spotify_short_logistic_track_id_individual_count_statistics.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import sklearn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tf_mini = pd.read_csv(r'F:\\AppliedDataScience\\data\\track_features\\tf_mini.csv')\n",
    "log_mini = pd.read_csv(r'F:\\AppliedDataScience\\data\\training_set\\log_mini.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>track_id</th>\n",
       "      <th>duration</th>\n",
       "      <th>release_year</th>\n",
       "      <th>us_popularity_estimate</th>\n",
       "      <th>acousticness</th>\n",
       "      <th>beat_strength</th>\n",
       "      <th>bounciness</th>\n",
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       "      <th>dyn_range_mean</th>\n",
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       "      <th>...</th>\n",
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       "      <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",
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       "      <td>-0.213120</td>\n",
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       "      <td>160.839996</td>\n",
       "      <td>1951</td>\n",
       "      <td>99.602549</td>\n",
       "      <td>0.812884</td>\n",
       "      <td>0.425890</td>\n",
       "      <td>0.508280</td>\n",
       "      <td>0.491625</td>\n",
       "      <td>8.368670</td>\n",
       "      <td>0.358813</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.726769</td>\n",
       "      <td>0.021720</td>\n",
       "      <td>-0.743634</td>\n",
       "      <td>0.333247</td>\n",
       "      <td>0.568447</td>\n",
       "      <td>0.411094</td>\n",
       "      <td>-0.187749</td>\n",
       "      <td>-0.387599</td>\n",
       "      <td>-0.433496</td>\n",
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       "      <td>175.399994</td>\n",
       "      <td>1951</td>\n",
       "      <td>99.665018</td>\n",
       "      <td>0.396854</td>\n",
       "      <td>0.400934</td>\n",
       "      <td>0.359990</td>\n",
       "      <td>0.552227</td>\n",
       "      <td>5.967346</td>\n",
       "      <td>0.514585</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
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       "      <td>-0.051825</td>\n",
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       "      <td>0.614825</td>\n",
       "      <td>-0.111419</td>\n",
       "      <td>-0.265953</td>\n",
       "      <td>-0.542753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>t_d6990e17-9c31-4b01-8559-47d9ce476df1</td>\n",
       "      <td>369.600006</td>\n",
       "      <td>1951</td>\n",
       "      <td>99.991764</td>\n",
       "      <td>0.728831</td>\n",
       "      <td>0.371328</td>\n",
       "      <td>0.335115</td>\n",
       "      <td>0.483044</td>\n",
       "      <td>5.802681</td>\n",
       "      <td>0.721442</td>\n",
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       "      <td>-0.174819</td>\n",
       "      <td>-0.034422</td>\n",
       "      <td>0.717229</td>\n",
       "      <td>-0.016239</td>\n",
       "      <td>-0.392694</td>\n",
       "      <td>-0.455496</td>\n",
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       "  </tbody>\n",
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       "<p>5 rows × 30 columns</p>\n",
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      ],
      "text/plain": [
       "                                 track_id    duration  release_year  \\\n",
       "0  t_a540e552-16d4-42f8-a185-232bd650ea7d  109.706673          1950   \n",
       "1  t_67965da0-132b-4b1e-8a69-0ef99b32287c  187.693329          1950   \n",
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       "3  t_070a63a0-744a-434e-9913-a97b02926a29  175.399994          1951   \n",
       "4  t_d6990e17-9c31-4b01-8559-47d9ce476df1  369.600006          1951   \n",
       "\n",
       "   us_popularity_estimate  acousticness  beat_strength  bounciness  \\\n",
       "0               99.975414      0.458040       0.519497    0.504949   \n",
       "1               99.969430      0.916272       0.419223    0.545530   \n",
       "2               99.602549      0.812884       0.425890    0.508280   \n",
       "3               99.665018      0.396854       0.400934    0.359990   \n",
       "4               99.991764      0.728831       0.371328    0.335115   \n",
       "\n",
       "   danceability  dyn_range_mean    energy        ...          time_signature  \\\n",
       "0      0.399767        7.511880  0.817709        ...                       4   \n",
       "1      0.491235        9.098376  0.154258        ...                       3   \n",
       "2      0.491625        8.368670  0.358813        ...                       4   \n",
       "3      0.552227        5.967346  0.514585        ...                       4   \n",
       "4      0.483044        5.802681  0.721442        ...                       4   \n",
       "\n",
       "    valence  acoustic_vector_0  acoustic_vector_1  acoustic_vector_2  \\\n",
       "0  0.935512          -0.033284          -0.411896          -0.028580   \n",
       "1  0.359675           0.145703          -0.850372           0.123860   \n",
       "2  0.726769           0.021720          -0.743634           0.333247   \n",
       "3  0.859075           0.039143          -0.267555          -0.051825   \n",
       "4  0.562343           0.131931          -0.292523          -0.174819   \n",
       "\n",
       "   acoustic_vector_3 acoustic_vector_4  acoustic_vector_5  acoustic_vector_6  \\\n",
       "0           0.349438          0.832467          -0.213871          -0.299464   \n",
       "1           0.746904          0.371803          -0.420558          -0.213120   \n",
       "2           0.568447          0.411094          -0.187749          -0.387599   \n",
       "3           0.106173          0.614825          -0.111419          -0.265953   \n",
       "4          -0.034422          0.717229          -0.016239          -0.392694   \n",
       "\n",
       "   acoustic_vector_7  \n",
       "0          -0.675907  \n",
       "1          -0.525795  \n",
       "2          -0.433496  \n",
       "3          -0.542753  \n",
       "4          -0.455496  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_mini.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "                               session_id  session_position  session_length  \\\n",
       "0  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 1              20   \n",
       "1  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 2              20   \n",
       "2  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 3              20   \n",
       "3  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 4              20   \n",
       "4  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 5              20   \n",
       "\n",
       "                           track_id_clean  skip_1  skip_2  skip_3  \\\n",
       "0  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   False   \n",
       "1  t_9099cd7b-c238-47b7-9381-f23f2c1d1043   False   False   False   \n",
       "2  t_fc5df5ba-5396-49a7-8b29-35d0d28249e0   False   False   False   \n",
       "3  t_23cff8d6-d874-4b20-83dc-94e450e8aa20   False   False   False   \n",
       "4  t_64f3743c-f624-46bb-a579-0f3f9a07a123   False   False   False   \n",
       "\n",
       "   not_skipped  context_switch  no_pause_before_play  \\\n",
       "0         True               0                     0   \n",
       "1         True               0                     1   \n",
       "2         True               0                     1   \n",
       "3         True               0                     1   \n",
       "4         True               0                     1   \n",
       "\n",
       "               ...               long_pause_before_play  \\\n",
       "0              ...                                    0   \n",
       "1              ...                                    0   \n",
       "2              ...                                    0   \n",
       "3              ...                                    0   \n",
       "4              ...                                    0   \n",
       "\n",
       "   hist_user_behavior_n_seekfwd  hist_user_behavior_n_seekback  \\\n",
       "0                             0                              0   \n",
       "1                             0                              0   \n",
       "2                             0                              0   \n",
       "3                             0                              0   \n",
       "4                             0                              0   \n",
       "\n",
       "   hist_user_behavior_is_shuffle  hour_of_day        date premium  \\\n",
       "0                           True           16  2018-07-15    True   \n",
       "1                           True           16  2018-07-15    True   \n",
       "2                           True           16  2018-07-15    True   \n",
       "3                           True           16  2018-07-15    True   \n",
       "4                           True           16  2018-07-15    True   \n",
       "\n",
       "         context_type hist_user_behavior_reason_start  \\\n",
       "0  editorial_playlist                       trackdone   \n",
       "1  editorial_playlist                       trackdone   \n",
       "2  editorial_playlist                       trackdone   \n",
       "3  editorial_playlist                       trackdone   \n",
       "4  editorial_playlist                       trackdone   \n",
       "\n",
       "  hist_user_behavior_reason_end  \n",
       "0                     trackdone  \n",
       "1                     trackdone  \n",
       "2                     trackdone  \n",
       "3                     trackdone  \n",
       "4                     trackdone  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_mini.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['track_id', '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": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_mini.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sample = pd.read_csv(r'F:\\AppliedDataScience\\data\\data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>acousticness</th>\n",
       "      <th>danceability</th>\n",
       "      <th>duration_ms</th>\n",
       "      <th>energy</th>\n",
       "      <th>instrumentalness</th>\n",
       "      <th>key</th>\n",
       "      <th>liveness</th>\n",
       "      <th>loudness</th>\n",
       "      <th>mode</th>\n",
       "      <th>speechiness</th>\n",
       "      <th>tempo</th>\n",
       "      <th>time_signature</th>\n",
       "      <th>valence</th>\n",
       "      <th>target</th>\n",
       "      <th>song_title</th>\n",
       "      <th>artist</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0102</td>\n",
       "      <td>0.833</td>\n",
       "      <td>204600</td>\n",
       "      <td>0.434</td>\n",
       "      <td>0.021900</td>\n",
       "      <td>2</td>\n",
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       "      <td>-8.795</td>\n",
       "      <td>1</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>150.062</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.286</td>\n",
       "      <td>1</td>\n",
       "      <td>Mask Off</td>\n",
       "      <td>Future</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.1990</td>\n",
       "      <td>0.743</td>\n",
       "      <td>326933</td>\n",
       "      <td>0.359</td>\n",
       "      <td>0.006110</td>\n",
       "      <td>1</td>\n",
       "      <td>0.1370</td>\n",
       "      <td>-10.401</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0794</td>\n",
       "      <td>160.083</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.588</td>\n",
       "      <td>1</td>\n",
       "      <td>Redbone</td>\n",
       "      <td>Childish Gambino</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>0.0344</td>\n",
       "      <td>0.838</td>\n",
       "      <td>185707</td>\n",
       "      <td>0.412</td>\n",
       "      <td>0.000234</td>\n",
       "      <td>2</td>\n",
       "      <td>0.1590</td>\n",
       "      <td>-7.148</td>\n",
       "      <td>1</td>\n",
       "      <td>0.2890</td>\n",
       "      <td>75.044</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.173</td>\n",
       "      <td>1</td>\n",
       "      <td>Xanny Family</td>\n",
       "      <td>Future</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0.6040</td>\n",
       "      <td>0.494</td>\n",
       "      <td>199413</td>\n",
       "      <td>0.338</td>\n",
       "      <td>0.510000</td>\n",
       "      <td>5</td>\n",
       "      <td>0.0922</td>\n",
       "      <td>-15.236</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0261</td>\n",
       "      <td>86.468</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.230</td>\n",
       "      <td>1</td>\n",
       "      <td>Master Of None</td>\n",
       "      <td>Beach House</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0.1800</td>\n",
       "      <td>0.678</td>\n",
       "      <td>392893</td>\n",
       "      <td>0.561</td>\n",
       "      <td>0.512000</td>\n",
       "      <td>5</td>\n",
       "      <td>0.4390</td>\n",
       "      <td>-11.648</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0694</td>\n",
       "      <td>174.004</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.904</td>\n",
       "      <td>1</td>\n",
       "      <td>Parallel Lines</td>\n",
       "      <td>Junior Boys</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  acousticness  danceability  duration_ms  energy  \\\n",
       "0           0        0.0102         0.833       204600   0.434   \n",
       "1           1        0.1990         0.743       326933   0.359   \n",
       "2           2        0.0344         0.838       185707   0.412   \n",
       "3           3        0.6040         0.494       199413   0.338   \n",
       "4           4        0.1800         0.678       392893   0.561   \n",
       "\n",
       "   instrumentalness  key  liveness  loudness  mode  speechiness    tempo  \\\n",
       "0          0.021900    2    0.1650    -8.795     1       0.4310  150.062   \n",
       "1          0.006110    1    0.1370   -10.401     1       0.0794  160.083   \n",
       "2          0.000234    2    0.1590    -7.148     1       0.2890   75.044   \n",
       "3          0.510000    5    0.0922   -15.236     1       0.0261   86.468   \n",
       "4          0.512000    5    0.4390   -11.648     0       0.0694  174.004   \n",
       "\n",
       "   time_signature  valence  target      song_title            artist  \n",
       "0             4.0    0.286       1        Mask Off            Future  \n",
       "1             4.0    0.588       1         Redbone  Childish Gambino  \n",
       "2             4.0    0.173       1    Xanny Family            Future  \n",
       "3             4.0    0.230       1  Master Of None       Beach House  \n",
       "4             4.0    0.904       1  Parallel Lines       Junior Boys  "
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'acousticness', 'danceability', 'duration_ms', 'energy',\n",
       "       'instrumentalness', 'key', 'liveness', 'loudness', 'mode',\n",
       "       'speechiness', 'tempo', 'time_signature', 'valence', 'target',\n",
       "       'song_title', 'artist'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['session_id', 'session_position', 'session_length', 'track_id_clean',\n",
       "       'skip_1', 'skip_2', 'skip_3', 'not_skipped', 'context_switch',\n",
       "       '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",
       "      dtype='object')"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_mini.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['track_id', '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": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_mini.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>dyn_range_mean</th>\n",
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       "      <th>acoustic_vector_2</th>\n",
       "      <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>1950</td>\n",
       "      <td>99.975414</td>\n",
       "      <td>0.458040</td>\n",
       "      <td>0.519497</td>\n",
       "      <td>0.504949</td>\n",
       "      <td>0.399767</td>\n",
       "      <td>7.511880</td>\n",
       "      <td>0.817709</td>\n",
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       "      <td>-0.02858</td>\n",
       "      <td>0.349438</td>\n",
       "      <td>0.832467</td>\n",
       "      <td>-0.213871</td>\n",
       "      <td>-0.299464</td>\n",
       "      <td>-0.675907</td>\n",
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       "      <td>t_67965da0-132b-4b1e-8a69-0ef99b32287c</td>\n",
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       "      <td>1950</td>\n",
       "      <td>99.969430</td>\n",
       "      <td>0.916272</td>\n",
       "      <td>0.419223</td>\n",
       "      <td>0.545530</td>\n",
       "      <td>0.491235</td>\n",
       "      <td>9.098376</td>\n",
       "      <td>0.154258</td>\n",
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       "      <td>0.359675</td>\n",
       "      <td>0.145703</td>\n",
       "      <td>-0.850372</td>\n",
       "      <td>0.12386</td>\n",
       "      <td>0.746904</td>\n",
       "      <td>0.371803</td>\n",
       "      <td>-0.420558</td>\n",
       "      <td>-0.213120</td>\n",
       "      <td>-0.525795</td>\n",
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       "                                 track_id    duration  release_year  \\\n",
       "0  t_a540e552-16d4-42f8-a185-232bd650ea7d  109.706673          1950   \n",
       "1  t_67965da0-132b-4b1e-8a69-0ef99b32287c  187.693329          1950   \n",
       "\n",
       "   us_popularity_estimate  acousticness  beat_strength  bounciness  \\\n",
       "0               99.975414      0.458040       0.519497    0.504949   \n",
       "1               99.969430      0.916272       0.419223    0.545530   \n",
       "\n",
       "   danceability  dyn_range_mean    energy        ...          time_signature  \\\n",
       "0      0.399767        7.511880  0.817709        ...                       4   \n",
       "1      0.491235        9.098376  0.154258        ...                       3   \n",
       "\n",
       "    valence  acoustic_vector_0  acoustic_vector_1  acoustic_vector_2  \\\n",
       "0  0.935512          -0.033284          -0.411896           -0.02858   \n",
       "1  0.359675           0.145703          -0.850372            0.12386   \n",
       "\n",
       "   acoustic_vector_3 acoustic_vector_4  acoustic_vector_5  acoustic_vector_6  \\\n",
       "0           0.349438          0.832467          -0.213871          -0.299464   \n",
       "1           0.746904          0.371803          -0.420558          -0.213120   \n",
       "\n",
       "   acoustic_vector_7  \n",
       "0          -0.675907  \n",
       "1          -0.525795  \n",
       "\n",
       "[2 rows x 30 columns]"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_mini.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "                               session_id  session_position  session_length  \\\n",
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       "1  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 2              20   \n",
       "\n",
       "                           track_id_clean  skip_1  skip_2  skip_3  \\\n",
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       "\n",
       "   hist_user_behavior_n_seekfwd  hist_user_behavior_n_seekback  \\\n",
       "0                             0                              0   \n",
       "1                             0                              0   \n",
       "\n",
       "   hist_user_behavior_is_shuffle  hour_of_day        date premium  \\\n",
       "0                           True           16  2018-07-15    True   \n",
       "1                           True           16  2018-07-15    True   \n",
       "\n",
       "         context_type hist_user_behavior_reason_start  \\\n",
       "0  editorial_playlist                       trackdone   \n",
       "1  editorial_playlist                       trackdone   \n",
       "\n",
       "  hist_user_behavior_reason_end  \n",
