spotify_classifier_raw_data_withEDA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000\n"
     ]
    },
    {
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       "      <td>2.3</td>\n",
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       "   Unnamed: 0                              session_id  \\\n",
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       "\n",
       "                                 track_id  skip_1  skip_2  skip_3  \\\n",
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       "\n",
       "   not_skipped  context_switch  hist_user_behavior_reason_start  \\\n",
       "0            1               0                              1.0   \n",
       "1            0               0                              0.3   \n",
       "2            1               0                              1.0   \n",
       "3            1               0                              0.3   \n",
       "4            0               0                              1.0   \n",
       "\n",
       "   hist_user_behavior_reason_end  hist_user_behavior_is_shuffle  skip_score  \\\n",
       "0                            1.0                              1         1.0   \n",
       "1                            0.4                              0         0.2   \n",
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       "3                            1.0                              0         1.0   \n",
       "4                            0.3                              1         0.2   \n",
       "\n",
       "   liking  rating  \n",
       "0     3.0     4.0  \n",
       "1     0.7     0.9  \n",
       "2     2.0     3.0  \n",
       "3     1.3     2.3  \n",
       "4     2.3     2.5  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import scipy as sp\n",
    "\n",
    "df = pd.read_csv(r'F:\\AppliedDataScience\\data\\ratingdf_likescore.csv')\n",
    "print(len(df))\n",
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    10000.000000\n",
       "mean         1.326170\n",
       "std          1.472203\n",
       "min         -1.100000\n",
       "25%          0.300000\n",
       "50%          1.200000\n",
       "75%          2.900000\n",
       "max          4.000000\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['rating'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df['rating_round'] = df['rating'].round()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "   Unnamed: 0                              session_id  \\\n",
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       "4           4  0_01a5f0dc-9938-48c9-92f1-c7e51f34d290   \n",
       "\n",
       "                                 track_id  skip_1  skip_2  skip_3  \\\n",
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       "\n",
       "   not_skipped  context_switch  hist_user_behavior_reason_start  \\\n",
       "0            1               0                              1.0   \n",
       "1            0               0                              0.3   \n",
       "2            1               0                              1.0   \n",
       "3            1               0                              0.3   \n",
       "4            0               0                              1.0   \n",
       "\n",
       "   hist_user_behavior_reason_end  hist_user_behavior_is_shuffle  skip_score  \\\n",
       "0                            1.0                              1         1.0   \n",
       "1                            0.4                              0         0.2   \n",
       "2                            1.0                              0         1.0   \n",
       "3                            1.0                              0         1.0   \n",
       "4                            0.3                              1         0.2   \n",
       "\n",
       "   liking  rating  rating_round  \n",
       "0     3.0     4.0           4.0  \n",
       "1     0.7     0.9           1.0  \n",
       "2     2.0     3.0           3.0  \n",
       "3     1.3     2.3           2.0  \n",
       "4     2.3     2.5           2.0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'session_id', 'track_id', 'skip_1', 'skip_2', 'skip_3',\n",
       "       'not_skipped', 'context_switch', 'hist_user_behavior_reason_start',\n",
       "       'hist_user_behavior_reason_end', 'hist_user_behavior_is_shuffle',\n",
       "       'skip_score', 'liking', 'rating', 'rating_round'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " # Import Decision Tree Classifier\n",
    "from sklearn.model_selection import train_test_split # Import train_test_split function\n",
    "from sklearn import metrics #Import scikit-learn metrics module for accuracy calculation\n",
    "df = df.dropna()\n",
    "len(df)\n",
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.   0.   0.   1.   1.   1. ]\n",
      " [ 0.   0.   0.2  0.3  0.4  0. ]\n",
      " [ 0.   0.   0.   1.   1.   0. ]\n",
      " ...\n",
      " [ 0.  -0.5  0.2  0.2  0.3  0. ]\n",
      " [ 0.  -0.5  0.2  1.   0.3  0. ]\n",
      " [-1.  -0.5  0.2  0.2  0.4  0. ]]\n"
     ]
    }
   ],
   "source": [
    "X = df[['skip_1','skip_2','skip_3','hist_user_behavior_reason_start','hist_user_behavior_reason_end','hist_user_behavior_is_shuffle']]\n",
    "X = X.values\n",
    "print(X)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 4.]\n",
      " [ 1.]\n",
      " [ 3.]\n",
      " ...\n",
      " [ 0.]\n",
      " [ 1.]\n",
      " [-1.]]\n"
     ]
    }
   ],
   "source": [
    "y = df[['rating_round']]\n",
    "y = y.values\n",
    "print(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.15, random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2. 2. 0. ... 0. 1. 2.]\n",
      "Accuracy: 0.9726666666666667\n"
     ]
    },
    {
     "data": {
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+qeGxMsLmFTeGHUJK5WQ1DDuEtBepQoTOmhMRyTiRuo5IZ82JiGSeSBWiUsFt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\nEREJlQqRiIiESoVIRERCpUIkIiKh+n+Ng3UH2LTy1gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9726666666666667\n",
      "Precision: [1.         0.99666667 0.94871795 0.94925373 0.96732026 0.96341463]\n",
      "Recall: [1.         0.99006623 0.93908629 0.95209581 0.9704918  0.9875    ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ted\\Anaconda3\\lib\\site-packages\\sklearn\\ensemble\\weight_boosting.py:29: DeprecationWarning: numpy.core.umath_tests is an internal NumPy module and should not be imported. It will be removed in a future NumPy release.\n",
      "  from numpy.core.umath_tests import inner1d\n",
      "C:\\Users\\Ted\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:40: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2. 2. 0. ... 0. 1. 2.]\n",
      "Accuracy: 0.9753333333333334\n"
     ]
    },
    {
     "data": {
      "image/png": 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f+hqmbMsNO4S0F6lChK6aExHJOJG6j0hXzYmIZJ5IFaIKwWMgrgK6ocdAiIik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\n1xkTk/3fAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9753333333333334\n",
      "Precision: [1.         1.         0.94897959 0.94674556 0.97689769 0.97560976]\n",
      "Recall: [1.         0.99006623 0.94416244 0.95808383 0.9704918  1.        ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ted\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py:578: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  y = column_or_1d(y, warn=True)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2. 2. 0. ... 0. 1. 2.]\n"
     ]
    },
    {
     "data": {
      "image/png": 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RCZW65kREJFzqmhMRkVClX4NIhUhEJFLUIhIRkVCpEImISKjUNSciImFytYhERCRU6VeH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\nREL1/wHKZ4qEnf+kSgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.986\n",
      "Precision: [1.         1.         0.97487437 0.9876161  0.96794872 0.97560976]\n",
      "Recall: [1.         1.         0.98477157 0.95508982 0.99016393 1.        ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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Xk/wqo//wtw7bflFVP924qW+6Va/dojFvAL5dVd9f7wk3sta12wI8P8kWRn/xPu17kM9h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\nWdGUxGTqOnsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Decision Tree Classifier \n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "clf = DecisionTreeClassifier(max_depth=None, max_leaf_nodes=20)\n",
    "clf.fit(X_train, y_train)\n",
    "y_pred = clf.predict(X_test)\n",
    "print(y_pred)\n",
    "print(\"Accuracy:\",metrics.accuracy_score(y_test, y_pred))\n",
    "from sklearn.metrics import confusion_matrix\n",
    "cnf_matrix = metrics.confusion_matrix(y_test, y_pred)\n",
    "cnf_matrix\n",
    "class_names=[0,1] # name  of classes\n",
    "fig, ax = plt.subplots()\n",
    "tick_marks = np.arange(len(class_names))\n",
    "plt.xticks(tick_marks, class_names)\n",
    "plt.yticks(tick_marks, class_names)\n",
    "# create heatmap\n",
    "sns.heatmap(pd.DataFrame(cnf_matrix), annot=True, cmap=\"YlGnBu\" ,fmt='g')\n",
