Data preprocessing + log reg.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as pyplot\n",
    "import seaborn as sns\n",
    "import numpy as np \n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn import metrics \n",
    "from sklearn.metrics import classification_report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"webcam_test_2017-09-30-12-26-14.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
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       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>0.833</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>0.875</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0.917</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>0.958</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>1.042</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>1.083</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>1.125</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>1.167</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>1.208</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>6536</th>\n",
       "      <td>6537</td>\n",
       "      <td>0</td>\n",
       "      <td>272.333</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.318829</td>\n",
       "      <td>0.468742</td>\n",
       "      <td>-0.823790</td>\n",
       "      <td>-0.421208</td>\n",
       "      <td>0.742920</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6537</th>\n",
       "      <td>6538</td>\n",
       "      <td>0</td>\n",
       "      <td>272.375</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.326869</td>\n",
       "      <td>0.478771</td>\n",
       "      <td>-0.814822</td>\n",
       "      <td>-0.402046</td>\n",
       "      <td>0.732414</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6538</th>\n",
       "      <td>6539</td>\n",
       "      <td>0</td>\n",
       "      <td>272.417</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.335902</td>\n",
       "      <td>0.470934</td>\n",
       "      <td>-0.815715</td>\n",
       "      <td>-0.469190</td>\n",
       "      <td>0.700496</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6539</th>\n",
       "      <td>6540</td>\n",
       "      <td>0</td>\n",
       "      <td>272.458</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.339839</td>\n",
       "      <td>0.465885</td>\n",
       "      <td>-0.816983</td>\n",
       "      <td>-0.405154</td>\n",
       "      <td>0.606846</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6540</th>\n",
       "      <td>6541</td>\n",
       "      <td>0</td>\n",
       "      <td>272.500</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.345396</td>\n",
       "      <td>0.486849</td>\n",
       "      <td>-0.802297</td>\n",
       "      <td>-0.426202</td>\n",
       "      <td>0.712371</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6541</th>\n",
       "      <td>6542</td>\n",
       "      <td>0</td>\n",
       "      <td>272.542</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.354721</td>\n",
       "      <td>0.495150</td>\n",
       "      <td>-0.793095</td>\n",
       "      <td>-0.398843</td>\n",
       "      <td>0.703926</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6542</th>\n",
       "      <td>6543</td>\n",
       "      <td>0</td>\n",
       "      <td>272.583</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.370091</td>\n",
       "      <td>0.484333</td>\n",
       "      <td>-0.792751</td>\n",
       "      <td>-0.294535</td>\n",
       "      <td>0.595303</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6543</th>\n",
       "      <td>6544</td>\n",
       "      <td>0</td>\n",
       "      <td>272.625</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.346260</td>\n",
       "      <td>0.512075</td>\n",
       "      <td>-0.786056</td>\n",
       "      <td>-0.241335</td>\n",
       "      <td>0.570379</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6544</th>\n",
       "      <td>6545</td>\n",
       "      <td>0</td>\n",
       "      <td>272.667</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.374852</td>\n",
       "      <td>0.513227</td>\n",
       "      <td>-0.772065</td>\n",
       "      <td>-0.253287</td>\n",
       "      <td>0.607272</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6545</th>\n",
       "      <td>6546</td>\n",
       "      <td>0</td>\n",
       "      <td>272.708</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.287790</td>\n",
       "      <td>0.598376</td>\n",
       "      <td>-0.747745</td>\n",
       "      <td>-0.303277</td>\n",
       "      <td>0.662635</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6546</th>\n",
       "      <td>6547</td>\n",
       "      <td>0</td>\n",
       "      <td>272.750</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.342689</td>\n",
       "      <td>0.601672</td>\n",