       "0                     trackdone  \n",
       "1                     trackdone  \n",
       "\n",
       "[2 rows x 21 columns]"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_mini.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "167880"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(log_mini)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50704"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tf_mini)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = log_mini"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tf_mini = tf_mini.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50704"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tf_mini)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "### creating label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df['label'] = np.where((df['not_skipped'] == True) | \n",
    "                       (df['hist_user_behavior_is_shuffle'] == True) & \n",
    "                       (df['hour_of_day'] > 12), 1, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe thead th {\n",
       "        text-align: left;\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>session_id</th>\n",
       "      <th>session_position</th>\n",
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       "      <td>t_bff5b6c6-6968-41be-b723-7e860b372975</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>16</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>editorial_playlist</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0_00006f66-33e5-4de7-a324-2d18e439fc1e</td>\n",
       "      <td>18</td>\n",
       "      <td>20</td>\n",
       "      <td>t_bf496d77-9eb2-4fe1-80f7-2c7ecd6f9b8e</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>16</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>editorial_playlist</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0_00006f66-33e5-4de7-a324-2d18e439fc1e</td>\n",
       "      <td>19</td>\n",
       "      <td>20</td>\n",
       "      <td>t_1051bc37-1a73-4301-812b-f83ae0c9bbcd</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>16</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>editorial_playlist</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0_00006f66-33e5-4de7-a324-2d18e439fc1e</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>t_358c9cce-7a1e-4dd4-81de-206dda80363f</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>16</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>editorial_playlist</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0_0000a72b-09ac-412f-b452-9b9e79bded8f</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>t_e975c3a1-6a6c-4955-8bc7-02eb8e701bec</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0_0000a72b-09ac-412f-b452-9b9e79bded8f</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>t_0632570b-b4b4-4c3c-b47c-443ec9fbaa11</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0_0000a72b-09ac-412f-b452-9b9e79bded8f</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>t_83024f1d-d384-4550-8b37-78a3c0cf0c42</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0_0000a72b-09ac-412f-b452-9b9e79bded8f</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>t_981c30c6-7f94-4b81-b4f1-9992dae4f6a3</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0_0000a72b-09ac-412f-b452-9b9e79bded8f</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>t_7e1e8880-1f59-4b55-b5b3-1b2335320932</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0_0000a72b-09ac-412f-b452-9b9e79bded8f</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>t_6ced9628-fac7-439c-abbb-621400f2f041</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0_0000a72b-09ac-412f-b452-9b9e79bded8f</td>\n",
       "      <td>7</td>\n",
       "      <td>20</td>\n",
       "      <td>t_c6146a93-09d6-4c2d-949f-ab79e0a845a5</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0_0000a72b-09ac-412f-b452-9b9e79bded8f</td>\n",
       "      <td>8</td>\n",
       "      <td>20</td>\n",
       "      <td>t_e382b87e-bd8d-493d-ab65-113e8f627eb4</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0_0000a72b-09ac-412f-b452-9b9e79bded8f</td>\n",
       "      <td>9</td>\n",
       "      <td>20</td>\n",
       "      <td>t_0b38d601-8996-4aec-843c-74f6d96db1f5</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0_0000a72b-09ac-412f-b452-9b9e79bded8f</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>t_b269ccd8-9bd6-4554-bb4c-da4f5eba1462</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>backbtn</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167850</th>\n",
       "      <td>0_0eae096d-ae4c-4556-8227-0f6294958330</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "      <td>t_3a9183ba-ee90-4afd-b54c-0071e6393cc1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>20</td>\n",
       "      <td>2018-07-14</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167851</th>\n",
       "      <td>0_0eae096d-ae4c-4556-8227-0f6294958330</td>\n",
       "      <td>4</td>\n",
       "      <td>12</td>\n",
       "      <td>t_ccc357cc-842b-4bd7-abc7-a4d1ca5b6ab3</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>20</td>\n",
       "      <td>2018-07-14</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167852</th>\n",
       "      <td>0_0eae096d-ae4c-4556-8227-0f6294958330</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>t_ad195fc6-41bd-49d4-a8a3-7809b5c5c75d</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>20</td>\n",
       "      <td>2018-07-14</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167853</th>\n",
       "      <td>0_0eae096d-ae4c-4556-8227-0f6294958330</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>t_8a82d7b1-5314-4321-b205-17f2f0ba4023</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>20</td>\n",
       "      <td>2018-07-14</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167854</th>\n",
       "      <td>0_0eae096d-ae4c-4556-8227-0f6294958330</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>t_0c343e55-4284-4637-b0c2-c8ea0efa62a8</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>20</td>\n",
       "      <td>2018-07-14</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167855</th>\n",
       "      <td>0_0eae096d-ae4c-4556-8227-0f6294958330</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>t_91ab3ccb-9202-4c40-8ec5-3cac21b2ff1b</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>20</td>\n",
       "      <td>2018-07-14</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167856</th>\n",
       "      <td>0_0eae096d-ae4c-4556-8227-0f6294958330</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>t_d4c83551-0b13-4fe0-bca6-7392f5f7292f</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>20</td>\n",
       "      <td>2018-07-14</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167857</th>\n",
       "      <td>0_0eae096d-ae4c-4556-8227-0f6294958330</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>t_8160da16-8962-4f26-8e3b-ea29377415f2</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>20</td>\n",
       "      <td>2018-07-14</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167858</th>\n",
       "      <td>0_0eae096d-ae4c-4556-8227-0f6294958330</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>t_56bc277a-86e3-4a74-8cf4-93a45f7fc4d6</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>20</td>\n",
       "      <td>2018-07-14</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167859</th>\n",
       "      <td>0_0eae096d-ae4c-4556-8227-0f6294958330</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>t_d8c9417d-d0f5-40df-82d4-c3298bbafc91</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>20</td>\n",
       "      <td>2018-07-14</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167860</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>t_f80ee4db-b284-4ef7-bdde-604ea6354f3c</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>clickrow</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167861</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>t_e76ba594-cebd-472d-a2da-483568be0406</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167862</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>t_360910e8-2a84-42b0-baf1-59abcf96a1f2</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167863</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>t_aa2fff77-9b0a-4fa3-a685-ecef50310e8a</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167864</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>t_f673e1b7-4ebe-4fc1-ac24-a9f25de70381</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167865</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>t_e172e8e7-7161-42a9-acb0-d606346c8f87</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167866</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>7</td>\n",
       "      <td>20</td>\n",
       "      <td>t_77977dd6-597e-4425-8f8f-4efb32ecfba6</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167867</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>8</td>\n",
       "      <td>20</td>\n",
       "      <td>t_96a13618-10dc-498e-9de5-0940e4c84605</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167868</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>9</td>\n",
       "      <td>20</td>\n",
       "      <td>t_356f276e-ffac-4ff1-9c1b-0f59f402dc5f</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167869</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>t_e880d88c-bc6d-4f29-a220-b2d75aaade43</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167870</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>11</td>\n",
       "      <td>20</td>\n",
       "      <td>t_773a9f8f-2d00-4467-965a-df709d650bfd</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167871</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>12</td>\n",
       "      <td>20</td>\n",
       "      <td>t_94c1dd31-2410-4167-a75b-d6433d20bb04</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167872</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>13</td>\n",
       "      <td>20</td>\n",
       "      <td>t_bda3bb62-b717-4766-b417-4e7b0a31579b</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167873</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>14</td>\n",
       "      <td>20</td>\n",
       "      <td>t_f80ee4db-b284-4ef7-bdde-604ea6354f3c</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>fwdbtn</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167874</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>t_e76ba594-cebd-472d-a2da-483568be0406</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167875</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>16</td>\n",
       "      <td>20</td>\n",
       "      <td>t_360910e8-2a84-42b0-baf1-59abcf96a1f2</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167876</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>t_aa2fff77-9b0a-4fa3-a685-ecef50310e8a</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167877</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>18</td>\n",
       "      <td>20</td>\n",
       "      <td>t_f673e1b7-4ebe-4fc1-ac24-a9f25de70381</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167878</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>19</td>\n",
       "      <td>20</td>\n",
       "      <td>t_e172e8e7-7161-42a9-acb0-d606346c8f87</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167879</th>\n",
       "      <td>0_0eaeef5d-25e9-4429-bd55-af15d3604c9f</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>t_77977dd6-597e-4425-8f8f-4efb32ecfba6</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>2018-07-15</td>\n",
       "      <td>True</td>\n",
       "      <td>user_collection</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>167880 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    session_id  session_position  \\\n",
       "0       0_00006f66-33e5-4de7-a324-2d18e439fc1e                 1   \n",
       "1       0_00006f66-33e5-4de7-a324-2d18e439fc1e                 2   \n",
       "2       0_00006f66-33e5-4de7-a324-2d18e439fc1e                 3   \n",
       "3       0_00006f66-33e5-4de7-a324-2d18e439fc1e                 4   \n",
       "4       0_00006f66-33e5-4de7-a324-2d18e439fc1e                 5   \n",
       "5       0_00006f66-33e5-4de7-a324-2d18e439fc1e                 6   \n",
       "6       0_00006f66-33e5-4de7-a324-2d18e439fc1e                 7   \n",
       "7       0_00006f66-33e5-4de7-a324-2d18e439fc1e                 8   \n",
       "8       0_00006f66-33e5-4de7-a324-2d18e439fc1e                 9   \n",
       "9       0_00006f66-33e5-4de7-a324-2d18e439fc1e                10   \n",
       "10      0_00006f66-33e5-4de7-a324-2d18e439fc1e                11   \n",
       "11      0_00006f66-33e5-4de7-a324-2d18e439fc1e                12   \n",
       "12      0_00006f66-33e5-4de7-a324-2d18e439fc1e                13   \n",
       "13      0_00006f66-33e5-4de7-a324-2d18e439fc1e                14   \n",
       "14      0_00006f66-33e5-4de7-a324-2d18e439fc1e                15   \n",
       "15      0_00006f66-33e5-4de7-a324-2d18e439fc1e                16   \n",
       "16      0_00006f66-33e5-4de7-a324-2d18e439fc1e                17   \n",
       "17      0_00006f66-33e5-4de7-a324-2d18e439fc1e                18   \n",
       "18      0_00006f66-33e5-4de7-a324-2d18e439fc1e                19   \n",
       "19      0_00006f66-33e5-4de7-a324-2d18e439fc1e                20   \n",
       "20      0_0000a72b-09ac-412f-b452-9b9e79bded8f                 1   \n",
       "21      0_0000a72b-09ac-412f-b452-9b9e79bded8f                 2   \n",
       "22      0_0000a72b-09ac-412f-b452-9b9e79bded8f                 3   \n",
       "23      0_0000a72b-09ac-412f-b452-9b9e79bded8f                 4   \n",
       "24      0_0000a72b-09ac-412f-b452-9b9e79bded8f                 5   \n",
       "25      0_0000a72b-09ac-412f-b452-9b9e79bded8f                 6   \n",
       "26      0_0000a72b-09ac-412f-b452-9b9e79bded8f                 7   \n",
       "27      0_0000a72b-09ac-412f-b452-9b9e79bded8f                 8   \n",
       "28      0_0000a72b-09ac-412f-b452-9b9e79bded8f                 9   \n",
       "29      0_0000a72b-09ac-412f-b452-9b9e79bded8f                10   \n",
       "...                                        ...               ...   \n",
       "167850  0_0eae096d-ae4c-4556-8227-0f6294958330                 3   \n",
       "167851  0_0eae096d-ae4c-4556-8227-0f6294958330                 4   \n",
       "167852  0_0eae096d-ae4c-4556-8227-0f6294958330                 5   \n",
       "167853  0_0eae096d-ae4c-4556-8227-0f6294958330                 6   \n",
       "167854  0_0eae096d-ae4c-4556-8227-0f6294958330                 7   \n",
       "167855  0_0eae096d-ae4c-4556-8227-0f6294958330                 8   \n",
       "167856  0_0eae096d-ae4c-4556-8227-0f6294958330                 9   \n",
       "167857  0_0eae096d-ae4c-4556-8227-0f6294958330                10   \n",
       "167858  0_0eae096d-ae4c-4556-8227-0f6294958330                11   \n",
       "167859  0_0eae096d-ae4c-4556-8227-0f6294958330                12   \n",
       "167860  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                 1   \n",
       "167861  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                 2   \n",
       "167862  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                 3   \n",
       "167863  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                 4   \n",
       "167864  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                 5   \n",
       "167865  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                 6   \n",
       "167866  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                 7   \n",
       "167867  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                 8   \n",
       "167868  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                 9   \n",
       "167869  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                10   \n",
       "167870  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                11   \n",
       "167871  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                12   \n",
       "167872  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                13   \n",
       "167873  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                14   \n",
       "167874  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                15   \n",
       "167875  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                16   \n",
       "167876  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                17   \n",
       "167877  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                18   \n",
       "167878  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                19   \n",
       "167879  0_0eaeef5d-25e9-4429-bd55-af15d3604c9f                20   \n",
       "\n",
       "        session_length                          track_id_clean  skip_1  \\\n",
       "0                   20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "1                   20  t_9099cd7b-c238-47b7-9381-f23f2c1d1043   False   \n",
       "2                   20  t_fc5df5ba-5396-49a7-8b29-35d0d28249e0   False   \n",
       "3                   20  t_23cff8d6-d874-4b20-83dc-94e450e8aa20   False   \n",
       "4                   20  t_64f3743c-f624-46bb-a579-0f3f9a07a123   False   \n",
       "5                   20  t_c815228b-3212-4f9e-9d4f-9cb19b248184   False   \n",
       "6                   20  t_e23c19f5-4c32-4557-aa44-81372c2e3705    True   \n",
       "7                   20  t_0be6eced-f56f-48bd-8086-f2e0b760fdee    True   \n",
       "8                   20  t_f3ecbd3b-9e8e-4557-b8e0-39cfcd7e65dd   False   \n",
       "9                   20  t_2af4dfa0-7df3-4b7e-b7ab-353ba48237f9    True   \n",
       "10                  20  t_79570b2a-639a-4ec0-9853-71c5299ac44d    True   \n",
       "11                  20  t_69016f19-84aa-40c0-afa9-54404397b7a2    True   \n",
       "12                  20  t_59dc3fcd-7aec-4da5-a747-b59b19bab3bb    True   \n",
       "13                  20  t_a157ba98-7eae-4e7d-99d5-ed760b2c0978   False   \n",
       "14                  20  t_87d95b75-af5c-4ef6-8dc4-cd888ae17cce   False   \n",
       "15                  20  t_db945033-3dc5-4a22-8889-c72fd2781299   False   \n",
       "16                  20  t_bff5b6c6-6968-41be-b723-7e860b372975   False   \n",
       "17                  20  t_bf496d77-9eb2-4fe1-80f7-2c7ecd6f9b8e   False   \n",
       "18                  20  t_1051bc37-1a73-4301-812b-f83ae0c9bbcd    True   \n",
       "19                  20  t_358c9cce-7a1e-4dd4-81de-206dda80363f    True   \n",
       "20                  20  t_e975c3a1-6a6c-4955-8bc7-02eb8e701bec   False   \n",
       "21                  20  t_0632570b-b4b4-4c3c-b47c-443ec9fbaa11    True   \n",
       "22                  20  t_83024f1d-d384-4550-8b37-78a3c0cf0c42   False   \n",
       "23                  20  t_981c30c6-7f94-4b81-b4f1-9992dae4f6a3   False   \n",
       "24                  20  t_7e1e8880-1f59-4b55-b5b3-1b2335320932   False   \n",
       "25                  20  t_6ced9628-fac7-439c-abbb-621400f2f041    True   \n",
       "26                  20  t_c6146a93-09d6-4c2d-949f-ab79e0a845a5    True   \n",
       "27                  20  t_e382b87e-bd8d-493d-ab65-113e8f627eb4    True   \n",
       "28                  20  t_0b38d601-8996-4aec-843c-74f6d96db1f5    True   \n",
       "29                  20  t_b269ccd8-9bd6-4554-bb4c-da4f5eba1462    True   \n",
       "...                ...                                     ...     ...   \n",
       "167850              12  t_3a9183ba-ee90-4afd-b54c-0071e6393cc1   False   \n",
       "167851              12  t_ccc357cc-842b-4bd7-abc7-a4d1ca5b6ab3    True   \n",
       "167852              12  t_ad195fc6-41bd-49d4-a8a3-7809b5c5c75d    True   \n",
       "167853              12  t_8a82d7b1-5314-4321-b205-17f2f0ba4023    True   \n",
       "167854              12  t_0c343e55-4284-4637-b0c2-c8ea0efa62a8    True   \n",
       "167855              12  t_91ab3ccb-9202-4c40-8ec5-3cac21b2ff1b    True   \n",
       "167856              12  t_d4c83551-0b13-4fe0-bca6-7392f5f7292f   False   \n",
       "167857              12  t_8160da16-8962-4f26-8e3b-ea29377415f2    True   \n",
       "167858              12  t_56bc277a-86e3-4a74-8cf4-93a45f7fc4d6    True   \n",