    "ax.xaxis.set_label_position(\"top\")\n",
    "plt.tight_layout()\n",
    "plt.title('Confusion matrix', y=1.1)\n",
    "plt.ylabel('Actual label')\n",
    "plt.xlabel('Predicted label')\n",
    "plt.show()\n",
    "dtree_accuracy = metrics.accuracy_score(y_test, y_pred)\n",
    "dtree_precision_score = metrics.precision_score(y_test, y_pred, average=None)\n",
    "dtree_recall_score = metrics.recall_score(y_test, y_pred, average=None)\n",
    "print(\"Accuracy:\",dtree_accuracy)\n",
    "print(\"Precision:\",dtree_precision_score)\n",
    "print(\"Recall:\",dtree_recall_score)\n",
    "plt.figure(figsize=(7,5))\n",
    "plt.hist(dtree_precision_score)\n",
    "plt.hist(dtree_recall_score)\n",
    "plt.show()\n",
    "\n",
    "\n",
    "### RandomForestClassifier ####\n",
    "\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "clf2 = RandomForestClassifier(max_depth=None, max_leaf_nodes=20)\n",
    "clf2.fit(X_train, y_train)\n",
    "y_pred = clf2.predict(X_test)\n",
    "print(y_pred)\n",
    "print(\"Accuracy:\",metrics.accuracy_score(y_test, y_pred))\n",
    "from sklearn.metrics import confusion_matrix\n",
    "cnf_matrix = metrics.confusion_matrix(y_test, y_pred)\n",
    "cnf_matrix\n",
    "class_names=[0,1] # name  of classes\n",
    "fig, ax = plt.subplots()\n",
    "tick_marks = np.arange(len(class_names))\n",
    "plt.xticks(tick_marks, class_names)\n",
    "plt.yticks(tick_marks, class_names)\n",
    "# create heatmap\n",
    "sns.heatmap(pd.DataFrame(cnf_matrix), annot=True, cmap=\"YlGnBu\" ,fmt='g')\n",
    "ax.xaxis.set_label_position(\"top\")\n",
    "plt.tight_layout()\n",
    "plt.title('Confusion matrix', y=1.1)\n",
    "plt.ylabel('Actual label')\n",
    "plt.xlabel('Predicted label')\n",
    "plt.show()\n",
    "\n",
    "rftree_accuracy = metrics.accuracy_score(y_test, y_pred)\n",
    "rftree_precision_score = metrics.precision_score(y_test, y_pred, average=None)\n",
    "rftree_recall_score = metrics.recall_score(y_test, y_pred, average=None)\n",
    "print(\"Accuracy:\",rftree_accuracy)\n",
    "print(\"Precision:\",rftree_precision_score)\n",
    "print(\"Recall:\",rftree_recall_score)\n",
    "plt.figure(figsize=(7,5))\n",
    "plt.hist(rftree_precision_score)\n",
    "plt.hist(rftree_recall_score)\n",
    "plt.show()\n",
    "\n",
    "\n",
    "#### SVM Classifier\n",
    "\n",
    "from sklearn import svm\n",
    "model = svm.SVC(kernel='rbf', C=1E6)\n",
    "model.fit(X_train, y_train)\n",
    "y_pred = model.predict(X_test)\n",
    "print(y_pred)\n",
    "from sklearn import metrics\n",
    "cnf_matrix = metrics.confusion_matrix(y_test, y_pred)\n",
    "cnf_matrix\n",
    "class_names=[0,1] # name  of classes\n",
    "fig, ax = plt.subplots()\n",
    "tick_marks = np.arange(len(class_names))\n",
    "plt.xticks(tick_marks, class_names)\n",
    "plt.yticks(tick_marks, class_names)\n",
    "# create heatmap\n",
    "sns.heatmap(pd.DataFrame(cnf_matrix), annot=True, cmap=\"YlGnBu\" ,fmt='g')\n",
    "ax.xaxis.set_label_position(\"top\")\n",
    "plt.tight_layout()\n",
    "plt.title('Confusion matrix', y=1.1)\n",
    "plt.ylabel('Actual label')\n",
    "plt.xlabel('Predicted label')\n",
    "plt.show()\n",
    "\n",
    "svm_accuracy = metrics.accuracy_score(y_test, y_pred)\n",
    "svm_precision_score = metrics.precision_score(y_test, y_pred, average=None)\n",
    "svm_recall_score = metrics.recall_score(y_test, y_pred, average=None)\n",
    "print(\"Accuracy:\",svm_accuracy)\n",
    "print(\"Precision:\",svm_precision_score)\n",
    "print(\"Recall:\",svm_recall_score)\n",
    "plt.figure(figsize=(7,5))\n",
    "plt.hist(svm_precision_score)\n",
    "plt.hist(svm_recall_score)\n",
    "plt.show()\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "#### "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xhCJJjXIZoSQ1anrCtwFc0sBYQpGkRs1OUQ5uAJc0KGbgktSoMgOXpDaZgUtSo1xGKEmN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\nUQZwSWqUAVySGmUAl6RGGcAlqVH/D0ugf9SxxhWBAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.972667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.975333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.986000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0\n",
       "0  0.972667\n",
       "1  0.975333\n",
       "2  0.986000"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_accuracy = [dtree_accuracy,rftree_accuracy,svm_accuracy]\n",
    "model_accuracy = pd.DataFrame(model_accuracy)\n",
    "sns.heatmap(model_accuracy)\n",
    "plt.show()\n",
    "\n",
    "model_accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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w0gvH2vtTS+qtef7p9KgK+bNJ3vTyTpec3wl8BfBNpzMwSToV89yyGFUhX8/q+6FeUVVL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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.996667</td>\n",
       "      <td>0.948718</td>\n",
       "      <td>0.949254</td>\n",
       "      <td>0.967320</td>\n",
       "      <td>0.963415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.948980</td>\n",
       "      <td>0.946746</td>\n",
       "      <td>0.976898</td>\n",
       "      <td>0.975610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.974874</td>\n",
       "      <td>0.987616</td>\n",
       "      <td>0.967949</td>\n",
       "      <td>0.975610</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     0         1         2         3         4         5\n",
       "0  1.0  0.996667  0.948718  0.949254  0.967320  0.963415\n",
       "1  1.0  1.000000  0.948980  0.946746  0.976898  0.975610\n",
       "2  1.0  1.000000  0.974874  0.987616  0.967949  0.975610"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_precision = [dtree_precision_score,rftree_precision_score,svm_precision_score]\n",
    "model_precision = pd.DataFrame(model_precision)\n",
    "sns.heatmap(model_precision)\n",
    "plt.show()\n",
    "\n",
    "model_precision"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "      <th>2</th>\n",
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       "      <th>4</th>\n",
       "      <th>5</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.990066</td>\n",
       "      <td>0.939086</td>\n",
       "      <td>0.952096</td>\n",
       "      <td>0.970492</td>\n",
       "      <td>0.9875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.990066</td>\n",
       "      <td>0.944162</td>\n",
       "      <td>0.958084</td>\n",
       "      <td>0.970492</td>\n",
       "      <td>1.0000</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     0         1         2         3         4       5\n",
       "0  1.0  0.990066  0.939086  0.952096  0.970492  0.9875\n",
       "1  1.0  0.990066  0.944162  0.958084  0.970492  1.0000\n",
       "2  1.0  1.000000  0.984772  0.955090  0.990164  1.0000"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_recall = [dtree_recall_score,rftree_recall_score,svm_recall_score]\n",
    "model_recall = pd.DataFrame(model_recall)\n",
    "sns.heatmap(model_recall)\n",
    "plt.show()\n",
    "\n",
    "model_recall"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ted\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py:578: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  y = column_or_1d(y, warn=True)\n"
     ]
    }
   ],
   "source": [
    "from sklearn import svm\n",
    "model = svm.SVC(kernel='rbf', C=1E6)\n",
    "model.fit(X_train, y_train)\n",
    "y_pred = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_pred = pd.DataFrame(y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 4.,  1.,  3.,  2., -1., -0.])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['rating_round'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ted\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py:578: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  y = column_or_1d(y, warn=True)\n"
     ]
    }
   ],
   "source": [
    "#### Creating a Full y_pred list with based in SVM Classifier ####\n",
    "from sklearn import svm\n",
    "model = svm.SVC(kernel='rbf', C=1E6)\n",
    "model.fit(X,y)\n",
    "svm_pred = model.predict(X)\n",
    "svm_pred = pd.DataFrame(svm_pred)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df['svm_pred'] = svm_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>session_id</th>\n",
       "      <th>track_id</th>\n",
       "      <th>skip_1</th>\n",
       "      <th>skip_2</th>\n",
       "      <th>skip_3</th>\n",
       "      <th>not_skipped</th>\n",
       "      <th>context_switch</th>\n",
       "      <th>hist_user_behavior_reason_start</th>\n",
       "      <th>hist_user_behavior_reason_end</th>\n",
       "      <th>hist_user_behavior_is_shuffle</th>\n",
       "      <th>skip_score</th>\n",
       "      <th>liking</th>\n",
       "      <th>rating</th>\n",
       "      <th>rating_round</th>\n",
       "      <th>svm_pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0_013cc010-c476-4ad2-8972-73449e0b2ef4</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>2.3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0_01a5f0dc-9938-48c9-92f1-c7e51f34d290</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0                              session_id  \\\n",
