wnoiXQTWSzDGcyNE/kZl1Itu9s5vbrt7AaDJPzlGELZP2aICvPnaKPX+9v+oEVS2o/OJQnOZwgKDlBfARiARNkjmbP/3ly/jILTtpCVvFtFgFJHMuQ4ks3zvYx2O9I2TyDuOpHOfGPEMxnpq9UdFSppqWGp68L7ZoIAwnsot6nwKrLVi/EigY00DXlivqPVe7lV7G1JP6WupiyTkupiEodyqrqNJEML1XgVKwoS1MSyRI4a4FiY/p9wj6InnTZ/xQcbuhcADlVJfTKI1x5F3FmdEUIlJ0WdmO4vxEGvAC3pUmsgO9o2xsjxRdS5PpPMPjaRIZm+3dMU6OJLjzH58qc69VKwzzdiFZ4hmbnOMSMIRY2GJjm+emuv/ZPlojAXp8F9JExmYyk0cp+PGLw/z4xWHWxIK86bK13LKrh43tUUaTOUaTOUIBs6gYa5akSS1lqmlpTCZoGtiuQmQqfXixU1qXo+BuNaURz0WpSxHl1p3PqncOmpoo3QUEDMFxFS6quNKvNhGUFs5dvbl9htR16Xml9+hpCWFKuW2wDGFtSxhHKQKGJ95Xa5Db9d/ruKpYKJf3pcDPjKUYSWYrjn/6yns4kcUQz9VVzb12bGCy4mpdKa9a2ws2ewZrJJln9yVdvDiQ4EjfBOfG0xwfTHBmLE3OduhpDtIasbh6cxsAI4kc/+fxM/zGl5/g9775DP92uJ903iGbdxhJZDk9mqJ/IkMi6+3WljLVtLTIqqs55P//UARNY0lSWpe64O5C25ksVD5DGwdNTZS6oaIhC0OENU1BmsNWzRNB6UQ1mc5xfCDOyZEkY8ks+44Olt3D9RsIXdrTTMDw+lW7ylt5myIgMqOOoBZUyVdp0HswnqsYS5heZVpYFQdNo6p7Le+oijpXIkJ3c5CgaeAq7xrdzUEeONjHnz/wfHEshfHl8i6D8RxrokH+6teu5OvvvY7fuP4VdDd7Bvm5sxPc9eAL/NrfH+AzDx3j+b5JXNcllbMZnMxwaiTFZRta+K97dtIVCy165Xzp/89YyGJNLIAhQiRgLEmF/mLqh1XiQuvVXcmY1oN2K2lqptQNNZ/c9oKb6a4HjxYrjje2Rci7qiyzpXCdv/nBMf5+fy95fxY3xYs9FMTzFqtER/BUWQ/0jvKBkuP7jg4ylsxyciSJARiGge1XQLdHLUZTuYrutaBlFCfN0hqQoGWwpilEZ2yqZ7dSiuODCTa2R4ppuIVkXAcwoZiCta41wm++ZgvvuuEVPH16jL0H+/n3l4ZJ5Ry+91wf33uuD9PwYjq/9Zqt3HxpN4mMzY6eZu667ZVEg57bKTyHaGIl1wpUzu4qdRtuWRPjL966dG6YxdYPm86F1qu7kkuxHnQRnGbZqaW47G9+cIzPPfxiMRupgCEQtAw6owHO+c2DFkrIFHasbS6rgyj1106mcwwlvLiI5bu6RARTpsT21rdGaIkEip+jEHsoNZ537++t+LnPjqXZ0R3jhYE4AtjulKjg5o4Ijqv4l/ffSMJvdFTKRDrPl398gr2H+r16jxJ2rW/hHT+3mVdv6SjGIR7vHeWbT56hfzLDpvYo/3n3RTN6T1RqEatgRciOL2XB3WL2RFkJLFSyW+8cNMtOLSu0L/74hFfvAMUiiMK8uL0rxkQ67/v+Fz6erKM4O5bi0nWtxWOlLob+iQwh0wBftqMzFmIgnsHxtaPao4EZ7rVKu6xjA5Mksg4dTQHWNE11otvW2UQ67xSDuiHLk/mwTClKlHTGQnREgyRyNhOpfDFDqTUS4Mxomp6WEIYIE5m83y0PDp2f5E++c4jOWJA3Xd5DJmdz/3N9uH6leN52+JPvHOTDt+zkjbt6CAfMikHfc2NpEG/nUjjWKOXVevXD6mGpdybLTenObj7yGdo4aJadWjJokjkHy/AD0iUGwFXee5uC5qyGobxOem7G0zY9LcHi61IDlnO8rClPJwpIZFnbHMJV8Mm37Jp1JVu6elvXGmE4kWU0mSfvqKJsB3g9tlsiFsPxHK54I28OB8omJ8MQWsIBWsIB0jmvgVEqZ9M3maYlbCF4cuJdMUU8azOWzJHzCwe//tPTZZ83nXfJ2i4dUfjyv59k18ZWAqbByZEk7dFyw227blkTKVjd7pZqTHeTXQhSIAVjKneePFjvudo4aJadWlZoTUGTRLZy9t25sRTN4eo69QK8Yk2Us2PpGa6W2bj/uX7ecpUXGC81YIYIWcctiunZruLceIYd3bE5V7J37+8lZzuMJOxipXh7NMDWzliZq6IwKeWdODnbJWgKWztjVSenSNAkEjTJO25xrGHLCz4aIjiOS8A0aI6YWCIMJbIzxA9dBWPpPKbhTfJ5x2Vtc5iRZJZo0CrKpFuGMUPb/EJVXl3KnclqQxsHTUNoCprF5jpb10T501+6rOyP8r03buUzPzhe8dysrWgzhJApFftZF2ohpktpzIVTEhgvkzv2/VkKsMRL47VdxfHBeFGOo9qEcmxgksmMjYGnk1QowrOdybL3zXdSCpgG73/tdv70u4eKxmc0mWU0lac5ZJHMeAV81Wyk48JE2uafnjrLGy7t5u2v3sTnHj5OKmcTDniaUNGgCQLJbJ5o0Fr17hZNbeiAtGZZmU3NdfrkeNnHHiSVm0pdNEUIWEIm79IUNOmMhWb0szYE2iIBJtL5uuMRhsDWzqZiALIQK3j85CgmCsMwyLuqKPstAq9Y01Q2/umZPs+eGSfvut7q28d2vVX9lRvbFq3YqjRQO57KYYh4z84fZ86e+2FYhvDzF63hos4YT58e4/RYipztEjCFjmgQESGVd9jUHuV3fnEbN1+6tuzeF0Lh2IWKVmXVrHhqrXLdd3SwLFPJa8ijcFzv+6zt0hIJsIkow4ksWdtb4b5uZxf3P9c/r0B1SzhQ5ksvrOZLs1h6hxLYjioGp0vHD8wQucvYDkqB7ThF+Q8BHNeZUWw1H5G66RPzJ9+yi49+9xCjiWxRtXZq3zOTjqjFa3Z08fDzgyRzDvuPD7P/+DAtYQtXKVrCXqe9TN7Fdl0+ePMOrtvWgYjXp/vpU2N86oHnCVrGkgj7aRZG4fdj1clniMhJII6X0m3Xa9k0q49ac8nv3t9LezTAwGR5uqrtKNqjAZI5h1TOpjlsYfmFZ7ddvYH7nj7HfPrOFWooKvnSS11MOT/2gBK6/GK0wvgrGT7LEHKOJyshvnVwFQSN+mUgphuCG7Z1cN/T52YorjaHLPom0p5+FQJKYVDe49oSaI4E+C9v2sl12zr43V+8iB8dH2bvoX6eOTPOZMaL9ySyDpG0TWvEi0F844kzXLetA+VXiP/9o71ezwxf46rSZ9E7i8awUPmMlbBzeK1SarjRg9AsD7Vq/ZwZS9EZC+G4XrZNYdVtCMTCAX7z57fM6CVx14NHGZzMMIsOXUUsAdP0pLEr+dJ37+zmtrPjfPHHJ8g7XpFad3OwGBQvjL9iQ3ffbRs0DMQPZtvKU5DtHUrQGQvREglUNJClk2pzyGIokaU1Eigags/ve4mOpgCtEa+orjAxK6WwDAPHVZj+PUsfiSEghvArV67nOr8qPBwwecNla3nDZWs5N57md772FFnbU79N551iZXLfRIZvP3WWX716AyJSzJRyfTkVXE8Y8cxosvgZKkmG33Z2nAO9o9pgLCELlc9YCcZB8zKi1lzyghHpafVE70pdR4UmQ9MreI8NJjz1VarvHbpjQYaTOU/V1V/FhwImWdulKWhVjH3sOzrIfU+fo6s5RHs0wLnxDCPJHOGAgWUaxfFXKnJz8IrsLFPI2C5uiausIPyXytnEszZKwZ6/3u9rMGXLaiJeHEx4wnZA/0SGnON6we14tqziOhIwmUjned/ui/j8vpewXYVTElcMW17zIxF49twE76rwjDa0RdjR3cyZ0QTjGbvM2LoKPr/vJb7wo17eeFkPXU0hJjL5KZkGBcm8Q2cszJnRFH/7yItYBmW7pCHfsG1sjyypK+rlvmM5M5bCFOgdSiBmIFLv+Y3WVlLA90XkKRG5o9IbROQOEXlSRJ4cGhpa5uFpFptapcJLdXuawxY9rWHWt0V4741bue/pczP89Xc9eJSAKZ4bpQqmwNrWCJs7osW+101Bs3jtv3n7qypOHqUrsJZIkA1tESxT6J/Mlo2/ksidZRi0NwXZ1hUj7Et1F0aYcz1jMZzIYTuK1rDF8cEELw4lSWQdrz9CotAO1VvFDyVyZG3Xb3gEOddTii1Q2MV84PUXc/c7r2FHd6xYPBg0vfjD+fEMrqsYintigy2RgC/dMcWrNrUylrar7sJyjuJ7B/s40j/JUDzLaCqHqzy3nO0q3v7qTeQd15ugDCFn+7InShHP2Niuu6QaRheaiN58aA5ZnBvPFNK56/a1NnrncKNS6pyIdAMPichRpdT+0jcope4B7gEvW6kRg9QsLrWkbVYrSKoW0O4dTtLTEuL8RKZ4jcIOYsuaKFnbYTSZLxOJG03miyJxs60qp7uLWiJeRfREOl9Wq1BpzG+5cj33PX2OVM4mY081J7J8ZdtCLtbG9ghD8awnc6EgZ7uELK9iejCeLRuP4yqvhajhtUgdiGdoDs9MMd29s5u79/cSDniaUJ4sh3f/U6OeO+gnLw6ze2c3HdEgcV8iPO+4/OzMBGuaAkXZkFIsExx/4K6CjO2SSXjS4V2xEL9xw5aiu2pdS4SRZJZIwEvjBbze2qaglCoW1y12Ud1yyHsXWKk7lGIm6jxnzYYaB6XUOf/fQRH5DnAdsH/2szQvFyoZkY9+91DFgDbgSU20RuifSJP1BfJCpjeJBkyT9+3eXIxT1CMSV09PhEpjfuXGNu7e31us6yjsWgKmdx1DvGroc+Ppsl4MSnkZWso/J1eyjM+7LgHDoDsWYCJjM5HOV6zo9eIVZsVJ3jQoc+e0RgO0RgMkszYnRxJeP40KeJXYwvq2MMPxHFu7mnjmzASugoF4lr/8/gs89PwAt17Rw3+4egP/69GXSOedYt2E4fexKPTJNkTI5O1FLapbLhG9hbRhrdeo1Pv+RM5hQ1uYYa81b90axg0zDiLSBBhKqbj//RvxCkU1mqpUm6i3romSyns5+TvWNjOcyDKWytMctsp2Bh+Y5drVWKjmTsFgXPPJ7zOZsb0djVIoX1xvyu3j7RRQngvIZUqAr/Qvu+AkMARGUjmaghaffMuuihPFpvYoPzszhiUwvdQhZ6uiO6f03CdOjJLOuziuW/E8FHQ0BcnZiq2dMT7ztis5N5bmwcP9/NvhfoYTOZ45M84zZ8ZpCplcsb6V0WSOiXSOda1RXr+zmwePDJDOeQYjmXeLrqh0ziESnL/MdOnnXqomR6XMd4dSr1GZjxHa1B7l+b4JL5lguv5JDTQy5rAW+LGIPAs8DvxfpdSDDRyPZhVQrXnNh/dcWhbL2NoZ4+53XsOTH30D995xfVlaZb09iOttqVqNi9e2sKYpiGUKjvKE9SK+fPaRvglsx8V2XByl6GkNs6Yp6NcqeD22u2JBAqYU+3A7ynMvRYNmVX964XkZJTsSwTM+Ocetmkbc0RTAEAPTNChV+A4Y0NUcxBApTugAG9ojvOfGrdz729fzF7+6i5t2dGIZQjLr8NiJUY4NJmgKB3jNjjW8+VUb+ODNO1jTFCKesVnTFOKDN+/gio2t9E2kOT2SYiSRrblPdiXqbXI0397U821AVG/viPn0muhpCTKe9kQY5+NaatjOQSnVC1zZqPtrVidziaMt5mpt+n3n40eeno5qu97EHwmYDCeyDCVytEUtcrYia3sul4Ko39bOGO+4bnOxliESMDENYSCexRRvp1FIha22Wt29s5uLu2OcGE5SKIfz+nd7KafV0ojXNIUIWSZD8Sw5JUQDns7SpetbOTvq/fztr95UjC0UMA3h57au4ee2rmE8