spotify_short_logistic_track_id.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "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": 2,
   "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": 3,
   "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",
       "      <th>danceability</th>\n",
       "      <th>dyn_range_mean</th>\n",
       "      <th>energy</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>t_a540e552-16d4-42f8-a185-232bd650ea7d</td>\n",
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       "      <td>0.504949</td>\n",
       "      <td>0.399767</td>\n",
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       "      <td>0.817709</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
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       "      <td>0.349438</td>\n",
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       "      <td>t_67965da0-132b-4b1e-8a69-0ef99b32287c</td>\n",
       "      <td>187.693329</td>\n",
       "      <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",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
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       "      <td>0.145703</td>\n",
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       "      <td>0.123860</td>\n",
       "      <td>0.746904</td>\n",
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       "      <td>-0.420558</td>\n",
       "      <td>-0.213120</td>\n",
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       "      <th>2</th>\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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\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",
       "      <td>0.859075</td>\n",
       "      <td>0.039143</td>\n",
       "      <td>-0.267555</td>\n",
       "      <td>-0.051825</td>\n",
       "      <td>0.106173</td>\n",
       "      <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",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.562343</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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "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",
       "2  t_0614ecd3-a7d5-40a1-816e-156d5872a467  160.839996          1951   \n",
       "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": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_mini.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_mini.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_mini.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sample = pd.read_csv(r'F:\\AppliedDataScience\\data\\data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <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",
       "      <td>0.1650</td>\n",
       "      <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": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_mini.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_mini.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>bounciness</th>\n",
       "      <th>danceability</th>\n",
       "      <th>dyn_range_mean</th>\n",
       "      <th>energy</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",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>109.706673</td>\n",
       "      <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",
       "      <td>...</td>\n",
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       "      <td>-0.033284</td>\n",
       "      <td>-0.411896</td>\n",
       "      <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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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>t_67965da0-132b-4b1e-8a69-0ef99b32287c</td>\n",
       "      <td>187.693329</td>\n",
       "      <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",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <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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       "<p>2 rows × 30 columns</p>\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": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_mini.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "                               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",
       "\n",
       "                           track_id_clean  skip_1  skip_2  skip_3  \\\n",
       "0  t_0479f24c-27d2-46d6-a00c-7ec928f2b539   False   False   False   \n",
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       "               ...               long_pause_before_play  \\\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": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_mini.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "167880"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(log_mini)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50704"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tf_mini)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = log_mini"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tf_mini = tf_mini.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50704"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tf_mini)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "### creating label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "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": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe thead th {\n",
       "        text-align: left;\n",
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       "    .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",
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       "  </thead>\n",
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       "      <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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       "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": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#import matplotlib.pyplot as plt\n",
    "#plt.hist(df['label'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "label = df[['label']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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 0x19783591940>"
      ]
     },
     "execution_count": 56,
     "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": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "167880"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50704"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tf_mini)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_1 = df.head(50704)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50704"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "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": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
       "        text-align: left;\n",
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       "\n",
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       "        vertical-align: top;\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>session_id</th>\n",
       "      <th>session_position</th>\n",
       "      <th>session_length</th>\n",
       "      <th>track_id</th>\n",
       "      <th>skip_1</th>\n",
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       "      <th>no_pause_before_play</th>\n",
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       "      <th>hour_of_day</th>\n",
       "      <th>date</th>\n",
       "      <th>premium</th>\n",
       "      <th>context_type</th>\n",
       "      <th>hist_user_behavior_reason_start</th>\n",
       "      <th>hist_user_behavior_reason_end</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>16</td>\n",
       "      <td>2018-07-15</td>\n",
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       "      <td>editorial_playlist</td>\n",
       "      <td>trackdone</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>False</td>\n",
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       "      <td>2018-07-15</td>\n",
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       "      <td>trackdone</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0_00006f66-33e5-4de7-a324-2d18e439fc1e</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>0</td>\n",
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       "      <td>2018-07-15</td>\n",
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       "      <td>editorial_playlist</td>\n",
       "      <td>trackdone</td>\n",
       "      <td>trackdone</td>\n",
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       "    </tr>\n",
