Genre_RandomForest_scaled.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>track_id</th>\n",
       "      <th>artist</th>\n",
       "      <th>track</th>\n",
       "      <th>spotify_genre</th>\n",
       "      <th>spotify_track_id</th>\n",
       "      <th>spotify_track_album</th>\n",
       "      <th>spotify_track_explicit</th>\n",
       "      <th>spotify_track_duration_ms</th>\n",
       "      <th>spotify_track_popularity</th>\n",
       "      <th>danceability</th>\n",
       "      <th>...</th>\n",
       "      <th>key</th>\n",
       "      <th>loudness</th>\n",
       "      <th>mode</th>\n",
       "      <th>speechiness</th>\n",
       "      <th>acousticness</th>\n",
       "      <th>instrumentalness</th>\n",
       "      <th>liveness</th>\n",
       "      <th>valence</th>\n",
       "      <th>tempo</th>\n",
       "      <th>time_signature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AdictoTainy, Anuel AA &amp; Ozuna</td>\n",
       "      <td>Tainy, Anuel AA &amp; Ozuna</td>\n",
       "      <td>Adicto</td>\n",
       "      <td>['pop reggaeton']</td>\n",
       "      <td>3jbT1Y5MoPwEIpZndDDwVq</td>\n",
       "      <td>Adicto (with Anuel AA &amp; Ozuna)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>270740.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>0.734</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>-4.803</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0735</td>\n",
       "      <td>0.01700</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>0.1790</td>\n",
       "      <td>0.623</td>\n",
       "      <td>80.002</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Ones That Didn't Make It Back HomeJustin M...</td>\n",
       "      <td>Justin Moore</td>\n",
       "      <td>The Ones That Didn't Make It Back Home</td>\n",
       "      <td>['arkansas country', 'contemporary country', '...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ShallowLady Gaga &amp; Bradley Cooper</td>\n",
       "      <td>Lady Gaga &amp; Bradley Cooper</td>\n",
       "      <td>Shallow</td>\n",
       "      <td>['dance pop', 'pop']</td>\n",
       "      <td>2VxeLyX666F8uXCJ0dZF8B</td>\n",
       "      <td>A Star Is Born Soundtrack</td>\n",
       "      <td>0.0</td>\n",
       "      <td>215733.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>0.572</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-6.362</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0308</td>\n",
       "      <td>0.37100</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2310</td>\n",
       "      <td>0.323</td>\n",
       "      <td>95.799</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>EnemiesPost Malone Featuring DaBaby</td>\n",
       "      <td>Post Malone Featuring DaBaby</td>\n",
       "      <td>Enemies</td>\n",
       "      <td>['dfw rap', 'melodic rap', 'rap']</td>\n",
       "      <td>0Xek5rqai2jcOWCYWJfVCF</td>\n",
       "      <td>Hollywood's Bleeding</td>\n",
       "      <td>1.0</td>\n",
       "      <td>196760.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>0.542</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-4.169</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2100</td>\n",
       "      <td>0.05880</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0955</td>\n",
       "      <td>0.667</td>\n",
       "      <td>76.388</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Bacc At It AgainYella Beezy, Gucci Mane &amp; Quavo</td>\n",
       "      <td>Yella Beezy, Gucci Mane &amp; Quavo</td>\n",
       "      <td>Bacc At It Again</td>\n",
       "      <td>['dfw rap', 'rap', 'southern hip hop', 'trap']</td>\n",
       "      <td>2biNa12dMbHJrHVFRt8JyO</td>\n",
       "      <td>Bacc At It Again</td>\n",
       "      <td>1.0</td>\n",
       "      <td>228185.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>0.948</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>-5.725</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1680</td>\n",