leOh5wfZe7CPkyMpeoeSfP6Rl7hnfy+vuaiT239uE1dvbi9zpYFXQT6RdplI5z19qLBFU8giYNa+lq1HRG8hvxfz3aHU6/aaj5vsh0eHihl59TuVGh+Q1mjqZr4T9XIGKWHmpJPOOwjepOwpqjp0NwfLUlEr9Q8oxCzOjqXY2hnzDExLuMxTMNtE8aFbdvKx+w97AoDJHAqFcqGlKTBrGnFzOFCs5Zg+rkzeU4VNVhFHBGiLBvm1azZy29UbONof5ys/OcWTp0bJO4p9x4bYd2yI7uYQb7p8LXt2raOnNTzjGnnHnbNPdjVm+z0pNdqT6TxNIXNGvchdDx6d08c/X5djvUZlPkYokbWramrVQqNTWTWaZWOpexBPp5IroCUSoL0pxI8+dDMtEa+GYa7xlPbhvveO69nR3VxXu8yCW2xrZ4ywJX4/bUUy63Db1RtmTSOu5pIJB0zWtoTZ1FE5FbYUESGetjkzlmJda5i1zcGiOOJgPMvXHjvNO774U/7on57lh88PkM1XdicV+mSfGknSN5EmnsmX1Y3UyvQ011TOYTieI56ZCtrbjsuxwcScqbDzdTnW6/aaTy/whcrm6Z2D5mXDcgUpC8zlCpjveOazWi1MVh+7/zDdJaKH9z19jldubCubzOpxyQR819b0VNjpfOOJM1iGFI1zayTIZCbv6U4pxUgix9Onx3n69DixkMXrdnaz54oednTHKsZS0zmHdM5hWHJEg96OIho0a4q7Tt9BhiwvE2woni3ulAYmszXvMuezk623d8R8ek0sNO9fGwfNy4bl7vQ11+Q/3/HMtylNPW61eic8w5BiKmwiazOZzpMp2QEUZDZKaQ5bxDM233jv9TxxcpS9h/r5yUsjJLI23332PN999jwXdTWxZ1cPr7t0La3TpUnwsr6SWZtk1vaC86GCoSi/V6kbaSiepadlasfWGQtxfiLtiyR6ciF512VjW3lR8WLvMut9xsvda0IbB83LhuXu9DXX5L+Q8cxnoliu3P9CXCCTd5jM5ElmnZJiuCm3Xibv0tMSwTSE67et4fptaxhL5fjBkQEeONTPqZEULw0l+dtHXuJuP4i954oernlFe0U3lqsUiYxNImN71e/+OB57aaQs9jMcz3JuPAMILZEALZEAWdsh5XfX29geJWAI+Wkuqwu1wVE1tHHQvKxYztVXLZP/co5nud1q4YBJOGBiR13ec+MW/vveo2XFcKWpsAXao0F+7dpN3HbNRo72x3ngYD+PvDBIKueUBbFvubyHW3b1VAxig1dFPpnOM5nO87kfHscQbzwiQk9rmLNj6bLK8qBl8ulffWVZyvNq7yddb6vcGefrZj8azcuDehotFd6/mLIQjzw/wP969CXOjqZY2xKpmApbiXTeYf+xIR442M/BcxPF4wJcvbmNW3at4xd2dBK0KufX3P6Fx4o9tkW8lNxkNs9APEd3c6jqjq20gdJq7Cf9+994mu880wdA31d+j2zf8boSWrVx0GheRtQ64dVrSOollfMkP9K5+grdzoymePBwP98/PMBIMlc8HgtZvO7Sbm7d1cOOtc1l5/zBN5+d4dJK5x06YyG+9JuvpilkErIWXpW9Ern97p9w4MSYNg4ajWZxKO1+V6BSDcZCydlesVsia1PPXOS4iidOjvLAwX4O9I6UdQ3c3hXjll09vP7SbloiAR7vHeVzDx/HMqTMpVXoagde1lUs5HW9q6fYbiVTauB/9Ol3p3JDp5rqOV/HHDQazQyWK3gdtAy6mkN0NAWJZ/JMpj0577mYHsR+6MgAew/2c2o0xYtDCf72kRe5e/9L3Li9kz27evh/X7udbz15lv7JND0VXFp5x2UslWMsVX+x3UpFN/vRaDSLznIHr01DaIsGaYsGK6bCzkZ7NMjbrt3Er12zkef74jxwqI9Hjg6Rzjs88sIQj7zgB7F39fBfdl1CT0vlIHaBbN4pFtxF/BqKpqBVpk+1GqjYmbAOtHHQaDQzWO6akFIqpcLW4nISES5b38Jl61t43+7tPHpsiL2H+jh4bpLBeJavHjjF1w6c4upXtLNnVw83bq8exC4wvdiuKWTRVGOxXaOpZODrQcccNBpNRVZKto7tuExmbOKZfFlsoVbOjKbYe6if7x8ZYLQkiN0c9iqxb71iHdu7YzVfr7TYLhJYuYZioTEHbRw0Gs2qQClF3Hc55ao0IpoNx1X89MQIew/181jvaHkQuzvGHj+IXZDQqAXT8Hz6sZC1KH0oFpuCgf/2R2/P5QZPhOY+YwptHDQazaoj7Vczp3LVVWFnYzTpB7EP9XN6dCrIHjCFX9jRxZ5dPbxqc9usgoLTsQyDppDnegoHVpahEJGnlFLX1nVOI42DiNwCfA4wgS8qpT492/u1cdBoNKXkbJfJTJ5Exi72x64HpRRH+ibZe7Cfh18YJJOf2pGsbZmqxF47RxB7OgHT8OITK6SGYlUZBxExgWPAG4CzwBPA7UqpI9XO0cZBo9FUwnFVXamwlUj7Eh17D/Zx6Pxk8bgA1/hB7NfUEMSeTqGGoilk1X3uYrHajMMNwMeVUm/yX38EQCn1F9XO0cZBo9HMhlKKpO9yqtYXohZOj6Z48JDXE3ssNdXnoSVs8bpL13Lrrh4uqiOIXSBoGTSHAjSFTKxlLLZbbcbhNuAWpdR7/dfvAn5OKfX+ae+7A7gDYPPmzdecOnVq2ceq0WhWH5m8w2Q6TzJXWypsJWzH5acnRnnwkFeJXZostaM7xq1X9HDzzvqC2AXCAbOoHLvUxXYXpHEoRe8cNBpNvSw0FbbAaDLH9w/388Chfs6OpYvHA6Zw044u9lzRw1Wb6gtiF1jqYrv5GIdGFsGdA0r1ejf6xzQajWbRsEyDjqYg7dHAglJhO5qCvP26zfz6qzdx+Pwkew95cuKZvMsPjw7yw6ODrGsNc8vlPbzp8rV01xHEXkhnu6WikTsHCy8g/To8o/AE8A6l1OFq5+idg0ajWQzSuUL19fxSYQukcjaPvjDEA4f6OTwtiH3tlnb27FrHz1+0Zl6B6MUstltVbiUAEbkV+Gu8VNYvK6U+Ndv7tXHQaDSLSd5xmUznic8zFbaU0yMp9h7q4/tHBmYEsV9/6Vr2XNHDRV31B7Fh4cV2q8441Is2DhqNZilw3anq67wzv1TYAoUg9gMH+/npifIg9sVrY+zZtY7X7ewmFp6fV7+0BWqtxXbaOGg0Gs0CSeVsJtP2vKuvSxlJZPm+X4ldGsQOWgY37fDkxK+cZxAbpqqyY2Fr1mI7bRw0Go1mkVho9XUpSikOnfOC2PteGCRTEhBf1xrmll093HJ5D13NdckflTFbsZ02DhqNRrPIOK4ikfHams63+rqUVM7mkaND7D3Uz5G+qSC2IXDtK9rZc8U6btg2vyB2gaA1ZSgCpqGNg0aj0SwlyaxnJGptRDQXp0aS7D3Uz0MVgthvuGwte3b1sG2eQewCzeEA3S1hbRw0Go1mqcnankRHrY2I5sJ2XB7rHWXvoZlB7EvWNrPHr8SOheoPYocDJhvao9o4aDQazXLhuKqYCrsYLieA4USW7x8e4MHDlYPYt16xjis3ttZc96CNg0aj0TQIpZTX+zpjL0jwb/o1D56bYO+hfh59YagsiL2+rVCJPXcQWxsHjUajWQEshuDfdJJZm0deGOLBQ30c6YsXjxsC127p4NZdPdxw0RoCFZRetXHQaDSaFcRiCf5N5+RIkr0HvSD2eHoqiN0aCfCGy7rZs2sdWzun2kVr46DRaDQrkELv64nUwquvS8kXg9h9PH5itCyIvbOnmT27enjtzm46Y6F5GYdGqrJqNBrNBY+I0BIO0BIOLLj3dSkB0+AXdnTyCzs6i0HsvYf6OTee5mh/nKP9cf7Xvpd47SXd87q+Ng4ajUazTESCJpGguaiCfwCdsRDv+LnN3H7dJp47O8GDh6eC2A8e7p/XNbVx0Gg0mmUmYBqsiYVojwYXTfAPvF3KlZvauHJTG+9/7XYeeWGIfzvcz3z6Z+qYg0aj0awAUjmv+jqdW5xU2ALzDUjrnYNGo9GsAKJBi2jQIme7TKTzJLL2oqXCzgdtHDQajWYFEbQMuppDdDQFiWfyTKYXr/q6HuYv+7cAROTjInJORJ7xv25txDg0Go1mpWIaQls0yKaOCN0t4Zob+ywWjdw5fFYp9VcNvL9Go9GseESEmN/5LZMv9L5evOrrami3kkaj0awSwgGTcMDEjrrEMzaTi1x9XUpD3Eo+7xeR50TkyyLSXu1NInKHiDwpIk8ODQ0t5/g0Go1mRWKZBu1NQTZ3ROlqDi2oMVA1liyVVUR+APRU+NF/BR4DhgEFfBJYp5T6rbmuqVNZNRqNpjIFwb9Etrz6esWlsiqlXl/L+0TkC8D3lmocGo1G83Kg4HLqWCTBv4bEHERknVKqz3/5VuBQI8ah0Wg0FxqWadDRFKQ9GiCetcnZ80uDbVRA+n+IyFV4bqWTwJ0NGodGo9FckBQE/+ZLQ4yDUupdjbivRqPRaGqjkdlKGo1Go1mhaOOg0Wg0mhlo46DRaDSaGWjjoNFoNJoZaOOg0Wg0mhlo46DRaDSaGWjjoNFoNJoZaOOg0Wg0mhmsqh7SIhIHXmj0OKbRiSciuJJYiWOClTkuPaba0GOqnZU4rkuUUs31nLDa+jm8UK+y4FIjIk/qMdXGShyXHlNt6DHVzkocl4jULWet3UoajUajmYE2DhqNRqOZwWozDvc0egAV0GOqnZU4Lj2m2tBjqp2VOK66x7SqAtIajUajWR5W285Bo9FoNMuANg4ajUajmcGqMQ4iclJEDorIM/NJy1qkMXxZRAZF5FDJsQ4ReUhEjvv/tq+AMX1cRM75z+oZEbl1mce0SUQeEZEjInJYRD7oH2/Ys5plTA17ViISFpHHReRZf0x/5h/fKiI/FZEXReSbIhJcrjHNMa5/EJETJc/qquUclz8GU0R+JiLf81839FlVGVNDn1OluXI+f3urxjj4vFYpdVUDc4j/Abhl2rEPAz9USu0Afui/bvSYAD7rP6urlFIPLPOYbOAPlVKXAdcD7xORy2jss6o2Jmjcs8oCNyulrgSuAm4RkeuBu/wxbQfGgPcs45hmGxfAH5c8q2eWeVwAHwSeL3nd6GdVaUzQ+Oc0fa6s+29vtRmHhqKU2g+MTjv8FuAr/vdfAX5lBYypoSil+pRST/vfx/H+cDbQwGc1y5gahvJI+C8D/pcCbgbu84834neq2rgaiohsBH4J+KL/Wmjws5o+phVM3X97q8k4KOD7IvKUiNzR6MGUsFYp1ed/3w+sbeRgSni/iDznu52W1dVViohsAV4F/JQV8qymjQka+Kx8l8QzwCDwEPASMK6Usv23nKUBRmz6uJRShWf1Kf9ZfVZEQss8rL8G/gvg+q/X0PhnNX1MBRr5nCrNlXX/7a0m43CjUupqYA+eS+CmRg9oOsrLC274Cgv4O+AiPJdAH/A/GzEIEYkB3wZ+Tyk1WfqzRj2rCmNq6LNSSjlKqauAjcB1wM7lvH81po9LRHYBH8Eb36uBDuBDyzUeEfllYFAp9dRy3XMuZhlTw56Tz6xzZa1/e6vGOCilzvn/DgLfwftDWgkMiMg6AP/fwQaPB6XUgP/H7QJfoAHPSkQCeJPw15VS/+wfbuizqjSmlfCs/HGMA48ANwBtIlLQPdsInGvEmKaN6xbfNaeUUlngf7O8z+o1wJtF5CTwDTx30udo7LOaMSYR+ccGP6dqc2Xdf3urwjiISJOINBe+B94IHJr9rGXjfuDd/vfvBr7bwLEAxf/5Bd7KMj8r3xf8JeB5pdRnSn7UsGdVbUyNfFYi0iUibf73EeANeLGQR4Db/Lct++9UlXEdLZlcBM9nvWzPSin1EaXURqXUFuDtwMNKqf9IA59VlTG9s