       "0           0  0_00006f66-33e5-4de7-a324-2d18e439fc1e   \n",
       "1           1  0_00079a23-1600-486a-91bd-5208be0c745a   \n",
       "2           2  0_012b0fb4-0cc3-429f-9a78-cc6e622153fb   \n",
       "3           3  0_013cc010-c476-4ad2-8972-73449e0b2ef4   \n",
       "4           4  0_01a5f0dc-9938-48c9-92f1-c7e51f34d290   \n",
       "\n",
       "                                 track_id  skip_1  skip_2  skip_3  \\\n",
       "0  t_0479f24c-27d2-46d6-a00c-7ec928f2b539       0     0.0     0.0   \n",
       "1  t_0479f24c-27d2-46d6-a00c-7ec928f2b539       0     0.0     0.2   \n",
       "2  t_0479f24c-27d2-46d6-a00c-7ec928f2b539       0     0.0     0.0   \n",
       "3  t_0479f24c-27d2-46d6-a00c-7ec928f2b539       0     0.0     0.0   \n",
       "4  t_0479f24c-27d2-46d6-a00c-7ec928f2b539       0     0.0     0.2   \n",
       "\n",
       "   not_skipped  context_switch  hist_user_behavior_reason_start  \\\n",
       "0            1               0                              1.0   \n",
       "1            0               0                              0.3   \n",
       "2            1               0                              1.0   \n",
       "3            1               0                              0.3   \n",
       "4            0               0                              1.0   \n",
       "\n",
       "   hist_user_behavior_reason_end  hist_user_behavior_is_shuffle  skip_score  \\\n",
       "0                            1.0                              1         1.0   \n",
       "1                            0.4                              0         0.2   \n",
       "2                            1.0                              0         1.0   \n",
       "3                            1.0                              0         1.0   \n",
       "4                            0.3                              1         0.2   \n",
       "\n",
       "   liking  rating  rating_round  svm_pred  \n",
       "0     3.0     4.0           4.0       4.0  \n",
       "1     0.7     0.9           1.0       1.0  \n",
       "2     2.0     3.0           3.0       3.0  \n",
       "3     1.3     2.3           2.0       2.0  \n",
       "4     2.3     2.5           2.0       2.0  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 4.,  1.,  3.,  2., -1.,  0.])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['svm_pred'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "### clustering of user ID based on the predicted ratings\n",
    "\n",
    "rating_1_uid = df.query('svm_pred==-1')['session_id']\n",
    "rating_1_uid = pd.DataFrame(rating_1_uid)\n",
    "\n",
    "rating_2_uid = df.query('svm_pred==0')['session_id']\n",
    "rating_2_uid = pd.DataFrame(rating_2_uid)\n",
    "\n",
    "rating_3_uid = df.query('svm_pred==1')['session_id']\n",
    "rating_3_uid = pd.DataFrame(rating_3_uid)\n",
    "\n",
    "rating_4_uid = df.query('svm_pred==2')['session_id']\n",
    "rating_4_uid = pd.DataFrame(rating_4_uid)\n",
    "\n",
    "rating_5_uid = df.query('svm_pred==3')['session_id']\n",
    "rating_5_uid = pd.DataFrame(rating_5_uid)\n",
    "\n",
    "rating_6_uid = df.query('svm_pred==4')['session_id']\n",
    "rating_6_uid = pd.DataFrame(rating_6_uid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>session_id</th>\n",
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       "      <th>5</th>\n",
       "      <td>0_01f86af2-cf48-42a6-9bf8-adb91f072909</td>\n",
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       "      <th>6</th>\n",
       "      <td>0_02340c3b-c370-4c98-b759-87be85e11aa3</td>\n",
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       "      <th>8</th>\n",
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       "      <th>10</th>\n",
       "      <td>0_04452794-0084-4712-9808-1845d338c8b9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "                                session_id\n",
       "5   0_01f86af2-cf48-42a6-9bf8-adb91f072909\n",
       "6   0_02340c3b-c370-4c98-b759-87be85e11aa3\n",
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       "10  0_04452794-0084-4712-9808-1845d338c8b9\n",
       "24  0_08766f3c-2c0f-447e-b864-358427c870de"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rating_1_uid.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0_08748019-88a3-4fb6-91c7-4a4acc30619d</td>\n",
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       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>0_00a8082d-1db1-4497-b76d-94b621b2dba4</td>\n",
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       "    <tr>\n",
       "      <th>57</th>\n",
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      "text/plain": [
       "                                session_id\n",
       "18  0_0792cde4-90a0-45e9-bf9e-b4f78114f1bf\n",
       "20  0_07ba5d63-0d11-472e-804e-ebdd584e21a1\n",
       "23  0_08748019-88a3-4fb6-91c7-4a4acc30619d\n",
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       "57  0_00c85d24-5f1b-4468-b67f-fa3d9e405e68"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rating_2_uid.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dat = pd.read_csv(r'F:\\AppliedDataScience\\data\\dat.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'session_id', 'session_position', 'session_length',\n",
       "       'track_id', 'skip_1', 'skip_2', 'skip_3', 'not_skipped',\n",
       "       'context_switch', 'no_pause_before_play', 'short_pause_before_play',\n",
       "       'long_pause_before_play', 'hist_user_behavior_n_seekfwd',\n",
       "       'hist_user_behavior_n_seekback', 'hist_user_behavior_is_shuffle',\n",
       "       'hour_of_day', 'date', 'premium', 'context_type',\n",
       "       'hist_user_behavior_reason_start', 'hist_user_behavior_reason_end',\n",
       "       'label', 'duration', 'release_year', 'us_popularity_estimate',\n",
       "       'acousticness', 'beat_strength', 'bounciness', 'danceability',\n",
       "       'dyn_range_mean', 'energy', 'flatness', 'instrumentalness', 'key',\n",
       "       'liveness', 'loudness', 'mechanism', 'mode', 'organism', 'speechiness',\n",
       "       'tempo', 'time_signature', 'valence', 'acoustic_vector_0',\n",
       "       'acoustic_vector_1', 'acoustic_vector_2', 'acoustic_vector_3',\n",
       "       'acoustic_vector_4', 'acoustic_vector_5', 'acoustic_vector_6',\n",
       "       'acoustic_vector_7'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>acoustic_vector_3</th>\n",
       "      <th>acoustic_vector_4</th>\n",
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       "      <th>acoustic_vector_6</th>\n",
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       "      <td>0.386409</td>\n",
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       "      <td>1</td>\n",
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       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
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       "      <td>4</td>\n",
       "      <td>0.152255</td>\n",
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       "      <td>0.23016</td>\n",
       "      <td>0.028028</td>\n",
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       "      <td>2</td>\n",
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       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.152255</td>\n",
       "      <td>-0.815775</td>\n",
       "      <td>0.386409</td>\n",
       "      <td>0.23016</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
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       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0_013cc010-c476-4ad2-8972-73449e0b2ef4</td>\n",
       "      <td>9</td>\n",
       "      <td>13</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
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       "      <td>4</td>\n",
       "      <td>0.152255</td>\n",
       "      <td>-0.815775</td>\n",
       "      <td>0.386409</td>\n",
       "      <td>0.23016</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0_01a5f0dc-9938-48c9-92f1-c7e51f34d290</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
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       "      <td>4</td>\n",
       "      <td>0.152255</td>\n",
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       "      <td>0.23016</td>\n",
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       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0                              session_id  session_position  \\\n",
       "0           0  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 1   \n",
       "1           1  0_00079a23-1600-486a-91bd-5208be0c745a                 7   \n",
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       "3           3  0_013cc010-c476-4ad2-8972-73449e0b2ef4                 9   \n",
       "4           4  0_01a5f0dc-9938-48c9-92f1-c7e51f34d290                 7   \n",
       "\n",
       "   session_length                                track_id  skip_1  skip_2  \\\n",