       "      <td>-0.721495</td>\n",
       "      <td>-0.306269</td>\n",
       "      <td>0.662499</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6547</th>\n",
       "      <td>6548</td>\n",
       "      <td>0</td>\n",
       "      <td>272.792</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.263855</td>\n",
       "      <td>0.613817</td>\n",
       "      <td>-0.744049</td>\n",
       "      <td>-0.301051</td>\n",
       "      <td>0.657583</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6548</th>\n",
       "      <td>6549</td>\n",
       "      <td>0</td>\n",
       "      <td>272.833</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.311539</td>\n",
       "      <td>0.630902</td>\n",
       "      <td>-0.710567</td>\n",
       "      <td>-0.295961</td>\n",
       "      <td>0.660575</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6549</th>\n",
       "      <td>6550</td>\n",
       "      <td>0</td>\n",
       "      <td>272.875</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.332144</td>\n",
       "      <td>0.633465</td>\n",
       "      <td>-0.698858</td>\n",
       "      <td>-0.297534</td>\n",
       "      <td>0.661657</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6550</th>\n",
       "      <td>6551</td>\n",
       "      <td>0</td>\n",
       "      <td>272.917</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.324841</td>\n",
       "      <td>0.638554</td>\n",
       "      <td>-0.697658</td>\n",
       "      <td>-0.255620</td>\n",
       "      <td>0.671209</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6551</th>\n",
       "      <td>6552</td>\n",
       "      <td>0</td>\n",
       "      <td>272.958</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.304509</td>\n",
       "      <td>0.637509</td>\n",
       "      <td>-0.707712</td>\n",
       "      <td>-0.283503</td>\n",
       "      <td>0.655675</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6552</th>\n",
       "      <td>6553</td>\n",
       "      <td>0</td>\n",
       "      <td>273.000</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.312529</td>\n",
       "      <td>0.614242</td>\n",
       "      <td>-0.724591</td>\n",
       "      <td>-0.290768</td>\n",
       "      <td>0.633221</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6553</th>\n",
       "      <td>6554</td>\n",
       "      <td>0</td>\n",
       "      <td>273.042</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.294600</td>\n",
       "      <td>0.611432</td>\n",
       "      <td>-0.734412</td>\n",
       "      <td>-0.263335</td>\n",
       "      <td>0.644378</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6554</th>\n",
       "      <td>6555</td>\n",
       "      <td>0</td>\n",
       "      <td>273.083</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.296551</td>\n",
       "      <td>0.599050</td>\n",
       "      <td>-0.743772</td>\n",
       "      <td>-0.248604</td>\n",
       "      <td>0.656992</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6555</th>\n",
       "      <td>6556</td>\n",
       "      <td>0</td>\n",
       "      <td>273.125</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.292875</td>\n",
       "      <td>0.598764</td>\n",
       "      <td>-0.745457</td>\n",
       "      <td>-0.249262</td>\n",
       "      <td>0.663020</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6556</th>\n",
       "      <td>6557</td>\n",
       "      <td>0</td>\n",
       "      <td>273.167</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.379342</td>\n",
       "      <td>0.588466</td>\n",
       "      <td>-0.714008</td>\n",
       "      <td>-0.249613</td>\n",
       "      <td>0.651480</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6557</th>\n",
       "      <td>6558</td>\n",
       "      <td>0</td>\n",
       "      <td>273.208</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.342119</td>\n",
       "      <td>0.610894</td>\n",
       "      <td>-0.713977</td>\n",
       "      <td>-0.231250</td>\n",
       "      <td>0.666951</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6558</th>\n",
       "      <td>6559</td>\n",
       "      <td>0</td>\n",
       "      <td>273.250</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.355195</td>\n",
       "      <td>0.601119</td>\n",
       "      <td>-0.715886</td>\n",
       "      <td>-0.223241</td>\n",
       "      <td>0.680350</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6559</th>\n",
       "      <td>6560</td>\n",
       "      <td>0</td>\n",
       "      <td>273.292</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.357529</td>\n",
       "      <td>0.591812</td>\n",
       "      <td>-0.722448</td>\n",
       "      <td>-0.200448</td>\n",
       "      <td>0.688256</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6560</th>\n",
       "      <td>6561</td>\n",