5HPaZa5sv6/PaXUiv8CtgHP+l+Hgf/aoHHci+d6yOP5N9+D5/f8IXAc+AHQsQLG9DXgIPCc/0uxbpnHdCPetvU54Bn/69ZGPqtZxtSwZwW8EviZf+9DwMf849uAx4EXgX8CQsv8/6/auB72n9Uh4B+B2HKOq2R8u4HvrYRnVWVMDXtO1ebK+fztafkMjUaj0cxgVbiVNBqNRrO8aOOg0Wg0mhlo46DRaDSaGWjjoNFoNJoZaOOg0Wg0mhlo46DRLCEisk9EVlSzeY2mFrRx0Gg0Gs0MtHHQaKYhIltE5Kivy39MRL4uIq8XkX/39fCv8ytRv+z3PfiZiLzFPzciIt8QkedF5DtAxD/+OyLylyX3+E0R+dsGfUSNZk50EZxGMw1ftfVFPOXWw8ATeBWn7wHeDPwn4AhwRCn1j77UxOP+++8EdimlfktEXgk8jdc/4hRwQHl9BxCRvcCnlFI/XsaPptHUjDX3WzSalyUnlFIHAUTkMF6jFCUiB4EteCJvbxaRP/LfHwY2AzcBfwOglHpORJ7zvx8SkV6/ac5xPNXOf1/OD6TR1IM2DhpNZbIl37slr128vxsH+A9KqRdKT/K01qryDeBtwFHgO0pv2zUrGB1z0Gjmx78B/6+vvImIvMo/vh94h39sF56IXYHv4HXkuh3PUGg0KxZtHDSa+fFJvPaZz/lup0/6x/8OiInI88AngGIjGKXUGJ4k9yuUUo8v83g1mrrQAWmNRqPRzEDvHDQajUYzA20cNBqNRjMDbRw0Go1GMwNtHDQajUYzA20cNBqNRjMDbRw0Go1GMwNtHDQajUYzg/8fiFMx6EX6qcgAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "mdev and indus: correlation -0.5016982293419983\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "mdev and tax: correlation -0.4957924067170343\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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QS1rE09acelYdGoyxpaubn7/aw2gik2vvqA9wzVkdXHlmO001vorOqY3hGo1mtmhlMUuyiiOSmNsVRypj8+s9fWzp6mbH4ZFcu2kI71zv2DbOXd1Q0WrD7zVp1MZwjUYzA7SymEMylk00aTGWTM+pcfytgRhbdh7lsVePFaw2ljeMrzYaQ+WvNnweg8aQT5d91Wg0ZaOVRZVIZWwibk3uuTKOpzI2v9rtrDZ2HhlfbXgM4ZL1y9h8dgfnrCp/taGVhkajKZdFpyxE5AAwBlhARil1gYg0AT8C1gAHgA8qpYbE8RG9HbgaiAEfU0q9ONX550tZ5JNIWznFYdlzM3YHBqJs6ermsVePEUmOrzZWNAS5prODK89oo6HM1YbPY9BU49PbUxqNZlIWq7K4QCnVn9f2v4FBpdStIvJloFEp9SURuRr4LI6yeDtwu1Lq7VOdfyGURRalFHFXccSScxM5nkxb/Gp3Hw92dfPq0dFcu9d0VhvXnr2cs1fWlxV7oVcaGo1mMpaKsngD2KSU6haRDmCrUupUEbnTfX1Pcb/Jzr+QyiIf21bE0haRRGbOPKr297urjdd6iCbHje2rGoNs7uzgvae3Ux/yTnser2nQWOOjVisNjUbjshiVxX5gCFDAnUqpu0RkWCnV4L4vwJBSqkFEtgC3KqWect97AviSUmp70TlvAm4CWL169fkHDx6smvwzwbIVsVSG6By54ibSFlvfcGwbr3UXrjYu3dDC5rM76Fwx/WrDaxo0hLyEA9MrGI1Gc3wzE2VR7cfNS5RSR0SkFfiFiOzKf1MppUSkotlUKXUXcBc4K4u5E3VuyEZdhwPe3Ioj6iY5nIniCHhNrjyznSvPbOfNvghburp5/LVjRFMWT+zq5YldvaxuCnFNZwfvO72NumBpZZC2bPrGkgzH0tSHdCoRjUZTGfPmDSUifw1EgE9xnG1DlYNSilhqXHHMxsYRT1ts3dXLg13d7OoZy7V7TeFdp7RwbedyzlxRN6Uy8BgGdUEPdQGvrhWu0ZxgLKptKBGpAQyl1Jj7+hfAV4HLgYE8A3eTUuovROQa4E8ZN3DfoZS6cKprLCVlkc9cGsf39rqrjdePEUuN2zbWNIfY3NnBe05vm3LryRAhHHDKvur8UxrNicFiUxbrgJ+6v3qA/6eU+lsRaQbuA1YDB3FcZwdd+8U/AlfiuM5+vNheUcxSVRb55K84ojPcqgKIpyye3NXLlp3dvJG32vB5DDad0sLmzg7OWD75akNEqPGZ1AV1KhGN5nhnUSmL+eB4UBb5KKWIpmZfyGn3sTEe6urm8dd7ieelLVm3rIZrOjt4z2lt1AYmN1f5vSZ1AQ+12q6h0RyXaGVxHJEt5BRNzTwAMJbK8OSuXh7c0c2e3kiu3e8x2HSqY9s4rSM8qUIwDaHW76Eu6MWrt6g0muMGrSyOU+bCxvFGzxgPdh3lyV29JNLjKUtObqlhc2cHl5/WNmUsRtDnpEifLjJ8665e7ty2j0NDMVY1hrj50nVs2thasbwajaZ6aGVxAjBbr6poMsMTu3rZsqObvX3jq42Ax+Cyja1c09nBxvbJVxte05jU9Xbrrl6+8sCreE0h6DWJpy3SluKr152hFYZGs4jQyuIEI6c4UhniKauirSqlFLt6xtjS1c0vd/WSyMusu76lls1nd3D5xtZJ04WYhlAX8FIX9GK6rrc33vUMvWOJgtVHLJWhNRzgnpsumuFdajSauUYrixOY2WxVRZIZnnj9GA92dbOvL5prD3id1ca1ncs5tT1c8tj8Kn6X/59f0RD0Fqw4lFKMxNP8+kuXzfzmNBrNnLIYI7g184SIEPJ5CPk8qNrK3HFr/R6uP2cF1529nNe7HdvG1jf6SKRtHt7Zw8M7e9jQWsu1Z3dw2cbWgpWDUopIwikY1Rr2MxRLUesfj+uIpy1WNoaqdt8ajWZ+0CuL4xw7W/0v6WxVlUskkeEXrx9jS1c3+/vHVxtBr8kVp7WyubODDW2Fq43n9g1y+5N78JqO4kplLDI22mah0Swy9DaUZkrSlu2sAioo4qSU4tWjo2zp6mbr7r6CqoGntoe5trODd29sJegG8j23b5B7nz9Ez2ic9vogH734JN53Zruur6HRLCK0stCUTSLPvpGxy1McY4k0v3jNsW0cHIjl2kM+kytOa+Pazg5Obq0teazHMKgNeKgLeHRaEY1mgdHKQjMjEnmZcctZcSileOXIKA92HeVXu/tIW+N/Qxvd1camvNVGMSGfh7qgR682NJoFQisLzayptGzsSDzNY68dY8uOoxwaiufaa3wmV5zexubODk5uKb3a8JoG4YCHcGDc/Vaj0VQfrSyOc0pFRwNViZhWSvHYKz38y1P72ds7RtpSTqnWoBdEiKYydNQFueFtq7hwXRNKKbqOjLBlRzfb9hSuNk7vCHN6Rz27e8Y4FkkUHAfj7rd1gdklMdTR4xpNeWhlcRxTKjp6NJ5GAfVB75xHTGevl8pYDERTKKWwbBBABNrq/JiGQcZW3HLZBgDu2vYmh4bjKKWoC/rIWDajiUzunALUBT0EvSYikjvu3ucP0T0ap6MuyB9ftJr3ndXB8/sGuOvX+8ue+O94fDf/tPVNLFvh9zgrFp/H1J5YGk0JtLI4jikVHb3n2BgIbGgdd2Gdq4jp7PV6RhJkLIVhCImMBcopsuQxhJVNIeIpC69pMBRLMRpPk91NythOLV1TwCrxJyZA2G8S8nvwmgYBr0EibZOxFVee3sbPXzuGz2NQ4zNJZOwpleDWXb3c/IMXsJXCFEEpsFE01/hYu6xWR49rNEXMRFlot5QlwqGh2ASDcca2J9gVgl6Tw0MxZkv2einLJhuQrZSjAAxDSNsKn2kQ9ns4PBQjmspgiGAYBoZhkJWqlKIA5zyjSYtjo0nGEhlSGUXQa+IxhPteOIxpCD7TIG0rvKaBaTjbbaW4c9s+MraNaQgigmEIBsJYIjMnY6HRaHQE95JhVWNowsrCYxjOI3oes4mYzt/zH42nsWwbn2mQsRQizvYTylEaPtNAREhaFiKCZduYIrhdCihu8xpCRqmc8hmOpxmOpwl6DeqCXmIpi+UN7nOMAlspPIZwYCDCWCI9oc7GoaEYftPAUuQUmwgkM7aOHtdo5gi9slgi3HzpOtKWIpbKuAkEM4TdAkX5bWlL5QzflZC1UfSOJWgIegn5THrHUvg8go0iY9uIAkPAshXLan25661tDrmxE86Tfb7+EsBT7Okk4BHBI877Xvf9eNrm2GgSBXSPJAoCABNpm7ZwkL6xJAcHYvRHkiQzTkT6qsYQ9SGvs/2kFAqFpRSmITMaC41GMxG9slgibNrYyldxtlwOD8VY2Rjir645HYraZuoBdOe2fbk0HQAt4QAAsZRFfcBDylL4ggbLanyICJGkYxvJTsZfvH8Hw7E0qmhbzDTAMIC88A2PITTV+EhlLIbjGdrCfmxgKJoi7tbaiCQtIskYQa9B0GfiMw1ueNsqwFEIo/E0o/E0Po/Bh9++mlsf3UVzrZeRWJqkZeMxDD6z6WRt3NZo5ght4NYAcMltT84qY+zWXb3c+sjr7Hcju1tqfYwlMyTTNhnbxhAhbSlaan00hHzE01bOmP3SoREnPUhdkGvOaufYWJKfvHiYwVg6d/6Qz+SaszrY3NnBqqaJW0vP7R/kx9sP0zMaZ1VjiE+/SysKjWYydNZZzYwpZROp1P7RWOMnkrImxIBkVz0Xr2vi6X2DHB6K0VEf5A8vXMXZqxv54xIPLDdcuIoXDg6xpaub3+ztJ5ay+PELh/nxC4c5Z1UD13Z2cMmGZblyrxeubeLCtU7chmk4K6RE2iqI29BxGBrNzNErCw0wuyp3sznWshVjiTRjicmTGw5EkjzySg8P7ezm2Ggy194Q9PK+M9rY3LmcFY3Bksf6PAbhgJcXDgzy1w++pqv4aTToOIslSTlPu/l9wn6PU0MiZRW8nu5J+Y7Hd3P3U/sZS2Rynkl1AQ+fvGQtn7vilILrHB6KUZt37lqfE0Q3lswUvM5e885t+yasSvrGEsRSFj6PQSpjYysbQwx8HoMNreGSsibSFmMJJ9VItnhTNott92ic9nCA81Y3srtvjKffHCDfPBL0Ouc+qamG81c38NKhkVyg37mr6rnvhcPE0xYBj0Gt30M0ZZHM2IR8JnfccO6sFMZSW7HMRt6ldq/5LGXZ54ov3PsiD3T1cPhfbyHZvaeiHDvTKgsROV0p9VpR2yal1NayLiBiAtuBI0qpzSKyFrgXaAZeAP5YKZUSET/wfeB8YAD4kFLqwFTnXurKopwn8vw+GcvmyHACgMaQh6GYEx29oiGAxzQmfVK+4/Hd3P7kXpSt8u3MCE7MxC2Xrc8pjJlcM5pM01EfzNk7RuNpjo7EsW2FIYKtFJbrSWWKsCzsw2tOHl2tlCKSzPDYqz18/bHdeAyZELT30Cs9uQSI+bEcIo5rb2PQw7Kwn6FoyrF9KDBNsG0n9sMUx/huKVjREJrxCmOp1R1fqBXkQrOUZZ8rvnDvi/z05W4Aur/7eZI9lSmLcmwW94nIvwH/Gwi4Py8ALi7zGrcArwN17u+3Ad9QSt0rIt8CPgF80/05pJRaLyI3uP0+VPadLEGKPZBCPscN9s5t+3J/wPl99vVFnIR7CgaiaWe/XkF/JMW6ltoJx2a5+6n9GALpousrnAn87qf2FyiLCdcUx8d1IJrG68Z25F8zbTklXbP30R9Jjp/fEKy82dwwhKFoGkjzye9vJ+Qzc6uNrE3j0FCMWp/Jvr4oKXf54DOFZbX+XNBeU42PhqCXtwajYCtsN2I8++wzFM+QzLguvzjOWLYF2fJPlnIafZ7xgL+58CIr9RnOhNnmAZvsKXo28t65bR9py2IgkiFlOTE4dUHPrO91PqjW57SUeKCrBxiPRaqUcuIs3g6sAn4LPA8cBd5ZzslFZCVwDXC3+7sAlwH3u12+B7zffX29+zvu+5eLzPS2lgalorKLI7Dz+2SjqUXAdgPQRJz2UsdmiaYsikMdshjivD+ZXOVc0+cxCmJAkm6uD0Mk96QPbgS4Um76DmeVEE9bjMTSvNEzyu1P7mV/fwRTYPexSE5ROHIoekYT2G6t8YDX+dPN2E48hdcUTKHgPmNpi5TlrGoU44oii6XIRY0f6I8wFE2RKbMoVKmxyjLbKPrimJfesQRfvH8Hf37/joK2rzzwKlt39ZZ1fLbvbOTd0ztG/1gqN+YZW9E/lmJP79iM73W+qMbntNQoJ4v0VJSjLNJAHAjirCz2K6XK/Ub9A/AXjHvZNwPDSqlsdrnDwAr39QrgEID7/ojbvwARuUlEtovI9r6+vjLFWJysagwRTxdOYcUeSPl9fKbhTrjOpJh97XM9gibzXqrxmUz2d2Ir5/3J5Crnmhtaw3z1ujNoDQcYiacJ+UyWhX34Pc6xuXQhOJM+OBO1E7BnYBjCsJtXaiyRoT+SmhAFnpX1qLslNhJPgzhpznMyeQzMPGUxXdZzUxz5E2mbtrogQ7EUbw3G6B6JE0lmpq1dXjxWWWZbdzz/KThbWz2SzDCWyBS0eU0pmQKl1PHZvrORN5VxMkkaIgiC4a4484MnFyvV+JyWGrMtA1COsngeR1m8Dfgd4EYR+fF0B4nIZqBXKfXCrCQsQil1l1LqAqXUBS0tLXN56nmnVFR2cQR2fp9ltT4s24lObq7x5l7nR1OXilj+5CVrsdXED1twJuBPXrJ2UrmW1fqwlMKy3Wu6r4uvuWljK/fcdBG//tJl3HHDuXhNk7qgB9tWE/N/5F0fxlcthrtiSWTsyQ5xs+x6GIimGY2nWFbjw7YVtlIEvAbZhYGBowym+noocONAVC7gDyCesugdTXBwIEbvaILoFIqjnM+wUko9BVu2mlDRcLIn46meomcjr9fVxLatUEo5ny3OFuFipxqf01Ljus52YHylXynl2Cw+oZTKWpG7getF5I/LOO6dwHUicjXOiqQOuB1oEBGPu3pYCRxx+x/B2e46LCIeoB7H0H3cUioqu3gfurjPhtZalFJEUxYbWgO519lo6lL7r1l7RLE3VLjIG2qya65vqclFba9v8U+I4C6+Zv7x0eRIQZryfGwgmbGcBISuwvCZxoQnwHwMgfqgD7/HcqLLgyantIWxbJsDAzE8phAOeHJV/7ymEy0+Gk8TT9s5xQTjP8MBD2k3KWP+05ftGtojSSdJYo3fSa/y7L6BAnvAB85bkYsfqXGjzf/yZ6+watvMPG5Kxbw4tqrCSXmyJ+OpYmbK+ZubjFPa6tjfH3ESP7o2i3DAy9plpYtbLSZmc9/HC9+44TzA8Yaa8ilqEsp2nRWRVpxJHwCl1FtlX0RkE/BF1xvqx8C/5xm4u5RS/ywinwHOUkp92jVw/55S6oNTnXepe0Md72zd1ctn73mRseTkk3+WWr9JPG3TUuujdyw56baZxwBDDDrq/diKgujyS257kvqAB1uB5WYpVCjGEhk+f/kp3P7kHjyGYBowGE0TSWYKrtNc6+PqM9u5+qwO2uoCJa7uuPLe8eQefB6DkM8kmZc+HZgTj5tSnjsj8bRbD2T62iXV8vzRHkXHD1VJUS4i14rIHmA/8CvgAPDIjCR0+BLwZyKyF8cm8W23/dtAs9v+Z8CXZ3ENzSLgzm37JhjPS2G6++C3XLaetctq8ZoGXgO8Jf46vaaJCBwbTU54ql7VGCKRsfGYBj7TwGMaJDM27XVBLlzXxC2XbaC5xk8ibbNuWS1fu+5M/ua6M3jbmkYEGIik+Ldn3uKP7n6W//bTnfz2zf4JRsF7nz+US5+esZRjcxH45q/enNJWUAmbNrYW2IBawwG+/oGz+bsPnF3QNtkkXer4uZjQq3VezdKgnDiLHTgeTI8rpc4VkXcDH1ZKfWI+BJwKvbJY3Fxy25MczqvLXYzXAEQ4tS1ckIMq/wn24EAUcIopeQQ8puHGbSi+/ZG3FUxUkz35/verN3LO6kaiydLbYQDdI3Ee6urmkVd6GMrLSdVS6+fqs5zVRkvYz43/8gx1AQ/5uXWzqxdwospN03CMv1SWX0ujmS+qlRsqrZQaEBFDRAyl1C9F5B9mJqLmRGJVY4ijw/FJt5QMw8BjyIS998L95TgiTkBgLGWRspwiR+uaaqa0lRTvS2/d1cs3f/Umbw3GaKsLcMMF4zXAATrqg3zyd9bxsXes4bdvDvBgVzcvHByiL5Lke08f5N+eOchF65oJeT3EU1aBPSCRdlYvAAPRJE6ZcscOk8hU1+NGRyVr5otylMWwiNQC24AfikgvEKmuWJrjgZsvXccrR4YntVnYtqKuxlvSK2XTxtbcJJ9dLbTVBXKrhS9fdVrJc2aPyyf/HM01PkbjKf7xl3u5xdjA+WsaC/p6TINLT2nh0lNaODoc56Gd3TzqrjZ++6bjb2EI1Po9NNd4ydgUeFPd/uSeXBxILOV4Wv3euSsYiCSpDXjwewq9lGZD/n3lx1N81R0HjWYuKcd1dgcQA74APAq8CeyqplCa44NNG1v5vzeex8p6fy7WwhAIeJy8VPUhL2uaa6fc956LffJiW0KN34vfa/CTl47QXh8g6Cs9gS9vCPKp31nHvTddxFc2n855qxsAx4tqNJFh/0CckXiaK09v5/w1jQV2kbFEhuYaP7dc5iikkXiaI0NxDg3GGIqm5iQ2Ya5sJBpNOZRjs3hRKXVeUVuXUqqzqpKVgbZZaMqhnFodqYzNaCJNJDGexLAUh4diPNTVzc9fPcZwfNy20Vbn55qzOrjqzHaaa/1lyeU1naSGIb85oxXHbGuQaE5c5tRmISJ/Avxn4GQR6cp7Kwz8ZmYiajTzz1RxB8V7/p/6nbWcf1ITo4l0yZTpKxtD3Pyuk/n4O9fym739PNjVzcuHhjk2muQ7vznA954+yDtObmZzZwfnn9SYM3SXIm3Z/PyVHu59/hA9o3FWNob49KXruOKM9lnfl0Yz10y6shCReqAR+P8odGMdU0oNzoNs06JXFppymMxL6gPnreD+F49MGjcQS2UYiaeJT+P+e2gwlrNt5AcgdtQHuOasDq48s52mGt+E457bN5iL/cjPqvtf3nMKV5zeRsjnweeZfKdYxz1oZoquZ6GpGkvF62YyOfNrdWS9pErV4YilnMj0e266KNeWzDhBcdGkNWW+qFTG5td7+tnSdZQdh0dy7aYhvNNdbZyXt9r4sx/tcL2nxreg4mmL5ho/f/+hswEn31Wt30ON35OrCljqfk/UqGTNzNDKQlMVlsoT7HRyFiuSPb1jtNcFyt7zz1g2Y4kMo4n0tBk83xqIsWXnUR579VjBamN5w/hq4z//8MVJYzb+36cumnBOv9d0FIfPxFNCcWhmx1J5IJoLtLLQVIWr/mEb+/ujWErhMw1awn5MQyY8gc+WSqsGFve58a5nJl0p3HzpugmK5PBQnKYaL8tqAxP6T3VfSinGkhlGYqXtGvmkMja/2t3Hlq5udh4ZX214DKHW78m5vWYVVvHKYjICXjOXq2q22UQ1S+eBaK6oSroPzYnN1l297O6NYKvxGgZHhxNkLHtOawFMVYOh3D5TZVst5WbaGPIyGE1XnIlURKgLeFnVFKK1LjClXcHnMXjP6W3cfsM5fOdjF/B7562g1u8hYyuG42n6Iin2D8QYjKWIJDMTMuBORiJtMRBJ8tZgjJ6RRNkp1TWl0W7I06OVhWZKsl+i7H/ZgkalcjPNxXWm+rJO12eqmgWlFMmyWj9hvzmrGI5av4eVjaEp4zWyrGmu4U/fvZ4f33wRX77yVM5c7hSPzNiK/kiK7pEErWE/Xo+UPfFnlVw2pfqx0QRjiXQufbimPHRxpOkpJ4JbcwJzaChGW9jP0ZEE2Nka14qMmttaAIeGYjQEvQVtpaoGTtZn665ehqJJDgxE8RoGbXV+khmboViakXiaVMYmY9m0hMe3nOJpiw1tdTPaSptsOyyRthiNOxltJ8PvNXnvGe2894x29vdH2dLVzWOv9RBNWuw4PMJ/+XEXKxuDbO7s4H2nt1Mf8k56rnxspYgmM0STGfolRcBrEPI6cRyljOOacbQb8vTovyDNlKxqDOExDZbXB/GYgqUUhiFsaHFqGNx41zNcctuT3HjXMyVLfJbD1l29jMbT7OoZY19fhFE32G2qqoFZ4mmLWr+HrzzwKmlbsbIhCAJvDcYZiKZoqvHSXhegxm/SF0nRN5aYdfGbqbbDAl6T1roAq5pChAOFAXOlWLushs9etp4f33wxf/G+Uzm9IwzA4aE43/rVPj5419P87UOvs+PQcEXbTEop4imLgWiSQ4MxDg85kePJzPRZgE9EdHGk6dEGbs2U5Bv+MpbNsbEkaUuxvN7J01Tv1lfojyQZiqUJBzxsaA2X7Ulyx+O7+aetb5K2bGwFpuGkK2+u8eHzmAXbQlt39fLn9+9gLJEhY9t4DINwwENzjY+0rQqeCvf0joGCDW3hXFt/JEE0aeEzhWjKIuNW8fN6DIJeg1Pa6qaUe+uuXm595HXe6I2gFAQ8Bm11AeqC3kkN4xnLZjSRYTSenjIyPMtz+wb5198c4K2hKMmMXZCE0TSEtrCfT16ydlZGV69p8PJbQ/zgmbd4sz9CKuMUiZrs/k8UL6F8N+Qan4mIMJbMHJf3rA3cmjknm5vJawiHh+OgYGVDgL6xJMOxNBnLcfUciKawlSKWzJQ0Tpdi665e/mnrm9hK4fM4GWht20kwGEtZJe0HCkAcIzPi/N4fTZVVhrS5xu8Yo0VIW05p0LR7reF4mv39kUnl3rqrly/ev4O9fdFcWcpExubIcJzReHrS/W2PadBU42N1U4imGt+UnkvZIL1YOsPKxiAd9QFCPjN3jGUrjo4k+OpDr/Nf7tvBzsMjMzJq/2ZPP//rkV3s6x9jOJrKBR+Wuv9yHA+OF7Klgb92/ZnE0jYpyz7u77kStLLQTMumja001vhZ01zDhrYwdUGnLrch0B9J0h9JYiCYhuSe8MvxJLlz2z6nlKk4xnOvaeDzGPg9BvVB7wRFcee2fdQHvWxoDbOxvY4NrWHqg15SGXvC9pRpCB6j8M87nrZIZWwiyQymCLZyqksKYNswlshMKved2/bljjNk/DjLVvRHktPubxuG0BDysaoxRHONv6TSuPf5Q3gMx3VTEGp8HjK2jSlwUmOQ+qCX7GEvHRrmlh+9zH/63nb+/cXDjCXSE843GdnrRJIWYgimYSAII/G0U8hp65sF932ieQmdiPdcDlpZaMqi2FvE5xpMU5bzBOYYvsfby/EkOTQUw+8xCgrIi0DSsktOvJN5rPhMmbDfXOv3uLW4C/egvaZg2Sonr3NRZ4WSsuxJ5T40FMsdl6+EFORKq5azv20YQn3IW1JpdI/GCRSVB7RthWUr/F6TtrCfdc01tIZ9eN3jDg7E+Kdfvskf3PkMtz6yi1eOTL/ayF4n7X5u4Ix7tmb5wcEohwZjrmtu9ITzEtKeUaXRykJTFsXG5Zaw37UxOCVGLaVQymmH8jxJVjWGCAc82Chs29kWsmynVGmpiXcyA/eGtrqyy5Ce0laHaQhKkZsocVcYPtOYVO5VjaHccabhrIKygdchn1mxy21WaaxucpSGxzDoqAuSSNsT+uUrFMMQ/B6TM5bX860Pn8e1nR0EvSapjM1jrx3jc/e+zCe//wI/efEIkURpj6zsdbzmuKJWyrFlZAs5pS2bkXialtoAo4k0GcvO2VyOdy+hqVywT2S0stCURbG3iGkIjSEva5pCBL1OGdHmWi+1fk/ZniQ3X7oOn8ekucaHx3QC/gwRPrPp5JIT78Xrmjg8FOe17hHe7B2jP5LIXSe73/zrL13GPTddlCuCVNx286XrqPV7cttoivF/2QmylNz5x1m2DTjbZy21Pu644dwZGz9F3JVGU5BP/c5aLFsRT1sonJ81PicvVH5bNnDvlLYwX3jPKfz40xfxZ+/ZwIZWx0Ntf3+Uf/zlXv7gzqe57dFdvHZ0tGC1ccPbVpGxFbV+E2U796NQ1PjMCUGBN7xtFWlLEUlmSGUsRuIpEmmbj1180nEbBKg9o0qjvaGOYyr1Ypmu/1RJ67LvvXp0hGjKwrYV4YCHT16yls9dccq015wqEd7WXb3c9ugudvdGMF17geU+4X9m08l87opTKrrXrFfT3r4IGds5nyHOk3U44OHvPnB2yWOzx+0fcLYj1i2r4UtXbgSYM2+hX75+jH/e+iaHh2K01QVzE3c2jXm725ZfEjaf3cfGeHBHN0/sOlawSlnXUsPmszq44vQ2av0ents3yL3PH+LgYJRUxsZnCic115Y8d7Zv8fVNQwj6nHxVQa85rZvwUuJ4T9Coc0MdR+RPfrV5bnxhvwelFJGUVfA6O0l1HR7m7qf2M5bIoHAmwpDPJBzw4POYfOC8FTy9b7BkVtYv3r+DSDLjGJ3d3EVfn2TiBMftNXstwxAMFGnbcX/1GI4B2VZwy2Xr6VzZwJ3b9rH72Chpa/xvrthls3jSv3hdE//2zEH6I6nc/RiGsLLBifsozvuU7957SmstX7pyY8nzlso6O5ZI0zOSQAHnrW4sS7ne+sjr7OmL5AIBU5bNYDRNrd+c1hW3+HPO/zyUcp7mf/5KDz945i26R+N0TKEoshP6gYFIzjZT6/diKUX3SCLXL+AxePfGVjZ3drCxPTxnE7whQshnEvJ7CHlNjDLzVS2UW241rzvTc8/1w91UaGVxnFAc23Bk2PmyN4W8DMYcr5fGkIehmLMnvaIhgMc06B1NEE1ZuSfvLAZgmkKt3ySWslnZGMwlS+uPJF1vIucp1HSfsJUCSynWt9Tw6BfeVSDbndv2sfPIEJGkjeC6s+YhOOcwDckFgYkIylbYRf2y+DwGV5/ZxgtvjRQkc3trMEbGUhOuAVDjMwl6DTa01bG/P+IEnVmFPQ2BxqCX0WTGsTe4W0+WcsZleUOAuqCPsUSao8MJnLyvsLopNGUiuXyXUttWiEguE62IY/9orw+UdY6psuR+5YFXMQ3wGkZuC+qWyzYUKIysy206Y41X71PQWOPFNAx+/9yV7B+I8uSuXhJ55VzXt9RyTWcHV5zWSo1/7pI5iKs4aqZRHAuVvK+a153puSs9brb3sKjiLEQkICLPicgOEXlVRP7GbV8rIs+KyF4R+ZGI+Nx2v/v7Xvf9NdWSbbGT77rXH0lhimPk7I+mMA3BFGEgms697o+kCPk8zvaPmjh524CBMBJ3Vg1Zl8BIIsNIPFOwXWEpJ1eRYTguotktFyicIGMp55icQ1HRfJCxbdco6qwuUIWKInts9nhbKf5jRzdpyypwWUxPoigAoimL/mial94aZCCaImVN7GkrGIilSVuKjK1IWsrppxSWUhwZdnIp9Y0lcUI3HIP9dO6S2c/Icu0shqssLOXYMlKWXfY5JnPRzL5f6/fi95rUBbx4TeHe5w8VnCfrCus8KLiusK5rrNc0+M2bA3zxfady36cv5pbL17OupQaAvX0Rbn9iD39w59N8/bE3eKNnbJKRrgzlph3pHU1wcNDJVxVJZibkq1ooF9VqXnem5670uIUYu2rmhkoClymlIiLiBZ4SkUeAPwO+oZS6V0S+BXwC+Kb7c0gptV5EbgBuAz5URfkWLfk5kFKWjekGoNl5Hjz5r1Numuzsd7HUYlHc44N5rpl9kWTJ62dshbdETrz8P9Ap89S5bqlW3jQ/VXflCq0UjMTSBSnDyyGRqXx1nI2xyCjFAVchOvF6krv+VO6S2c/IZxpkLNcVFxBVvgtxca6rsUSa3tEEBwZiXPmNX/FmfxRwzrWs1k9d0EtdwEtfJIHPY5ByVwndo3HqAh7Slp0rrJR1hQ14DXpG44CT9PD6c1Zw3dnLeb17jC1d3fzyjV4SaZuHd/bw8M4eNrTWcu3ZHVy2sbUgIn6mZBVHNJlBxHkKrvGbhHyesvKBVYNqXnem5670uIUYu6qtLJRDxP3V6/5TwGXA/W7794D3u6+vd3/Hff9yOZ4sZhWQ77rnc7eElHK2VEq9zk5M2dV+qVGzlDOhhQPjE0B2wnd1UQG2UtjKMeJmyfc/n2pLOqussuf3mjK1cgEytnPO5DT1IeYKRXbFVShDyGtS534Jp3KXzH5Gy2r9Odff8fMqltVO70Kc/zlnt8HStsIjsLcvmosyz1iKoyNOpHg8bbG6qYaVjSHa3PTo5bjC5iMinL68jr+48lR+fPPFfPay9ax1P+c9vRH+/hd7+INvPcPf/2I3u4/NzWrDkcnxLOobc1Krt4b9E1Krz4eLajVdY2d67kqPWwj33qq6zoqIKSIvA73AL4A3gWGlVNYB/DCwwn29AjgE4L4/AjSXOOdNIrJdRLb39fVVU/wFI991b1mtz3XXVCyr8eW2OpprvLnXy2p9xFIZanxmLro4H8fbR3j/2R34PGbOJTDbzxTBUzT7C9AY8ua8faDwD7S5qKZ09vvuN13lI463UlPIy4qG4ASZilFAXcCDxzAKXBarjY0ja3bBNZLIMBpPTesumf2MPKawvD6AGFmPKievVTYgsJxzZFOM5zbcRHKfiWXjpDcBjo0lCs5X46ZHv/ld67Bsx/VV4brCuq6x09XHqA14+N1zV3D3R87njhvO4b2nt+HzOPaRLV3dfPoHL/InP3iRLV3d09YirwSlFB88fxXJjOOunExbjCWc7MDVdlGtpmvsTM9d6XEL4d47LwZuEWkAfgr8FfBdpdR6t30V8IhS6kwReQW4Uil12H3vTeDtSqn+yc57vBq4oXRSs0jSiUxWShFNWQWvVxZ5Q0XcZX/Ia3DmioaStajByW7qMR37RNpyVhN1AQ9nLK8v6Tqbb1Q7PBRjJOEYjrNeSh5DClxKs/1H4yn6IlOnpPCawuaz2ukZTeVcFtvrfPz05e6qjXOWfEO9ABvbwzlPqsnIjuWeY6OkLCe/VUutf8JnMlVivqxH256+KAGPs910dCSe23rMWAq/xyCZsTANgzs/fP6kBs9/3vpmgSwnNdVM6WY7GWOJNL947RgPdnVzMM9mFfKZXHFaG5s7O1jvxnTMllJuue9Yv4yQ33HJDZTaD50DqukaO9NzV3rcbO5hUXtDichXgDjwJaBdKZURkYuBv1ZKvU9Efu6+flpEPEAP0KKmEPB4VhbzRdb9NZqyqPGZM4qLAEcppDIWY4kMyYydi4HIuszu6R0jmsyQythYynGtzRTtTZkCTTW+gjiHrbt6ueVHLzEaz0xp9zBgggG9XEp5dC2r9U3pNpxlrrxYQl4jl1drX1+EjOVoYI8hrGupLavca5axRJrhEiVfsxPzdG64WZRSvHp0lAe7utn6Rm+By/PG9jDXdnawaWPrhNQYc4lpODYyR3EYx1Usx0KyqJSFiLQAaaXUsIgEgcdwjNYfBf49z8DdpZT6ZxH5DHCWUurTroH795RSH5zqGlpZLA5uvOsZ9vdHGIimMHAq6TkR0sKdHz4foGCC7I8kOTaWzK1Ism62trs1du7qxtykWFxXe1f3COkqmzUEZ5IqdhsuxVR1v++56aIJvvBD0eSEdOqxVAafaRBNWRPcpbNu0TNx7cxXGln3Wo8hBLyOLaOUG+5kjMbTPPbaMbZ0dfPW4Phqo8ZncsXpzmrj5Ja5WW1MRlZx1PjN4y4IcL5ZbMqiE8dgbeI8+N2nlPqqiKwD7gWagJeADyulkiISAP4NOBcYBG5QSk3pB6aVxeLgktueZCiaysVDZOzxOgwhr5kzrreFndoPo/E0B90JJ19ZKBTpjI3HNGgJ+1nVGGL3sVFq/Y4LccqyC55uq4XHdRsWEd74n1dN2feS256kIVhY5EgpxUg8zdeuP9MpymRZjMTSJC0by4aWWi/t9aGS/UttPc52mySSzPCRu5+lL5IsWAXE0xbNNX7+/kNnl30upRRdR0bYsqObbXv6Cj6P0zvCXNO5nHef2lK17aMshkhuq0orjspZVMpiPtDKYnFw413P8PyBQccVNc8rKIsBeExBAQ1BL8PxdEGgXVZhKBRpSxHwGqxvqWUgmqR7JJnr43FToFcbRx4pS1lMtbIAODAQYSCSzhn9szEtflOwcTzZ6oIe1jTXzqi8a7lcctuT1Pk9OCEmzhhGkmn6IimaanxlbUsVMxJL89hrPTzY1c3hoXiuvcZv8p7T2rj27OU5L6tqko0er/F7CPm04iiHRRWUpzlxuPnSdblaFsWI+z8RwUByW1X5JaGz6cGzT6lhv4dIMsNAkUG82MZRLRRMcBuejKm8Ug4NxRiJOYrCcGt2mLnYGCeRYcqy6R1LcXGFRuhKWdUYImnZ+DwGXo9BNJXh2GgSwXFoGIgmuf3JPTy3b7Dsc9aHvPzBBav43sffxt9/8GzefWqLExyYtPiPl4/yie9t57P3vMTPX+0hma5eOVfbTY1yzI1ROTbqBFpa8/T3cqKglYVm1mza2MpnNp0MTDQUZwPdlHISadjuT0MMWmt9eIoeAk2B4Xia7uF4QbxINuitUmb6jFnjNwvchicjW0mwOBX6po2tuQk6/z5ygZNAMuO4RIf9Jk9XMEnPhHylJsBANAVAa9iP4NiSPMbE6PByEBHOWdXAX20+nftuvoibL13HykYntuPVo6Pc9ugb/MGdz/CPT+7lwEB0Lm9rAtkgwL6xJAcHohwdjjMcS+UCGDUzp5oR3JoTiM9dcQoP7+zmwKBTJMhJgwGGGPhMoSXsp2ckgYhj+G6vDxAOeJ0UFZadCyzM1sVOWTZ+r+Qme7/HJJG2KlYY+f1LeT2VIrstVi7ZdOjF3HzpOl58a8itBugGUeZdw+8xyNiKkXiGZ/YNcONdz0ya6Tc/sWI2EaTgVCpMWWpaT7ZNG1v5KuRsIkrBysYgdUEfthvHkx/tPVN290R4dt8gqYxFR51TCyOasogkM/zkpSP85KUjnLWijs2dy3nXKS1OmdsqkkhbJNIWg9EUXtOgxu8YyP2e8m0qkyX1XIq1ubPej762k8+r9Fhts9DMGZMlQMz36PnAeSu4/8UjOc+oXT1jCLDCfRLNJvPLBrxZbpI+j8iMoruzCiKvztHkfcVZaq9qcgodleuqOhV3PL6bf9r6plPtzmMQSzkKL6sc05aNwgnoW7uspmQiwXwvsr5IitawD8tS9Eac1UF29ZbN8DuV63OWUraWaDJNY8jP1z949oxqVeR7XFm2zbFRx960rNZHImMTSVoFW0N1AQ/vPaONzWctZ3Xz/BYW8ppGzs4xlTG+nL/paic+nCvueHw3tz+5F0PgrW9/zk727K3IC0FvQ2nmjPwtGVvBhtZa1rfUYCty2zOfu+KUgm2bkM9kWdhHOOAlHPCyvCGAIeIGCgqtYT8rG5wI6Sxe11upHBpCnpyiCPlM1jSHaK315Y4P+UzHAG84nlurmkKEA945y7PzuStO4c4Pn8/b1jTRVOPDYzh2CxHHayzLVIkEs8nixhIZDIHReIb+aCp3X7ZySr0aAnc/tb8suUrZWjI2fPay9axqDFJX5OFVDvk1xIdiaTcZpTCayNAWDtBR5+fkZTVcesoyTMNpv/+FI3zsu8/z+R+9zBOvH5u37aJsoaujw3EODkTpHZs+2WFBUk83eedSqs1