       "0              20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "1              12  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "2              20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "3              13  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "4              12  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "\n",
       "   skip_3  not_skipped  context_switch        ...         time_signature  \\\n",
       "0   False         True               0        ...                      4   \n",
       "1    True        False               0        ...                      4   \n",
       "2   False         True               0        ...                      4   \n",
       "3   False         True               0        ...                      4   \n",
       "4    True        False               0        ...                      4   \n",
       "\n",
       "    valence  acoustic_vector_0  acoustic_vector_1  acoustic_vector_2  \\\n",
       "0  0.152255          -0.815775           0.386409            0.23016   \n",
       "1  0.152255          -0.815775           0.386409            0.23016   \n",
       "2  0.152255          -0.815775           0.386409            0.23016   \n",
       "3  0.152255          -0.815775           0.386409            0.23016   \n",
       "4  0.152255          -0.815775           0.386409            0.23016   \n",
       "\n",
       "   acoustic_vector_3  acoustic_vector_4 acoustic_vector_5  acoustic_vector_6  \\\n",
       "0           0.028028          -0.333373          0.015452           -0.35359   \n",
       "1           0.028028          -0.333373          0.015452           -0.35359   \n",
       "2           0.028028          -0.333373          0.015452           -0.35359   \n",
       "3           0.028028          -0.333373          0.015452           -0.35359   \n",
       "4           0.028028          -0.333373          0.015452           -0.35359   \n",
       "\n",
       "  acoustic_vector_7  \n",
       "0          0.205826  \n",
       "1          0.205826  \n",
       "2          0.205826  \n",
       "3          0.205826  \n",
       "4          0.205826  \n",
       "\n",
       "[5 rows x 52 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True, False])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat['hist_user_behavior_is_shuffle'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dat['svm_rating'] = svm_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>session_id</th>\n",
       "      <th>session_position</th>\n",
       "      <th>session_length</th>\n",
       "      <th>track_id</th>\n",
       "      <th>skip_1</th>\n",
       "      <th>skip_2</th>\n",
       "      <th>skip_3</th>\n",
       "      <th>not_skipped</th>\n",
       "      <th>context_switch</th>\n",
       "      <th>...</th>\n",
       "      <th>valence</th>\n",
       "      <th>acoustic_vector_0</th>\n",
       "      <th>acoustic_vector_1</th>\n",
       "      <th>acoustic_vector_2</th>\n",
       "      <th>acoustic_vector_3</th>\n",
       "      <th>acoustic_vector_4</th>\n",
       "      <th>acoustic_vector_5</th>\n",
       "      <th>acoustic_vector_6</th>\n",
       "      <th>acoustic_vector_7</th>\n",
       "      <th>svm_rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0_00006f66-33e5-4de7-a324-2d18e439fc1e</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152255</td>\n",
       "      <td>-0.815775</td>\n",
       "      <td>0.386409</td>\n",
       "      <td>0.23016</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0_00079a23-1600-486a-91bd-5208be0c745a</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152255</td>\n",
       "      <td>-0.815775</td>\n",
       "      <td>0.386409</td>\n",
       "      <td>0.23016</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>0_012b0fb4-0cc3-429f-9a78-cc6e622153fb</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152255</td>\n",
       "      <td>-0.815775</td>\n",
       "      <td>0.386409</td>\n",
       "      <td>0.23016</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0_013cc010-c476-4ad2-8972-73449e0b2ef4</td>\n",
       "      <td>9</td>\n",
       "      <td>13</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152255</td>\n",
       "      <td>-0.815775</td>\n",
       "      <td>0.386409</td>\n",
       "      <td>0.23016</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0_01a5f0dc-9938-48c9-92f1-c7e51f34d290</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152255</td>\n",
       "      <td>-0.815775</td>\n",
       "      <td>0.386409</td>\n",
       "      <td>0.23016</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0                              session_id  session_position  \\\n",
       "0           0  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 1   \n",
       "1           1  0_00079a23-1600-486a-91bd-5208be0c745a                 7   \n",
       "2           2  0_012b0fb4-0cc3-429f-9a78-cc6e622153fb                 6   \n",
       "3           3  0_013cc010-c476-4ad2-8972-73449e0b2ef4                 9   \n",
       "4           4  0_01a5f0dc-9938-48c9-92f1-c7e51f34d290                 7   \n",
       "\n",
       "   session_length                                track_id  skip_1  skip_2  \\\n",
       "0              20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "1              12  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "2              20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "3              13  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "4              12  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "\n",
       "   skip_3  not_skipped  context_switch    ...       valence  \\\n",
       "0   False         True               0    ...      0.152255   \n",
       "1    True        False               0    ...      0.152255   \n",
       "2   False         True               0    ...      0.152255   \n",
       "3   False         True               0    ...      0.152255   \n",
       "4    True        False               0    ...      0.152255   \n",
       "\n",
       "   acoustic_vector_0  acoustic_vector_1  acoustic_vector_2  acoustic_vector_3  \\\n",
       "0          -0.815775           0.386409            0.23016           0.028028   \n",
       "1          -0.815775           0.386409            0.23016           0.028028   \n",
       "2          -0.815775           0.386409            0.23016           0.028028   \n",
       "3          -0.815775           0.386409            0.23016           0.028028   \n",
       "4          -0.815775           0.386409            0.23016           0.028028   \n",
       "\n",
       "   acoustic_vector_4  acoustic_vector_5 acoustic_vector_6  acoustic_vector_7  \\\n",
       "0          -0.333373           0.015452          -0.35359           0.205826   \n",
       "1          -0.333373           0.015452          -0.35359           0.205826   \n",
       "2          -0.333373           0.015452          -0.35359           0.205826   \n",
       "3          -0.333373           0.015452          -0.35359           0.205826   \n",
       "4          -0.333373           0.015452          -0.35359           0.205826   \n",
       "\n",
       "  svm_rating  \n",
       "0        4.0  \n",
       "1        1.0  \n",
       "2        3.0  \n",
       "3        2.0  \n",
       "4        2.0  \n",
       "\n",
       "[5 rows x 53 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dat_arr = dat.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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UO5KtjSYvXKxizyZ4nxXk3RpWQ9XX9LqCsBLiRVMW49pc7pGr2XEcx3GcH0LW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3r7hnjLkR+PYRkjxHaY0txD19n7VRaGOwbjuxk58ZbW66pGMJCm2IUnXLb6SxJs80jnvzwrSE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\naTrZ0TRN0zRtS/v/AaC2SIelF75VAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "z = np.random.rand(15)\n",
    "z=z*z\n",
    "plt.figure(figsize=(10,8)) \n",
    "\n",
    "# Change color with c and alpha. I map the color to the X axis value.\n",
    "plt.scatter(dat['release_year'], dat['Unnamed: 0'], s=dat['hour_of_day']*50, c = dat['svm_rating'] , alpha=0.4, linewidth=2)\n",
    "\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9JPuAnUk2A4eB2wGq6mCSncDzwHHgrqo60Y51J/AwsAx4sj0AHgIeTTJGb2awcT4GJ0nq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\nf08AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dat['hour_of_day'].describe()\n",
    "plt.hist(dat['acousticness'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    167880.000000\n",
       "mean         17.651823\n",
       "std           3.422025\n",
       "min          10.000000\n",
       "25%          15.000000\n",
       "50%          20.000000\n",
       "75%          20.000000\n",
       "max          20.000000\n",
       "Name: session_length, dtype: float64"
      ]
     },