       "      <td>0.00124</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.0716</td>\n",
       "      <td>0.856</td>\n",
       "      <td>135.979</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            track_id  \\\n",
       "0                      AdictoTainy, Anuel AA & Ozuna   \n",
       "1  The Ones That Didn't Make It Back HomeJustin M...   \n",
       "2                  ShallowLady Gaga & Bradley Cooper   \n",
       "3                EnemiesPost Malone Featuring DaBaby   \n",
       "4    Bacc At It AgainYella Beezy, Gucci Mane & Quavo   \n",
       "\n",
       "                            artist                                   track  \\\n",
       "0          Tainy, Anuel AA & Ozuna                                  Adicto   \n",
       "1                     Justin Moore  The Ones That Didn't Make It Back Home   \n",
       "2       Lady Gaga & Bradley Cooper                                 Shallow   \n",
       "3     Post Malone Featuring DaBaby                                 Enemies   \n",
       "4  Yella Beezy, Gucci Mane & Quavo                        Bacc At It Again   \n",
       "\n",
       "                                       spotify_genre        spotify_track_id  \\\n",
       "0                                  ['pop reggaeton']  3jbT1Y5MoPwEIpZndDDwVq   \n",
       "1  ['arkansas country', 'contemporary country', '...                     NaN   \n",
       "2                               ['dance pop', 'pop']  2VxeLyX666F8uXCJ0dZF8B   \n",
       "3                  ['dfw rap', 'melodic rap', 'rap']  0Xek5rqai2jcOWCYWJfVCF   \n",
       "4     ['dfw rap', 'rap', 'southern hip hop', 'trap']  2biNa12dMbHJrHVFRt8JyO   \n",
       "\n",
       "              spotify_track_album  spotify_track_explicit  \\\n",
       "0  Adicto (with Anuel AA & Ozuna)                     0.0   \n",
       "1                             NaN                     NaN   \n",
       "2       A Star Is Born Soundtrack                     0.0   \n",
       "3            Hollywood's Bleeding                     1.0   \n",
       "4                Bacc At It Again                     1.0   \n",
       "\n",
       "   spotify_track_duration_ms  spotify_track_popularity  danceability  ...  \\\n",
       "0                   270740.0                      91.0         0.734  ...   \n",
       "1                        NaN                       NaN           NaN  ...   \n",
       "2                   215733.0                      88.0         0.572  ...   \n",
       "3                   196760.0                      86.0         0.542  ...   \n",
       "4                   228185.0                      61.0         0.948  ...   \n",
       "\n",
       "    key  loudness  mode  speechiness  acousticness  instrumentalness  \\\n",
       "0  10.0    -4.803   0.0       0.0735       0.01700          0.000016   \n",
       "1   NaN       NaN   NaN          NaN           NaN               NaN   \n",
       "2   7.0    -6.362   1.0       0.0308       0.37100          0.000000   \n",
       "3   6.0    -4.169   1.0       0.2100       0.05880          0.000000   \n",
       "4   8.0    -5.725   0.0       0.1680       0.00124          0.000001   \n",
       "\n",
       "   liveness  valence    tempo  time_signature  \n",
       "0    0.1790    0.623   80.002             4.0  \n",
       "1       NaN      NaN      NaN             NaN  \n",
       "2    0.2310    0.323   95.799             4.0  \n",
       "3    0.0955    0.667   76.388             4.0  \n",
       "4    0.0716    0.856  135.979             4.0  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "audio = pd.read_csv('data/audio_features_hot_100_1958_2019.csv')\n",
    "audio.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# billboard = pd.read_csv('data/billboard_hot_100_1958_2019.csv')\n",