991P7MYQJtenLRW9DaeaUybZkJuuTfXKLpTIEvabzRF/nKBYY3zY5d1Ujhwaj9IwmnZTXtirIN1W8xeRsgcHG9nouXtdUsJoxDSHg8+SeCEs9Zc9lnp38+73xrmc4MBBhNJ4hmXFkNEXweyYmHixOFpey7JxRPJsIEcZTrRjiZOItV6b8bali99xltf6c59pYIlPWSiOb0BCcyTibmjwbHBj0mYwlMvz1tWcwGE3x6Cs9PLSzm+6RBF2HR+g6PEJdYC/vO6OdzZ0drGqan9WGZSsiiQyRhJP1IOA1CHk9hPzmpEk9s8k7l1JtbicrsXLKBohUrDG0stAsKNNNWsX7939+/45cYads1HZWUZjipBxprvHh8xTWxc5Gkpe6RrZ4UlZhZaOqq5FnJ3ut9noP3cNxkhk7V0p1X1+EcMDD2mVOcNuqxlCBEvOZRm7CSjMxdbutnCC5ciiu+ldbop6Fx812Wx/0MhRLEUlkpowC76gLMhB1Yjm8ppGzP2XtP/lJDZtqfPzh21dzw4WreOHgEFu6uvnN3n5GExl+/MJhfvzCYc5Z1cDmzg4uWb+s6raNLEop4imLeMpiIAqttX4GYylq/J5chmEY30ZcSrW5faYQT+d5WFSItllolhTF6UayBt89vWO58qAbyqhQN915q2m4zC9BO+puLWUz8+bbHUrZLHrHkjnlmL+yygYRlmOzyFZFHI6lc9txtnISR05WUhbg8Vd7+B8PvoYhlIwCn8xm0VbnxzSMaSPGByJJHn21h4e6eugZHa/uVx/08r4znCjx+Z6YJ7unlY3BJWez+J3bnuTQUBwBjn738yR79lS0z6iVhWbJUmnd7bksozkXpTNH42lMA1IZRcr1CCsO0CtWYocGIvTHxmMIsrEpplGeogBnK+ylQ0Mom9xWUalUK6WO6x1LEPCaWLaTlr04Cjw/MWDI5wGliKWtaWuH52PZihcODvFg11GefnOgQCmeu7qBazs7eOf6ZRV5rM2GgnvyOmmV46kMKxpD3PQ763jvme3zIsdsueS2J0mlLfqjKY589/MkuytTFnobSrOglDPpluoD4/mmGoJeescSfOWBV/kqTKi5XeszGYimqAt6S/YtV458eaa69lT3mn9c90gcQ4Tl9cFcDQ2lVMEeeLEN6JLbnmR9S23J9CLlKApwbCGOO+/4OUQgY9mT7r9v3dXrugHb+D0mLWE/NX4PIhS42164rqniLLfFmIZw4domLlzbRN9YMmfb6B1L8tJbw7z01jCNIS/vO6Odazo7WNEQnP6ks2C6ezo4EF0SyQ6z25pt9UEOZ1IVG1q0N5Rmwcgv05o/6W7d1Tttn9se3TVpWcniYw4Mxhhyn8ZLeR2VI0c+c1U6M+D6+vfnVSycbg98LorerGp0XIPzNxWU61FV6jzZ8clGomdsxdHhBNFkhoytWN1UQ7BMW0mltIT9/PHFJ/HDT76d//W7Z/KOk5sxBIZiae59/hB//O3n+PP7u9i2u4/MPBXOKsayFWOJNN0jcd4ajNE75ozNYtu1yfeAmwlaWWgWjHIm3cn67OuPTkiNnfVMKT4mGyDYN5ac0LdcOfLJrxhY6nyTUXxcS9gPCpIZu+wCNnNR9ObmS9dR6/e4RbVs958iHPCUPE92fNrCAbcErvO/nhGnGNN/3nQyHfVBljcEqSlhKJ8LTEO4aF0z//P9Z3LPpy7iY+84idawU43whYND/PWDr/Ghu57h7l/vo3tkdoGFsyHrWbUYU4/ku7YjRsUflN6GOo6Y6335uZDntkd3sc+tJb22OcSXrzoNcCag5w4M5gr+ZLdhspNu9l4m6wPOE3Upd9dil1OfaZC27Jy7Y37f7PaKrRQ+N1ArlrJIWTaHh+Js3dU7YQxXNYZy7q/FtoapKPZuCge8LAtbRJMWI/F0WYb16bzHymHTxla+/oGzC7yhNrTUTFrsKTue4nO2V7JR4woKjLsBr0nAa5LMOFl2I8nqVDpsCfv5yMVr+KO3n8Rz+wd5sOsoz+0fZCiW5v89d4h7njvEBWsauaazg3esa8YzT7aNYvLrj0OSgNekxuch6DPnzburmOy2ptx8YGelx2oD93FCpUV45kOeP79/hxOcledxE/QaBNw6193D8Vzywey+fSyVwWsIsbSN15Sy+hTf753b9hVMyqPxNEeG43gMYX1rba5vNpq8dzSRqzmecWtgZwPKsjEf+WOYHwnrhnyUFT292D6jcpmuZsdkpC2bYVdpVHue6R1N8PDOHh5+pZt+N7IdnPK/V57p2Dba6wJVlaESshHkId/C2Dl01tkTmJnuo1dTnrFEBtMQTMNw/okQTTnV9EI+D611AbLZn/ojydyWiojk7mWyPl++6rRJE/gVb9V4TKEh5GXtspqCvk/vG8RrOnmqQLDcCc2xCDjtpcbw6X2DtNT68JkGtnJWLi21vmmTAU6VdHAxM9OtL2+uLkmQ+hlEhFdCa12Aj71zDfd86iK+dv0ZvH1tUy5h4g+ffYs/+pdn+fJPdvLUnv5FsSWUjSDvHolzcCBG72jpCPLFhN6GOk4o3nqB+Y0uzQ/ysm1Fxla5nEcewyluJO5TeDbNhZPeA7qH40RTFm/2jWck9QiIIfhMg8aQl7FEmkTGpjUc4OJ1TQXbbV+7/syCCbfUVs1fXXP6BM+n5w4M4jed1cPyhsB4vWkFyxucRIfF3kngjPWyWj8t4fEn1VL9phofr8cglsrkFNFCKYxyyuqWGs/sZ/CXP3tlwpbnZNuhDSEfI/E0o/E0dpVWGqYhvHP9Mt65fhk9owke2dnNw6/0MBBJ8dz+QZ7bP0hzrY+rz2zn6rM6aFsEq41sivVIMi+C3OfU5phr9+DsZ+NtWXNWpcfqbajjhJluFcwF+UFeoChO75PN4ipA2nb2+De0hQGn9OeBgdKTrClOFLFS0FzrZU1zbS4CeqZbOflbQT0jCVKWjSAsbwjQN5bM2SDWuSVCS41hpWM92fiYBrTU+idEm88X1dhOA6b9fGxbMZpIMxKfH8OvZSuefnOALV1Hef7AUC542RC4cG0T15zVwUXrmjHLTTg2j/g8BjU+J/VIJZlyS5H/uf361o/GUn0HK6pMpbehjhPmwktmpty5bR+RZAbTzXxa/JVTOMtuSzmptMMBT07OnpHxSN3iXQpLZVN5KAajaW6+dN2st9vyj19W63flU/SOJqgLerAVhAOeKcew0rEuNT4C2DaMJTLzvl24dVcvN971DN94fI+z7aGcVPLlJiO87dFd9I4m2N8f5bXuUQ4MOO6itz7yelmfj2EIDSEfq5tCNNf6Z5zYrlxMQ7hkwzJu/f1OfvDJC/mjt6+mqcaHreCZfYP81c9e5Q//5Vm++9sDBR5zi4FUxmYoluLIUJxDgzEGIkkSMywklf/ZzAS9DXWcMBdeMjMlP8hLufnApah2gwLWt9QUeEMdHopNm6LGcr2Ugl6DTRtb+cufvTKr7bb87bqsd1V/JEkiY7OmuZYb3+akD5lqDCsd6wnj4w6Kcut2zPd2YfbpMiuK40Dg1D6fLhnh1l297O6NgMpL5KgUgmJPX4TGaGqCIXmy+xMR6oNe6gJOZcThWDqXdLBadNQH+cQla/noxSfx2zcHeLCrmxcODtEXSfL9pw/yg2cO8va1zVx7dgdvW9O0qFYbjp3DsXWYhlQcCFhqq7oStLI4jign42s1WNUYoj+SRNluRTt3EhGcFODt9YEJWzT5WVif3V+Y0iGLkzW2rqCmdbH7KVQWlFZ8fF3Qi8csrF3xuTLOU8lYlxwfd4XhM415TUaX/3Rp5BVkspTCw/TJCLPHJ92EdOI+CVi2U8wplbEndWmeDBHJpah3lEb1K9t5TINLT2nh0lNaODoc56Gd3Tz6Sg9DsTRP7xvg6X0DtIb9XHNWB1ee2e7ExCwisoGAY4m0U4Pc77jlTlWDvNR3pxL0NpRm1uQHeRlu+VMFGIazpTPVFs3Nl67LTU7F5rPmGu+ELZ7ZbrctxHbdbMZnrskPDGyp9edWF1nHA1vBJy9ZO+XxbeHx47IvFE7CQJ8psxrfWr+HlY0h2uoC8xaLsLwhyKd+Zx333nQRX9l8OuevbgCgdyzJv/72ADf+yzP81X+8wrP7BxaFJ1UxtiodCFjsWTXbCG5t4NbMCRO8fUyDkM8oKwPs1l29/OVPuzgymkQp5wm1pcaLuOknJis1OtPttvnMMJt/zWJvqJC3vPGZS4qN872jCXrHkiicynVTlWbNP/7wUHz86V/AbxqsaAzSGg7kbEtzMb7RZIahBaihfWTIWW088koPI/F0rr2tzs/VZ3Vw1ZntOZvXYkXEcTKocVcdhiG5v/1//8sbU6ne/RXdQNWUhYisAr4PtOE8eNyllLpdRJqAHwFrgAPAB5VSQ+KsnW4HrgZiwMeUUi9OdQ2tLDSayphtYGD2+FTGYiDqBr8pWBb24TWr59UVSWYYiqaqbtMoJpWx+c3efh7s6ublQ8O5dkPgHScv49qzOzj/pEaMRZo8MEtWcQR9JjU+E6/HrDgor5rKogPoUEq9KCJh4AXg/cDHgEGl1K0i8mWgUSn1JRG5GvgsjrJ4O3C7UurtU11DKwuNpnLmamW259goKUvh8xhsaA3PywppLJGeF0N4KQ4NxnK2jdHE+FZOe12AazrbuerMDppqfPMuVyU8t2+QH20/xEN/8+HFs7KYcCGRnwH/6P7bpJTqdhXKVqXUqSJyp/v6Hrf/G9l+k51TKwuN5sRDKcVYMsPIAimNVMbm13v62dJ1lB2HR3LtpiG88+RmNnd2cN4iXG1kCzl5TeGZv/t4xXEW8+INJSJrgHOBZ4G2PAXQg7NNBbACOJR32GG3rUBZiMhNwE0Aq1evrp7QGk0Jqp2ssVrnn88kk9Nda7L6JOXKJyLUBbyE/R4e2dnNv/x6P0dHJpZ5rRY+j8Hlp7Vy+WmtvDUQY8vOozz26jFGExm27eln255+OuoDbO7s4H1ntC+a1ca9zx8iY1kMxyzE9FZcBKTqKwsRqQV+BfytUuonIjKslGrIe39IKdUoIluAW5VST7ntTwBfUkpNunTQK4uZUenEUa2KdJNlpZ0rWeaaaicCLHX+0Xia5hofkZQ14/udzwSG012r1Psj8TSC48ZciXzZc3kM8HtMoq7n1VSlW6tFKmOzbU8fD+7oZueR8dWGx00/cm1nB+esbljQ1cbvf/O3jMXTGIZw8Nufs5M9eysKCa+qb5qIeIF/B36olPqJ23zM3X7K2jWyFWaOAKvyDl/ptmnmkEoL/VTSv9K+f37/Dvb0RlBKoZRib1+UL96/Y05kqQbVTtZYqg7HUCzNgcHYrO53PpNMTnetUu9HkplccsmZFJOq8XvxmAZ1AS9+j8GPth+a8rhq4PMYXHFaG7ffcA7f+dgF/P55KwgHPGRsxa929/HF+7v46Hee597n3mI4lpr+hFUglbGdgNkZKqyqKQvXu+nbwOtKqb/Pe+sB4KPu648CP8tr/4g4XASMTGWv0MyMSieOSvpX2rdUVtpIMjMnslSDmRY9mun5+8aSGMKkFf4Wi9yVXKvU+5atcsklK5Gv+FwiQq3fQ99YgmVh/7zV6C5mTXMNn3n3eu676SK+fNVGzlpRB8CR4Th3/Xo/H7zzGb625TVeemtoXqvpeU1HSagZxopU02bxTuCPgZ0i8rLb9t+AW4H7ROQTwEHgg+57D+N4Qu3FcZ39eBVlO2GpNDttJf0r7Zux7YLCNOJOjHMhSzWYbfR4ped3khw6Ud5ZZnK/1Za7kmuVet80BFTh02458k12rVVNNTmbxkIawv1ek/ee3sZ7T29jf3+Uh7q6eey1Y0SSGX75Rh+/fKOPlY1Bx7Zxejv1oZmn4iiHNc21HB6KZtO5VLy8qJrqVUo9pZQSpVSnUuoc99/DSqkBpdTlSqkNSqkrlFKDbn+llPqMUupkpdRZU9kqNDOn0hrOlfSvtK/HMCbUgTYNmRNZqkG1o7+Lz59NPJgf/DWT+53PqPXprlXq/Vq/pyC5ZLnyTXetrCF8VVOIlgVcaQCsXVbDn162nvtuvogvXXkqZyx3VhuHh+J861f7+OBdT/M/H3qdHYeGq7bauOFtq/B6TFrCfpSVrrj2rE73cYJR6cRRSf9K+4YDHiw7rw60UtT6S9eBnonsc021ixcVn3/tshoaQk7uqtnc73wWXZruWqXe//oHzubvPnB2xfJVcl9hV2m01QXwe2eX6ns2BLwm7zujnf9747nc/ZHzef85y6nxm6QtxZO7evnCfTv4+He38+MXDjOaFzk+F1y4rolbLttAc41/RjW4dbqPE5BKg7Iq6V9p35l6Q813Zt2F4kS73/kinrIYjqeIT5Fhd95kSVtsfaOPLV1Heb17LNfuNYV3ndLC5s4OzlpRP2eVBr2mwermmsUTwT0faGWh0WhmQyJtMRxLzzi53lyztzfClq5uHn/9GLE8RXZSc4jNnR289/Q2woHZ2Ta0stBoNJoZkkhbDMUWx0oDnNXGL3f18mBXN2/0jK82fB6DTe5q44zldTNabWhlodFoNLNksSkNgD3Hxtiys5vHX+stcPBYu6yGa85yVhu1gfJNEFpZaDQazRyxGJVGPGXxxK5etnQdZfexSK7d7zHYdKqz2ji9Y/rVhlYWGo1GM8ck0haD0dSM615Xi93HxnhwRzdP7DpGIj0eQ7JuWQ2bOzu44vQ2av2lVxtaWWg0Gk2ViKcsBmMpkotMacRSGZ543bFt7O0dX20EPAbv3tjK5s4ONraHC1YbWlloNBpNlYmlMgxG579y33QopXjj2Bhburp58vVeEnnyrW+p5ZrODq44rZUav0crC41Go5kvoklHaSxEGpHpiCYzPP66Y9t4sy+aaw94DS7b2MrvnrOC957ZoZWFRqPRzBcLVe61HJRS7OpxVhu/3FW42jh42+aKlcW8FD/SaDSa45Fav4dav2dBy71OhohwWkcdp3XU8SebTubx146xpas7lzGh4vPplYVGo9HMnmy51+FoekLK9cWCUordxyJc3blcryw0Go1mIcgv9zqacFKjLzalISKcuaJ+RsdqZaHRaDRziIhQH/RSF1i8SmMmaGWh0Wg0VeB4UxpaWWg0Gk0VOV6UhlYWGo1GMw/kK43FbggvhVYWGo1GM4/kG8IXskZ4pWhlodFoNAtAvtKIJDOLLk6jGK0sNBqNZgEREcIBL+GAd1FHhGtlodFoNIuEbER4NJlhKLa4EhYa1TqxiHxHRHpF5JW8tiYR+YWI7HF/NrrtIiJ3iMheEekSkfOqJZdGo9Esdmr8HlY2hmivD+D3mgstDlBFZQF8F7iyqO3LwBNKqQ3AE+7vAFcBG9x/NwHfrKJcGo1GsyQI+TysaAjSUR8ksMBKo2rKQim1DRgsar4e+J77+nvA+/Pav68cngEaRKSjWrJpNBrNUiLoM1m+wEqjmiuLUrQppbrd1z1Am/t6BXAor99ht20CInKTiGwXke19fX3Vk1Sj0WgWGQupNOZbWeRQTrrbilPeKqXuUkpdoJS6oKWlpQqSaTQazeImqzTm06Yx38riWHZ7yf3Z67YfAVbl9Vvptmk0Go1mErI2jflQGvOtLB4APuq+/ijws7z2j7heURcBI3nbVRqNRqOZgnylUa3tqarFWYjIPcAmYJmIHAb+B3ArcJ+IfAI4CHzQ7f4wcDWwF4gBH6+WXBqNRnO8EvJ5CPk8xFMWQ7EUibQ1Z+eumrJQSt04yVuXl+irgM9USxaNRqM5kQj6TIK+4JwqDR3BrdFoNMcpWaWRSDtKI56audLQykKj0WiOcwJek456R2mMJTIzOodWFhqNRnOCEPCaMzaAL1ichUaj0WiWDlpZaDQajWZatLLQaDQazbRoZaHRaDSaadHKQqPRaDTTopWFRqPRaKZFKwuNRqPRTItWFhqNRqOZFq0sNBqNRjMt4uTwW5qIyBjwxkLLUcQyoH+hhShiMcoEi1MuLVN5aJnKZzHKdapSKlzJAUs93ccbSqkLFlqIfERku5apPBajXFqm8tAylc9ilEtEtld6jN6G0mg0Gs20aGWh0Wg0mmlZ6sriroUWoARapvJZjHJpmcpDy1Q+i1GuimVa0gZujUaj0cwPS31lodFoNJp5QCsLjUaj0UzLklUWInJARHaKyMszcQObIxm+IyK9IvJKXluTiPxCRPa4PxsXgUx/LSJH3LF6WUSunmeZVonIL0XkNRF5VURucdsXbKymkGmhxyogIs+JyA5Xrr9x29eKyLMisldEfiQivkUg03dFZH/eWJ0zXzLlyWaKyEsissX9fcHGaQqZFnScSs2VM/nuLVll4fJupdQ5C+jD/F3gyqK2LwNPKKU2AE+4vy+0TADfcMfqHKXUw/MsUwb4L0qp04GLgM+IyOks7FhNJhMs7FglgcuUUmcD5wBXishFwG2uXOuBIeATi0AmgD/PG6uX51GmLLcAr+f9vpDjNJlMsPDjVDxXVvzdW+rKYkFRSm0DBouarwe+577+HvD+RSDTgqKU6lZKvei+HsP5Iq1gAcdqCpkWFOUQcX/1uv8UcBlwv9s+32M1mUwLioisBK4B7nZ/FxZwnErJtIip+Lu3lJWFAh4TkRdE5KaFFiaPNqVUt/u6B2hbSGHy+FMR6XK3qeZ1aywfEVkDnAs8yyIZqyKZYIHHyt3GeBnoBX4BvAkMK6UybpfDzLNiK5ZJKZUdq791x+obIuKfT5mAfwD+ArDd35tZ4HEqIVOWhRynUnNlxd+9pawsLlFKnQdchbOFcOlCC1SMcvySF/wJDPgmcDLOFkI38H8WQggRqQX+Hfi8Umo0/72FGqsSMi34WCmlLKXUOcBK4EJg43zLUEyxTCJyJvBfcWR7G9AEfGm+5BGRzUCvUuqF+brmdEwh04KNk8uUc2W5370lqyyUUkfcn73AT3G+VIuBYyLSAeD+7F1geVBKHXO/7DbwLyzAWImIF2dS/qFS6idu84KOVSmZFsNYZVFKDQO/BC4GGkQkm8ttJXBkgWW60t3KU0qpJPCvzO9YvRO4TkQOAPfibD/dzsKO0wSZROQHCzxOk82VFX/3lqSyEJEaEQlnXwPvBV6Z+qh54wHgo+7rjwI/W0BZgNwfQ5bfZZ7Hyt1L/jbwulLq7/PeWrCxmkymRTBWLSLS4L4OAu/Bsaf8EviA222+x6qUTLvyJhvB2fOet7FSSv1XpdRKpdQa4AbgSaXUH7GA4zSJTB9eyHGaYq6s/LunlFpy/4B1wA7336vAf18gOe7B2apI4+yPfgJn3/QJYA/wONC0CGT6N2An0OX+kXTMs0yX4Cxzu4CX3X9XL+RYTSHTQo9VJ/CSe/1XgK+47euA54C9wI8B/yKQ6Ul3rF4BfgDUzudY5cm3Cdiy0OM0hUwLNk6TzZUz+e7pdB8ajUajmZYluQ2l0Wg0mvlFKwuNRqPRTItWFhqNRqOZFq0sNBqNRjMtWlloNBqNZlq0stBo5hER2SoiC5X4UqOZMVpZaDQajWZatLLQaKZBRNaIyC63LsFuEfmhiFwhIr9x6wFc6EbKfset+/CSiFzvHhsUkXtF5HUR+SkQdNs/LSJ/l3eNj4nIPy7QLWo006KD8jSaaXCz0u7FyUz7KvA8TkTsJ4DrgI8DrwGvKaV+4KbGeM7tfzNwplLqP4lIJ/AiTv2Mg8DTyqm7gIg8AvytUuqpebw1jaZsPNN30Wg0wH6l1E4AEXkVp3CMEpGdwBqcpHXXicgX3f4BYDVwKXAHgFKqS0S63Nd9IrLPLSK0Bycr6W/m84Y0mkrQykKjKY9k3ms773cb53tkAb+vlHoj/yAnd9yk3At8ENgF/FTpZb5mEaNtFhrN3PBz4LNuZlFE5Fy3fRvwh27bmThJ+bL8FKdi2Y04ikOjWbRoZaHRzA1fwyk32uVuU33Nbf8mUCsirwNfBXKFcZRSQzjpx09SSj03z/JqNBWhDdwajUajmRa9stBoNBrNtGhlodFoNJpp0cpCo9FoNNOilYVGo9FopkUrC41Go9FMi1YWGo1Go5kWrSw0Go1GMy3/Pz10mijVTG2yAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cols = ['crim', 'rm', 'ptratio', 'lstat', 'indus', 'tax']\n",
+    "for i in cols:\n",
+    "    print (f\"\\nmdev and {i}: correlation {(data['medv'].corr(data[i]))}\")\n",
+    "    sns.regplot(x='medv',y=i , data=data)\n",
+    "    plt.show()"
    ]
   },
   {
@@ -72,7 +1056,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your response here"
+    "# Your response here\n",
+    "#most corelated is lstat\n"
    ]
   },
   {
@@ -84,11 +1069,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 792x648 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Your response here"
+    "# Your response here\n",
+    "import seaborn as sns\n",
+    "corr = data.corr()\n",
+    "mask = np.triu(np.ones_like(corr))\n",
+    "fig, ax = plt.subplots(figsize=(11,9))\n",
+    "cmap = sns.diverging_palette(10, 110, as_cmap=True)\n",
+    "sns.heatmap(corr, mask=mask, cmap=cmap, vmax=1, center=0.5, square=True, linewidths=0.5, cbar_kws={\"shrink\":0.5})"
    ]
   },
   {
@@ -102,11 +1116,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "count    404.000000\n",
+       "mean      22.312376\n",
+       "std        8.837019\n",
+       "min        5.000000\n",
+       "25%       17.100000\n",
+       "50%       21.400000\n",
+       "75%       25.000000\n",
+       "max       50.000000\n",
+       "Name: medv, dtype: float64"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "# Your code here\n",
+    "\n",
+    "data.medv.describe()"
    ]
   },
   {
@@ -128,7 +1163,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -137,7 +1172,8 @@
     "def performance_metric(y_true, y_predict):\n",
     "    \"\"\" Calculates and returns the performance score between \n",