       "167859              12  t_d8c9417d-d0f5-40df-82d4-c3298bbafc91    True   \n",
       "167860              20  t_f80ee4db-b284-4ef7-bdde-604ea6354f3c   False   \n",
       "167861              20  t_e76ba594-cebd-472d-a2da-483568be0406   False   \n",
       "167862              20  t_360910e8-2a84-42b0-baf1-59abcf96a1f2   False   \n",
       "167863              20  t_aa2fff77-9b0a-4fa3-a685-ecef50310e8a   False   \n",
       "167864              20  t_f673e1b7-4ebe-4fc1-ac24-a9f25de70381   False   \n",
       "167865              20  t_e172e8e7-7161-42a9-acb0-d606346c8f87   False   \n",
       "167866              20  t_77977dd6-597e-4425-8f8f-4efb32ecfba6   False   \n",
       "167867              20  t_96a13618-10dc-498e-9de5-0940e4c84605   False   \n",
       "167868              20  t_356f276e-ffac-4ff1-9c1b-0f59f402dc5f   False   \n",
       "167869              20  t_e880d88c-bc6d-4f29-a220-b2d75aaade43   False   \n",
       "167870              20  t_773a9f8f-2d00-4467-965a-df709d650bfd   False   \n",
       "167871              20  t_94c1dd31-2410-4167-a75b-d6433d20bb04   False   \n",
       "167872              20  t_bda3bb62-b717-4766-b417-4e7b0a31579b    True   \n",
       "167873              20  t_f80ee4db-b284-4ef7-bdde-604ea6354f3c   False   \n",
       "167874              20  t_e76ba594-cebd-472d-a2da-483568be0406   False   \n",
       "167875              20  t_360910e8-2a84-42b0-baf1-59abcf96a1f2   False   \n",
       "167876              20  t_aa2fff77-9b0a-4fa3-a685-ecef50310e8a   False   \n",
       "167877              20  t_f673e1b7-4ebe-4fc1-ac24-a9f25de70381   False   \n",
       "167878              20  t_e172e8e7-7161-42a9-acb0-d606346c8f87   False   \n",
       "167879              20  t_77977dd6-597e-4425-8f8f-4efb32ecfba6   False   \n",
       "\n",
       "        skip_2  skip_3  not_skipped  context_switch  no_pause_before_play  \\\n",
       "0        False   False         True               0                     0   \n",
       "1        False   False         True               0                     1   \n",
       "2        False   False         True               0                     1   \n",
       "3        False   False         True               0                     1   \n",
       "4        False   False         True               0                     1   \n",
       "5        False    True        False               0                     1   \n",
       "6         True    True        False               0                     1   \n",
       "7         True    True        False               0                     1   \n",
       "8         True    True        False               0                     1   \n",
       "9         True    True        False               0                     1   \n",
       "10        True    True        False               0                     1   \n",
       "11        True    True        False               0                     1   \n",
       "12        True    True        False               0                     1   \n",
       "13       False   False         True               0                     1   \n",
       "14        True    True        False               0                     1   \n",
       "15        True    True        False               0                     0   \n",
       "16        True    True        False               0                     1   \n",
       "17        True    True        False               0                     1   \n",
       "18        True    True        False               0                     1   \n",
       "19        True    True        False               0                     1   \n",
       "20        True    True        False               0                     0   \n",
       "21        True    True        False               0                     1   \n",
       "22       False   False        False               0                     1   \n",
       "23       False   False        False               0                     1   \n",
       "24       False   False        False               0                     0   \n",
       "25        True    True        False               0                     1   \n",
       "26        True    True        False               0                     1   \n",
       "27        True    True        False               0                     1   \n",
       "28        True    True        False               0                     1   \n",
       "29        True    True        False               0                     1   \n",
       "...        ...     ...          ...             ...                   ...   \n",
       "167850   False    True        False               0                     0   \n",
       "167851    True    True        False               0                     1   \n",
       "167852    True    True        False               0                     1   \n",
       "167853    True    True        False               0                     1   \n",
       "167854    True    True        False               0                     1   \n",
       "167855    True    True        False               0                     1   \n",
       "167856   False    True        False               0                     1   \n",
       "167857    True    True        False               0                     1   \n",
       "167858    True    True        False               0                     1   \n",
       "167859    True    True        False               0                     1   \n",
       "167860   False   False         True               0                     0   \n",
       "167861   False   False         True               0                     0   \n",
       "167862   False   False         True               0                     1   \n",
       "167863   False   False         True               0                     1   \n",
       "167864   False   False         True               0                     1   \n",
       "167865   False   False         True               0                     1   \n",
       "167866   False   False         True               0                     1   \n",
       "167867   False   False         True               0                     1   \n",
       "167868   False   False         True               0                     1   \n",
       "167869   False   False         True               0                     1   \n",
       "167870   False   False         True               0                     1   \n",
       "167871   False   False         True               0                     1   \n",
       "167872    True    True        False               0                     0   \n",
       "167873   False   False         True               0                     1   \n",
       "167874   False   False         True               0                     1   \n",
       "167875   False   False         True               0                     1   \n",
       "167876   False   False         True               0                     1   \n",
       "167877   False   False         True               0                     1   \n",
       "167878   False   False         True               0                     1   \n",
       "167879   False   False         True               0                     1   \n",
       "\n",
       "        ...   hist_user_behavior_n_seekfwd  hist_user_behavior_n_seekback  \\\n",
       "0       ...                              0                              0   \n",
       "1       ...                              0                              0   \n",
       "2       ...                              0                              0   \n",
       "3       ...                              0                              0   \n",
       "4       ...                              0                              0   \n",
       "5       ...                              0                              0   \n",
       "6       ...                              0                              0   \n",
       "7       ...                              0                              0   \n",
       "8       ...                              0                              0   \n",
       "9       ...                              0                              0   \n",
       "10      ...                              0                              0   \n",
       "11      ...                              0                              0   \n",
       "12      ...                              0                              0   \n",
       "13      ...                              0                              0   \n",
       "14      ...                              0                              0   \n",
       "15      ...                              0                              0   \n",
       "16      ...                              0                              0   \n",
       "17      ...                              0                              0   \n",
       "18      ...                              0                              0   \n",
       "19      ...                              0                              0   \n",
       "20      ...                              0                              1   \n",
       "21      ...                              0                              0   \n",
       "22      ...                              0                              0   \n",
       "23      ...                              0                              0   \n",
       "24      ...                              0                              0   \n",
       "25      ...                              0                              0   \n",
       "26      ...                              0                              0   \n",
       "27      ...                              0                              0   \n",
       "28      ...                              0                              0   \n",
       "29      ...                              0                              0   \n",
       "...     ...                            ...                            ...   \n",
       "167850  ...                              0                              0   \n",
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       "167871  ...                              0                              0   \n",
       "167872  ...                              0                              0   \n",
       "167873  ...                              0                              0   \n",
       "167874  ...                              0                              0   \n",
       "167875  ...                              0                              0   \n",
       "167876  ...                              0                              0   \n",
       "167877  ...                              0                              0   \n",
       "167878  ...                              0                              0   \n",
       "167879  ...                              0                              0   \n",
       "\n",
       "        hist_user_behavior_is_shuffle  hour_of_day        date  premium  \\\n",
       "0                                True           16  2018-07-15     True   \n",
       "1                                True           16  2018-07-15     True   \n",
       "2                                True           16  2018-07-15     True   \n",
       "3                                True           16  2018-07-15     True   \n",
       "4                                True           16  2018-07-15     True   \n",
       "5                                True           16  2018-07-15     True   \n",
       "6                                True           16  2018-07-15     True   \n",
       "7                                True           16  2018-07-15     True   \n",
       "8                                True           16  2018-07-15     True   \n",
       "9                                True           16  2018-07-15     True   \n",
       "10                               True           16  2018-07-15     True   \n",
       "11                               True           16  2018-07-15     True   \n",
       "12                               True           16  2018-07-15     True   \n",
       "13                               True           16  2018-07-15     True   \n",
       "14                               True           16  2018-07-15     True   \n",
       "15                               True           16  2018-07-15     True   \n",
       "16                               True           16  2018-07-15     True   \n",
       "17                               True           16  2018-07-15     True   \n",
       "18                               True           16  2018-07-15     True   \n",
       "19                               True           16  2018-07-15     True   \n",
       "20                               True           14  2018-07-15     True   \n",
       "21                               True           14  2018-07-15     True   \n",
       "22                               True           14  2018-07-15     True   \n",
       "23                               True           14  2018-07-15     True   \n",
       "24                               True           14  2018-07-15     True   \n",
       "25                               True           14  2018-07-15     True   \n",
       "26                               True           14  2018-07-15     True   \n",
       "27                               True           14  2018-07-15     True   \n",
       "28                               True           14  2018-07-15     True   \n",
       "29                               True           14  2018-07-15     True   \n",
       "...                               ...          ...         ...      ...   \n",
       "167850                          False           20  2018-07-14     True   \n",
       "167851                          False           20  2018-07-14     True   \n",
       "167852                          False           20  2018-07-14     True   \n",
       "167853                          False           20  2018-07-14     True   \n",
       "167854                          False           20  2018-07-14     True   \n",
       "167855                          False           20  2018-07-14     True   \n",
       "167856                          False           20  2018-07-14     True   \n",
       "167857                          False           20  2018-07-14     True   \n",
       "167858                          False           20  2018-07-14     True   \n",
       "167859                          False           20  2018-07-14     True   \n",
       "167860                          False           12  2018-07-15     True   \n",
       "167861                          False           12  2018-07-15     True   \n",
       "167862                          False           12  2018-07-15     True   \n",
       "167863                          False           12  2018-07-15     True   \n",
       "167864                          False           12  2018-07-15     True   \n",
       "167865                          False           12  2018-07-15     True   \n",
       "167866                          False           12  2018-07-15     True   \n",
       "167867                          False           12  2018-07-15     True   \n",
       "167868                          False           13  2018-07-15     True   \n",
       "167869                          False           13  2018-07-15     True   \n",
       "167870                          False           13  2018-07-15     True   \n",
       "167871                          False           13  2018-07-15     True   \n",
       "167872                          False           13  2018-07-15     True   \n",
       "167873                          False           13  2018-07-15     True   \n",
       "167874                          False           13  2018-07-15     True   \n",
       "167875                          False           13  2018-07-15     True   \n",
       "167876                          False           13  2018-07-15     True   \n",
       "167877                          False           13  2018-07-15     True   \n",
       "167878                          False           13  2018-07-15     True   \n",
       "167879                          False           13  2018-07-15     True   \n",
       "\n",
       "              context_type  hist_user_behavior_reason_start  \\\n",
       "0       editorial_playlist                        trackdone   \n",
       "1       editorial_playlist                        trackdone   \n",
       "2       editorial_playlist                        trackdone   \n",
       "3       editorial_playlist                        trackdone   \n",
       "4       editorial_playlist                        trackdone   \n",
       "5       editorial_playlist                        trackdone   \n",
       "6       editorial_playlist                           fwdbtn   \n",
       "7       editorial_playlist                           fwdbtn   \n",
       "8       editorial_playlist                           fwdbtn   \n",
       "9       editorial_playlist                           fwdbtn   \n",
       "10      editorial_playlist                           fwdbtn   \n",
       "11      editorial_playlist                           fwdbtn   \n",
       "12      editorial_playlist                           fwdbtn   \n",
       "13      editorial_playlist                           fwdbtn   \n",
       "14      editorial_playlist                        trackdone   \n",
       "15      editorial_playlist                           fwdbtn   \n",
       "16      editorial_playlist                           fwdbtn   \n",
       "17      editorial_playlist                           fwdbtn   \n",
       "18      editorial_playlist                           fwdbtn   \n",
       "19      editorial_playlist                           fwdbtn   \n",
       "20         user_collection                        trackdone   \n",
       "21         user_collection                           fwdbtn   \n",
       "22         user_collection                           fwdbtn   \n",
       "23         user_collection                           fwdbtn   \n",
       "24         user_collection                           fwdbtn   \n",
       "25         user_collection                           fwdbtn   \n",
       "26         user_collection                           fwdbtn   \n",
       "27         user_collection                           fwdbtn   \n",
       "28         user_collection                           fwdbtn   \n",
       "29         user_collection                           fwdbtn   \n",
       "...                    ...                              ...   \n",
       "167850     user_collection                           fwdbtn   \n",
       "167851     user_collection                           fwdbtn   \n",
       "167852     user_collection                           fwdbtn   \n",
       "167853     user_collection                           fwdbtn   \n",
       "167854     user_collection                           fwdbtn   \n",
       "167855     user_collection                           fwdbtn   \n",
       "167856     user_collection                           fwdbtn   \n",
       "167857     user_collection                           fwdbtn   \n",
       "167858     user_collection                           fwdbtn   \n",
       "167859     user_collection                           fwdbtn   \n",
       "167860     user_collection                         clickrow   \n",
       "167861     user_collection                        trackdone   \n",
       "167862     user_collection                        trackdone   \n",
       "167863     user_collection                        trackdone   \n",
       "167864     user_collection                        trackdone   \n",
       "167865     user_collection                        trackdone   \n",
       "167866     user_collection                        trackdone   \n",
       "167867     user_collection                        trackdone   \n",
       "167868     user_collection                        trackdone   \n",
       "167869     user_collection                        trackdone   \n",
       "167870     user_collection                        trackdone   \n",