    "# billboard.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['pop', 'country', 'rap', 'hiphop', 'other', 'latin', 'house',\n",
       "       'folk', 'r&b', 'adult standards', 'rock', 'metal', 'show tunes',\n",
       "       'soul', 'jazz'], dtype=object)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genre = pd.read_csv('data/songGenre.csv')[['track_id','supergenre']].rename(columns = {'songid':'SongID'})\n",
    "genre = genre.drop_duplicates()\n",
    "genre['supergenre'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>spotify_track_duration_ms</th>\n",
       "      <th>danceability</th>\n",
       "      <th>energy</th>\n",
       "      <th>loudness</th>\n",
       "      <th>speechiness</th>\n",
       "      <th>acousticness</th>\n",
       "      <th>instrumentalness</th>\n",
       "      <th>valence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>270740.0</td>\n",
       "      <td>0.734</td>\n",
       "      <td>0.836</td>\n",
       "      <td>-4.803</td>\n",
       "      <td>0.0735</td>\n",
       "      <td>0.01700</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>0.623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>215733.0</td>\n",
       "      <td>0.572</td>\n",
       "      <td>0.385</td>\n",
       "      <td>-6.362</td>\n",
       "      <td>0.0308</td>\n",
       "      <td>0.37100</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>215733.0</td>\n",
       "      <td>0.572</td>\n",
       "      <td>0.385</td>\n",
       "      <td>-6.362</td>\n",
       "      <td>0.0308</td>\n",
       "      <td>0.37100</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>196760.0</td>\n",
       "      <td>0.542</td>\n",
       "      <td>0.674</td>\n",
       "      <td>-4.169</td>\n",
       "      <td>0.2100</td>\n",
       "      <td>0.05880</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>228185.0</td>\n",
       "      <td>0.948</td>\n",
       "      <td>0.623</td>\n",
       "      <td>-5.725</td>\n",
       "      <td>0.1680</td>\n",
       "      <td>0.00124</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.856</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   spotify_track_duration_ms  danceability  energy  loudness  speechiness  \\\n",
       "0                   270740.0         0.734   0.836    -4.803       0.0735   \n",
       "2                   215733.0         0.572   0.385    -6.362       0.0308   \n",
       "3                   215733.0         0.572   0.385    -6.362       0.0308   \n",
       "4                   196760.0         0.542   0.674    -4.169       0.2100   \n",
       "5                   228185.0         0.948   0.623    -5.725       0.1680   \n",
       "\n",
       "   acousticness  instrumentalness  valence  \n",
       "0       0.01700          0.000016    0.623  \n",
       "2       0.37100          0.000000    0.323  \n",
       "3       0.37100          0.000000    0.323  \n",
       "4       0.05880          0.000000    0.667  \n",
       "5       0.00124          0.000001    0.856  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "join_df = genre.merge(audio, on = 'track_id', how = 'left').dropna(how='any')\n",
    "target = join_df[['supergenre']]\n",
    "feature_names =['spotify_track_duration_ms','danceability','energy','loudness','speechiness','acousticness','instrumentalness','valence']\n",
    "features = join_df[feature_names]\n",
    "features.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.724930</td>\n",
       "      <td>0.887160</td>\n",
       "      <td>1.089516</td>\n",
       "      <td>1.081177</td>\n",
       "      <td>0.021188</td>\n",
       "      <td>-0.986422</td>\n",
       "      <td>-0.240036</td>\n",
       "      <td>0.074276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.083008</td>\n",
       "      <td>-0.171642</td>\n",
       "      <td>-1.165912</td>\n",
       "      <td>0.649717</td>\n",