     "        true and predicted values based on the metric chosen. \"\"\"\n",
-    "    # Your code here:"
+    "    # Your code here:\n",
+    "    return r2_score(y_true, y_predict)"
    ]
   },
   {
@@ -150,11 +1186,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here"
+    "# Your code here\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "train_set, test_set = train_test_split(data, test_size= 0.2, shuffle=True, random_state=123)\n",
+    "train_X = train_set.drop(columns='medv')\n",
+    "train_y =train_set['medv']\n",
+    "test_X = test_set.drop(columns='medv')\n",
+    "test_y =test_set['medv']"
    ]
   },
   {
@@ -167,6 +1209,16 @@
     "Next, we are going to build a Random Forest Regressor, and test its performance with several different parameter settings."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.ensemble import RandomForestRegressor\n",
+    "from sklearn.model_selection import GridSearchCV"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -177,11 +1229,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Five separate RFR here with the given max depths"
+    "RFR = GridSearchCV(estimator=RandomForestRegressor(),\n",
+    "                             param_grid={\"max_depth\":[2, 4, 6, 8, 10]},\n",
+    "                             scoring='r2',\n",
+    "                             cv=5\n",
+    "                             )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "GridSearchCV(cv=5, estimator=RandomForestRegressor(),\n",
+       "             param_grid={'max_depth': [2, 4, 6, 8, 10]}, scoring='r2')"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "RFR.fit(train_X, train_y)"
    ]
   },
   {
@@ -193,13 +1270,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 24,
    "metadata": {
     "scrolled": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:>"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Produce a plot with the score for the testing and training for the different max depths"
+    "# Produce a plot with the score for the testing and training for the different max depths\n",
+    "curves = RFR.cv_results_\n",
+    "    \n",
+    "result = pd.DataFrame(curves['mean_test_score'], \n",
+    "                       columns=['Train_R2'], \n",
+    "                       index = RFR.param_grid['max_depth'])\n",
+    " \n",
+    "sns.lineplot(data=result, linewidth=2.5)"
    ]
   },
   {
@@ -215,7 +1322,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your response here"
+    "# Your response here\n",
+    "# error increases with tree depth increases\n",
+    "# error increases less with deth"
    ]
   },
   {
@@ -232,7 +1341,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your response here"
+    "# Your response here\n",
+    "# max depth of 1 suffers from bias\n",
+    "# max depth of 10 suffers from variance"
    ]
   },
   {
@@ -249,7 +1360,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your response here"
+    "# Your response here\n",
+    "#depth=8"
    ]
   },
   {
@@ -292,7 +1404,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.2"
+   "version": "3.8.6"
   }
  },
  "nbformat": 4,
diff --git a/your-code/lab_overfitting.ipynb b/your-code/lab_overfitting.ipynb
index 9739877..fdf9d1f 100644
--- a/your-code/lab_overfitting.ipynb
+++ b/your-code/lab_overfitting.ipynb
@@ -21,7 +21,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -56,11 +56,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "from sklearn import svm\n",
+    "\n",
+    "list_1 = svm.SVC(gamma = 0.001)\n",
+    "list_2 = svm.SVC(gamma = 1)\n",
+    "list_3 = svm.SVC(gamma = 20)"
    ]
   },
   {
@@ -72,12 +77,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 864x432 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "from matplotlib.colors import ListedColormap\n",
     "\n",
+    "classifiers = [list_1,list_2,list_3]\n",
     "figure = plt.figure(figsize=(12, 6))\n",
     "i = 1\n",
     "h = .02  # step size in the mesh\n",
@@ -86,7 +103,8 @@
     "xx, yy = np.meshgrid(np.arange(x_min, x_max, h),\n",
     "                     np.arange(y_min, y_max, h))\n",
     "cm = plt.cm.RdBu\n",
-    "cm_bright = ListedColormap(['#FF0000', '#0000FF'])\nnames = ['gamma = 0.001', 'gamma = 1', 'gamma = 20']\n",
+    "cm_bright = ListedColormap(['#FF0000', '#0000FF'])\n",
+    "names = ['gamma = 0.001', 'gamma = 1', 'gamma = 20']\n",
     "\n",
     "# iterate over classifiers\n",
     "for name, clf in zip(names, classifiers):\n",
@@ -112,7 +130,7 @@
     "    ax.set_yticks(())\n",
     "    ax.set_title(name)\n",
     "    i += 1\n",
-    "plt.show()"
+    "plt.show()\n"
    ]
   },
   {
@@ -133,7 +151,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your response here"
+    "# Your response here\n",
+    "# 1 it's the best one (list_2)"
    ]
   },
   {
@@ -146,11 +165,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.93"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "# Your code here\n",
+    "list_4 = svm.SVC(gamma=0.7)\n",
+    "list_4.fit(X,y)\n",
+    "list_4.score(X,y)"
    ]
   },
   {
@@ -162,11 +195,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.0"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "list_3.fit(train_X, train_y)\n",
+    "y_pred = list_3.predict(test_X)\n",
+    "r2_score(test_y, y_pred)"
    ]
   },
   {
@@ -178,11 +224,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-1.2727272727272725"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "# Your code here\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.metrics import r2_score\n",
+    "\n",
+    "train_X, test_X, train_y, test_y = train_test_split(X, y, random_state = 1234)\n",
+    "\n",
+    "list_1.fit(train_X, train_y)\n",
+    "\n",
+    "y_pred = list_1.predict(test_X)\n",
+    "r2_score(test_y, y_pred)"
    ]
   },
   {
@@ -218,7 +284,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.2"
+   "version": "3.8.6"
   }
  },
  "nbformat": 4,