       "167871     user_collection                        trackdone   \n",
       "167872     user_collection                        trackdone   \n",
       "167873     user_collection                           fwdbtn   \n",
       "167874     user_collection                        trackdone   \n",
       "167875     user_collection                        trackdone   \n",
       "167876     user_collection                        trackdone   \n",
       "167877     user_collection                        trackdone   \n",
       "167878     user_collection                        trackdone   \n",
       "167879     user_collection                        trackdone   \n",
       "\n",
       "       hist_user_behavior_reason_end label  \n",
       "0                          trackdone     1  \n",
       "1                          trackdone     1  \n",
       "2                          trackdone     1  \n",
       "3                          trackdone     1  \n",
       "4                          trackdone     1  \n",
       "5                             fwdbtn     1  \n",
       "6                             fwdbtn     1  \n",
       "7                             fwdbtn     1  \n",
       "8                             fwdbtn     1  \n",
       "9                             fwdbtn     1  \n",
       "10                            fwdbtn     1  \n",
       "11                            fwdbtn     1  \n",
       "12                            fwdbtn     1  \n",
       "13                         trackdone     1  \n",
       "14                            fwdbtn     1  \n",
       "15                            fwdbtn     1  \n",
       "16                            fwdbtn     1  \n",
       "17                            fwdbtn     1  \n",
       "18                            fwdbtn     1  \n",
       "19                            fwdbtn     1  \n",
       "20                            fwdbtn     1  \n",
       "21                            fwdbtn     1  \n",
       "22                            fwdbtn     1  \n",
       "23                            fwdbtn     1  \n",
       "24                            fwdbtn     1  \n",
       "25                            fwdbtn     1  \n",
       "26                            fwdbtn     1  \n",
       "27                            fwdbtn     1  \n",
       "28                            fwdbtn     1  \n",
       "29                           backbtn     1  \n",
       "...                              ...   ...  \n",
       "167850                        fwdbtn     0  \n",
       "167851                        fwdbtn     0  \n",
       "167852                        fwdbtn     0  \n",
       "167853                        fwdbtn     0  \n",
       "167854                        fwdbtn     0  \n",
       "167855                        fwdbtn     0  \n",
       "167856                        fwdbtn     0  \n",
       "167857                        fwdbtn     0  \n",
       "167858                        fwdbtn     0  \n",
       "167859                        fwdbtn     0  \n",
       "167860                     trackdone     1  \n",
       "167861                     trackdone     1  \n",
       "167862                     trackdone     1  \n",
       "167863                     trackdone     1  \n",
       "167864                     trackdone     1  \n",
       "167865                     trackdone     1  \n",
       "167866                     trackdone     1  \n",
       "167867                     trackdone     1  \n",
       "167868                     trackdone     1  \n",
       "167869                     trackdone     1  \n",
       "167870                     trackdone     1  \n",
       "167871                     trackdone     1  \n",
       "167872                        fwdbtn     0  \n",
       "167873                     trackdone     1  \n",
       "167874                     trackdone     1  \n",
       "167875                     trackdone     1  \n",
       "167876                     trackdone     1  \n",
       "167877                     trackdone     1  \n",
       "167878                     trackdone     1  \n",
       "167879                     trackdone     1  \n",
       "\n",
       "[167880 rows x 22 columns]"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#import matplotlib.pyplot as plt\n",
    "#plt.hist(df['label'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "label = df[['label']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ted\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1ee3b13b3c8>"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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IKGP+XeCjVfUYQFU9Os81zrZRxlzAIW35UCZ5n9RCUlVfBnbsocsa4MoauAU4LMlLZrOG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\nkjqGgySp83+M8N0sOirIMAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "sns.distplot(df['label'],bins = 5,kde = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "167880"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50704"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tf_mini)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_1 = df.head(50704)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50704"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ted\\Anaconda3\\lib\\site-packages\\pandas\\core\\frame.py:2746: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  **kwargs)\n"
     ]
    }
   ],
   "source": [
    "df_1.rename(columns = {'track_id_clean':'track_id'}, inplace = True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               session_id  session_position  session_length  \\\n",
       "0  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 1              20   \n",
       "1  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 2              20   \n",
       "2  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 3              20   \n",
       "3  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 4              20   \n",
       "4  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 5              20   \n",
       "\n",
       "                                 track_id  skip_1  skip_2  skip_3  \\\n",
       "0  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   False   \n",
       "1  t_9099cd7b-c238-47b7-9381-f23f2c1d1043   False   False   False   \n",
       "2  t_fc5df5ba-5396-49a7-8b29-35d0d28249e0   False   False   False   \n",
       "3  t_23cff8d6-d874-4b20-83dc-94e450e8aa20   False   False   False   \n",
       "4  t_64f3743c-f624-46bb-a579-0f3f9a07a123   False   False   False   \n",
       "\n",
       "   not_skipped  context_switch  no_pause_before_play  ...   \\\n",
       "0         True               0                     0  ...    \n",
       "1         True               0                     1  ...    \n",
       "2         True               0                     1  ...    \n",
       "3         True               0                     1  ...    \n",
       "4         True               0                     1  ...    \n",
       "\n",
       "   hist_user_behavior_n_seekfwd  hist_user_behavior_n_seekback  \\\n",
       "0                             0                              0   \n",
       "1                             0                              0   \n",
       "2                             0                              0   \n",
       "3                             0                              0   \n",
       "4                             0                              0   \n",
       "\n",
       "   hist_user_behavior_is_shuffle  hour_of_day        date  premium  \\\n",
       "0                           True           16  2018-07-15     True   \n",
       "1                           True           16  2018-07-15     True   \n",
       "2                           True           16  2018-07-15     True   \n",
       "3                           True           16  2018-07-15     True   \n",
       "4                           True           16  2018-07-15     True   \n",
       "\n",
       "         context_type  hist_user_behavior_reason_start  \\\n",
       "0  editorial_playlist                        trackdone   \n",
       "1  editorial_playlist                        trackdone   \n",
       "2  editorial_playlist                        trackdone   \n",
       "3  editorial_playlist                        trackdone   \n",
       "4  editorial_playlist                        trackdone   \n",
       "\n",
       "  hist_user_behavior_reason_end label  \n",
       "0                     trackdone     1  \n",
       "1                     trackdone     1  \n",
       "2                     trackdone     1  \n",
       "3                     trackdone     1  \n",
       "4                     trackdone     1  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#### merging Both Dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_merge_col_1 = pd.merge(df_1, tf_mini, on='track_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "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>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>no_pause_before_play</th>\n",
       "      <th>...</th>\n",
       "      <th>time_signature</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\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>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",
       "      <td>0.015452</td>\n",
       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\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>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",
       "      <td>0.015452</td>\n",
       "      <td>-0.35359</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 51 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               session_id  session_position  session_length  \\\n",
       "0  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 1              20   \n",
       "1  0_00079a23-1600-486a-91bd-5208be0c745a                 7              12   \n",
       "\n",
       "                                 track_id  skip_1  skip_2  skip_3  \\\n",
       "0  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   False   \n",
       "1  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False    True   \n",
       "\n",
       "   not_skipped  context_switch  no_pause_before_play        ...         \\\n",
       "0         True               0                     0        ...          \n",
       "1        False               0                     0        ...          \n",
       "\n",
       "   time_signature   valence  acoustic_vector_0  acoustic_vector_1  \\\n",
       "0               4  0.152255          -0.815775           0.386409   \n",
       "1               4  0.152255          -0.815775           0.386409   \n",
       "\n",
       "   acoustic_vector_2  acoustic_vector_3 acoustic_vector_4  acoustic_vector_5  \\\n",
       "0            0.23016           0.028028         -0.333373           0.015452   \n",
       "1            0.23016           0.028028         -0.333373           0.015452   \n",
       "\n",
       "  acoustic_vector_6 acoustic_vector_7  \n",
       "0          -0.35359          0.205826  \n",
       "1          -0.35359          0.205826  \n",
       "\n",
       "[2 rows x 51 columns]"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merge_col_1.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50704"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_merge_col_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#### Merging both Dataframes before cutting short"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df2 = df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df2.rename(columns = {'track_id_clean':'track_id'}, inplace = True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_merge_col_2 = pd.merge(df2, tf_mini, on='track_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "167880"
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_merge_col_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_merge_col_2 = df_merge_col_2.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "167880"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_merge_col_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['session_id', 'session_position', 'session_length', 'track_id',\n",
       "       'skip_1', 'skip_2', 'skip_3', 'not_skipped', 'context_switch',\n",
       "       '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": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merge_col_2.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dat = df_merge_col_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1ee3b10f550>"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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amJmZmZmZmZnV4J4mlk1EPAw8XF0u6Wmgb1XxMRExcxU0y8zMzMzMzKxTnDSxlS4ids0R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\n1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vxv4LnAR4GPVNWPkuwKXAA8AXgH8L2qemWSrYDLk3wHeBmwG7BvVS1NsnXffu+sqv2S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7E4PMui0MzwBulXQNw/VRpnpy4QwiaX42DUkINBB/t133e2xCkFrWDiPuIyaSip92tMU0Ef0Q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\nkiRJkjQPmyaSJEmSJEnz+H9DrafVvFVUQAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1296x1008 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.figure(figsize=(18, 14))\n",
    "sns.heatmap(dat.corr())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "features = dat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "#features = features.drop('label', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['session_id', 'session_position', 'session_length', 'track_id',\n",
       "       'skip_1', 'skip_2', 'skip_3', 'not_skipped', 'context_switch',\n",
       "       '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": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ff1 = features[['not_skipped','hist_user_behavior_is_shuffle']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y = dat[['label']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [],
   "source": [
    "from patsy import dmatrices\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.stats.outliers_influence import variance_inflation_factor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 167880 entries, 0 to 167879\n",
      "Data columns (total 51 columns):\n",
      "session_id                         167880 non-null object\n",
      "session_position                   167880 non-null int64\n",
      "session_length                     167880 non-null int64\n",
      "track_id                           167880 non-null object\n",
      "skip_1                             167880 non-null bool\n",
      "skip_2                             167880 non-null bool\n",
      "skip_3                             167880 non-null bool\n",
      "not_skipped                        167880 non-null bool\n",
      "context_switch                     167880 non-null int64\n",
      "no_pause_before_play               167880 non-null int64\n",
      "short_pause_before_play            167880 non-null int64\n",
      "long_pause_before_play             167880 non-null int64\n",
      "hist_user_behavior_n_seekfwd       167880 non-null int64\n",
      "hist_user_behavior_n_seekback      167880 non-null int64\n",
      "hist_user_behavior_is_shuffle      167880 non-null bool\n",
      "hour_of_day                        167880 non-null int64\n",
      "date                               167880 non-null object\n",
      "premium                            167880 non-null bool\n",
      "context_type                       167880 non-null object\n",
      "hist_user_behavior_reason_start    167880 non-null object\n",
      "hist_user_behavior_reason_end      167880 non-null object\n",
      "label                              167880 non-null int32\n",
      "duration                           167880 non-null float64\n",
      "release_year                       167880 non-null int64\n",
      "us_popularity_estimate             167880 non-null float64\n",
      "acousticness                       167880 non-null float64\n",
      "beat_strength                      167880 non-null float64\n",
      "bounciness                         167880 non-null float64\n",
      "danceability                       167880 non-null float64\n",
      "dyn_range_mean                     167880 non-null float64\n",
      "energy                             167880 non-null float64\n",
      "flatness                           167880 non-null float64\n",
      "instrumentalness                   167880 non-null float64\n",
      "key                                167880 non-null int64\n",
      "liveness                           167880 non-null float64\n",
      "loudness                           167880 non-null float64\n",
      "mechanism                          167880 non-null float64\n",
      "mode                               167880 non-null object\n",
      "organism                           167880 non-null float64\n",
      "speechiness                        167880 non-null float64\n",
      "tempo                              167880 non-null float64\n",
      "time_signature                     167880 non-null int64\n",
      "valence                            167880 non-null float64\n",
      "acoustic_vector_0                  167880 non-null float64\n",
      "acoustic_vector_1                  167880 non-null float64\n",
      "acoustic_vector_2                  167880 non-null float64\n",
      "acoustic_vector_3                  167880 non-null float64\n",
      "acoustic_vector_4                  167880 non-null float64\n",
      "acoustic_vector_5                  167880 non-null float64\n",
      "acoustic_vector_6                  167880 non-null float64\n",
      "acoustic_vector_7                  167880 non-null float64\n",
      "dtypes: bool(6), float64(25), int32(1), int64(12), object(7)\n",
      "memory usage: 59.2+ MB\n"
     ]
    }
   ],
   "source": [
    "features.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1ee2f281eb8>"
      ]
     },
     "execution_count": 190,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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amJmZmZmZmZnV4J4mlk1EPAw8XF0u6Wmgb1XxMRExcxU0y8zMzMzMzKxTnDSxlS4ids0R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\n1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vxv4LnAR4GPVNWPkuwKXAA8AXgH8L2qemWSrYDLk3wHeBmwG7BvVS1NsnXffu+sqv2S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7E4PMui0MzwBulXQNw/VRpnpy4QwiaX42DUkINBB/t133e2xCkFrWDiPuIyaSip92tMU0Ef0Q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\nkiRJkjQPmyaSJEmSJEnz+H9DrafVvFVUQAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1296x1008 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18, 14))\n",
    "sns.heatmap(features.corr())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "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>not_skipped</th>\n",
       "      <th>hist_user_behavior_is_shuffle</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   not_skipped  hist_user_behavior_is_shuffle\n",
       "0         True                           True\n",
       "1        False                          False\n",
       "2         True                          False\n",
       "3         True                          False\n",
       "4        False                           True"
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ff1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(167880, 2)"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ff1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ff1 = ff1.values\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "le = LabelEncoder()\n",
    "ff1[1] = le.fit_transform(ff1[1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ff1 = pd.DataFrame(ff1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(167880, 2)"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ff1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ff1 = ff1.transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "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>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   label\n",
       "0      1\n",
       "1      0\n",
       "2      1\n",
       "3      1\n",
       "4      1"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y = y.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   0  1\n",
       "0  0  0\n",
       "1  0  0\n",
       "2  1  0\n",
       "3  1  0\n",
       "4  0  1"