     "execution_count": 216,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "dat['session_length'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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hsjrg+DT4rA0RkcQyLJib9p30CCCaZcHc0L5PbEYas0cO7un9c5KSiLkNrP4e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\npcG7qxjzby+/i7newOKN/0k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RIRBKBEUDQ3R+HktHQzgdCGcIvfXQaDwZ5+DC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Be5bS/tumf24ala7WVP9+PAxTMQnRDiWCDFDmCYJgtLPnJuN2tauuhJxdkx2EjilFbUqa3YftAu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Hdw\nXldnTemDoi7YMXSJabcPI8UBRZ420wgJiS+V4P64koYTkmmcmkAowcLanATyGmtILNHw6pKqeoHJ\npIME3RAkBoLYqwXOwxJ46MxbibW1v05SRx0xdTTjfy9Ye30uyU+VIMrqD5peuh1UXTGI+K+9/OTv\nc7osH0rXMlvMzL1xDnNv3FdGUkomnXsX5MaBrYNfUYuJwKA4HnthMTdddugFTrvLkZPy+b/7L+Zv\n97/LrsLqdtPFxjr42dUzmTO7c311lOgViD3oGj4HtSdAWr12hQp2DmYAdVCOumDHZNJwzNGo/8qO\n4Q1irm69avgelsogiS+VkPhSSbjM3SZCoxKoHd/EmClHYNlUgPSGvzXCJZk0eSLXTjybZHv3DAP+\n+7O/ZN6Muyi+PANRnU78kkrErlpE86y6UghIj6VhWjL+oWbiXqvhsadvxmpXQyz7k1qvD91p7fxP\nVgSvvbusV4MdgNGjs/jvv69mzdpdvPnWKjZsKKLR48dut5Cbk8zppx3OtGNHYLVG3W1I6QpdUHFZ\nUVHx4w8y0KlmrP5J0zRsY8xYPvKjD3IT0howV7Yf8OxhxJkx5cZhSvaTcLrGvcddjeuUnu0EmpyZ\nyJOL7+aWk++lyAL1J6YQTE+FgAAdsIO5wcCx3EfqJ5Xc98ZtjDyq61cuV7pXQVkV0iwimtOpleYA\nyePpG+s+CSGYcHguEw7P7e2sKANMqK7z++7p5xNr69g6bEr/FXXBDkDjRyk4zqug6aMA0uTCnywx\nlzZgqm1dLWq4TAQyXdhjzDA6hGME1H7qxHVa74x2SctN4T9r/ofPXvmK1x96jy1bSpFWCwiBCIZI\nS4jhnBvncOIVx+Hu5JpBSu/asGMbml/vXPVxc82OjMpvthJNQiuATq70IARUl9s54ojJXZqnAUnV\n7PRf91zzEx4o/ysENZreDsBoO+bNcYSkiYAnEC5cTWC2WrDbJP4cIBDEmmcQe3SIM0pO79X8W+1W\nTrzsOE687DiKt5ZQWVyNoRvEp8SSO2YQmhaV0ycNGBt3rMdc5SWQ6QbdCM+pEykJ+EPoWf13WQ1F\nicTFJ13E4vpnccceuma+LVWvC4Y+2reWX1G6T1QGO0dOGMbOSxIZ8tNyRIoN8UQ90mFFHm6DchP4\nNLAZkGyg7wzg+MGL43oXsTkGBS/Fc8XjM350Hqp8HjbWllEf8JHqcDEuMRObqePFkTU0g6yhatr7\ngaTOU4KeaQ03Y3WkKcuQoBs4fqiCMX1rdXRF6WqnX3Iqz972Iu7LAh0efu7zmTk6uUeneemnpKrZ\n6e9e+/udnPObexhxVRW7r4zHmmAQeL8Ja0EA4ZFIhwCLFdtlDvxeB0n5dex8LY4xsyv47bqLCQXH\nc/+k33a4FuWL0u3cv+4TvqspbfG6WWjMyhrO7eOOJ8fduSnzlYHBZAtCvgn7ymp8QxLA1Fy7c7A7\nugwHOlhMSLvAvdPbs5lWlF5wpG0im39YRfpwb8QBj24ItvzFzPyXb+z+DPZ3kn3TX/RzUdvekZ6e\nyDN/+DXrH0ojJkYnI70ByzF2uDIB8YskuCoR7bgY0rPrcMfpbPpXMkOn1JA0zI/FZOCwr+aqZdcQ\nCEVWhSql5Lav3+KKz15sFegAhKTB+0WbOWHRY7xVsL6rL1fpRxoDTuybPegJJkz1fggZ4Vqb9u7k\nhgwvN2Ex4fx2N2KCiTFTK3s204rSC2790y+RC2Ip2ezc+/U4WEVEMKSx6S927rn9N1isqqk3mkRt\nsAMwJD+Tpc/8mZTlY1nx5zT0MoOYRIOYJJ2YBB3Nq7N6fgZVC61MvbaQ1LH7RrhICZmx1cz74udE\nsuTGnd8u4vWd3x0ynYHkl8vfZEnxDz/q2pT+K2g4GDaqEtPwAKa6Jsw14c+d8AbDH7yQEf6nGxDU\nw//MGs7lRegnOjHv8CB9XTfHk6L0VUIInnz5YWLeTGbjw06qKh1t/iYIhjR2fhvLxlst3H3zrzn8\naDWvU8Sa1+zr0n+9IGqbsfaw22388x838Nz6z1n82RMUvxNH0GfGbNNJGdXI+Ht3tDtLv5SQl1DG\nHZ+/wPzp7a8f8n1tOS/vWNPyxQCIQPPwYgnSIWG/lSN+sfwN1p59G1pn5lpR+jWheUmO1XAv9eI7\n0o5nhwXn8iL8gxMIxVjAvN9nQtdx/FCN8IcwTnXhr/MxOqmMTZXZvXcBitKDNE3j4ef/j5WfrObB\nBx9lbb3EPt2KOUFgBCTB7QahzSGmHzWO617/Ga747pkHTenboj7Y2eOl4pcZN81D9rS2Z1Vui2he\nSmK7/hnQfrAzf+3HLffzCKRDIq37RbhBwnPlNM//5w0FeWfXBs7IPSzi/CgDQwiDFQWZjD1rO9+9\nk4l/AmgjYwiVmon5phgttKcNXRDIcBCa4SbeqKSqroncb0rJOlVQva39WYsVZSA6YuYEnp75L2rK\n61i1dA0lu3fjSnSSP3kIY6eOUqNUO0t1UO5aQojZwD8I1288KaWc31PnLmusY2RK6340kRqaUMnn\nu7YwLaf1BH4BXefLsh37XjBA2mXrBkQLCK9oEQA9uvFLFexEIb3GhLOpGu/3sRx26m62vpRG5SiJ\nkW7gmqMTtFgxhAmLDGH2NFEdNAhukwzeXczY83Q+XzsYR+7BlxNRlIEqITWOE87t5AQ8yoDVJ0Jd\nIYQJeASYA4wGLhJCjO6p8//m3dexmn7EOisa3P3Zwja3Vfoa0feLjEWT1qK5aq89TVn6vpdKmxo6\nnSel/0quTkDPtlJoSSS01cnwyysZUriLwe9VEvweAjtDBAsC+LeFsK8OMfjNIsZP2cWEM4J88XUe\nzsYyNNVlR1GUH02GB0B09b9e0Fdqdo4CtkoptwMIIRYAc4GNPXHybdXlZP7IvjH1etvNXwFDb/nC\nwaoEm/vv7BEaIEP+lI45euJIdoQ2YVuyi51jc3As93LkpHLKUr1Io5LGtRCqB3sOxMwyE1NoghIb\nH+0YjNVfhTHGhmexFW7o7StRFKVfkyDlwHgO9YmaHSALKNzv76Lm13qEEZSITrZL7tkt6Gs7WEq0\nxbRMb5PQ1mdHgGgSLcLPGLMaGhmNpk0fS/1HNurGpuH8chdNmVYWbxnFd1+l4S60MTzLzKiRZvLt\nZiqXxfH58qGstWRhLq3APcbAniFJsaqqHUVRlD36Ss1OW5FCq+hDCHENcA1ATk5Ol5083WvBH7Rg\ntXa8KUsIEDo46tsOTGKtdjIcsZQ0NfehsIBWr2HEHhDxGLS64hMy1SKe0SgnPx17nYmAQ1J5VCZZ\n35dQsqQS87xE1liz8ZVYkQENs0vHlt+I9n015lfKcV6Qgi0pRPGbVn5/09zevgxFUQaCXmp26mp9\npWanCBi039/ZwO4DE0kpn5BSTpJSTkpJSemyk1+YOopVFZmd3v+7qjTO9Ke1u/3qkVNa/G24DUSj\nhvAIhE8gGjTwC2RMyw/VLeNmdjpPSv92yUUzMb1rxZQiqc5NQfw8haSaKmwLtmN9aSvmV7Zie2kL\n7sUlJB0bovSsobhSQ+xabCXGsHDS8Uf29iUoiqL0GX0l2PkWGCaEyBdCWIELgbd66uRnXDyLoi2x\nmDoRwZoMg+8LU7jmZ+e1m+bioROJt+63SroA6TKQTom0S6TbAEfLcx+fMZRku5oPIlpdetFs7LIe\n7Q0L1QEzSfGNeJNjKT57BHW3DKHpzjwqbxhO0Yg8bG6D+BwvhQstuH0uLjh/BkLNz6QoSlcYIJMK\n9olgR0oZAm4EPgA2AS9LKTf01Pmtdiszttj4pCgfrQOdgoUhWV6ay7CvJQmpce2ms2gm3jjxKhym\nyPrgjIxL5bFj2w+elIHPbDbx0H//gKWphrhvY6h90cyu7Vbicj2kJ9WSFldDWlod/hSDgvdssEDg\nsrgZe1gWP730tN7OvqIoA4GU4bWxuvpfL+gTwQ6AlHKRlHK4lHKIlPLPPX3+P/76arxvWFlWkoc5\ngsLQDIPVFZmUfuLmb9dcesj0g1zxLDn1ekbGpbabxiQEp+WM5q2TrsKsJsCKekOyM3jkxXux+Cux\num2klLgwL9DwPQ+eFwTB5yXxi624LXFYvLUcM3U0/3vvTb2dbUVRlD6nr3RQ7nXpg1J58KLT+fkL\n77Do9JFMTi8kxd5IQGs5KY7F0KkPOPiqdBDez6zcPfFIRk0cEdE5Uh0u3p19NcWeOv5n3RLW15Ti\n10O4zDZOyh7BdaOOwa5GYCn7GZKZztuLH+PlJZ/z8iNvEaquhAQnmMwInw+9sohRk6fw8+t+weCU\n9gNpRVGUThkgMyiLSBax7IsmTZokV6xY0eXH/frLr7n9F89ScUESMs8gP74Gt8WPEBJPyMb2mgT0\nIhNJC2r43R2nMHvu7C7Pg6K0p7ihlm0lZXi9PlKT4xmTkYXNpH6zKEo0EEKslFJO6qnzxZmS5dHO\n07v8uB80PNWj1wGqZqeVyVMn894X43n5uRd56f5vqUp1U5IeC5rAUqGTubOKMy8dy+WLb8Xldvd2\ndpUok+WOJ8sd39vZUBQlSsgBMrmtCnba4LDbueKn87jip/MoKixk9+5ipDRIS00nNz9fjXRRFEVR\nokDvjZ7qairYOYTsQYPIHjTo0AkVRVEURemTVLCjKIqiKEprEjWDsqIoiqIoSn+ganYURVEURWmb\nWvVcURRFURSl71M1O4qiKIqitCIBOUD67KhgR1EURVGU1qRUzViKoiiKoig9SQhxnhBigxDCEEJE\nPAuzqtlRFEVRFKVNfbAZaz1wNvDPjuykgh1FURRFUfoFKeUmoMMrGahgR1EURVGUtg2QPjv9dtVz\nIUQFUNCFh0wGKrvweErHqTLoG1Q59D5VBr2vL5ZBrpQypadOJoR4n/D70NXsgG+/v5+QUj6x33k/\nAtLb2O+3Uso3m9N8CtwqpVwRyQn7bc1OVxe4EGJFTy85r7SkyqBvUOXQ+1QZ9D5VBiClnN1L553V\n1cdUo7EURVEURRnQVLCjKIqiKEq/IIQ4SwhRBBwNvCuE+CCS/fptM1Y3eOLQSZRupsqgb1Dl0PtU\nGfQ+VQZ9kJRyIbCwo/v12w7KiqIoiqIokVDNWIqiKIqiDGhRF+wIIWYLIb4XQmwVQvymje1CCPFg\n8/Z1QoiJvZHPgSyCMrik+b1fJ4RYJoQY3xv5HMgOVQb7pTtSCKELIc7tyfxFg0jKQAgxQwixpnl6\n/M96Oo8DXQT3ojghxNtCiLXNZTCvN/Kp/HhR1YwlhDABPwAnAkXAt8BFUsqN+6U5BbgJOAWYDPxD\nSjm5F7I7IEVYBscAm6SUNUKIOcDdqgy6TiRlsF+6xYTnw/iPlPLVns7rQBXh9yAeWAbMllLuEkKk\nSinLeyXDA1CEZXAnECelvF0IkQJ8D6RLKQO9kWel86KtZucoYKuUcnvzh3UBMPeANHOBZ2TYciBe\nCJHR0xkdwA5ZBlLKZVLKmuY/lwPZPZzHgS6S7wGEg/7XAPWA7XqRlMHFwOtSyl0AKtDpcpGUgQTc\nIrw2gQuoBkI9m02lK0RbsJMFFO73d1Hzax1No3ReR9/fq4D3ujVH0eeQZSCEyALOAh7vwXxFk0i+\nB8OBBCHEp0KIlUKIy3ssd9EhkjJ4GBgF7Aa+A34h5QBZPyHKRNvQ87ZWDjuwHS+SNErnRfz+CiFm\nEg52ju3WHEWfSMrgAeB2KaXe0QX3lIhEUgZm4AjgBMABfCWEWC6l/KG7MxclIimDk4E1wPHAEGCx\nEOJzKWV9d2dO6VrRFuwUAYP2+zubcMTe0TRK50X0/gohxgFPAnOklFU9lLdoEUkZTAIWNAc6ycAp\nQoiQlPKNnsnigBfpvahSSukBPEKIpcB4wv1MlB8vkjKYB8yX4c6tW4UQO4CRwDc9k0Wlq0RbM9a3\nwDAhRL4QwgpcCLx1QJq3gMubR2VNAeqklCU9ndEB7JBlIITIAV4HLlO/YrvFIctASpkvpcyTUuYB\nrwLXq0CnS0VyL3oTmCaEMAshYggPmNjUw/kcyCIpg12Ea9YQQqQBI4DtPZpLpUtEVc2OlDIkhLgR\n+AAwER5hskEIcW3z9seBRYRHYm0FvIQje6WLRFgGvweSgEebaxZC0b51QfBJAAAAkElEQVQgX1eK\nsAyUbhRJGUgpNzWvOr0OMIAnpZTrey/XA0uE34M/AU8JIb4j3Ox1u5Syr62ErkQgqoaeK4qiKIoS\nfaKtGUtRFEVRlCijgh1FURRFUQY0FewoiqIoijKgqWBHURRFUZQBTQU7iqIoiqIMaCrYURRFURRl\nQFPBjqIoiqIoA5oKdhRFURRFGdD+H0rH6e8PZThrAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "z = np.random.rand(15)\n",
    "z=z*z\n",
    "plt.figure(figsize=(10, 8)) \n",
    "\n",
    "# Change color with c and alpha. I map the color to the X axis value.\n",
    "plt.scatter(dat['acousticness'], dat['Unnamed: 0'], s=dat['hour_of_day']*10, c = dat['svm_rating'] , alpha=1, linewidth=2)\n",
    "\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([   5,    6,    8,   10,   24,   29,   36,   39,   40,   41,\n",
       "            ...\n",
       "            9876, 9905, 9911, 9931, 9936, 9944, 9949, 9952, 9981, 9999],\n",
       "           dtype='int64', length=1868)"
      ]
     },
     "execution_count": 234,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rating_1_uid.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'session_id', 'session_position', 'session_length',\n",
       "       'track_id', 'skip_1', 'skip_2', 'skip_3', 'not_skipped',\n",
       "       'context_switch', 'no_pause_before_play', 'short_pause_before_play',\n",
       "       'long_pause_before_play', 'hist_user_behavior_n_seekfwd',\n",
       "       'hist_user_behavior_n_seekback', 'hist_user_behavior_is_shuffle',\n",
       "       'hour_of_day', 'date', 'premium', 'context_type',\n",
       "       'hist_user_behavior_reason_start', 'hist_user_behavior_reason_end',\n",
       "       'label', 'duration', 'release_year', 'us_popularity_estimate',\n",
       "       'acousticness', 'beat_strength', 'bounciness', 'danceability',\n",
       "       'dyn_range_mean', 'energy', 'flatness', 'instrumentalness', 'key',\n",
       "       'liveness', 'loudness', 'mechanism', 'mode', 'organism', 'speechiness',\n",
       "       'tempo', 'time_signature', 'valence', 'acoustic_vector_0',\n",
       "       'acoustic_vector_1', 'acoustic_vector_2', 'acoustic_vector_3',\n",
       "       'acoustic_vector_4', 'acoustic_vector_5', 'acoustic_vector_6',\n",
       "       'acoustic_vector_7', 'svm_rating'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 235,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "n = rating_1_uid.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "n = [n]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Int64Index([   5,    6,    8,   10,   24,   29,   36,   39,   40,   41,\n",