       "      <td>-0.509763</td>\n",
       "      <td>0.265609</td>\n",
       "      <td>-0.240156</td>\n",
       "      <td>-1.185554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.083008</td>\n",
       "      <td>-0.171642</td>\n",
       "      <td>-1.165912</td>\n",
       "      <td>0.649717</td>\n",
       "      <td>-0.509763</td>\n",
       "      <td>0.265609</td>\n",
       "      <td>-0.240156</td>\n",
       "      <td>-1.185554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.361682</td>\n",
       "      <td>-0.367716</td>\n",
       "      <td>0.279362</td>\n",
       "      <td>1.256639</td>\n",
       "      <td>1.718488</td>\n",
       "      <td>-0.838584</td>\n",
       "      <td>-0.240156</td>\n",
       "      <td>0.259052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.099885</td>\n",
       "      <td>2.285823</td>\n",
       "      <td>0.024314</td>\n",
       "      <td>0.826009</td>\n",
       "      <td>1.196242</td>\n",
       "      <td>-1.042162</td>\n",
       "      <td>-0.240148</td>\n",
       "      <td>1.052745</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3         4         5         6  \\\n",
       "0  0.724930  0.887160  1.089516  1.081177  0.021188 -0.986422 -0.240036   \n",
       "1 -0.083008 -0.171642 -1.165912  0.649717 -0.509763  0.265609 -0.240156   \n",
       "2 -0.083008 -0.171642 -1.165912  0.649717 -0.509763  0.265609 -0.240156   \n",
       "3 -0.361682 -0.367716  0.279362  1.256639  1.718488 -0.838584 -0.240156   \n",
       "4  0.099885  2.285823  0.024314  0.826009  1.196242 -1.042162 -0.240148   \n",
       "\n",
       "          7  \n",
       "0  0.074276  \n",
       "1 -1.185554  \n",
       "2 -1.185554  \n",
       "3  0.259052  \n",
       "4  1.052745  "
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "scaler = StandardScaler()\n",
    "transform = features \n",
    "transform.head()\n",
    "features = pd.DataFrame(scaler.fit_transform(transform))\n",
    "features.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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b84HX9BR3/Pjx0RdbnnB5n45f07G7i9HV1dWU8xUVpy/l7us52zV2X89ZRIyyl7tdY7frZ7Co2MAdUSP/1tPGfzuwtaQxktYGPgLMrDrmcWAvAEljgaHA0/V//ZiZ2ZrSa+KPiGXAUcDVwDzS6J37JZ0uaf/ssP8CPiXpHuBi4LDs28bMzEqmrnH8kcbkX1m175Tczw8AexRbNDMzawbfuWtm1mE8V4/ZAOGhuVYvJ36zAcJ3M1u9nPjNrFe+mhhYnPjNrFe+mhhY3LlrZtZhnPjNzDqMm3qsLa0/9kTefN6JtZ88r9bxAKs3VZiVUbM/30781pYWz5vmNmcbsJr9+XZTj5lZh3HiNzPrMB3V1ON1cc3MOizxe11cM7MSJn7Xylfn92Tg8GgkK4PSJX7Xylfn92Tg8GgkKwN37pqZdRgnfjOzDuPEb2bWYZz4zcw6jBO/mVmHKd2oHluzPLzQrPM48Xc4Dy+0gcwVm9qc+M1swHLFpja38ZuZdRjX+M2spbyQ+5rnxF+QvrQldko7olk9vJD7mufEX5C+tCX6g2tmreQ2fjOzDuPEb2bWYZz4zcw6jBO/mVmHqatzV9I+wHeAwcBPImJajWM+DJwKBHBPRHy0wHJaG/Jdk2bl1GvilzQYOBt4F7AAuF3SzIh4IHfM1sBJwB4RsVDSa5pVYGsfvmvSrJzqqfHvCjwUEfMBJM0ADgAeyB3zKeDsiFgIEBF/L7qgZtY6vnobWOpJ/JsBT+S2FwC7VR2zDYCkm0jNQadGxFXVgSQdARwBMHLkSGbNmlXzhLX2L1mypOb+7mJ0x7Ebi93X+O0auy/nLCJG2d+TxfOmce4+w2rGHj58+Gr7D7tqaSnK7djdiIgeH8BBpHb9yvahwFlVx1wO/BpYCxhD+nIY0VPc8ePHRy1bnnB5zf1dXV11H9sdx24sdl/jt2vsvp6ziBhlf08cuz1jA3dEjfxbz6ieBcAWue3NgadqHPPbiHg5Ih4BHgS2rv/rx8zM1pR6mnpuB7aWNAZ4EvgIUD1i5zfAZOBcSZuQmn7mF1lQs2rddgZfVXtir3p50jAb6HpN/BGxTNJRwNWk9vufRsT9kk4nXUbMzJ57t6QHgFeAz0fEM80suHW2WqOFICXm7p6rlycNs4GurnH8EXElcGXVvlNyPwdwXPYwsxbwyBurl2fnNBsgfN+E1ctTNpiZdRjX+M3MSqhZgxfAid/MrHSaOXgBnPjbgpd1NLMiOfG3AS/raGZF6qjE75qzmVmHJX7XnM3MPJzTzKzjdFSN32pr5rAxMysfJ/4O1+xhY2ZWPqVL/O6ANbN20M5zI5Uu8bsD1szaQTvPjeTOXTOzDuPEb2bWYUrX1GM20HkUlbWaE7/ZGuRRVKtr507SduXEb2Yt1c6dpO3KbfxmZh3Gid/MrMM48ZuZdRgnfjOzDuPEb2bWYTyqx8wGNN83sTonfjMbsHzfRG1O/AWqt2bRKbUKMysnJ/6CuGZhZu3CnbtmZh3Gid/MrMM48ZuZdZi6Er+kfSQ9KOkhSd1MoweSPiQpJO1cXBHNzKxIvSZ+SYOBs4F9gXHAZEnjahy3PnAM8KeiC2lmZsWpp8a/K/BQRMyPiH8BM4ADahz3FeBrwIsFls/MzApWT+LfDHgit70g27eCpB2BLSLi8gLLZmZmTVDPOH7V2BcrnpQGAd8GDus1kHQEcATAyJEjmTVrVs3jau1fsmRJzf3dxehOM2P35ZxFxBho5W7mOYuI0enlbtfYfTlnETHaodxERI8PYHfg6tz2ScBJue0NgX8Aj2aPF4GngJ17ijt+/PioZcsTLq+5v6urq+5ju9PM2H09ZxExBlK5m33Ovtju3O36/ChDuZv5frdr7L6es4gYZSo3cEfUyL/11PhvB7aWNAZ4EvgI8NHcF8dzwCaVbUmzgP8XEXc09I1k1iJeCtAGul4Tf0Qsk3QUcDUwGPhpRNwv6XTSt8nMZhfSzOrjmSitHnXN1RMRVwJXVu07pZtjJzZeLDPrK88XZfXynbtmZh3Gs3O2CU/5bK3mZqSBw4m/DfgS3lrNn8GBxYnfmsq1RLPyceK3pnEt0aycOi7xu63czDpdRyV+10DNzEqa+F0rNzNrntIlftfKzcyayzdwmZl1GCd+M7MO48RvZtZhStfGb2adxzf6rVlO/GbWUh7Qsea5qcfMrMO4xm9m1k/t2kTlxG9m1g/t3ETlxG9tT9Kq22eu/DmtN9137VqTM6uHE7+1vXxy725B9L5o55qcWT3cuWtm1mGc+M3MOowTv5lZh3HiNzPrME78ZmYdxonfzKzDOPGbmXUYJ34zsw7jxG9m1mGc+M3MOowTv5lZh3HiNzPrMHUlfkn7SHpQ0kOSTqzx/HGSHpB0r6TrJG1ZfFHNzKwIvSZ+SYOBs4F9gXHAZEnjqg67C9g5It4CXAp8reiCmplZMeqp8e8KPBQR8yPiX8AM4ID8ARHRFRH/zDZvBTYvtphmZlaUehL/ZsATue0F2b7uTAF+30ihzMyseepZiEU19tVc1kjSIcDOwJ7dPH8EcATAyJEjmTVrVn2lzPT1eMfunNjXXXcdF154IY8//jijRo3ikEMOYa+99ir0HNBe74ljO3a3IqLHB7A7cHVu+yTgpBrH7Q3MA17TW8yIYPz48dEXW55weZ+Od+zOiX3RRRfFmDFj4vrrr48//OEPcf3118eYMWPioosuKvQ87fSeOLZjR0QAd0SN/FtPU8/twNaSxkhaG/gIMDN/gKQdgR8C+0fE3xv/OjKr39SpU5k+fTqTJk1iyJAhTJo0ienTpzN16tRWF82slHpN/BGxDDgKuJpUo/9lRNwv6XRJ+2eHfR0YDlwi6W5JM7sJZ1a4efPmMWHChFX2TZgwgXnz5rWoRGblVtdi6xFxJXBl1b5Tcj/vXXC5zOo2duxYZs+ezaRJk1bsmz17NmPHjm1hqczKy3fuWts7+eSTmTJlCl1dXSxbtoyuri6mTJnCySef3OqimZVSXTV+szKbPHkyAEcffTTz5s1j7NixTJ06dcV+M1uVE78NCJMnT2by5MnMmjWLiRMntro4ZqXmph4zsw7jxG9m1mGc+M3MOozb+G0FadXZOXTmyp/TTYBmNhC4xm8r5G/p7urqqp6Sw8wGCCd+M7MO48RvZtZhnPjNzDqME7+ZWYdx4jcz6zBO/GZmHcbj+M3MSqwZ99e4xm9mVmLNuL/Gid/MrEGSVjweO/P9q2wX4eKLL2a77bZjr732YrvttuPiiy9uKJ4TfxM0+0PQTEV/wMw6QTPver/44os59thjWbp0KQBLly7l2GOPbej/ptv4myD/x26n+eEvvvhiTj75ZKZPn84rr7zC4MGDmTJlCoAXNTFrkeOPP56lS5eyaNEili9fzpNPPslaa63F8ccf3+//l67x2wpTp05l+vTpTJo0iSFDhjBp0iSmT5/O1KlTW100s461YMECXnzxRaZNm8bvf/97pk2bxosvvsiCBQv6HdOJ31aYN28eEyZMWGXfhAkTmDdvXotKZGYAhx9+OMcddxxDhw7luOOO4/DDD28onpt6bIWxY8cye/ZsJk2atGLf7NmzGTt2bAtLZWYzZszgmmuu4fHHH2fUqFE8++yzDcXr2MTvuedXd/LJJzNlypQVbfxdXV1MmTLFTT1mLTRo0CAWL17Muuuuy/Lly3nhhRdYvHgxgwb1v8GmYxN/u3bANlOlo+joo49m3rx5jB07lqlTp7pj16yFRowYwcKFC5HEoEGDVlRaR4wY0e+YbuM3MyuxRYsWceSRR7Jw4UKWL1/OwoULOfLII1m0aFG/Y3Zsjd9W5+GcZuUzduxYDjroIL7//e+vaJ3o6urixhtv7HdM1/htBQ/nXF0734xnA0Ol762rq4tly5at6Hs7+eST+x2z1DX+7jpgO7XzFZrbKd3M4Zzt2pnezL6gdn1Pmlnudo3dTM3oeyt1jb+726A7WTNvDa8M58wrajinF3JfXbu+J80sd7vGbrbJkyczd+5crrvuOubOndtw02upE7+tWc24pDSz8qmrqUfSPsB3gMHATyJiWtXz6wDnA+OBZ4CDI+LRYotqzebhnGadodcav6TBwNnAvsA4YLKkcVWHTQEWRsQbgG8DZ2JtqehLSjMrn3qaenYFHoqI+RHxL2AGcEDVMQcA52U/XwrsJQ97MDMrpXoS/2bAE7ntBdm+msdExDLgOWDjIgpoZmbFUm892pIOAt4TEYdn24cCu0bE0blj7s+OWZBtP5wd80xVrCOAIwBGjhw5fsaMGXUXdMmSJQwfPrzu4/vCsR17oMXOT7RXraurq7DztNN70omxJ02aNCcidl7tifyQploPYHfg6tz2ScBJVcdcDeye/TwE+AfZl0p3j/Hjx0dfdHV19el4x3Zsx3bsTo8N3BE18m89TT23A1tLGiNpbeAjwMyqY2YCn8h+/hBwfXZSMzMrmV6Hc0bEMklHkWr1g4GfRsT9kk4nfZvMBKYDF0h6CHiW9OVgZmYlVNc4/oi4Eriyat8puZ9fBA4qtmhmZtYMvnPXzKzDOPGbmXUYJ34zsw7jxG9m1mGc+M3MOkyvd+427cTS08BjfXjJJqQbw5rBsR3bsR17IMbeMiJeXb2zZYm/ryTdEbVuPXZsx3Zsx3bsPnFTj5lZh3HiNzPrMO2U+H/k2I7t2I7t2I1rmzZ+MzMrRjvV+M3MrABO/GZmHaYtEr+kQZI2aHU5+kvSOq0uQytJeljSkVX7Lm9VecyKJGmYpEHZz9tI2l/SWq0uV09Km/glXSRpA0nDgAeAByV9vqDYl0l6X+WPVSRJP63aHk7VlNYFnOMDkr4l6ZuS/q3AuJJ0iKRTsu1RknYtIPTLwCRJP8sW84HV121uiKTNJL1N0jsqjyLjF0nSYEn/2epy9JekoZKOk/Sr7P/Sf0oa2upy9aZWBUzSqwoIfSMwVNJmwHXAJ4FzC4jbNKXt3JV0d0TsIOljwHjgBGBORLylgNh7k/44bwUuAc6NiP9tNG4W+yvAJhHxGUkbAVcAP46InxUU//vAG4CLs10HAw9HxH8UEPscYDnwzogYm5X/mojYpcG4d0bETpKOBz4IfBj4dUTs1GiZs/hnkt6HB4BXst0REfs3EPN3QLf/ORqJncWfFRETG4nRS/ytgO+Qlk5dDtwC/GdEzC8g9i+BxcCF2a7JwEYR0fCaHE0u9xXAgRHxcrb9OuDyiBjfYNzK5/toYN2I+JqkuyJixwbjnkXPn8Fj+hu7roVYWmSt7HLpQOB7EfGypEK+pSLiWuBaSRuSPrR/kPQE8GPgwsoHo5+xvyTpTEk/IH1hTYuIy4ood2ZPYLvK0paSzgPuKyj2btkH+C6AiFiYq6E3Qlm8r0maQ1rNrYiaVsWBwLYR8VKBMb9RYKxabpL0PeAXwNLKzoi4s6D4FwFnA5Urwo+QKgu7FRB724jYPrfdJemeAuJCc8v9G+ASSR8EtiAtGfv/CogrSbsDHwOmZPuKyK13FBCjpjIn/h8CjwL3ADdK2hJ4vqjgkjYGDgEOBe4Cfg5MIK0dPLEf8T6Q27wN+FL2b0j6QET8qtEyZx4ERrFynqMtgHsLiv2ypMFktQxJrybVuhqVX63tOknvYeUazUWYD6wFFJb4I+KGomJ1423Zv6fnTwu8s6D4iogLctsXZkuoFuEuSW+NiFsBJO0G3FRQ7KaVOyJ+nFVkfgOMBj4dETcXEPpzwEmkq9j7s6uWrkaDRsR5DZesG6Vt6qlF0pCIWFZAnF8BbwQuIDXz