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ff1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ff1 = ff1.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 0],\n",
       "       [0, 0],\n",
       "       [1, 0],\n",
       "       ...,\n",
       "       [1, 1],\n",
       "       [0, 1],\n",
       "       [0, 1]], dtype=int64)"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ff1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cross_validation import train_test_split\n",
    "x_train,x_test,y_train,y_test=train_test_split(ff1,y,test_size=1/4,random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "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"
     ]
    },
    {
     "data": {
      "text/plain": [
       "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
       "          intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
       "          penalty='l2', random_state=None, solver='liblinear', tol=0.0001,\n",
       "          verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 213,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "logreg = LogisticRegression()\n",
    "logreg.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_pred=logreg.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 0, ..., 1, 0, 0])"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[19131,  2918],\n",
       "       [    1, 19920]], dtype=int64)"
      ]
     },
     "execution_count": 216,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "cnf_matrix = metrics.confusion_matrix(y_test, y_pred)\n",
    "cnf_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9304503216583274\n",
      "Precision: 0.8722304930379192\n",
      "Recall: 0.9999498017167813\n"
     ]
    }
   ],
   "source": [
    "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",
    "print(\"Accuracy:\",metrics.accuracy_score(y_test, y_pred))\n",
    "print(\"Precision:\",metrics.precision_score(y_test, y_pred))\n",
    "print(\"Recall:\",metrics.recall_score(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></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",
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       "      <th>not_skipped</th>\n",
       "      <th>context_switch</th>\n",
       "      <th>no_pause_before_play</th>\n",
       "      <th>...</th>\n",
       "      <th>time_signature</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>7</td>\n",
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       "      <td>False</td>\n",
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       "      <td>0.230160</td>\n",
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       "      <td>0.015452</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>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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
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       "      <td>-0.353590</td>\n",
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       "      <th>3</th>\n",
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       "      <td>9</td>\n",
       "      <td>13</td>\n",
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       "      <td>0.386409</td>\n",
       "      <td>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\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>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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0_01f86af2-cf48-42a6-9bf8-adb91f072909</td>\n",
       "      <td>7</td>\n",
       "      <td>20</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0_02340c3b-c370-4c98-b759-87be85e11aa3</td>\n",
       "      <td>8</td>\n",
       "      <td>20</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0_02a8ebbd-5a12-4343-a7da-2ea912102f90</td>\n",
       "      <td>2</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>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0_032c39c8-3a11-4f90-a3c5-38461b4d365d</td>\n",
       "      <td>13</td>\n",
       "      <td>19</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0_03373b7c-3c30-4bac-a909-1a4ecc310797</td>\n",
       "      <td>5</td>\n",
       "      <td>19</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0_04452794-0084-4712-9808-1845d338c8b9</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0_04ab5699-1f6a-40ef-b8a6-9ebad09e85f6</td>\n",
       "      <td>16</td>\n",
       "      <td>20</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>1</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0_05219b57-68f2-4eac-a139-85cef6f3809b</td>\n",
       "      <td>14</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>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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0_05b0cc6b-6615-44bd-ba6d-d6737cd5324a</td>\n",
       "      <td>16</td>\n",
       "      <td>20</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>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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0_05de15dc-d2a9-43aa-b00e-e7298df02293</td>\n",
       "      <td>9</td>\n",
       "      <td>15</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>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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0_0677eaaf-e4bf-4418-9cc0-55e596171a6a</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0_069bb1f2-5fc7-4ab0-9d5f-3d915dbc3ad3</td>\n",
       "      <td>4</td>\n",
       "      <td>16</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>1</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0_06a28c80-2dca-434d-8404-3a86f77a0a10</td>\n",
       "      <td>8</td>\n",
       "      <td>20</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>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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0_0792cde4-90a0-45e9-bf9e-b4f78114f1bf</td>\n",
       "      <td>19</td>\n",
       "      <td>20</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0_07ac84c3-df8b-465a-8687-926376ef1dc2</td>\n",
       "      <td>6</td>\n",
       "      <td>10</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>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0_07ba5d63-0d11-472e-804e-ebdd584e21a1</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0_07ba5d63-0d11-472e-804e-ebdd584e21a1</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0_083f4637-5ab2-46b4-a587-e5f6d17361ed</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0_083f4637-5ab2-46b4-a587-e5f6d17361ed</td>\n",
       "      <td>2</td>\n",
       "      <td>15</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>1</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0_0868aba4-fa29-4a4b-9a8b-19af02be48c3</td>\n",
       "      <td>13</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>1</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0_08748019-88a3-4fb6-91c7-4a4acc30619d</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0_08766f3c-2c0f-447e-b864-358427c870de</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0_089a63ed-e193-4a67-ae5d-558589df70ae</td>\n",
       "      <td>8</td>\n",
       "      <td>17</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>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0_08e4428d-daf9-454f-948b-3443504575c2</td>\n",
       "      <td>10</td>\n",
       "      <td>20</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>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0_0953e151-1282-483d-ae79-11aded89caa8</td>\n",
       "      <td>5</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>1</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>0.230160</td>\n",
       "      <td>0.028028</td>\n",
       "      <td>-0.333373</td>\n",
       "      <td>0.015452</td>\n",
       "      <td>-0.353590</td>\n",
       "      <td>0.205826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167850</th>\n",
       "      <td>0_0eab7430-d291-4d57-9c92-ac7cb682f2c6</td>\n",
       "      <td>7</td>\n",
       "      <td>20</td>\n",
       "      <td>t_3a00192e-0b70-4c93-b21f-57db215e468d</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.625544</td>\n",
       "      <td>-0.281968</td>\n",
       "      <td>0.037951</td>\n",
       "      <td>-0.239047</td>\n",
       "      <td>0.238496</td>\n",
       "      <td>-0.102690</td>\n",
       "      <td>-0.486494</td>\n",
       "      <td>-0.224573</td>\n",
       "      <td>-0.431867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167851</th>\n",
       "      <td>0_0eab7430-d291-4d57-9c92-ac7cb682f2c6</td>\n",
       "      <td>9</td>\n",
       "      <td>20</td>\n",
       "      <td>t_b56157c4-ed95-433b-a0ce-457ef4e4c110</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.162715</td>\n",
       "      <td>-0.286236</td>\n",
       "      <td>0.014840</td>\n",
       "      <td>-0.223812</td>\n",
       "      <td>0.254035</td>\n",
       "      <td>-0.095313</td>\n",
       "      <td>-0.534176</td>\n",
       "      <td>-0.227929</td>\n",
       "      <td>-0.495369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167852</th>\n",
       "      <td>0_0eab7430-d291-4d57-9c92-ac7cb682f2c6</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>t_43ab18f3-fbc0-4e45-8673-0c7eb4488414</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.189097</td>\n",
       "      <td>-0.307814</td>\n",
       "      <td>-0.017920</td>\n",
       "      <td>-0.211223</td>\n",
       "      <td>0.288907</td>\n",
       "      <td>-0.179076</td>\n",
       "      <td>-0.546285</td>\n",
       "      <td>-0.290156</td>\n",
       "      <td>-0.464621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167853</th>\n",
       "      <td>0_0eab7430-d291-4d57-9c92-ac7cb682f2c6</td>\n",
       "      <td>11</td>\n",
       "      <td>20</td>\n",
       "      <td>t_23034a69-b95e-46e8-977a-7de554561170</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.384743</td>\n",
       "      <td>-0.287573</td>\n",
       "      <td>0.038921</td>\n",
       "      <td>-0.278049</td>\n",
       "      <td>0.216598</td>\n",
       "      <td>-0.138562</td>\n",
       "      <td>-0.535953</td>\n",
       "      <td>-0.296982</td>\n",
       "      <td>-0.412306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167854</th>\n",
       "      <td>0_0eab7430-d291-4d57-9c92-ac7cb682f2c6</td>\n",
       "      <td>12</td>\n",
       "      <td>20</td>\n",
       "      <td>t_63a6819c-47cb-4416-bf7d-eb7c9391df9a</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.049998</td>\n",
       "      <td>-0.200057</td>\n",
       "      <td>0.025851</td>\n",
       "      <td>-0.162609</td>\n",
       "      <td>0.239263</td>\n",
       "      <td>-0.206402</td>\n",
       "      <td>-0.500973</td>\n",
       "      <td>-0.117964</td>\n",
       "      <td>-0.507854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167855</th>\n",
       "      <td>0_0eab7430-d291-4d57-9c92-ac7cb682f2c6</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>t_8095d037-3c67-4f39-a077-55794da35095</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>0.249501</td>\n",
       "      <td>-0.220669</td>\n",
       "      <td>-0.004662</td>\n",
       "      <td>-0.322330</td>\n",
       "      <td>0.254388</td>\n",
       "      <td>-0.116826</td>\n",
       "      <td>-0.579517</td>\n",
       "      <td>-0.198343</td>\n",
       "      <td>-0.459952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167856</th>\n",
       "      <td>0_0eab7430-d291-4d57-9c92-ac7cb682f2c6</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>t_8095d037-3c67-4f39-a077-55794da35095</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>0.249501</td>\n",
       "      <td>-0.220669</td>\n",
       "      <td>-0.004662</td>\n",
       "      <td>-0.322330</td>\n",
       "      <td>0.254388</td>\n",
       "      <td>-0.116826</td>\n",
       "      <td>-0.579517</td>\n",
       "      <td>-0.198343</td>\n",
       "      <td>-0.459952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167857</th>\n",
       "      <td>0_0eab7430-d291-4d57-9c92-ac7cb682f2c6</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>t_7b70f495-d688-41a5-8647-aeedd6ee33ef</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>0.345805</td>\n",
       "      <td>-0.326657</td>\n",
       "      <td>0.044544</td>\n",
       "      <td>-0.185697</td>\n",
       "      <td>0.252924</td>\n",
       "      <td>-0.096228</td>\n",
       "      <td>-0.468579</td>\n",
       "      <td>-0.234028</td>\n",
       "      <td>-0.458663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167858</th>\n",
       "      <td>0_0eabeb73-eb50-412c-80dc-dfc832581563</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>t_ff15dbcb-b7c9-4eb0-beeb-eb443cfc3403</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0.312961</td>\n",
       "      <td>-0.076285</td>\n",
       "      <td>-0.543137</td>\n",
       "      <td>0.134288</td>\n",
       "      <td>0.636808</td>\n",
       "      <td>0.618381</td>\n",
       "      <td>-0.333008</td>\n",
       "      <td>-0.111789</td>\n",
       "      <td>-0.758606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167859</th>\n",
       "      <td>0_0eabeb73-eb50-412c-80dc-dfc832581563</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>t_ff15dbcb-b7c9-4eb0-beeb-eb443cfc3403</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0.312961</td>\n",
       "      <td>-0.076285</td>\n",
       "      <td>-0.543137</td>\n",
       "      <td>0.134288</td>\n",
       "      <td>0.636808</td>\n",
       "      <td>0.618381</td>\n",
       "      <td>-0.333008</td>\n",
       "      <td>-0.111789</td>\n",
       "      <td>-0.758606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167860</th>\n",
       "      <td>0_0eabeb73-eb50-412c-80dc-dfc832581563</td>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "      <td>t_ff15dbcb-b7c9-4eb0-beeb-eb443cfc3403</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0.312961</td>\n",
       "      <td>-0.076285</td>\n",
       "      <td>-0.543137</td>\n",
       "      <td>0.134288</td>\n",
       "      <td>0.636808</td>\n",
       "      <td>0.618381</td>\n",
       "      <td>-0.333008</td>\n",
       "      <td>-0.111789</td>\n",
       "      <td>-0.758606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167861</th>\n",
       "      <td>0_0eabeb73-eb50-412c-80dc-dfc832581563</td>\n",
       "      <td>8</td>\n",
       "      <td>14</td>\n",
       "      <td>t_ff15dbcb-b7c9-4eb0-beeb-eb443cfc3403</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0.312961</td>\n",
       "      <td>-0.076285</td>\n",
       "      <td>-0.543137</td>\n",
       "      <td>0.134288</td>\n",
       "      <td>0.636808</td>\n",
       "      <td>0.618381</td>\n",
       "      <td>-0.333008</td>\n",
       "      <td>-0.111789</td>\n",
       "      <td>-0.758606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167862</th>\n",
       "      <td>0_0eabeb73-eb50-412c-80dc-dfc832581563</td>\n",
       "      <td>12</td>\n",
       "      <td>14</td>\n",
       "      <td>t_ff15dbcb-b7c9-4eb0-beeb-eb443cfc3403</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0.312961</td>\n",
       "      <td>-0.076285</td>\n",
       "      <td>-0.543137</td>\n",
       "      <td>0.134288</td>\n",
       "      <td>0.636808</td>\n",
       "      <td>0.618381</td>\n",
       "      <td>-0.333008</td>\n",
       "      <td>-0.111789</td>\n",
       "      <td>-0.758606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167863</th>\n",
       "      <td>0_0eabeb73-eb50-412c-80dc-dfc832581563</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>t_ff15dbcb-b7c9-4eb0-beeb-eb443cfc3403</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0.312961</td>\n",
       "      <td>-0.076285</td>\n",
       "      <td>-0.543137</td>\n",
       "      <td>0.134288</td>\n",
       "      <td>0.636808</td>\n",
       "      <td>0.618381</td>\n",
       "      <td>-0.333008</td>\n",
       "      <td>-0.111789</td>\n",
       "      <td>-0.758606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167864</th>\n",
       "      <td>0_0eabeb73-eb50-412c-80dc-dfc832581563</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>t_d0b94483-2e1f-4b76-ab74-7d2d749dfa94</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.749148</td>\n",
       "      <td>-0.904019</td>\n",
       "      <td>0.226712</td>\n",
       "      <td>0.413872</td>\n",
       "      <td>0.441320</td>\n",
       "      <td>0.037881</td>\n",
       "      <td>0.097167</td>\n",
       "      <td>0.141576</td>\n",
       "      <td>0.271749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167865</th>\n",
       "      <td>0_0eac164c-f209-4590-8608-a56e67658952</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>t_6e0c5849-c376-4fb2-a706-ff3073e85a15</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.268244</td>\n",
       "      <td>-0.446560</td>\n",
       "      <td>0.446865</td>\n",
       "      <td>0.347977</td>\n",
       "      <td>-0.259426</td>\n",
       "      <td>-0.478007</td>\n",
       "      <td>0.197709</td>\n",
       "      <td>-0.155761</td>\n",
       "      <td>0.190814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167866</th>\n",
       "      <td>0_0eac164c-f209-4590-8608-a56e67658952</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>t_67e82cb9-0c1e-487a-bc2c-6b455b1d6190</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.358613</td>\n",
       "      <td>-0.805200</td>\n",
       "      <td>0.278679</td>\n",
       "      <td>0.217043</td>\n",
       "      <td>0.098510</td>\n",
       "      <td>-0.287822</td>\n",
       "      <td>-0.021297</td>\n",
       "      <td>-0.505806</td>\n",
       "      <td>0.108890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167867</th>\n",
       "      <td>0_0eac164c-f209-4590-8608-a56e67658952</td>\n",
       "      <td>8</td>\n",
       "      <td>20</td>\n",
       "      <td>t_03c2f852-5293-4e96-9234-8240f884c403</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.083944</td>\n",
       "      <td>-0.161051</td>\n",
       "      <td>-0.005678</td>\n",
       "      <td>0.072186</td>\n",
       "      <td>-0.042731</td>\n",
       "      <td>-0.576186</td>\n",
       "      <td>0.122020</td>\n",
       "      <td>-0.004586</td>\n",
       "      <td>0.690514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167868</th>\n",
       "      <td>0_0eac164c-f209-4590-8608-a56e67658952</td>\n",
       "      <td>9</td>\n",
       "      <td>20</td>\n",
       "      <td>t_33ef80a6-e00e-4edc-96f7-e7f72363428a</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.423568</td>\n",
       "      <td>-0.158492</td>\n",
       "      <td>0.006921</td>\n",
       "      <td>0.395930</td>\n",
       "      <td>0.159193</td>\n",
       "      <td>-0.183987</td>\n",
       "      <td>-0.126784</td>\n",
       "      <td>-0.030806</td>\n",
       "      <td>-0.469252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167869</th>\n",
       "      <td>0_0eac164c-f209-4590-8608-a56e67658952</td>\n",
       "      <td>12</td>\n",
       "      <td>20</td>\n",
       "      <td>t_987480f8-a048-4c5e-aac3-0bcad5290731</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.310271</td>\n",
       "      <td>-0.038612</td>\n",
       "      <td>0.650589</td>\n",
       "      <td>-0.072997</td>\n",
       "      <td>-0.528393</td>\n",
       "      <td>-0.009909</td>\n",
       "      <td>0.178357</td>\n",
       "      <td>-0.185356</td>\n",
       "      <td>0.364100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167870</th>\n",
       "      <td>0_0eac164c-f209-4590-8608-a56e67658952</td>\n",
       "      <td>14</td>\n",
       "      <td>20</td>\n",
       "      <td>t_1e86bfc8-4204-4645-8b00-7722efca192a</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.185627</td>\n",
       "      <td>-0.385327</td>\n",
       "      <td>0.252581</td>\n",
       "      <td>0.197736</td>\n",
       "      <td>-0.094862</td>\n",
       "      <td>-0.501758</td>\n",
       "      <td>0.166349</td>\n",
       "      <td>-0.030234</td>\n",
       "      <td>0.537973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167871</th>\n",
       "      <td>0_0eac164c-f209-4590-8608-a56e67658952</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>t_3f587cf3-f197-4353-90f8-30fd80ee4069</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.346405</td>\n",
       "      <td>0.190880</td>\n",
       "      <td>-0.431414</td>\n",
       "      <td>0.054029</td>\n",