       "  </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": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#### merging Both Dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_merge_col_1 = pd.merge(df_1, tf_mini, on='track_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "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": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merge_col_1.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50704"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_merge_col_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#### Merging both Dataframes before cutting short"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2.rename(columns = {'track_id_clean':'track_id'}, inplace = True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_merge_col_2 = pd.merge(df2, tf_mini, on='track_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "167880"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_merge_col_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_merge_col_2 = df_merge_col_2.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "167880"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_merge_col_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "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": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merge_col_2.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dat = df_merge_col_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1979f13c748>"
      ]
     },
     "execution_count": 102,
     "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": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = dat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "#features = features.drop('label', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "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",
       "       'duration', 'release_year', 'us_popularity_estimate', 'acousticness',\n",
       "       'beat_strength', 'bounciness', 'danceability', 'dyn_range_mean',\n",
       "       'energy', 'flatness', 'instrumentalness', 'key', 'liveness', 'loudness',\n",
       "       'mechanism', 'mode', 'organism', 'speechiness', 'tempo',\n",
       "       'time_signature', 'valence', 'acoustic_vector_0', 'acoustic_vector_1',\n",
       "       'acoustic_vector_2', 'acoustic_vector_3', 'acoustic_vector_4',\n",
       "       'acoustic_vector_5', 'acoustic_vector_6', 'acoustic_vector_7'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ff1 = features[['not_skipped','hist_user_behavior_is_shuffle']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y = dat[['label']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "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": 142,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 167880 entries, 0 to 167879\n",
      "Data columns (total 50 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",
      "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), int64(12), object(7)\n",
      "memory usage: 63.6+ MB\n"
     ]
    }
   ],
   "source": [
    "features.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x197a6026d30>"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7mpiZmZmZmZmZVeCeJpZNRDwMPFzeLulpoG9Z8xciYn4npGVmZmZmZmaNqvhJNdXIRRNb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\nF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iRnJTkyyaVJfpJkVlfv1CSfTvKdrvxVXXm62NcmWZDk+HE8XkmSJEmS/oB3z9EgbwH2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\nFd4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ZMZEflFYbYyqp1caYSmtVhpRaaVIZCpJvxeHARsDNpDHBtm8caGCVBY6kWURVx522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\nmyaSJEmSJEkj/D+MCd0ChUuvHwAAAABJRU5ErkJggg==\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": 191,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 1],\n",
       "       [0, 0],\n",
       "       [1, 0],\n",
       "       ...,\n",
       "       [1, 1],\n",
       "       [0, 1],\n",
       "       [0, 1]], dtype=int64)"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ff1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 167880)"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ff1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ff1 = ff1.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ff1 = pd.DataFrame(ff1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ff1 = ff1.transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "le = LabelEncoder()\n",
    "ff1[1] = le.fit_transform(ff1[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   label\n",
       "0      1\n",
       "1      0\n",
       "2      1"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y = y.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1],\n",
       "       [0],\n",
       "       [1],\n",
       "       ...,\n",
       "       [1],\n",
       "       [1],\n",
       "       [1]])"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ted\\Anaconda3\\lib\\site-packages\\sklearn\\cross_validation.py:41: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n",
      "  \"This module will be removed in 0.20.\", DeprecationWarning)\n"
     ]
    }
   ],
   "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": 194,
   "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": 194,
     "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": 195,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_pred=logreg.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 0, ..., 1, 0, 0])"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[19131,  2918],\n",
       "       [    0, 19921]], dtype=int64)"
      ]
     },
     "execution_count": 197,
     "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": 198,
   "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: 0.930474148201096\n",
      "Precision: 0.8722360873943693\n",
      "Recall: 1.0\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": 199,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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>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",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>False</td>\n",
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       "      <td>-0.815775</td>\n",
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       "      <td>0.230160</td>\n",
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       "      <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>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>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",
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       "    <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>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>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 × 50 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 50 columns]"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 0, ..., 1, 0, 0])"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "41970"
      ]
     },
     "execution_count": 202,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": 203,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "167880"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "125910"
      ]
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "41970"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "41970"
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {},
   "outputs": [],
   "source": [
    "#y2 = np.concatenate((y_train, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(125910, 1)"
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = y_pred.reshape(-1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(41970, 1)"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(167880, 1)"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [],
   "source": [
    "y2 = pd.DataFrame(y2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "   0\n",
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   "source": [
    "y2.head()"
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  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = pd.DataFrame(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "data": {
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  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [],
   "source": [
    "dat['predicted_output'] = y2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "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": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>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",
       "    <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": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "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 0x197a65a8fd0>"
      ]
     },
     "execution_count": 228,
     "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": 234,
   "metadata": {},
   "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": 235,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "82703"
      ]
     },
     "execution_count": 235,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(break_bubble)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "85177"
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dont_break_bubble)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "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": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "break_bubble.head(34)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}