/DX3XL/mwpDUU1NORMS/972kNc9zA7AL6UuF7OdbgH9mJ2qkeeNjpCaTnYDzgA8BX4yISxos83XAN7MlPCv7fhQRRzQSNxfrMmB7UvvqiuTfyKVwLvbWwBnAOGBFO3ZEbNVo7GaSNA1YBMwgfaEcDKxDqk0TEc/2I+Z9Way1gG2Bx7PtLYEHImK7kpb7uPwmqbJ3H6nCR0R8q7FSrzjPsIhY2vuRfY7bRY0mn4jodyWhdIm/6o+0mkb/SFmH7hcj4vReDy4hSXv29HyjNVVJbwT2Iv0HuS4i5jUSL4s5H3gCuD4iTsv23VlgG3/Nq4ciakySZgNfBr4N7EfqG1JEfLnBuCOB/wY2jTFH1UkAABSlSURBVIh9JY0Ddo+I6Y2WOYv/SA9PR3++uLKr7p6C9mW23e7O0Yxy9/i3qnwm+ytr5pkODI+IUZK2J11NfLaRuLn4+T6IoaR+smURcXy/Y5Yw8Vf+SNuSarMzs+39gBsj4vACznFLROzeaJyqmN/t6fkiap+5c40kvTcAt0XE3wuK+3pgQUS8JGki8Bbg/IhY1GDcO4Fdge+SmqYOAbqKSvzNJGlORIyXdF9EvDnb98eIeHuDcX8P/Aw4OSK2lzQEuKtyjnYgaWylYpBv+uk0kv5EujqeWenQlTS3iCugHs55Q0T0WAnsSena+HM1wmuAnSJicbZ9KmkEThGuyTp4fhXFffPNKShOjyR9GPg6MItUKz9L0ucj4tICwl8G7CzpDcBPgN+ROtve22BcZU10n5V0GDAb2KjBmEj6ZUR8ONcEsYoiRoABL2ZXiX/J2pqfBF5TQNxNIuKXkk4CiIhlkl7p7UX1ygZGfAaoDGudBfywkYELNXwjGyAxEzgc2KaIoJK2Y/WmtfMLiPsH4KBKRSYbtTYjIt7TaOyIeEJSfleRf8v8QIhBpEEjr20kZukSf84o4F+57X+ROmSKcBwwDFgm6UVSAo2I6PdNYtXNCpLWz2IuaaikqzsZ2KVSy886YK8Fikj8y7ME9AHgOxFxVmWET4N+UPkhIs7NEnXDw0+BY7N/319ArO58DlgPOAb4CjAJ+HgBcZdmAwwqHelvBZ4rIG7FOaS2+O9n24dm+/p9xSxpNPBsRDwPEBHvk3QMqSLy0UYKmzvHl0mDK8aR7n/Zl1RRaDjxA6/OX71mo9aK+BJ/QtLbSAM51iZ9VhpuIs2ZQ/qcCFgGPMLK0UP9ExGlfJAS3D3AqaQ21ruBk1pdrjrKvR2p0+gxUufXHOBNBca/r2p7UPW+BmL/iTS8dS4wJts3t8Cyv4b0hT4KGFVg3DPr2dfP2AfVs68fcXcijYR5Lvv3z8BbCnxP7qlnXx9jzgE2zG0fk5V9LKn/pohy35d9pu/JtkcCvyso9pz8547UKX1nAXE3IY0K/Bvwd9L9DRsX9bdsxqPlBejlDd2JVKs7FtixwLjX1bOvn7FvBiblticCNxdY9q+TxsEflj1+X2CSG0dqh5+cbY8BTiwg7n7AX0jj1R8hXQYX+YWy2n9e4N4mxm44WWRxhgBvyioLaxX1flTKCLw+t71Vo+XOv6ekjunfA+tl23MKKvftlXjABqRa7v0Fxd6HVBm7IHs8BrynyPe9GQ/SldsxpKv6S4GjGv28lLKpJ2tTvTdS50hRN7SgdFv5esAmWftepVFuA2DTgk4zLCJWjOGNiFlK004UIiI+n/VP7EEq/48i4tcFxX6A9AGrbD8CTCsg9FdJd0lfGxE7SppEurJoiKTPAJ8FtpKUv5dhfRocVy5pX1LfxmZVHfcbkC63i7ArqflyCLCTJKKAtuzM50k3VlXueB1NGpHUiIezYcubkyplb4qIf0oa22BcIN0FBdwraQTpZso5wBJWDl1uSERcJWkn0mcR0h3BDa+NmzW3foqVf8vK+QoZwk0Tmu1KmfgjYrmkeySNiojHCwz9aVKb7aakD1Ul8T9PNk64APMlfYlUo4A0gqWnIWp9FulO4CLvBgZWDKWr1Una6Jj1lyPiGaXJ9gZFRJfSNAuNuohU6zwDODG3f3H0Y7x3ladId07uz6od94uBhufZkXQB8HpSE+aKaSYopi0b0hffD0lDc8l+vqXBmAeT7qQN0g1L10r6O+memIZvyIuIkLRDpHb4H0i6CtggIoq6QRHSjXP5eZyKmCzwt8AfSX1thXXq5uwSq94pfb0avFO6dMM5KyRdz8oblfK3tDc0R0oW++iIOKvROFUxL4iIQ7P7EEaT7gIWcANwWkQsLOg8HwDOJLWXiwI6pnOxN85tDgUOAl4VEad085J6415LmlZhGrAxqR10l4h4W48v7Pt5XsOqI0EarjRko2OGkNqGH2w0Xi7uPGBcNOk/oNJ8Os+T2p6h2Pl0KkNc1yU1U/0lGhzym4t9NummytuLiFcVexopp+Tfkzsi4qQG494dETs0Wr4e4t9J6ld6ONveCrg0GhgOXebEX3OMahR0K33WCz+aVS/N+l3bkvQAaQTCTNLID5GrPRdQA62c5yFgvyjgxqo6zzc7IiY0GGM9oDJ66hBSc8nPC3xP9gO+RbqS+zup025eRLypoNjfANaOiDGSdgBOb7QCIukS4JjI3TVeJEn3VNUSa+7rZ+xmJucHSMNCHyNV+CoVmyImZ7wX2CEilmfbg0n3TjQUW9JXSf14hc7Cm4v/TtJsn6s02+WblPuqlE090Ny5Upp0mf0D4CpSJ1p+cqXKF0BRt/j/rVlJP2v/rBgE7ExqL+9vvMqXxt9Y+SVYaV77qqRnga9HxPdrBqhfU/oQMqeS2uJnAUTE3dmwxn7Rylk/1wcekHQbq04z0fAVbaaZ8+lMAj4tqfDkTKo8NdMIoFLh2LCgmMcCX5D0EmkK8sKuwjMbk66sRgMHkJqrGhr6W+Ya/1uBs0hDxdYGBgNLC2rSaNpltqRzIuIzTYhbmQRuT9LNG79h1YTR8CRwSnOCVCwjTZL3jSKbOKrOtzGpprRtg3HuiIids3bPHbM+otsiouG1BCT9KSJ2U26aXUn39jfJdXclW1HgFe08Vs6nA2kI7TzSpHsNJWl1M3VDFDBlQ7NkHceHku7F6CIl53eQhojPaGXZelP5vEmaQBpN9U3gCxHR7xlLS1vjB75H6ki6hFTz/DiwdUGx55KSZ+GX2c1I+pn9cj//E3h3/rRAw4k/IiY1GqOP53tGaWqIRi1SWvDmRuDnWYdjUSNv5kr6KDBYacK2Y0hDdvulktglnRkRJ+Sfyzq8i7rS3aegOKspc4LvTtZxfCzpynAXUuI/ISL+r9HY6mbRn4i4sdHYmUqrxPuAH0TEb5VmMui3Mtf4K7W4FbUrSTcX0SGY1Wx3IHUcN+Myuy0p3X7/ZVaOeriB1J5d5B2lhcuGy1b6ED5GuoT/eUQ8U0Ds9Ug3E1a+aK8GvhINzv2vGpPUNXIlYb1rVt9E1nxXMZTUNDgnGpg9syr+5aSpQvYmTdfwAmmOrn7315Q58d9I+kV/AvwfqXZ+WEGdU03tOG4mrVyh6K2kmv4twOeyMfeNxr6MdDVUmX7iUGD7iPhA968a2CTtTEr8o1l5hdzvppLcvQevBx7KPbU+qdnrY/0vrfWkmR3HVefZAvhaRBTSz5RVPvYh3aH/F6WVw94cEdf0O2aJE/+WpBEaa5HGTW8IfD8iHurxhQOcpFtJ9xxUll78CHB0I+19udirDUtr9lC1RkhaTO2l6Yoc4vogaZWmueQWpelvc0d2VbUR6d6Daay8upodEUXMi2TdWFN9E5Ub0aLEM62Wto0/98d4AWhovuxqVQljbdKXSyEdx2tAM1dWekHShIiYDSBpD9L7X0oR0e8RR33wdET8rvfD6pM1mz2XfYFfSOqbEXCepB8XfX+JrdSsvgmtujbuIFIzclFLUTZF6Wr86maK3YpmtIFKOhDYNSK+UHTsoqkJKxTlYu9AauapDHNbCHwiir