       "      <td>0.153106</td>\n",
       "      <td>-0.212964</td>\n",
       "      <td>0.009224</td>\n",
       "      <td>-0.180716</td>\n",
       "      <td>0.235676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167872</th>\n",
       "      <td>0_0eac164c-f209-4590-8608-a56e67658952</td>\n",
       "      <td>18</td>\n",
       "      <td>20</td>\n",
       "      <td>t_19a1fed1-2040-4a88-8d06-ab4bb9373ec1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.601404</td>\n",
       "      <td>-0.896841</td>\n",
       "      <td>0.286329</td>\n",
       "      <td>0.195760</td>\n",
       "      <td>0.149982</td>\n",
       "      <td>-0.342862</td>\n",
       "      <td>-0.085681</td>\n",
       "      <td>-0.551803</td>\n",
       "      <td>0.171962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167873</th>\n",
       "      <td>0_0eac164c-f209-4590-8608-a56e67658952</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>t_1539cd4a-e7ab-4e75-b1da-65a979b2de88</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.292506</td>\n",
       "      <td>-0.201742</td>\n",
       "      <td>0.269581</td>\n",
       "      <td>0.287458</td>\n",
       "      <td>-0.312325</td>\n",
       "      <td>-0.637581</td>\n",
       "      <td>0.304690</td>\n",
       "      <td>0.168871</td>\n",
       "      <td>0.635113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167874</th>\n",
       "      <td>0_0eacbee7-9868-48a0-9ab0-f86069329f50</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>t_2990bc55-5ae8-411c-93ac-b386d12b8c2a</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.250441</td>\n",
       "      <td>-0.863488</td>\n",
       "      <td>0.287187</td>\n",
       "      <td>0.271733</td>\n",
       "      <td>0.168048</td>\n",
       "      <td>-0.269257</td>\n",
       "      <td>-0.026314</td>\n",
       "      <td>-0.483045</td>\n",
       "      <td>0.148550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167875</th>\n",
       "      <td>0_0ead11fc-f32c-4eb4-8fc1-15b51432a404</td>\n",
       "      <td>8</td>\n",
       "      <td>20</td>\n",
       "      <td>t_c6d511e7-d986-4614-b694-ace9df48a665</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.599401</td>\n",
       "      <td>-0.842907</td>\n",
       "      <td>0.325243</td>\n",
       "      <td>0.207480</td>\n",
       "      <td>0.064804</td>\n",
       "      <td>-0.258140</td>\n",
       "      <td>-0.001348</td>\n",
       "      <td>-0.548543</td>\n",
       "      <td>0.176667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167876</th>\n",
       "      <td>0_0ead11fc-f32c-4eb4-8fc1-15b51432a404</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>t_44a3360f-a06d-458a-91fc-4d9efa506697</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.322569</td>\n",
       "      <td>-0.922512</td>\n",
       "      <td>0.331971</td>\n",
       "      <td>0.218592</td>\n",
       "      <td>0.093307</td>\n",
       "      <td>-0.309999</td>\n",
       "      <td>-0.004573</td>\n",
       "      <td>-0.549420</td>\n",
       "      <td>0.219733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167877</th>\n",
       "      <td>0_0ead11fc-f32c-4eb4-8fc1-15b51432a404</td>\n",
       "      <td>16</td>\n",
       "      <td>20</td>\n",
       "      <td>t_3f71a175-f7ca-4cd4-829d-65fc82b09486</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.443760</td>\n",
       "      <td>-0.771976</td>\n",
       "      <td>0.383800</td>\n",
       "      <td>0.367541</td>\n",
       "      <td>0.026499</td>\n",
       "      <td>-0.370684</td>\n",
       "      <td>0.083014</td>\n",
       "      <td>-0.334056</td>\n",
       "      <td>0.097527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167878</th>\n",
       "      <td>0_0ead11fc-f32c-4eb4-8fc1-15b51432a404</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>t_ac792fc0-a591-4c0f-a03c-652a97a864d2</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.416596</td>\n",
       "      <td>-0.978526</td>\n",
       "      <td>0.346568</td>\n",
       "      <td>0.250859</td>\n",
       "      <td>0.163195</td>\n",
       "      <td>-0.274763</td>\n",
       "      <td>-0.047336</td>\n",
       "      <td>-0.546883</td>\n",
       "      <td>0.142521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167879</th>\n",
       "      <td>0_0ead11fc-f32c-4eb4-8fc1-15b51432a404</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>t_76cb529c-86e9-41e2-a136-f5bd97481a9a</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.583041</td>\n",
       "      <td>-0.883477</td>\n",
       "      <td>0.275426</td>\n",
       "      <td>0.203538</td>\n",
       "      <td>0.146071</td>\n",
       "      <td>-0.287761</td>\n",
       "      <td>-0.047060</td>\n",
       "      <td>-0.573223</td>\n",
       "      <td>0.141425</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>167880 rows × 51 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    session_id  session_position  \\\n",
       "0       0_00006f66-33e5-4de7-a324-2d18e439fc1e                 1   \n",
       "1       0_00079a23-1600-486a-91bd-5208be0c745a                 7   \n",
       "2       0_012b0fb4-0cc3-429f-9a78-cc6e622153fb                 6   \n",
       "3       0_013cc010-c476-4ad2-8972-73449e0b2ef4                 9   \n",
       "4       0_01a5f0dc-9938-48c9-92f1-c7e51f34d290                 7   \n",
       "5       0_01f86af2-cf48-42a6-9bf8-adb91f072909                 7   \n",
       "6       0_02340c3b-c370-4c98-b759-87be85e11aa3                 8   \n",
       "7       0_02a8ebbd-5a12-4343-a7da-2ea912102f90                 2   \n",
       "8       0_032c39c8-3a11-4f90-a3c5-38461b4d365d                13   \n",
       "9       0_03373b7c-3c30-4bac-a909-1a4ecc310797                 5   \n",
       "10      0_04452794-0084-4712-9808-1845d338c8b9                 5   \n",
       "11      0_04ab5699-1f6a-40ef-b8a6-9ebad09e85f6                16   \n",
       "12      0_05219b57-68f2-4eac-a139-85cef6f3809b                14   \n",
       "13      0_05b0cc6b-6615-44bd-ba6d-d6737cd5324a                16   \n",
       "14      0_05de15dc-d2a9-43aa-b00e-e7298df02293                 9   \n",
       "15      0_0677eaaf-e4bf-4418-9cc0-55e596171a6a                 2   \n",
       "16      0_069bb1f2-5fc7-4ab0-9d5f-3d915dbc3ad3                 4   \n",
       "17      0_06a28c80-2dca-434d-8404-3a86f77a0a10                 8   \n",
       "18      0_0792cde4-90a0-45e9-bf9e-b4f78114f1bf                19   \n",
       "19      0_07ac84c3-df8b-465a-8687-926376ef1dc2                 6   \n",
       "20      0_07ba5d63-0d11-472e-804e-ebdd584e21a1                 3   \n",
       "21      0_07ba5d63-0d11-472e-804e-ebdd584e21a1                 5   \n",
       "22      0_083f4637-5ab2-46b4-a587-e5f6d17361ed                 1   \n",
       "23      0_083f4637-5ab2-46b4-a587-e5f6d17361ed                 2   \n",
       "24      0_0868aba4-fa29-4a4b-9a8b-19af02be48c3                13   \n",
       "25      0_08748019-88a3-4fb6-91c7-4a4acc30619d                 2   \n",
       "26      0_08766f3c-2c0f-447e-b864-358427c870de                13   \n",
       "27      0_089a63ed-e193-4a67-ae5d-558589df70ae                 8   \n",
       "28      0_08e4428d-daf9-454f-948b-3443504575c2                10   \n",
       "29      0_0953e151-1282-483d-ae79-11aded89caa8                 5   \n",
       "...                                        ...               ...   \n",
       "167850  0_0eab7430-d291-4d57-9c92-ac7cb682f2c6                 7   \n",
       "167851  0_0eab7430-d291-4d57-9c92-ac7cb682f2c6                 9   \n",
       "167852  0_0eab7430-d291-4d57-9c92-ac7cb682f2c6                10   \n",
       "167853  0_0eab7430-d291-4d57-9c92-ac7cb682f2c6                11   \n",
       "167854  0_0eab7430-d291-4d57-9c92-ac7cb682f2c6                12   \n",
       "167855  0_0eab7430-d291-4d57-9c92-ac7cb682f2c6                15   \n",
       "167856  0_0eab7430-d291-4d57-9c92-ac7cb682f2c6                17   \n",
       "167857  0_0eab7430-d291-4d57-9c92-ac7cb682f2c6                20   \n",
       "167858  0_0eabeb73-eb50-412c-80dc-dfc832581563                 2   \n",
       "167859  0_0eabeb73-eb50-412c-80dc-dfc832581563                 4   \n",
       "167860  0_0eabeb73-eb50-412c-80dc-dfc832581563                 6   \n",
       "167861  0_0eabeb73-eb50-412c-80dc-dfc832581563                 8   \n",
       "167862  0_0eabeb73-eb50-412c-80dc-dfc832581563                12   \n",
       "167863  0_0eabeb73-eb50-412c-80dc-dfc832581563                14   \n",
       "167864  0_0eabeb73-eb50-412c-80dc-dfc832581563                10   \n",
       "167865  0_0eac164c-f209-4590-8608-a56e67658952                 3   \n",
       "167866  0_0eac164c-f209-4590-8608-a56e67658952                 6   \n",
       "167867  0_0eac164c-f209-4590-8608-a56e67658952                 8   \n",
       "167868  0_0eac164c-f209-4590-8608-a56e67658952                 9   \n",
       "167869  0_0eac164c-f209-4590-8608-a56e67658952                12   \n",
       "167870  0_0eac164c-f209-4590-8608-a56e67658952                14   \n",
       "167871  0_0eac164c-f209-4590-8608-a56e67658952                17   \n",
       "167872  0_0eac164c-f209-4590-8608-a56e67658952                18   \n",
       "167873  0_0eac164c-f209-4590-8608-a56e67658952                20   \n",
       "167874  0_0eacbee7-9868-48a0-9ab0-f86069329f50                 4   \n",
       "167875  0_0ead11fc-f32c-4eb4-8fc1-15b51432a404                 8   \n",
       "167876  0_0ead11fc-f32c-4eb4-8fc1-15b51432a404                10   \n",
       "167877  0_0ead11fc-f32c-4eb4-8fc1-15b51432a404                16   \n",
       "167878  0_0ead11fc-f32c-4eb4-8fc1-15b51432a404                17   \n",
       "167879  0_0ead11fc-f32c-4eb4-8fc1-15b51432a404                20   \n",
       "\n",
       "        session_length                                track_id  skip_1  \\\n",
       "0                   20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "1                   12  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "2                   20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "3                   13  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "4                   12  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "5                   20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539    True   \n",
       "6                   20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539    True   \n",
       "7                   20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "8                   19  t_0479f24c-27d2-46d6-a00c-7ec928f2b539    True   \n",
       "9                   19  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "10                  11  t_0479f24c-27d2-46d6-a00c-7ec928f2b539    True   \n",
       "11                  20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "12                  20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "13                  20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "14                  15  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "15                  13  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "16                  16  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "17                  20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "18                  20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539    True   \n",
       "19                  10  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "20                  20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539    True   \n",
       "21                  20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539    True   \n",
       "22                  15  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "23                  15  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "24                  13  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "25                  15  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "26                  13  t_0479f24c-27d2-46d6-a00c-7ec928f2b539    True   \n",
       "27                  17  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "28                  20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "29                  20  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   \n",
       "...                ...                                     ...     ...   \n",
       "167850              20  t_3a00192e-0b70-4c93-b21f-57db215e468d   False   \n",
       "167851              20  t_b56157c4-ed95-433b-a0ce-457ef4e4c110   False   \n",
       "167852              20  t_43ab18f3-fbc0-4e45-8673-0c7eb4488414   False   \n",
       "167853              20  t_23034a69-b95e-46e8-977a-7de554561170   False   \n",
       "167854              20  t_63a6819c-47cb-4416-bf7d-eb7c9391df9a   False   \n",
       "167855              20  t_8095d037-3c67-4f39-a077-55794da35095   False   \n",
       "167856              20  t_8095d037-3c67-4f39-a077-55794da35095   False   \n",
       "167857              20  t_7b70f495-d688-41a5-8647-aeedd6ee33ef   False   \n",
       "167858              14  t_ff15dbcb-b7c9-4eb0-beeb-eb443cfc3403   False   \n",
       "167859              14  t_ff15dbcb-b7c9-4eb0-beeb-eb443cfc3403   False   \n",
       "167860              14  t_ff15dbcb-b7c9-4eb0-beeb-eb443cfc3403    True   \n",
       "167861              14  t_ff15dbcb-b7c9-4eb0-beeb-eb443cfc3403   False   \n",
       "167862              14  t_ff15dbcb-b7c9-4eb0-beeb-eb443cfc3403    True   \n",
       "167863              14  t_ff15dbcb-b7c9-4eb0-beeb-eb443cfc3403    True   \n",
       "167864              14  t_d0b94483-2e1f-4b76-ab74-7d2d749dfa94   False   \n",
       "167865              20  t_6e0c5849-c376-4fb2-a706-ff3073e85a15    True   \n",
       "167866              20  t_67e82cb9-0c1e-487a-bc2c-6b455b1d6190    True   \n",
       "167867              20  t_03c2f852-5293-4e96-9234-8240f884c403    True   \n",
       "167868              20  t_33ef80a6-e00e-4edc-96f7-e7f72363428a    True   \n",
       "167869              20  t_987480f8-a048-4c5e-aac3-0bcad5290731    True   \n",
       "167870              20  t_1e86bfc8-4204-4645-8b00-7722efca192a    True   \n",
       "167871              20  t_3f587cf3-f197-4353-90f8-30fd80ee4069   False   \n",
       "167872              20  t_19a1fed1-2040-4a88-8d06-ab4bb9373ec1   False   \n",
       "167873              20  t_1539cd4a-e7ab-4e75-b1da-65a979b2de88   False   \n",
       "167874              20  t_2990bc55-5ae8-411c-93ac-b386d12b8c2a    True   \n",
       "167875              20  t_c6d511e7-d986-4614-b694-ace9df48a665    True   \n",
       "167876              20  t_44a3360f-a06d-458a-91fc-4d9efa506697    True   \n",
       "167877              20  t_3f71a175-f7ca-4cd4-829d-65fc82b09486   False   \n",
       "167878              20  t_ac792fc0-a591-4c0f-a03c-652a97a864d2   False   \n",
       "167879              20  t_76cb529c-86e9-41e2-a136-f5bd97481a9a    True   \n",
       "\n",
       "        skip_2  skip_3  not_skipped  context_switch  no_pause_before_play  \\\n",
       "0        False   False         True               0                     0   \n",
       "1        False    True        False               0                     0   \n",
       "2        False   False         True               0                     0   \n",
       "3        False   False         True               0                     1   \n",
       "4        False    True        False               0                     0   \n",
       "5         True    True        False               0                     1   \n",
       "6         True    True        False               0                     1   \n",
       "7        False   False        False               0                     1   \n",
       "8         True    True        False               0                     1   \n",
       "9        False   False        False               1                     1   \n",
       "10        True    True        False               0                     1   \n",
       "11       False    True        False               1                     1   \n",
       "12       False   False         True               0                     0   \n",
       "13       False    True        False               0                     0   \n",
       "14       False    True        False               0                     0   \n",
       "15        True    True        False               0                     1   \n",
       "16       False    True        False               1                     1   \n",
       "17       False    True        False               0                     0   \n",
       "18        True    True        False               0                     1   \n",
       "19       False   False         True               0                     1   \n",
       "20        True    True        False               0                     1   \n",
       "21        True    True        False               0                     1   \n",
       "22       False   False        False               0                     0   \n",
       "23       False   False         True               1                     1   \n",
       "24       False   False         True               1                     1   \n",
       "25        True    True        False               0                     1   \n",
       "26        True    True        False               0                     1   \n",
       "27       False   False         True               0                     1   \n",
       "28       False    True        False               0                     1   \n",
       "29       False   False         True               0                     1   \n",
       "...        ...     ...          ...             ...                   ...   \n",
       "167850   False   False         True               0                     0   \n",
       "167851   False    True        False               0                     0   \n",
       "167852   False   False         True               0                     1   \n",
       "167853   False   False         True               0                     1   \n",
       "167854   False    True        False               0                     0   \n",
       "167855   False   False         True               0                     1   \n",
       "167856   False   False         True               0                     1   \n",
       "167857   False   False         True               0                     1   \n",
       "167858    True    True        False               0                     0   \n",
       "167859   False   False         True               0                     0   \n",
       "167860    True    True        False               0                     1   \n",
       "167861   False   False         True               0                     1   \n",
       "167862    True    True        False               0                     1   \n",
       "167863    True    True        False               0                     0   \n",
       "167864   False    True        False               0                     0   \n",
       "167865    True    True        False               0                     1   \n",
       "167866    True    True        False               0                     1   \n",
       "167867    True    True        False               0                     1   \n",
       "167868    True    True        False               0                     1   \n",
       "167869    True    True        False               0                     1   \n",
       "167870    True    True        False               0                     1   \n",
       "167871   False   False         True               0                     1   \n",
       "167872   False   False         True               0                     1   \n",
       "167873   False    True        False               0                     1   \n",
       "167874    True    True        False               0                     1   \n",
       "167875    True    True        False               0                     0   \n",
       "167876    True    True        False               0                     0   \n",
       "167877   False   False         True               0                     1   \n",
       "167878   False    True        False               0                     0   \n",