       "             ...\n",
       "             9876, 9905, 9911, 9931, 9936, 9944, 9949, 9952, 9981, 9999],\n",
       "            dtype='int64', length=1868)]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "n2 = pd.DataFrame(n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <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",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>1858</th>\n",
       "      <th>1859</th>\n",
       "      <th>1860</th>\n",
       "      <th>1861</th>\n",
       "      <th>1862</th>\n",
       "      <th>1863</th>\n",
       "      <th>1864</th>\n",
       "      <th>1865</th>\n",
       "      <th>1866</th>\n",
       "      <th>1867</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>24</td>\n",
       "      <td>29</td>\n",
       "      <td>36</td>\n",
       "      <td>39</td>\n",
       "      <td>40</td>\n",
       "      <td>41</td>\n",
       "      <td>...</td>\n",
       "      <td>9876</td>\n",
       "      <td>9905</td>\n",
       "      <td>9911</td>\n",
       "      <td>9931</td>\n",
       "      <td>9936</td>\n",
       "      <td>9944</td>\n",
       "      <td>9949</td>\n",
       "      <td>9952</td>\n",
       "      <td>9981</td>\n",
       "      <td>9999</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 1868 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   0     1     2     3     4     5     6     7     8     9     ...   1858  \\\n",
       "0     5     6     8    10    24    29    36    39    40    41  ...   9876   \n",
       "\n",
       "   1859  1860  1861  1862  1863  1864  1865  1866  1867  \n",
       "0  9905  9911  9931  9936  9944  9949  9952  9981  9999  \n",
       "\n",
       "[1 rows x 1868 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "n2 = n2.transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    0\n",
       "0   5\n",
       "1   6\n",
       "2   8\n",
       "3  10\n",
       "4  24"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "n2 = list(n2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wWnz9Ve/ycXk5k2RFCHFJzXdvYIztXbY4G6DQtLT9zYDNTwMvXvQe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\nBu3/AX9RoNhWvWNxAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 8)) \n",
    "\n",
    "\n",
    "\n",
    "plt.scatter(dat['beat_strength'], dat['bounciness'],cmap=plt.get_cmap(\"jet\"),\n",
    "            c = dat['svm_rating'],s = dat['hour_of_day'])\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1ZsyYMWv8+PH1J5100p5TTjmlV6tPASZQiYiIiIiIiIiIqIyMTte89fRNqmnDUsBoNG1Y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\n++CDD0Jf281i8SFyjNHEuKukH8iMjcm7Z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      "text/plain": [
       "<Figure size 1364.88x216 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 8)) \n",
    "g = sns.FacetGrid(dat, col=\"svm_rating\",  hue=\"hour_of_day\")\n",
    "g = (g.map(plt.scatter, \"beat_strength\", \"bounciness\", edgecolor=\"w\").add_legend())\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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+J3anhDRLVTXtGIuQ2daOIjBbdqfZvYaxiJipfuZlzZboa36vYcwSYahkCj5n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N1rwS\nQDBe5F+O7fA8h2Sbv+1IJt4rTRCob8hgxAKBGzyAJjNTMCUTcebg4y/HdsImETiuceAai9kYsYTv\nwLbPX+KpO0YAACAASURBVNeeSx+lVTqb44y/9yYJDrcKSSR+MlOhCO93mO0wooQmbEEncBYHoPmP\ncGt+XziO8w4rZNIcV48r0IxmRDFnz57lb7vttt4AUFlZaeI4jiYlJckAsHPnzgMWi+UKtiHaBpFu\nhQ2nlE6hlP7Lc/sZmk4edwZwwufxSc9zXgghnQE8CMBwd8fnuEcJIaWEkNKKitYtsh9KF5CY/Vto\nOI6AC3Fsp9QULMobCskUfpeUEwQQSwII4UAsCawaoBXSlmwnogFSAehVzpcqDyAIHOItJnCEIN5i\nYhWcrZDWajv6QgYAxgzuhI+fvhWd2qeEHiAVAr3aLNB2mvI7PO9vO2GHtjFiktZqO36oqtb9QlXY\nUI8OCaLfy+Eq1S7XdjiOA2eJByHaPatma320NdsJO7zQg+/3HmIcqhyygcxU+PU+8zutn5i3nQhs\nAWicxeHrPyJZ8zOuMTTMjXH1UNUkOGsHgqrD4KwdCFVNavqk0HTo0EE5ePDg/oMHD+7Pz8+vmDVr\n1g/6Y4vFQt3ukCISDA+RZh8VQkgPSul3AEAI6Q6gKXEiow3mQJP7A4AXKKUKCdESDwCU0iUAlgBA\nZmZmqzZb6rSDGAwvMBwuEDjoYEAOcPtcEAKkiC4QmGD8v4HRVmhLthPRAKkAmqxyZrRZWqvtSCYe\n70waCrgdiE9oh8rqGtTUuJAUYoBUqM2cpqqcGW2X1mo7gCbJ4ZIVmF1VIGs06QCSloXfji2AQql3\nlke4SjVmO4xQxKTtqArgskcmT6aqgKNCqwA9vgV4YmvI4YVGvsdIZmp28Q5PFwIrqGnLxKTt+BJm\nkKevLQQO6IykO4BxjaGsMjoqUNUkOCq6Ys00ziP7JGJcUVfPvIHqpt8gMnJyctITExPlPXv2SIMG\nDXLEx8ercXFxyquvvvoDAPTq1av/xo0bj/Tu3du1ePHipD/96U/Xu91ucuONN9qXL19+TGhjxaGR\nRr7PA/iMEPI5IeRzAP8C8GwT55wE0MXn8Q0ATgcckwmghBBSDmAcgMWEkLERXlPrxCQZDxfwDBBU\nVYo6pwyVUjQQS+OQw4EPAXe9DLw/G+S1VJDiPC3gU9mvH6NtQA0GSNGcQk1TMwysypnRtqCIV84j\n4e+TQV5LRer7U2AzAa6xBcZDc8LAqs0YbQl9+Gdt7QUtEV3+JaDKQPmXMK+bgZfuSY+4Uo3ZDqNV\noCqAvQIomQC8lqrd2yu0543wlSJQZeCzecDYxRH7nnB6uXVOuckKaQYjajFJ2nc/AlvwHdDpHcrO\niGoud4Ahoxlx2ztjzTTON3bDmmkc3PbOTZ98aXz33XeWzZs3Hy4oKDgZ6pjt27db1qxZk1RaWnrw\n4MGD+zmOo2+//XZyc19LtBNp6n0zgHcA3Ol5/A6ALaEPBwBsBdCLENINwCkAuQAm+B5AKe2m/5sQ\n8hcAGyml6yK8plYJx/NQpZQgfTSO570LodnFO7xDON6ZdCPi84q1+udif/1orJkWpDXFYLRWOI6H\nGjBA0GiAlKpSONwKqyhgtE1cdv+5BOVfwrx2CqrGrkRD9lJ0ap8C4nI0Tm9nMBgAGqsyV00fYdhO\nnZKUiMOvZzO/wmg7uOyAPqsD0O7XTtfiMKOOtEApgr1rAcIBecWaz3E7AM+wdiNC6eUe+aEOL2/Y\nh0V5Q5FsE5ntMWIPjgOkVG3dLkpaRTSLw1oPbJ/s2iPaRGMpHJtofMLl89Of/rSmqQrnTZs2xe/d\nu1caPHhwXwBoaGjg2rdvLzf3tUQ7kf7CLQfQDcBrnls3ACvCnUAplQE8CeBjAAcA/JVSuo8QMosQ\nMuvyL7n1w/G8vy4gryXTfNvTZJViS1kVZq7cDjusWlvcJWp+MhitDY7j/XXQDRLRVXbXJesNMhit\nhVBzCRITEvDc+jLYXaq2mcMWQAyGH3pV5umKSq192pe0LBCXg1WqMdoWlzqrQ5ci8KX2LHDhBLD8\nAQAkrO8x0sudnzMIf/zsqFeyw+FuSkWSwYhSOE6zHcKxOKw1QVlldFTgsruMYje47K7m/qi4uDjv\n/1lBEKjqo1TgdDoJAFBKyUMPPVSla0yXl5fvffPNNwNVJFo9kf7K9aaUTqeUfua5PQogo6mTKKUf\nUkozKKU9KKWve557m1IaNLCQUjqVUrrm0i6/bRGuPc0wwNO1phiMaMV3kI2zrsVlZYw2dNjihdGW\noE67oa+oqqlhQ3AYbQJfubNLae3XqzJ/968TcIxZcsmyNgxGq0Of1eGLPqvDANVAihAPvAXs3xiR\nDfnq5R5+PRsvj+mPBf84hA27tPV7uMGhDAaDcS0gYMnoqMBkO4VxRWpA7KbCZDvVkh+bnp7u3Llz\npw0AvvrqK+nUqVNmALjvvvsubty4MfHUqVMCAPzwww/84cOHm71KO9qJNBm9gxByk/6AEDISmnQH\n4yqiL4R80YfkXIrWFIMRFeiDbIpzNa3B4twW1zkPu6HDYLQFRFvwXIJxRYiPb8famxmtnivpjtGr\nMitq3XjxH2dRMXoZ6EsVoHnF8AzAuQp/AYMRRYg2IGBWB3IKtecD0GzPjbe+uYBT2UtB51aA5q4G\nbdcFyHo8YhvS9XIdLgUvb9jnTUQDPmsiBoPBiCKISkPeGFcJjquGlHoMecUuvFQB5BW7IKUea87h\nhUbk5+fX1NTU8H369On31ltvpXbt2rUBAIYNG9Ywd+7cU3feeWdGRkZGvzvuuCPjxIkTppa8lmgk\nrJgJIWQPNJUbE4B8Qshxz+OuAPa3/OW1Xi5Ht1ZfCPlqRnsr2TjCtKYYsYXvIBsgYp3zK9F8DqU3\n6HApbBI7o03AcRxUWyrohL+CUEVLGrjssAic5kcYjFaMb3cMAG93TMGUzPA+QFXBuR1IiZOwKr8/\nXJwVoomH3alAEuNAmrAdNquA0SrheCBgVgdEm/Z8ALrt3dv/etjirwMlBBdVCywyhSXcbBtV1eLF\ngLVN2DURgxEjMN/QBqBgmtHRAsdVwxyvJZ/N8c361qEkNuLi4ujmzZuPGL02Y8aMmhkzZtQ064XE\nGE1lX+6/KlfRxjAaRBjJ0A3f9jRDp6VrTQFsaCEj+gkcZAM0qXN+ubajwxYvDIanJcpVq23+HN+i\ntVWPK2LVnYxWz2V1x+hdPGumgRzfApKWBX7ccpyvo7juukRQZx1Usw1cCNu5Ur/FYEQ1HN84rNBo\naKEHSeRx34DrkT2gIx5bud1rCwtzh8DEc+B5A/vxsb1AX8VxXPg1EYMR5TDf0HZgchwMhjFhV52U\n0mPhblfrIlsbV6Jbq7ensSE5jJinKZ1zAz3pK9V8DtQbLJiSyYI+RtvDtytBlRu7EtxsxgCjdRNW\n7iwUgfYS1x4muQ5JG6aAm5cK/t08EHtoiSk2q4DRlgilye5wKXhgSGfMKdnpZwtzSnaGtoUmfBVb\nEzFihhZY0zBiB6YZzWAYw0qgrgFMt5bR1lFVigZiAQ2lcx5CT1oycVdsO2zxwmjzXEZXAoPRGtC7\nY7K6J0PgCLK6JzfdHRNoL7c+B6x73C9BRtaG3sxhMR+jrRBOk10y8UiwmgxtwRZKIof5KkZroAXX\nNIwYgMZEMlpVVZUtiBkthuf7FfSNZ8noa4BvZc6YwR3w1f8bjsPz7vPulDIYrRl9sfKzv5TimY2n\njIdAyQ2A0w7krwdmfQn0uR9w2kEIsOXZkRgzuIP3/djAGgbDB4PqmyCa6kpgMFopYbtjAmxHVRTU\nNrhBXXZ/e0npfUkJssuqxmYwYhC90jM13owPZo/CyukjYXfKaJAVcByB3Skb2oLdKRu/IfNVjNZA\nqAp/l535hjYAAUBo6FuUsLeioqIdS0gzWgJVVUlFRUU7AHsDX2MTu5oZVZZBZId3kAcVJHCC4Deg\ngCPAorwhKPnmOKbdGAdpwyNeLTQ6rggQ4wCOB+FMhkNAGIxYJnCA1N93nkFW92QU5GcCbhWSCSCu\nWpD3Z2t2kfNnoP+DwFpNrzM1LQu/H1sAnhCcvehCUf6NsFIHKPUMz+FFEF5k2reMtkcYfU0/ezBJ\n2vO+x+UUAbwJUBXmdxitGr07BtAqpR1uBZKJA7FXaBXOHpsgOUX4yzcXUFZZh9+OLYB53QzttZpj\nms3ow3eBxgSZwbwONquA0RpRFE1mwGYWYHfKkEw8JJHH9QlmPHN3b7ywdrfP930ILAIPycSjKP9G\nmGk9OEs81IZaOIkV5lC2YOSr9A46BiNKCRxKaBMlkMANzPgOIARYPWMEKqtr8JtPjuHsRRcW5Q1h\nvqEVQtToyTobIcvy9LNnzxaePXt2AFixKqP5UQHslWV5euALLBndjKiyDFJfCbJ2us8CvxCqNQVV\n9YrfQuTtSTfiiVs6givJa1zQlH8JsmYaMHoRIEqg5gQQwcwSA4xWRciWZTOPiQXfYMED3dH5I08F\nwYAcoPutwLuT/OzEvG4G3swrhpuzwNRQFWRzVLSBmGwsIc1oW/hW3wCN1Td5Jf5JMo4DpGRg/Crt\n+crDwLZlwLB8wJwAML/DaAP4Do/y8zuAV3rjweyluOV/j0ChFC+NXoaUpETA3QDkFPklrmlOIShv\nMVzBNTl8msGIMRRFRZXdhTklO/0GEUoij6fvysALa3d7Cw40HdydKJiSiTgTgdVd7Y3Z+LQsWHMK\nQcRU4w/iOG0zNa9E6zxwObRENIvtGFGK0VDClZP7g/fdwByQA9z5K5DiPMBTZPPmuCJUqgkQjQZ5\nMmIbCpAoL3YfNmzYOQBjrvV1MNoe7BevGSGyQwuw/HQEp4PIjqABBbNWbgcx24xbPRO7Amung6hu\nwGW/Nn8Mg9FChGpZPl7lwJayKnRMTWm0i1ufA8zxhnZCRBtMSn2QzWm2I7NhbIy2x6Xoa7ocwLsT\ngVeTgMU3AZ+/DqydDjC/w2gtNCFZ49ul4+d3dI5vQafUFADAhl1nkfXGN6AggCqDbFsG/OR3wNxz\nwE9+B7JtudYVFwI2q4ARS4QaQqjjcCuGgwg5QpCWLIXWwXXZDddJYX0Ox2mbpsRzzxLRjCjGaCjh\n4s1nQHN8ZuTcPjd47sCaaXDW12LWyu1sgGFrhIa5MRhtGObRmxNznHEiwBxnGJghUIcQ0B5XHvKc\nF2/Y8slgxDLGA6SG4A+f/v/27j9I7ru+7/jzvbu3d7qTHGNJIRSjClO7QaFg1zJEgAsk08GmBZNK\nbSVcTBgZ1+kYO38kmOFXmTHuQCbT1g44jrBch6FIE2zKr8EQBpICtZxYxMJgCB4hu8YYUv0ALN1a\nurv9fvrHd++0d9q9H6vbvf3xfMx8Z3e/+927z8f6vvz53mc/38/nMQCePnzkdC7W/dN81GazOQOb\nZW7kV1zgRoNnKfNrNm2vbHfUB5osGFXfIV1/l86sdmfahi35/pqZuW2HV8M3PgJ3bKl9mbMlf21u\n1AfmW4Rw2thwqeHfNSPlIpVT88yRPs/fSVI/aHT3521fP0gaq43wf/9hOG9j0y8/XcCwD6V8mo5m\nmzTI7IxeTqdONO4IOHWi4YXZqViVz302/U3pxsvhqo/CN/649rnj+c+U+kijBaTGhkv8wzOnAPij\nr/+Yypt25Xk48hh8/wt5LupzsrU2Z2CzzJ38pQvcaPBMz69Zn5Vm82s2ba9sd9QHmi0YVXfHTP1d\nOrPanVp20tbd