1zsq1I2os0NLR6da+GOtOzMeW7R7ZiU9ZPcYvb+NuPVl0IaBnwaEQUNXS2KcpY469MsVuZtrdSu/0Y2fKCRYuI30g6sfcjS+Hg7N9PV+3/dxq/X2Ae8DVS+/MI0ljhAyluTd929EnSlARrsbKpp4hRVGLV2/tfYeU9DtZeRkTEd/I7JB1bva9MSlfjr5B0U0Ts0du+fsbOd1ZWblTaMwpelavdKM2Nsog0Md6KpBQR32xZoVpMuZW3Co57HGl+m8oEeweSRpz8T9HnsubqZoTWivs+yqiMNf6KYVXtzW8jLZ5ShPyY+MqNSgcUFLspJL0zIq6v+tJaoYgbuIDNI6Jp47/b1K2SxkWaubQwEfEtSbNYOafTJ925214kTSYtQDNG0szcU+sDDQ8lbqYyJ/4pwE+zURCQaqKFTHMaEY1OT9sKewLXs/JLKz8FQiE3cAE3S3pzRNxXQKyBYgLwCaWZS1+iwCGAEXEnBU47bmvczaRh5puQ7qatWEzJm0dL29RTIWkDUjkLu4lI0uak6SD2ICXN2cCxEbGgqHM0i9KaAh9k9XHlpzcQs9KhPoR0d/R8Ck5y7aodpycw601pa/yS1iGX4JQtZNxIgsv5GWku98oUtYdk+95VQOxm+w0r2+FfzPY1+u3dzDVr25oTvA1Epa3xZx2Nz5EWwSi0o7HdblTKkzQ30spkZmb9UtoaP83taPyHpENYeffrZEreGZPjdnizEsnmy781Ipoy3LwZylzj/xFwVjMSnKRRpNk/dyc1k9xMWhSjyGUeC+V2eLNyknQ+ae6sZ0hLMP6RNAVHIavuNUOZE/8DwBtI69UWmuAknUea2Gxhtv0q0rzzRS2OXLjuOhkr3BZt1lqSNgU+RJrbadOIKG2LSmkLRnNX4nlL/ts4Ip6VVNqbLcCJ3ayssmbjtwNvBv5Bak34Y0sL1YvSJv5KolPVAtoFGSRpo6oaf2nfCzMrtf8BHiYtv9oVEY+2tji9K22yk7Q/6aaIVRbQBhpeQDuLe7OkS0nt5h8GphYQ18w6TERsIulNpCm2p2YrtT0YEYe2uGjdGtTqAvTgK6QOkz9HxBhgLwpaLDoizifdI/A34GngA1VTHZuZ1SW7yXQUqXI6mjS77fKeXtNqZe7cbdoC2mZmRcmm2J6dPW5shxkAStvUQ3MX0DYzK0RuTfD1afwu+jWizDX+YaTVnwaxcgHtCxtZaMTMrGiStiOtG/Iq0rDzp0kLGM1tacF6UOY2/lMiYnlELIuI8yLiu8AJrS6UmVmVHwHHRcSWETEK+K9sX2mVOfHXmjCtmWP7zcz6Y1hEdFU2ImIWxa0d0hSla+OX9Bngs8Drs06TivUpaFSPmVmB5kv6EiuXiT2ENONAaZWujT9beGUj4Awgvw7uYrfvm1nZSNoIOI2Vq6ndCJzquXr6QdLrgQUR8ZKkicBbgPMjYlFrS2Zm1t7KnPjvJi2CPhq4GpgJbBsR721luczM8iRtQ5qYbTS55vOIeGerytSb0rXx5yyPiGXZ4uL/ExFnSfJi1GZWNpeQ5un5CblFo8qszIn/5WwV+4+zcoHxtVpYHjOzWpZFxDmtLkRflHk45ydJC6VMjYhHJI0BLmxxmczMgDSrbzaz7+8kfVbS6yr7sv2lVdo2fjOzMpP0CGmKBtV4OiJiqzVcpLo58ZuZdZgyN/WYmZWepIOyCdqQ9EVJvyr7in6lTfySDqpnn5lZi30pIhZLmgC8BziPNMqntEqb+IGT6txnZtZKlSGc7wPOiYjfAmu3sDy9Kt1wTkn7Au8FNpP03dxTG+D5+M2sfJ6U9ENgb+BMSetQ7kp1+Tp3JW0P7Eia++KU3FOLSQsZl3b+CzPrPJLWA/YB7ouIv0h6HfDmiLimxUXrVukSf4WkIRHhGr6ZWcFKl/gl3UcPy5dVljkzM7P+KWPi37Kn5yPisTVVFjOzgah0id/MzJqrdKN6KiQtZmWTz9qkCdqWRsQGrSuVmVn7K23ij4j189uSDgR2bVFxzMwGjLZq6pF0a0S8tdXlMDNrZ6Wt8WcLsFQMIq3G1T7fUmZmJVXaxM/KxVcg3bH7KHBAa4piZjZwtFVTj5mZNa50NX5JZ9HzDVzHrMHimJkNOGWcSOgOYA4wFNgJ+Ev22IE2WcjYzKzMStvUI6kLeHdEvJxtrwVcExGTWlsyM7P2VsYaf8WmQH4s//Bsn5mZNaB0bfw504C7spo/wJ7Aqa0rjpnZwFDaph4ASa8Fdss2/xQR/9fK8piZDQRlT/wbAVuTOnoBiIgbW1ciM7P2V9qmHkmHA8cCmwN3A28FbgHe2cpymZm1uzJ37h4L7AI8lo3k2RF4urVFMjNrf2VO/C9GxIsAktaJiP8Ftm1xmczM2l5pm3qABZJGAL8B/iBpIfBUi8tkZtb2St25WyFpT2BD4KqI+Fery2Nm1s7aIvGbmVlxytzGb2ZmTeDEb2bWYZz4rW1IGi3pBUl3t7osa4qkn0t6VtKHWl0WGzic+K3dPBwRO6zJEyppyv+V3mJHxMeAmc04t3UuJ35rS5KGSbpC0j2S5ko6ONv/qKRNsp93ljQr+/lUSRdIul7SXyR9Khfr85Jul3SvpNOyfaMlzZP0feBOYAtJUyT9WdIsST+W9L3s2FdLuiyLcbukPXLn/Gl2/HxJx/QQ+92SbpF0p6RLJA1fY2+mdRwnfmtX+wBPRcT2EbEdcFUdr3kL8D5gd+AUSZtKejdpPqhdSYv9jJf0juz4bYHzI2JH4GXgS6SpQ94FvDEX9zvAtyNiF+CDwE9yz70ReE8W/8vZuhLVsZcCXwT2joidSIsRHVf/W2HWN2W+gcusJ/cB35B0JnB5RPyxjtf8NiJeAF7IpvveFZgAvBu4KztmOOmL4HHSdCG3Zvt3BW6IiGcBJF0CbJM9tzcwTlLlPBtIqqwlcUVEvAS8JOnvwMhsfz72W4FxwE1ZjLVJ81KZNYUTv7WliPizpPHAe4EzJF0TEacDy1h5JTu0+mU1tgWcERE/zD8haTSpJr5iVw/FGQTsnn2p5GMAvJTb9Qor/89Vx/5DREzu4RxmhXFTj7UlSZsC/4yIC4FvkNZnBngUGJ/9/MGqlx0gaaikjYGJwO3A1cC/V9rUJW0m6TU1TnkbsKekjSQNqYp9DXBUrmx97Xy+FdhD0huy168naZteXmPWb67xW7t6M/B1SctJ7e+fyfafBkyX9AXgT1WvuQ24AhgFfCUingKekjQWuCWroS8BDiHVzleIiCcl/XcW8yngAeC57OljgLMl3Uv6P3UjcGS9v0hEPC3pMOBiSetku78I/LneGGZ94SkbrG1kzS+XZ525fX3tqcCSiPhGA+cfHhFLshr/r4GfRsSv+xuvD+c9l/R7X9rsc1lncFOPtZNXgA1beAPXqdm55wKPkGaObSpJPyetN/1is89lncM1fjOzDuMav5lZh3HiNzPrME78ZmYdxonfzKzDOPGbmXUYJ34zsw7z/wHcM9p5tgJhswAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for field in feature_names:\n",
    "    boxplot = join_df[['supergenre',f'{field}']].boxplot(by='supergenre',rot=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, target, random_state=420)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.41928365303004583"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "rf = RandomForestClassifier(n_estimators=200)\n",