       "167879    True    True        False               0                     0   \n",
       "\n",
       "              ...         time_signature   valence  acoustic_vector_0  \\\n",
       "0             ...                      4  0.152255          -0.815775   \n",
       "1             ...                      4  0.152255          -0.815775   \n",
       "2             ...                      4  0.152255          -0.815775   \n",
       "3             ...                      4  0.152255          -0.815775   \n",
       "4             ...                      4  0.152255          -0.815775   \n",
       "5             ...                      4  0.152255          -0.815775   \n",
       "6             ...                      4  0.152255          -0.815775   \n",
       "7             ...                      4  0.152255          -0.815775   \n",
       "8             ...                      4  0.152255          -0.815775   \n",
       "9             ...                      4  0.152255          -0.815775   \n",
       "10            ...                      4  0.152255          -0.815775   \n",
       "11            ...                      4  0.152255          -0.815775   \n",
       "12            ...                      4  0.152255          -0.815775   \n",
       "13            ...                      4  0.152255          -0.815775   \n",
       "14            ...                      4  0.152255          -0.815775   \n",
       "15            ...                      4  0.152255          -0.815775   \n",
       "16            ...                      4  0.152255          -0.815775   \n",
       "17            ...                      4  0.152255          -0.815775   \n",
       "18            ...                      4  0.152255          -0.815775   \n",
       "19            ...                      4  0.152255          -0.815775   \n",
       "20            ...                      4  0.152255          -0.815775   \n",
       "21            ...                      4  0.152255          -0.815775   \n",
       "22            ...                      4  0.152255          -0.815775   \n",
       "23            ...                      4  0.152255          -0.815775   \n",
       "24            ...                      4  0.152255          -0.815775   \n",
       "25            ...                      4  0.152255          -0.815775   \n",
       "26            ...                      4  0.152255          -0.815775   \n",
       "27            ...                      4  0.152255          -0.815775   \n",
       "28            ...                      4  0.152255          -0.815775   \n",
       "29            ...                      4  0.152255          -0.815775   \n",
       "...           ...                    ...       ...                ...   \n",
       "167850        ...                      4  0.625544          -0.281968   \n",
       "167851        ...                      4  0.162715          -0.286236   \n",
       "167852        ...                      4  0.189097          -0.307814   \n",
       "167853        ...                      4  0.384743          -0.287573   \n",
       "167854        ...                      4  0.049998          -0.200057   \n",
       "167855        ...                      3  0.249501          -0.220669   \n",
       "167856        ...                      3  0.249501          -0.220669   \n",
       "167857        ...                      3  0.345805          -0.326657   \n",
       "167858        ...                      1  0.312961          -0.076285   \n",
       "167859        ...                      1  0.312961          -0.076285   \n",
       "167860        ...                      1  0.312961          -0.076285   \n",
       "167861        ...                      1  0.312961          -0.076285   \n",
       "167862        ...                      1  0.312961          -0.076285   \n",
       "167863        ...                      1  0.312961          -0.076285   \n",
       "167864        ...                      4  0.749148          -0.904019   \n",
       "167865        ...                      4  0.268244          -0.446560   \n",
       "167866        ...                      4  0.358613          -0.805200   \n",
       "167867        ...                      4  0.083944          -0.161051   \n",
       "167868        ...                      4  0.423568          -0.158492   \n",
       "167869        ...                      4  0.310271          -0.038612   \n",
       "167870        ...                      4  0.185627          -0.385327   \n",
       "167871        ...                      4  0.346405           0.190880   \n",
       "167872        ...                      4  0.601404          -0.896841   \n",
       "167873        ...                      4  0.292506          -0.201742   \n",
       "167874        ...                      4  0.250441          -0.863488   \n",
       "167875        ...                      4  0.599401          -0.842907   \n",
       "167876        ...                      4  0.322569          -0.922512   \n",
       "167877        ...                      4  0.443760          -0.771976   \n",
       "167878        ...                      4  0.416596          -0.978526   \n",
       "167879        ...                      4  0.583041          -0.883477   \n",
       "\n",
       "        acoustic_vector_1  acoustic_vector_2  acoustic_vector_3  \\\n",
       "0                0.386409           0.230160           0.028028   \n",
       "1                0.386409           0.230160           0.028028   \n",
       "2                0.386409           0.230160           0.028028   \n",
       "3                0.386409           0.230160           0.028028   \n",
       "4                0.386409           0.230160           0.028028   \n",
       "5                0.386409           0.230160           0.028028   \n",
       "6                0.386409           0.230160           0.028028   \n",
       "7                0.386409           0.230160           0.028028   \n",
       "8                0.386409           0.230160           0.028028   \n",
       "9                0.386409           0.230160           0.028028   \n",
       "10               0.386409           0.230160           0.028028   \n",
       "11               0.386409           0.230160           0.028028   \n",
       "12               0.386409           0.230160           0.028028   \n",
       "13               0.386409           0.230160           0.028028   \n",
       "14               0.386409           0.230160           0.028028   \n",
       "15               0.386409           0.230160           0.028028   \n",
       "16               0.386409           0.230160           0.028028   \n",
       "17               0.386409           0.230160           0.028028   \n",
       "18               0.386409           0.230160           0.028028   \n",
       "19               0.386409           0.230160           0.028028   \n",
       "20               0.386409           0.230160           0.028028   \n",
       "21               0.386409           0.230160           0.028028   \n",
       "22               0.386409           0.230160           0.028028   \n",
       "23               0.386409           0.230160           0.028028   \n",
       "24               0.386409           0.230160           0.028028   \n",
       "25               0.386409           0.230160           0.028028   \n",
       "26               0.386409           0.230160           0.028028   \n",
       "27               0.386409           0.230160           0.028028   \n",
       "28               0.386409           0.230160           0.028028   \n",
       "29               0.386409           0.230160           0.028028   \n",
       "...                   ...                ...                ...   \n",
       "167850           0.037951          -0.239047           0.238496   \n",
       "167851           0.014840          -0.223812           0.254035   \n",
       "167852          -0.017920          -0.211223           0.288907   \n",
       "167853           0.038921          -0.278049           0.216598   \n",
       "167854           0.025851          -0.162609           0.239263   \n",
       "167855          -0.004662          -0.322330           0.254388   \n",
       "167856          -0.004662          -0.322330           0.254388   \n",
       "167857           0.044544          -0.185697           0.252924   \n",
       "167858          -0.543137           0.134288           0.636808   \n",
       "167859          -0.543137           0.134288           0.636808   \n",
       "167860          -0.543137           0.134288           0.636808   \n",
       "167861          -0.543137           0.134288           0.636808   \n",
       "167862          -0.543137           0.134288           0.636808   \n",
       "167863          -0.543137           0.134288           0.636808   \n",
       "167864           0.226712           0.413872           0.441320   \n",
       "167865           0.446865           0.347977          -0.259426   \n",
       "167866           0.278679           0.217043           0.098510   \n",
       "167867          -0.005678           0.072186          -0.042731   \n",
       "167868           0.006921           0.395930           0.159193   \n",
       "167869           0.650589          -0.072997          -0.528393   \n",
       "167870           0.252581           0.197736          -0.094862   \n",
       "167871          -0.431414           0.054029           0.153106   \n",
       "167872           0.286329           0.195760           0.149982   \n",
       "167873           0.269581           0.287458          -0.312325   \n",
       "167874           0.287187           0.271733           0.168048   \n",
       "167875           0.325243           0.207480           0.064804   \n",
       "167876           0.331971           0.218592           0.093307   \n",
       "167877           0.383800           0.367541           0.026499   \n",
       "167878           0.346568           0.250859           0.163195   \n",
       "167879           0.275426           0.203538           0.146071   \n",
       "\n",
       "       acoustic_vector_4  acoustic_vector_5 acoustic_vector_6  \\\n",
       "0              -0.333373           0.015452         -0.353590   \n",
       "1              -0.333373           0.015452         -0.353590   \n",
       "2              -0.333373           0.015452         -0.353590   \n",
       "3              -0.333373           0.015452         -0.353590   \n",
       "4              -0.333373           0.015452         -0.353590   \n",
       "5              -0.333373           0.015452         -0.353590   \n",
       "6              -0.333373           0.015452         -0.353590   \n",
       "7              -0.333373           0.015452         -0.353590   \n",
       "8              -0.333373           0.015452         -0.353590   \n",
       "9              -0.333373           0.015452         -0.353590   \n",
       "10             -0.333373           0.015452         -0.353590   \n",
       "11             -0.333373           0.015452         -0.353590   \n",
       "12             -0.333373           0.015452         -0.353590   \n",
       "13             -0.333373           0.015452         -0.353590   \n",
       "14             -0.333373           0.015452         -0.353590   \n",
       "15             -0.333373           0.015452         -0.353590   \n",
       "16             -0.333373           0.015452         -0.353590   \n",
       "17             -0.333373           0.015452         -0.353590   \n",
       "18             -0.333373           0.015452         -0.353590   \n",
       "19             -0.333373           0.015452         -0.353590   \n",
       "20             -0.333373           0.015452         -0.353590   \n",
       "21             -0.333373           0.015452         -0.353590   \n",
       "22             -0.333373           0.015452         -0.353590   \n",
       "23             -0.333373           0.015452         -0.353590   \n",
       "24             -0.333373           0.015452         -0.353590   \n",
       "25             -0.333373           0.015452         -0.353590   \n",
       "26             -0.333373           0.015452         -0.353590   \n",
       "27             -0.333373           0.015452         -0.353590   \n",
       "28             -0.333373           0.015452         -0.353590   \n",
       "29             -0.333373           0.015452         -0.353590   \n",
       "...                  ...                ...               ...   \n",
       "167850         -0.102690          -0.486494         -0.224573   \n",
       "167851         -0.095313          -0.534176         -0.227929   \n",
       "167852         -0.179076          -0.546285         -0.290156   \n",
       "167853         -0.138562          -0.535953         -0.296982   \n",
       "167854         -0.206402          -0.500973         -0.117964   \n",
       "167855         -0.116826          -0.579517         -0.198343   \n",
       "167856         -0.116826          -0.579517         -0.198343   \n",
       "167857         -0.096228          -0.468579         -0.234028   \n",
       "167858          0.618381          -0.333008         -0.111789   \n",
       "167859          0.618381          -0.333008         -0.111789   \n",
       "167860          0.618381          -0.333008         -0.111789   \n",
       "167861          0.618381          -0.333008         -0.111789   \n",
       "167862          0.618381          -0.333008         -0.111789   \n",
       "167863          0.618381          -0.333008         -0.111789   \n",
       "167864          0.037881           0.097167          0.141576   \n",
       "167865         -0.478007           0.197709         -0.155761   \n",
       "167866         -0.287822          -0.021297         -0.505806   \n",
       "167867         -0.576186           0.122020         -0.004586   \n",
       "167868         -0.183987          -0.126784         -0.030806   \n",
       "167869         -0.009909           0.178357         -0.185356   \n",
       "167870         -0.501758           0.166349         -0.030234   \n",
       "167871         -0.212964           0.009224         -0.180716   \n",
       "167872         -0.342862          -0.085681         -0.551803   \n",
       "167873         -0.637581           0.304690          0.168871   \n",
       "167874         -0.269257          -0.026314         -0.483045   \n",
       "167875         -0.258140          -0.001348         -0.548543   \n",
       "167876         -0.309999          -0.004573         -0.549420   \n",
       "167877         -0.370684           0.083014         -0.334056   \n",
       "167878         -0.274763          -0.047336         -0.546883   \n",
       "167879         -0.287761          -0.047060         -0.573223   \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",
       "5               0.205826  \n",
       "6               0.205826  \n",
       "7               0.205826  \n",
       "8               0.205826  \n",
       "9               0.205826  \n",
       "10              0.205826  \n",
       "11              0.205826  \n",
       "12              0.205826  \n",
       "13              0.205826  \n",
       "14              0.205826  \n",
       "15              0.205826  \n",
       "16              0.205826  \n",
       "17              0.205826  \n",
       "18              0.205826  \n",
       "19              0.205826  \n",
       "20              0.205826  \n",
       "21              0.205826  \n",
       "22              0.205826  \n",
       "23              0.205826  \n",
       "24              0.205826  \n",
       "25              0.205826  \n",
       "26              0.205826  \n",
       "27              0.205826  \n",
       "28              0.205826  \n",
       "29              0.205826  \n",
       "...                  ...  \n",
       "167850         -0.431867  \n",
       "167851         -0.495369  \n",
       "167852         -0.464621  \n",
       "167853         -0.412306  \n",
       "167854         -0.507854  \n",
       "167855         -0.459952  \n",
       "167856         -0.459952  \n",
       "167857         -0.458663  \n",
       "167858         -0.758606  \n",
       "167859         -0.758606  \n",
       "167860         -0.758606  \n",
       "167861         -0.758606  \n",
       "167862         -0.758606  \n",
       "167863         -0.758606  \n",
       "167864          0.271749  \n",
       "167865          0.190814  \n",
       "167866          0.108890  \n",
       "167867          0.690514  \n",
       "167868         -0.469252  \n",
       "167869          0.364100  \n",
       "167870          0.537973  \n",
       "167871          0.235676  \n",
       "167872          0.171962  \n",
       "167873          0.635113  \n",
       "167874          0.148550  \n",
       "167875          0.176667  \n",
       "167876          0.219733  \n",
       "167877          0.097527  \n",
       "167878          0.142521  \n",
       "167879          0.141425  \n",
       "\n",
       "[167880 rows x 51 columns]"
      ]
     },
     "execution_count": 218,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 0, ..., 1, 0, 0])"
      ]
     },
     "execution_count": 219,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "41970"
      ]
     },
     "execution_count": 220,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "### In y_pred where gets 1 means there we should break the boundary(recommend other genres) and\n",
    "###0 means we shouldnt break the boundary (recommend another song from the same genres)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "167880"
      ]
     },
     "execution_count": 222,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "125910"
      ]
     },
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "41970"
      ]
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "41970"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#y2 = np.concatenate((y_train, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(125910, 1)"
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_pred = y_pred.reshape(-1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(41970, 1)"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#y2 = np.concatenate((y_train, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y2 = pd.DataFrame(y2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [
    {
     "data": {
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   "cell_type": "code",
   "execution_count": 233,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "y = pd.DataFrame(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "data": {
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   "source": [
    "dat['predicted_output'] = y2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['session_id', 'session_position', 'session_length', 'track_id',\n",
       "       'skip_1', 'skip_2', 'skip_3', 'not_skipped', 'context_switch',\n",
       "       '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', 'predicted_output'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>session_id</th>\n",
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       "      <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",
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       "      <th>context_switch</th>\n",
       "      <th>no_pause_before_play</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>predicted_output</th>\n",
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       "      <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>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152255</td>\n",
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       "      <td>0.386409</td>\n",
       "      <td>0.23016</td>\n",
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       "      <td>False</td>\n",
       "      <td>0</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>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\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>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</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\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>1</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>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\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>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>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               session_id  session_position  session_length  \\\n",