/K/v/mLmS9Pbttfm8pznWk/qdY1Gdt645+FZozXnW4hwtNxowMElZkcDoemCtZPZ\n6RH+TQYOPH34iAsY9qnImm/SIIuUeusbmc2bN6f9+/evdDEaajRndNp6F6nBnNG377gkX8GdRJoc\nh/IYcewJ+Ov/Asd/ls9765zRaqyl+3u7Ojtz5li76bf+Cf/pVc+jMDxKjB/J57Pd9EZYdxFMnJhZ\n5LPZPO3OGa0m+i47Z8iyvMNtofk1sykYP5JPzVGXHeeMVhO9lZ2U5SOis6nT+wqlfFRa5Hlo2u6M\njBETFbLSKsYns1kLtBWLhXmv9Qoll2LRGXoqO1lKXPTe+5mqG7FXKgSP3Xolhcir0mzO6LVj5Twj\ncxZwm5kjPavC+OEz252x9bY5aqSnsgON54ye+Zt/enqmBotNV960i91/d4Ltr/jHs49Vt1vwH2rN\nueeni197U9P3v/W5d307pbR5WUsl9QivmpdRoVQiW7UOtn8q//bz1AlSaZRCqcTasWKTxWuCGF5D\nlk3B2Dr4N7vyEQKlMlEY8uJMA6HRAk+UCoxPZoyOrYff/D1iOO8goLxmpnOtUeYololi2Y5oDabp\n+TVh/lufC6W8zanPTqkMtjvqB9Mjz6YXjILZ0zvRuN2JoSIRAcOrKQBrinkW1owMzfyY+a71pF43\nPbJzegFCOD3Nxurh/BwvFgusHSuz65pLz/iyBk7PkQ7MPOZvFPOO5/p2pzxmm6O+sagFa+sW5kzl\nUdKpcUbKY7z98szFbftU9NbYT6lj7K1ZZoVSiRg5h4gCMXLOzB8nCy1eUyjM/lyURrw400Cpz8jo\nUJFjlcl8zsL3fZmrP/EoR05MkjUY7Tw3czE0Yke0tBiFEoyck48UHTkHbHfULxY5ZU2rCws2u9aT\nel3jdT1q02zUKRYLrBkZohDBmpGhmY7oBRWKs9sd2xz1mUW1K7WBAxEFCiNrKBQKLm7bx5ymQ2rM\nq2dJXad+zkJgZs7Cj79t8+xRNpIkzVU38mzBKWskzVjUyE5J0uIkoNr60OiIuAK4DSgCd6WUPjzn\n/auBm2svTwC/l1L6Tsu/UOogr8qXQZZlZCePk1L+mGV+zSUtRlatzs5ONV+0o9Fq1K4wLZ3WLDuS\naqanrInaox3R0qK0eseANKiq1YzjJyfJUuL4yUmqVfsCdFpkqek27+ciisDHgCuBTcCOiNg057DH\ngdeklF4K3ALsakMVpLbwyvwsZVlGjB+msHcHccv6/HH8sB3SGixZls/9l2qPizj/s2qVqByZnZ3K\nEbJqtflq1K4wLc2bHUmSzkoL13TSoJpe0PO6T3ybi957P9d94tscHZ+wQ1ozIjXfFvBy4GBK6VBK\naQLYC1xVf0BK6YGU0s9rLx8Ezl/u8kvtYmd0C7KpKdLJZ0gpIyZOEKeO54vkZFPwxDeJ+3bCxPhK\nF1PqjOlVofdsh1vW54+Vww3/eJmVnclxYuScM7MzWVn0nIXSoDgjOylrmB1Js1WnZt9FUJ3ySxup\nqfprul88CSkjBaSTz5BNTa106aSuMX1dVijA+vIEf/YfLmYqS+w7dJSb9h6gMmlbo1qn8/wjo9dF\nxP667bq6jz8f+HHd66dq+5rZCdy//LWQ2sPO6KXIMtLUBPHsEWLvW4hb1hN735Lf/vmen8BLtubH\nPbmPGB5b2bJKnTJZgXt3zuoY494zO8ayqakzs3Pyl/C+w2dkp37OwsduvZKPv20za8fK3iqqgdQw\nOxFwY92UcLY70hmqU1UKz86+i6Dw7BGqU1VvpZYamb6me9NH80Vt69qdePYIKZtySkINvEbXZWuq\nv+BHH3o9H3zjJh564hhjrnGjmqimphtwJKW0uW6rn2aj0R++DcdTR8TryDujb270vtSN7IxerNpI\ngZg6Sdx37eyOt/uuzd//7Q/knWobtpBOOTJaA6I8Ck/um73vyX35/joxVWmcnamTDbPjnIVSrml2\nRuumsrHdkc6QZ2fnGXcRxFTFW6mlRqav6UbPy9uZWdm5lpioOCWhBl6j67K471oKUxXe8M+ex5/s\nuJjxU95JIPKu4/m2+T0FvKDu9fnA03MPioiXAncBV6WUjp51maUOsTN6saZHCgyvbtzxNrwaPncD\nvO59pK27oewINQ2IiQps2DJ734Yt+f56i83O0OxObGngzZedQgk2Xm52pAZieKxhdmJ4zFuppUam\nr+nma3ecklCDbp583LT3AK++cL1TC6qm+RQdCy1gCDwEXBgRL4yIMrAd+Hz9ARGxAfgM8NaU0mNt\nqYLUJnZGL9b0SIFTJxp3vJ06AU/uI523kTS2noKrtmtQDI3Ctt2w8fKZjjG2NegYW0x2RtdRKHrx\nJs3SJDvp1Amy9x3mJ1fenbc7ZkeaJZ0ab5KdvBPNW6mlOaav6ea7ZgOnhtJgmycf0+1KsWhfgIC0\n4DQdzT+a0hRwA/AV4AfAX6SUHo2I6yPi+tphHwDWAndExIGI2N/O6kjLyf9LLtb0SIFjj8PWu2Z3\nvG29K9+/YQtMjNsRrb5XrWYcPzlJlhLHJ6pkq9bBjr3w/sP54+h6mJODVBolNcpOoTTTOWBnmnSm\nRtlJW+8ilUa44D338wefO8T4hKM7pbny7Oyek53dZMVVAFy28TxvpZbqFQowup5UGml8zVY5lh/n\n1FAaYM2uy45nZdsVnSlLzbcFpJS+lFK6KKX0opTSrbV9d6aU7qw9vzal9JyU0sW1bXObayMtG4eD\nLNb0SIF7d8Lrb4Xtn8pv0Tl1An7+OPzle+HNd0DYmab+Vq1mHB2f4Ka9B3joiWNctvE8btt+MWvH\nRilGIc9FA4VSKe+0rmUnTp3IL+A+9e9IW3eTSk4xIDUyNzucOkEqreKiD3yVLRes5bbtF3s7qNRA\nsVSkumodsX0PMTxGOjVOVlzFr//nvzQ7UjOFAlEon9HuxMQ4fPTS01NDOSWhBlSj67LjWZn/+MkD\ntis6Q6SFO52lQWRn9GLVRgqwY28+ZcfEOGlinBg/As99CbzxdtLwGqI0stIlldqqMlnlpr0H2Hco\nXx9het7NXddcyppigSxLVCarjJaLVCaqjA4VZxYfLJRKUDqH6lSVIIihEdL2PaTSKMWSF25SM9PZ\nAagOraYyWeWxW69k/NQUo0NFbweVmiiWilBaA0A2NMazZkc6LcvydXHKo/ldoEOjM3e21bc7WXk1\niSDefzgfEV0e805QDbSZv2mqGRVWsXpViV3XXGq7otkSsMB0HNKgsjN6KQp1oz6H1xBZBqsDImD1\nrxJ1F3BSvxobLvHQE8dm7ZueHy3LEkfHJ7hxz8Mzo6Zv33EJa8fKMx3SMLtzIEbWdLT8Uq8rFgus\nqf2hs2ZkaIVLI/UOsyPVyTKoHM7v+nxyXz7d4LbdDadaKxQKMOJ1mzSX7YrmE6S8z0jSGew5PRvT\nndPTUxPYEa0BMH5qiss2njdr3/T8aJXJKjfueZh9h44ylSX2HTrKjXsepjLpfLaSJEldY7KSd0Q/\n8U3IpvLHe3fm+yVJyyOl5ps0wOw9lbQko0NFbtt+MVsuWEupELPm3RwtFxuOmh4tOwWHJElS1yiP\n5iOi6z25L98vSTp7CaKamm7SIGtrZ3REXBERP4yIgxHx7gbvXx0Rj9S2ByLiZe0sj6SzVywWWDtW\nZtc1l/LYrVey65pLWTtWplgsUJmoNhw1XZlwZLQkSVLHZVm+4HqqPU7fMj5RyafmqLdhS75fkrQM\nUv7/3GabNMDa1hkdEUXgY8CVwCZgR0RsmnPY48BrUkovBW4BdrWrPJKWT7FYYM3IEIUI1owMzSzU\nMTpU5PYdl8waNX37jktcVVqSJKnTpueF3rMdblmfP1YO5/uHRvM5ojdeDoVS/rhtd75fknT2phcw\nbLZJA6ydCxi+HDiYUjoEEBF7gauA708fkFJ6oO74B4Hz21geSW1WKARrx8p8/G2bGS0XqUxUGR0q\nzlq8UOp7WZbPuVkezUeYubittChZlqhMVm0/pOVSPy80nJ4XesfefL2b0fX5c9srSWqLcG5oqaF2\nXm08H/hx3eunavua2Qnc3+iNiLguIvZHxP7Dhw8vYxGl/rYS2SkUgtXDJQpRe7QjQT2o5ezMNwpN\nGgCtZifLEkfHJ3jHn+/novfezzv+fD9HxyfIMv+I02BoyzXbQvNCuxi7+oB9BepaCahmzTdpgLXz\niqNRD1TDvygi4nXkndE3N3o/pbQrpbQ5pbR5/fr1y1hEqb+ZHak1LWenfhRaNnV6FNqkc3BqMLSa\nncpklRv3PMy+Q0eZyhL7Dh3lxj0PU5l0zQENhrZcszkvtAaAf++oezlntNRMOzujnwJeUPf6fODp\nuQdFxEuBu4CrUkpH21geSZLaa6FRaJIaGi0XeeiJY7P2PfTEMUbLrjkgtcx5oSVp5TgyWmqqnXNG\nPwRcGBEvBH4CbAfeUn9ARGwAPgO8NaX0WBvLIklS+02PQpuenxNOj0IbXr1y5ZK6XGWiymUbz2Pf\nodPjEi7beB6ViSqrh9t5uSr1sULBeaElacUkSHY6S4207UokpTQF3AB8BfgB8BcppUcj4vqIuL52\n2AeAtcAdEXEgIva3qzySJLWdo9CklowOFbl9xyVsuWAtpUKw5YK13L7jEkaHHBktnRXnhZakleHI\naKmptg41SSl9CfjSnH131j2/Fri2nWWQJKljHIUmtaRQCNaOlfn42zYzWi5SmagyOlR0EVxJktS7\nnBtaasj7HiXljeRkxc4zaTlMj0IDp+aQlqBQiJkpOZyaQ5Ik9bYEKa10IaSuZG+TNOiyDCqHYc92\nuGV9/lg57Le4kiRJkiS1IgHVavNNGmB2RkuDbrIC9+7MF1zLpvLHe3fm+yVJkiRJ0hIl54yWmvAe\nSGnQlUfhyX2z9z25L98vSZIkSZKWJkFyBLTUkCOjpUE3UYENW2bv27Al3y9JkiRJkpYupeabNMDs\njJYG3dAobNsNGy+HQil/3LY73y9JkiRJkpYmJeeMlppwmg5p0BUKMLoeduzNp+aYqOQd0QW/q5Ik\nSZIkaemS03RITdjbJCnveB5eDVF7tCNakiRJkqTWJM5qZHREXBERP4yIgxHx7gbvR0TcXnv/kYj4\n5+2ohtQO9jhJkiRJkiRJyyQBKUtNt/lERBH4GHAlsAnYERGb5hx2JXBhbbsO+NNlr4TUJnZGS5Ik\nSZIkScsl5dN0NNsW8HLgYErpUEppAtgLXDXnmKuAT6Tcg8C5EfG85a+ItPwi9dgqnhFxGPi/S/zY\nOuBIG4qzUqxPd2t3fY6klK5Y6ofMDmB9up3Z6V7Wp7uZne5lfbqb2ele1qe79UN2euHfpBfKCL1R\nPXKt7QAACeZJREFUzuUu44LnaER8ufZ7mxkBTta93pVS2lX77DbgipTStbXXbwVekVK6oe7nfxH4\ncErpW7XXXwNuTintb6VCUif13AKGKaX1S/1MROxPKW1uR3lWgvXpbt1aH7Njfbpdt9bH7Fifbtet\n9TE71qfbdWt9zI716XbdWp+lZKdb61CvF8oIvVHOlShjK1+o1IlGP7KFY6Su5DQdkiRJkiRJUnd4\nCnhB3evzgadbOEbqSnZGS5IkSZIkSd3hIeDCiHhhRJSB7cDn5xzzeeCayP0m8MuU0k87XVCpFT03\nTUeLdq10AZaZ9elu/VSffqoLWJ9u10/16ae6gPXpdv1Un36qC1ifbtdP9emnuoD16Xb9UJ9eqEMv\nlBF6o5y9UMYZKaWpiLgB+ApQBO5OKT0aEdfX3r8T+BLwBuAgUAHevlLllZaq5xYwlCRJkiRJkiT1\nHqfpkCRJkiRJkiS1nZ3RkiRJkiRJkqS266vO6Ii4IiJ+GBEHI+LdDd6/OiIeqW0PRMTLVqKci7VQ\nfeqOuywiqhGxrZPlW4rF1CUiXhsRByLi0Yj4350u41Is4lz7lYj4QkR8p1afrp6/yeyYnU4xO2an\nU8yO2ekks9O9zI7Z6RSz033Z6ZW89EIOeuX87ofzVhoIKaW+2Mgndf8RcAFQBr4DbJpzzCuB59Se\nXwn8zUqX+2zqU3fc18knr9+20uU+i3+bc4HvAxtqr391pct9lvV5D/CR2vP1wDGgvNJlP4v6mJ0u\nrYvZ6fr6mJ0urYvZ6fr6mJ0urYvZ6fr6mJ0urYvZ6co6rHheeiEHvXJ+98N56+Y2KFs/jYx+OXAw\npXQopTQB7AWuqj8gpfRASunntZcPAud3uIxLsWB9at4J3Af8v04WbokWU5e3AJ9JKT0JkFLq9fok\nYE1EBLCavJGb6mwxF83sdC+zY3Y6yex0L7NjdjrF7JidTjI73asfstMreemFHPTK+d0P5600EPqp\nM/r5wI/rXj9V29fMTuD+tpbo7CxYn4h4PvA7wJ0dLFcrFvNvcxHwnIj464j4dkRc07HSLd1i6vNR\n4MXA08B3gZtSSllnirdkZqd7mR2z00lmp3uZHbPTKWbH7HSS2ele/ZCdXslLL+SgV87vfjhvpYFQ\nWukCLKNosC81PDDideSNzavbWqKzs5j6/Hfg5pRSNf9ir2stpi4l4FLgt4FVwL6IeDCl9Fi7C9eC\nxdTn9cAB4LeAFwFfjYhvppSeaXfhWmB2upfZMTudZHbMTqeYne5ldsxOJ5kds9NOvZKXXshBr5zf\n/XDeSgOhnzqjnwJeUPf6fPJvu2aJiJcCdwFXppSOdqhsrVhMfTYDe2sN0jrgDRExlVL6bGeKuGiL\nqctTwJGU0jgwHhHfAF4GdOPF2WLq83bgwymlBByMiMeBXwf+tjNFXBKzY3Y6xeyYnU4xO2ank8yO\n2ekUs2N2OqUfstMreemFHPTK+d0P5600GFKHJqdu90besX4IeCGnJ6v/jTnHbAAOAq9c6fIuR33m\nHH8P3bugx2L+bV4MfK127CjwPeAlK132s6jPnwIfrD1/LvATYN1Kl/0s6mN2urQuZqfr62N2urQu\nZqfr62N2urQuZqfr62N2urQuZqcr67DieemFHPTK+d0P562b26BsfTMyOqU0FRE3AF8hX0X17pTS\noxFxfe39O4EPAGuBO2rfKk6llDavVJnns8j69ITF1CWl9IOI+DLwCJABd6WUvrdypW5ukf82twD3\nRMR3yW8XujmldGTFCj0Ps9O9zI7Z6SSzY3Y6xex0L7NjdjrJ7JidduqVvPRCDnrl/O6H81YaFJFS\nw2mTJEmSJEmSJElaNoWVLoAkSZIkSZIkqf/ZGS1JkiRJkiRJajs7oyVJkiRJkiRJbWdntCRJkiRJ\nkiSp7eyMliRJkiRJkiS1nZ3RkiRJkiRJkqS2szO6h0TExoj43jL8nDdHxKYWPvfaiHjl2f7+Rf6u\n34+I0brXJzrxe9WfzI7UGrMjtcbsSK0xOxoknu+SBpWd0YPpzcCSGyvgtUDDxioiSmdToAZ+Hxhd\n8Cips8yO1BqzI7XG7EitMTsaJJ7vknpKpJRWugxapIjYCHwZ+BvgEuAx4BrgxcB/BVYDR4DfTSn9\nNCLeAVwHlIGDwFuBi4EvAr+sbVtTSj9q8LtuBK4HpoDvA+8GHgSqwGHgncBO4FitLH8H3AF8DFgP\nVIB3pJT+PiLuAZ4BNgO/BrwrpXRvRBSAjwKvAR4n/3LkbuAfAX8M/BA4klJ6Xe2b09uAfw08C1yV\nUvqHs/nvqcFhdsyOWmN2zI5aY3bMjlpjdszOIPF893yXBlZKya1HNmAjkIBX1V7fDfwh8ACwvrbv\n3wN3156vrfvsh4B31p7fA2xb4Hc9DQzXnp9be/wg8Ad1x9xD3vAVa6+/BlxYe/4K4Ot1x32avDHa\nBBys7d8GfKm2/9eAn0+XC3gCWFf3uxLwxtrzPwLet9L/Hm69s5kds+PW2mZ2zI5ba5vZMTturW1m\nx+wM0ub57vnu5jao23LfeqH2+3FK6f/Unn8SeA/wEuCrEQFQBH5ae/8lEfEh4Fzyb1W/soTf8wjw\nPyPis8Bn5znu0ymlakSsJr/F59O1cgAM1x332ZRSBnw/Ip5b2/fq2ucz4GcR8Vfz/J4J8oYR4NvA\nv1xCXSQwO2B21BqzY3bUGrNjdtQas2N2Bonnu+e7NHDsjO49ac7r48CjKaUtDY69B3hzSuk7EfG7\n5HNCLda/Av4F8Cbg/RHxG02OG689FoBfpJQubnLcqbrnMedxMSZTStN1r+K5q6UzO2ZHrTE7Zket\nMTtmR60xO2ZnkHi+e75LA8cFDHvPhoiYbph2kM/ztH56X0QM1TUsa4CfRsQQcHXdzzhee6+h2lxP\nL0gp/RXwLk5/89r0cymlZ4DHI+Lf1n5GRMTLFqjLt4CtEVGofZv62sWWUWqB2ZFaY3ak1pgdqTVm\nR4PE813SwLEzuvf8AHhbRDwCnAf8CfncTB+JiO8ABzi9Iu77yRdD+Crw93U/Yy/whxHxcES8qMHv\nKAKfjIjvAg8D/y2l9AvgC8DvRMSBiLi8weeuBnbWyvEocNUCdbkPeAr4HvBntbL+svbeLuD+BW7t\nkZbC7EitMTtSa8yO1Bqzo0Hi+S5p4MTpOyOkzouI1SmlExGxFvhb8sUbfrbS5ZK6ndmRWmN2pNaY\nHak1ZkeDxPNd0mI4L49W2hcj4lygDNxiQyUtmtmRWmN2pNaYHak1ZkeDxPNd0oIcGT3gIuJjwKvm\n7L4tpfQ/VqI8Uq8wO1JrzI7UGrMjtcbsaJB4vkvqBXZGS5IkSZIkSZLazgUMJUmSJEmSJEltZ2e0\nJEmSJEmSJKnt7IyWJEmSJEmSJLWdndGSJEmSJEmSpLb7/3x1+uWeY1lrAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1450.38x216 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 8)) \n",
    "g = sns.FacetGrid(dat, col=\"svm_rating\",  hue=\"hist_user_behavior_is_shuffle\")\n",