    "rf = rf.fit(X_train, y_train.values.ravel())\n",
    "rf.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.14504002061289067, 'speechiness'),\n",
       " (0.1390384280413352, 'loudness'),\n",
       " (0.13154133918288347, 'danceability'),\n",
       " (0.1298091435848155, 'spotify_track_duration_ms'),\n",
       " (0.12492590708030027, 'acousticness'),\n",
       " (0.12427595990230063, 'valence'),\n",
       " (0.11995845446029023, 'energy'),\n",
       " (0.08541074713518411, 'instrumentalness')]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(zip(rf.feature_importances_, feature_names), reverse=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameters currently in use:\n",
      "\n",
      "{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': None, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}\n"
     ]
    }
   ],
   "source": [
    "print('Parameters currently in use:\\n')\n",
    "print(rf.get_params())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'bootstrap': [True], 'max_depth': [10, 40, 100], 'n_estimators': [100, 200, 1000, 2000]}\n"
     ]
    }
   ],
   "source": [
    "# Create the parameter grid based on the results of random search \n",
    "feature_grid = {\n",
    "    'bootstrap': [True],\n",
    "    'max_depth': [10, 40, 100],\n",
    "#     'max_features': [2, 3],\n",
    "#     'min_samples_leaf': [3, 4, 5],\n",
    "#     'min_samples_split': [8, 10, 12],\n",
    "    'n_estimators': [100, 200, 1000, 2000]\n",
    "}\n",
    "print(feature_grid)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "grid = GridSearchCV(rf, feature_grid, verbose=3, n_jobs=-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 12 candidates, totalling 60 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 4 concurrent workers.\n"
     ]
    }
   ],
   "source": [
    "grid.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'bootstrap': True, 'max_depth': 80, 'n_estimators': 1000}\n",
      "0.41753696227178044\n",
      "                 precision    recall  f1-score   support\n",
      "\n",
      "adult standards       0.50      0.02      0.04        50\n",
      "        country       0.58      0.29      0.39       262\n",
      "           folk       0.00      0.00      0.00        32\n",
      "         hiphop       0.51      0.29      0.37       146\n",
      "          house       0.00      0.00      0.00        51\n",
      "           jazz       0.36      0.05      0.09        78\n",
      "          latin       1.00      0.07      0.13        14\n",
      "          metal       0.67      0.04      0.07        52\n",
      "          other       0.34      0.24      0.28       481\n",
      "            pop       0.43      0.53      0.48       827\n",
      "            r&b       1.00      0.06      0.11        51\n",
      "            rap       0.61      0.42      0.50       164\n",
      "           rock       0.43      0.76      0.55       972\n",
      "     show tunes       0.00      0.00      0.00         5\n",
      "           soul       0.35      0.09      0.14       328\n",
      "\n",
      "       accuracy                           0.43      3513\n",
      "      macro avg       0.45      0.19      0.21      3513\n",
      "   weighted avg       0.44      0.43      0.39      3513\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\msflo\\anaconda3\\envs\\PythonData\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1272: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n"
     ]
    }
   ],
   "source": [
    "print(grid.best_params_)\n",
    "print(grid.best_score_)\n",
    "predictions = grid.predict(X_test)\n",
    "\n",
    "from sklearn.metrics import classification_report\n",
    "print(classification_report(y_test, predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import joblib\n",
    "# joblib.dump(rf, 'model_RandomForest.sav')"
   ]
  }
 ],
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