       "0  0_00006f66-33e5-4de7-a324-2d18e439fc1e                 1              20   \n",
       "1  0_00079a23-1600-486a-91bd-5208be0c745a                 7              12   \n",
       "2  0_012b0fb4-0cc3-429f-9a78-cc6e622153fb                 6              20   \n",
       "3  0_013cc010-c476-4ad2-8972-73449e0b2ef4                 9              13   \n",
       "4  0_01a5f0dc-9938-48c9-92f1-c7e51f34d290                 7              12   \n",
       "\n",
       "                                 track_id  skip_1  skip_2  skip_3  \\\n",
       "0  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   False   \n",
       "1  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False    True   \n",
       "2  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   False   \n",
       "3  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   False   \n",
       "4  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False    True   \n",
       "\n",
       "   not_skipped  context_switch  no_pause_before_play       ...         \\\n",
       "0         True               0                     0       ...          \n",
       "1        False               0                     0       ...          \n",
       "2         True               0                     0       ...          \n",
       "3         True               0                     1       ...          \n",
       "4        False               0                     0       ...          \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 predicted_output  \n",
       "0          0.205826                1  \n",
       "1          0.205826                0  \n",
       "2          0.205826                1  \n",
       "3          0.205826                0  \n",
       "4          0.205826                0  \n",
       "\n",
       "[5 rows x 52 columns]"
      ]
     },
     "execution_count": 237,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ted\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1ee2f281588>"
      ]
     },
     "execution_count": 238,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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rTNewkM8chpmSYy1wRVu+BjglyUS/kDcfTDneqrq5qr7TVm9j8Psk89mw0658APgfwNNz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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(dat['label'],bins = 5,kde = False)\n",
    "sns.distplot(dat['predicted_output'],bins = 5,kde = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "### align the predicted column with the track id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "break_bubble = dat.query('predicted_output==1')['track_id']\n",
    "dont_break_bubble = dat.query('predicted_output==0')['track_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "82703"
      ]
     },
     "execution_count": 241,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(break_bubble)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "85177"
      ]
     },
     "execution_count": 242,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dont_break_bubble)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "2     t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "5     t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "8     t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "9     t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "11    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "12    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "14    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "16    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "17    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "18    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "19    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "21    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "23    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "25    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "27    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "29    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "31    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "32    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "33    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "35    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "36    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "37    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "41    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "42    t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "49    t_9099cd7b-c238-47b7-9381-f23f2c1d1043\n",
       "55    t_fc5df5ba-5396-49a7-8b29-35d0d28249e0\n",
       "56    t_fc5df5ba-5396-49a7-8b29-35d0d28249e0\n",
       "57    t_fc5df5ba-5396-49a7-8b29-35d0d28249e0\n",
       "58    t_fc5df5ba-5396-49a7-8b29-35d0d28249e0\n",
       "61    t_fc5df5ba-5396-49a7-8b29-35d0d28249e0\n",
       "63    t_fc5df5ba-5396-49a7-8b29-35d0d28249e0\n",
       "64    t_fc5df5ba-5396-49a7-8b29-35d0d28249e0\n",
       "65    t_fc5df5ba-5396-49a7-8b29-35d0d28249e0\n",
       "Name: track_id, dtype: object"
      ]
     },
     "execution_count": 243,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "break_bubble.head(34)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(break_bubble)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "break_bubble = pd.DataFrame(break_bubble)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "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>track_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 track_id\n",
       "0  t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "2  t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "5  t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "8  t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "9  t_0479f24c-27d2-46d6-a00c-7ec928f2b539"
      ]
     },
     "execution_count": 246,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "break_bubble.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dont_break_bubble = pd.DataFrame(dont_break_bubble)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "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>track_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 track_id\n",
       "1  t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "3  t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "4  t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "6  t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "7  t_0479f24c-27d2-46d6-a00c-7ec928f2b539"
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dont_break_bubble.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [],
   "source": [
    "#sns.distplot(break_bubble.index,bins = 5)\n",
    "#sns.distplot(dont_break_bubble.index,bins = 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {},
   "outputs": [],
   "source": [
    "#plt.hist(break_bubble.index,bins = 30)\n",
    "#plt.hist(dont_break_bubble.index,bins = 30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "##### Find the unique values from the Dataframe of break_bubble#####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bubble_uid = break_bubble.track_id.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(bubble_uid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bubble_uid = pd.DataFrame(bubble_uid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "33050"
      ]
     },
     "execution_count": 255,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(bubble_uid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 323,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bubble_uid.rename(columns = {0:'track_id'}, inplace = True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 324,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>track_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>t_9099cd7b-c238-47b7-9381-f23f2c1d1043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>t_fc5df5ba-5396-49a7-8b29-35d0d28249e0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>t_23cff8d6-d874-4b20-83dc-94e450e8aa20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>t_64f3743c-f624-46bb-a579-0f3f9a07a123</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 track_id\n",
       "0  t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "1  t_9099cd7b-c238-47b7-9381-f23f2c1d1043\n",
       "2  t_fc5df5ba-5396-49a7-8b29-35d0d28249e0\n",
       "3  t_23cff8d6-d874-4b20-83dc-94e450e8aa20\n",
       "4  t_64f3743c-f624-46bb-a579-0f3f9a07a123"
      ]
     },
     "execution_count": 324,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bubble_uid.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "##### Find the unique values from the Dataframe of dont_break_bubble#####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 325,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "31289\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
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       "    .dataframe thead th {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>track_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>t_9099cd7b-c238-47b7-9381-f23f2c1d1043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>t_fc5df5ba-5396-49a7-8b29-35d0d28249e0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>t_23cff8d6-d874-4b20-83dc-94e450e8aa20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>t_64f3743c-f624-46bb-a579-0f3f9a07a123</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 track_id\n",
       "0  t_0479f24c-27d2-46d6-a00c-7ec928f2b539\n",
       "1  t_9099cd7b-c238-47b7-9381-f23f2c1d1043\n",
       "2  t_fc5df5ba-5396-49a7-8b29-35d0d28249e0\n",
       "3  t_23cff8d6-d874-4b20-83dc-94e450e8aa20\n",
       "4  t_64f3743c-f624-46bb-a579-0f3f9a07a123"
      ]
     },
     "execution_count": 325,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "no_bubble_uid = dont_break_bubble.track_id.unique()\n",
    "no_bubble_uid = pd.DataFrame(no_bubble_uid)\n",
    "print(len(no_bubble_uid))\n",
    "no_bubble_uid.rename(columns = {0:'track_id'}, inplace = True) \n",
    "no_bubble_uid.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "metadata": {},
   "outputs": [],
   "source": [
    "bcounts = break_bubble.track_id.value_counts()\n",
    "no_bcounts = dont_break_bubble.track_id.value_counts()\n",
    "bcounts = pd.DataFrame(bcounts)\n",
    "no_bcounts = pd.DataFrame(no_bcounts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    .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>track_id</th>\n",
       "      <th>track_frequency</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>t_bacf06d3-9185-4183-84ea-ff0db51475ce</td>\n",
       "      <td>696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>t_5718ab08-3a15-4d3f-9e63-42b2f6805e31</td>\n",
       "      <td>417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>t_8c4d29b1-e0bf-464c-88f7-ac19240cbba0</td>\n",
       "      <td>372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>t_77b02acb-1b1f-4b36-b8fc-2c3e01892b9a</td>\n",
       "      <td>361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>t_a66ea088-b357-449a-8a1e-64dd0b8d6cb5</td>\n",
       "      <td>344</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 track_id  track_frequency\n",
       "0  t_bacf06d3-9185-4183-84ea-ff0db51475ce              696\n",
       "1  t_5718ab08-3a15-4d3f-9e63-42b2f6805e31              417\n",
       "2  t_8c4d29b1-e0bf-464c-88f7-ac19240cbba0              372\n",
       "3  t_77b02acb-1b1f-4b36-b8fc-2c3e01892b9a              361\n",
       "4  t_a66ea088-b357-449a-8a1e-64dd0b8d6cb5              344"
      ]
     },
     "execution_count": 326,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bcounts.head(5)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "metadata": {},
   "outputs": [],
   "source": [
    "bcounts.reset_index(level=0, inplace=True)\n",
    "no_bcounts.reset_index(level=0, inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 327,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>track_id</th>\n",
       "      <th>track_frequency</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>t_bacf06d3-9185-4183-84ea-ff0db51475ce</td>\n",
       "      <td>731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>t_5718ab08-3a15-4d3f-9e63-42b2f6805e31</td>\n",
       "      <td>498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>t_8c4d29b1-e0bf-464c-88f7-ac19240cbba0</td>\n",
       "      <td>413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>t_a66ea088-b357-449a-8a1e-64dd0b8d6cb5</td>\n",
       "      <td>386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>t_77b02acb-1b1f-4b36-b8fc-2c3e01892b9a</td>\n",
       "      <td>358</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 track_id  track_frequency\n",
       "0  t_bacf06d3-9185-4183-84ea-ff0db51475ce              731\n",
       "1  t_5718ab08-3a15-4d3f-9e63-42b2f6805e31              498\n",
       "2  t_8c4d29b1-e0bf-464c-88f7-ac19240cbba0              413\n",
       "3  t_a66ea088-b357-449a-8a1e-64dd0b8d6cb5              386\n",
       "4  t_77b02acb-1b1f-4b36-b8fc-2c3e01892b9a              358"
      ]
     },
     "execution_count": 327,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "no_bcounts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 328,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>track_id</th>\n",
       "      <th>track_frequency</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>t_bacf06d3-9185-4183-84ea-ff0db51475ce</td>\n",
       "      <td>696</td>\n",
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       "      <th>1</th>\n",
       "      <td>t_5718ab08-3a15-4d3f-9e63-42b2f6805e31</td>\n",
       "      <td>417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>t_8c4d29b1-e0bf-464c-88f7-ac19240cbba0</td>\n",
       "      <td>372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>t_77b02acb-1b1f-4b36-b8fc-2c3e01892b9a</td>\n",
       "      <td>361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>t_a66ea088-b357-449a-8a1e-64dd0b8d6cb5</td>\n",
       "      <td>344</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 track_id  track_frequency\n",
       "0  t_bacf06d3-9185-4183-84ea-ff0db51475ce              696\n",
       "1  t_5718ab08-3a15-4d3f-9e63-42b2f6805e31              417\n",
       "2  t_8c4d29b1-e0bf-464c-88f7-ac19240cbba0              372\n",
       "3  t_77b02acb-1b1f-4b36-b8fc-2c3e01892b9a              361\n",
       "4  t_a66ea088-b357-449a-8a1e-64dd0b8d6cb5              344"
      ]
     },
     "execution_count": 328,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bcounts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#### renaming columns of bcounts and no_bcounts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "bcounts.rename(columns = {'track_id':'track_frequency'}, inplace = True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "bcounts.rename(columns = {'index':'track_id'}, inplace = True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "metadata": {},
   "outputs": [
    {
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      ],
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       "                                 track_id  track_frequency\n",
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       "1  t_5718ab08-3a15-4d3f-9e63-42b2f6805e31              417\n",
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       "4  t_a66ea088-b357-449a-8a1e-64dd0b8d6cb5              344"
      ]
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     "execution_count": 321,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bcounts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 322,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>t_a66ea088-b357-449a-8a1e-64dd0b8d6cb5</td>\n",
       "      <td>386</td>\n",
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       "      <td>t_77b02acb-1b1f-4b36-b8fc-2c3e01892b9a</td>\n",
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      ],
      "text/plain": [
       "                                 track_id  track_frequency\n",
       "0  t_bacf06d3-9185-4183-84ea-ff0db51475ce              731\n",
       "1  t_5718ab08-3a15-4d3f-9e63-42b2f6805e31              498\n",
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       "4  t_77b02acb-1b1f-4b36-b8fc-2c3e01892b9a              358"
      ]
     },
     "execution_count": 322,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "no_bcounts.rename(columns = {'track_id':'track_frequency'}, inplace = True) \n",
    "no_bcounts.rename(columns = {'index':'track_id'}, inplace = True) \n",
    "no_bcounts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 329,
   "metadata": {},
   "outputs": [],
   "source": [
    "bubble_uid_final = pd.merge(bubble_uid,bcounts, on = 'track_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 330,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
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       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>25</td>\n",
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       "      <td>t_9099cd7b-c238-47b7-9381-f23f2c1d1043</td>\n",
       "      <td>1</td>\n",
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       "      <td>t_fc5df5ba-5396-49a7-8b29-35d0d28249e0</td>\n",
       "      <td>137</td>\n",
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       "      <td>t_64f3743c-f624-46bb-a579-0f3f9a07a123</td>\n",
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      ],
      "text/plain": [
       "                                 track_id  track_frequency\n",
       "0  t_0479f24c-27d2-46d6-a00c-7ec928f2b539               25\n",
       "1  t_9099cd7b-c238-47b7-9381-f23f2c1d1043                1\n",
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       "4  t_64f3743c-f624-46bb-a579-0f3f9a07a123               61"
      ]
     },
     "execution_count": 330,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bubble_uid_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 333,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "no_bubble_uid_final = pd.merge(no_bubble_uid,no_bcounts, on = 'track_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 334,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
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       "      <th>track_id</th>\n",
       "      <th>track_frequency</th>\n",
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       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>20</td>\n",
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       "      <td>t_9099cd7b-c238-47b7-9381-f23f2c1d1043</td>\n",
       "      <td>4</td>\n",
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       "      <td>t_fc5df5ba-5396-49a7-8b29-35d0d28249e0</td>\n",
       "      <td>140</td>\n",
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       "      <th>3</th>\n",
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       "      <td>t_64f3743c-f624-46bb-a579-0f3f9a07a123</td>\n",
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      ],
      "text/plain": [
       "                                 track_id  track_frequency\n",
       "0  t_0479f24c-27d2-46d6-a00c-7ec928f2b539               20\n",
       "1  t_9099cd7b-c238-47b7-9381-f23f2c1d1043                4\n",
       "2  t_fc5df5ba-5396-49a7-8b29-35d0d28249e0              140\n",
       "3  t_23cff8d6-d874-4b20-83dc-94e450e8aa20               15\n",
       "4  t_64f3743c-f624-46bb-a579-0f3f9a07a123               61"
      ]
     },
     "execution_count": 334,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "no_bubble_uid_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ted\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "C:\\Users\\Ted\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1706: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1ee453176d8>"
      ]
     },
     "execution_count": 354,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AACMRCQAAAICRiAQAAADASEQCAAAAYCQiAQAAADASkQAAAAAYiUgAAAAAjEQk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\nbSI94QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 15))\n",
    "sns.distplot(bubble_uid_final['track_frequency'],bins = 5)\n",
    "sns.distplot(no_bubble_uid_final['track_frequency'],bins = 5)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}