    "g = (g.map(plt.scatter, \"beat_strength\", \"bounciness\", edgecolor=\"w\").add_legend())\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Kcuedd3bp1atXn3POOafXN998Y+7cubNaI3b48OEH2rZt64RCIdmjR4/Yv/71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\nlAJDnbOiKIqiFBjqnBVFURSlwPj/9kBddHbXAQEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 495.5x216 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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u2zCukulMo9lpXCnVgYLr8eDStWx74c22YU1jh3HOrONJOnajyTSulAJ838f4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\nTr7gXVXjnv7JcQBtzakFUXN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YwyPL1nPyBe+qirHauFq5uaVqWSs3t5BO7D2xqnGlBop6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mq56aabjtXV1RVOmDDhEsuyvPXr1zf2ywtCLwPqQoiXkKZyv1Lq6v4ayFCgmxrmVkzFpg5lpudW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\nJEmSJEmSJEmSJGmA/wKt+HUqXATUJwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 2007.5x216 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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+NsPbjVeRWfosuC5D58zBTyURgUI2QzFXLDdO1Dv/8wp5fLe6AUPjSqmOZcdr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\ni3TSZvsLB/jby+8yY24ZYRCiW1rBfqVqRiShdnAnFA1o6ZcSSTdG0TS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FMHvZ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\nGpAQEREREREREREREZF+9/8AWkgMqwG140oAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1575.5x216 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 8)) \n",
    "g = sns.FacetGrid(dat, col=\"hist_user_behavior_is_shuffle\",  hue=\"svm_rating\")\n",
    "g = (g.map(plt.scatter, \"beat_strength\", \"bounciness\", edgecolor=\"w\").add_legend())\n",
    "plt.colorbar()\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(10, 8)) \n",
    "g1 = sns.FacetGrid(dat, col=\"hist_user_behavior_reason_start\",  hue=\"svm_rating\")\n",
    "g1 = (g1.map(plt.scatter, \"beat_strength\", \"bounciness\", edgecolor=\"w\").add_legend())\n",
    "plt.colorbar()\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(10, 8)) \n",
    "g2 = sns.FacetGrid(dat, col=\"hist_user_behavior_reason_end\",  hue=\"svm_rating\")\n",
    "g2 = (g2.map(plt.scatter, \"beat_strength\", \"bounciness\", edgecolor=\"w\").add_legend())\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'session_id', 'session_position', 'session_length',\n",
       "       'track_id', 'skip_1', 'skip_2', 'skip_3', 'not_skipped',\n",
       "       'context_switch', 'no_pause_before_play', 'short_pause_before_play',\n",
       "       'long_pause_before_play', 'hist_user_behavior_n_seekfwd',\n",
       "       'hist_user_behavior_n_seekback', 'hist_user_behavior_is_shuffle',\n",
       "       'hour_of_day', 'date', 'premium', 'context_type',\n",
       "       'hist_user_behavior_reason_start', 'hist_user_behavior_reason_end',\n",
       "       'label', 'duration', 'release_year', 'us_popularity_estimate',\n",
       "       'acousticness', 'beat_strength', 'bounciness', 'danceability',\n",
       "       'dyn_range_mean', 'energy', 'flatness', 'instrumentalness', 'key',\n",
       "       'liveness', 'loudness', 'mechanism', 'mode', 'organism', 'speechiness',\n",
       "       'tempo', 'time_signature', 'valence', 'acoustic_vector_0',\n",
       "       'acoustic_vector_1', 'acoustic_vector_2', 'acoustic_vector_3',\n",
       "       'acoustic_vector_4', 'acoustic_vector_5', 'acoustic_vector_6',\n",
       "       'acoustic_vector_7', 'svm_rating'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>session_id</th>\n",
       "      <th>session_position</th>\n",
       "      <th>session_length</th>\n",
       "      <th>track_id</th>\n",
       "      <th>skip_1</th>\n",
       "      <th>skip_2</th>\n",
       "      <th>skip_3</th>\n",
       "      <th>not_skipped</th>\n",
       "      <th>context_switch</th>\n",
       "      <th>...</th>\n",
       "      <th>valence</th>\n",
       "      <th>acoustic_vector_0</th>\n",
       "      <th>acoustic_vector_1</th>\n",
       "      <th>acoustic_vector_2</th>\n",
       "      <th>acoustic_vector_3</th>\n",
       "      <th>acoustic_vector_4</th>\n",
       "      <th>acoustic_vector_5</th>\n",
       "      <th>acoustic_vector_6</th>\n",
       "      <th>acoustic_vector_7</th>\n",
       "      <th>svm_rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0_00006f66-33e5-4de7-a324-2d18e439fc1e</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152255</td>\n",
       "      <td>-0.815775</td>\n",
       "      <td>0.386409</td>\n",
       "      <td>0.23016</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0_00079a23-1600-486a-91bd-5208be0c745a</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152255</td>\n",
       "      <td>-0.815775</td>\n",
       "      <td>0.386409</td>\n",
       "      <td>0.23016</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>0_012b0fb4-0cc3-429f-9a78-cc6e622153fb</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152255</td>\n",
       "      <td>-0.815775</td>\n",
       "      <td>0.386409</td>\n",
       "      <td>0.23016</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0_013cc010-c476-4ad2-8972-73449e0b2ef4</td>\n",
       "      <td>9</td>\n",
       "      <td>13</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152255</td>\n",
       "      <td>-0.815775</td>\n",
       "      <td>0.386409</td>\n",
       "      <td>0.23016</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0_01a5f0dc-9938-48c9-92f1-c7e51f34d290</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152255</td>\n",
       "      <td>-0.815775</td>\n",
       "      <td>0.386409</td>\n",
       "      <td>0.23016</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0                              session_id  session_position  \\\n",
       "0           0  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 1   \n",
       "1           1  0_00079a23-1600-486a-91bd-5208be0c745a                 7   \n",
       "2           2  0_012b0fb4-0cc3-429f-9a78-cc6e622153fb                 6   \n",
       "3           3  0_013cc010-c476-4ad2-8972-73449e0b2ef4                 9   \n",
       "4           4  0_01a5f0dc-9938-48c9-92f1-c7e51f34d290                 7   \n",
       "\n",
       "   session_length                                track_id  skip_1  skip_2  \\\n",
       "0              20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "1              12  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "2              20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "3              13  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "4              12  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   \n",
       "\n",
       "   skip_3  not_skipped  context_switch    ...       valence  \\\n",
       "0   False         True               0    ...      0.152255   \n",
       "1    True        False               0    ...      0.152255   \n",
       "2   False         True               0    ...      0.152255   \n",
       "3   False         True               0    ...      0.152255   \n",
       "4    True        False               0    ...      0.152255   \n",
       "\n",
       "   acoustic_vector_0  acoustic_vector_1  acoustic_vector_2  acoustic_vector_3  \\\n",
       "0          -0.815775           0.386409            0.23016           0.028028   \n",
       "1          -0.815775           0.386409            0.23016           0.028028   \n",
       "2          -0.815775           0.386409            0.23016           0.028028   \n",
       "3          -0.815775           0.386409            0.23016           0.028028   \n",
       "4          -0.815775           0.386409            0.23016           0.028028   \n",
       "\n",
       "   acoustic_vector_4  acoustic_vector_5 acoustic_vector_6  acoustic_vector_7  \\\n",
       "0          -0.333373           0.015452          -0.35359           0.205826   \n",
       "1          -0.333373           0.015452          -0.35359           0.205826   \n",
       "2          -0.333373           0.015452          -0.35359           0.205826   \n",
       "3          -0.333373           0.015452          -0.35359           0.205826   \n",
       "4          -0.333373           0.015452          -0.35359           0.205826   \n",
       "\n",
       "  svm_rating  \n",
       "0        4.0  \n",
       "1        1.0  \n",
       "2        3.0  \n",
       "3        2.0  \n",
       "4        2.0  \n",
       "\n",
       "[5 rows x 53 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    167880.000000\n",
       "mean         17.651823\n",
       "std           3.422025\n",
       "min          10.000000\n",
       "25%          15.000000\n",
       "50%          20.000000\n",
       "75%          20.000000\n",
       "max          20.000000\n",
       "Name: session_length, dtype: float64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat['session_length'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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