       "      <td>0</td>\n",
       "      <td>273.333</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.342333</td>\n",
       "      <td>0.597744</td>\n",
       "      <td>-0.724920</td>\n",
       "      <td>-0.205528</td>\n",
       "      <td>0.696781</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6561</th>\n",
       "      <td>6562</td>\n",
       "      <td>0</td>\n",
       "      <td>273.375</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.379890</td>\n",
       "      <td>0.594685</td>\n",
       "      <td>-0.708543</td>\n",
       "      <td>-0.198039</td>\n",
       "      <td>0.703676</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6562</th>\n",
       "      <td>6563</td>\n",
       "      <td>0</td>\n",
       "      <td>273.417</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.374965</td>\n",
       "      <td>0.587188</td>\n",
       "      <td>-0.717364</td>\n",
       "      <td>-0.150392</td>\n",
       "      <td>0.706571</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6563</th>\n",
       "      <td>6564</td>\n",
       "      <td>0</td>\n",
       "      <td>273.458</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.381179</td>\n",
       "      <td>0.574120</td>\n",
       "      <td>-0.724630</td>\n",
       "      <td>-0.146471</td>\n",
       "      <td>0.702237</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6564</th>\n",
       "      <td>6565</td>\n",
       "      <td>0</td>\n",
       "      <td>273.500</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.347725</td>\n",
       "      <td>0.598589</td>\n",
       "      <td>-0.721650</td>\n",
       "      <td>-0.152610</td>\n",
       "      <td>0.706106</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6565</th>\n",
       "      <td>6566</td>\n",
       "      <td>0</td>\n",
       "      <td>273.542</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.351760</td>\n",
       "      <td>0.578569</td>\n",
       "      <td>-0.735883</td>\n",
       "      <td>-0.164034</td>\n",
       "      <td>0.689540</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6566 rows × 714 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      frame   face_id   timestamp   confidence   success   gaze_0_x  \\\n",
       "0         1         0       0.000         0.00         0   0.000000   \n",
       "1         2         0       0.042         0.00         0   0.000000   \n",
       "2         3         0       0.083         0.00         0   0.000000   \n",
       "3         4         0       0.125         0.00         0   0.000000   \n",
       "4         5         0       0.167         0.00         0   0.000000   \n",
       "5         6         0       0.208         0.00         0   0.000000   \n",
       "6         7         0       0.250         0.00         0   0.000000   \n",
       "7         8         0       0.292         0.00         0   0.000000   \n",
       "8         9         0       0.333         0.00         0   0.000000   \n",
       "9        10         0       0.375         0.00         0   0.000000   \n",
       "10       11         0       0.417         0.00         0   0.000000   \n",
       "11       12         0       0.458         0.00         0   0.000000   \n",
       "12       13         0       0.500         0.88         1   0.490115   \n",
       "13       14         0       0.542         0.98         1   0.502741   \n",
       "14       15         0       0.583         0.03         0   0.000000   \n",
       "15       16         0       0.625         0.03         0   0.000000   \n",
       "16       17         0       0.667         0.03         0   0.000000   \n",
       "17       18         0       0.708         0.03         0   0.000000   \n",
       "18       19         0       0.750         0.03         0   0.000000   \n",
       "19       20         0       0.792         0.03         0   0.000000   \n",
       "20       21         0       0.833         0.03         0   0.000000   \n",
       "21       22         0       0.875         0.38         0   0.000000   \n",
       "22       23         0       0.917         0.08         0   0.000000   \n",
       "23       24         0       0.958         0.03         0   0.000000   \n",
       "24       25         0       1.000         0.03         0   0.000000   \n",
       "25       26         0       1.042         0.03         0   0.000000   \n",
       "26       27         0       1.083         0.03         0   0.000000   \n",
       "27       28         0       1.125         0.03         0   0.000000   \n",
       "28       29         0       1.167         0.03         0   0.000000   \n",
       "29       30         0       1.208         0.03         0   0.000000   \n",
       "...     ...       ...         ...          ...       ...        ...   \n",
       "6536   6537         0     272.333         0.93         1   0.318829   \n",
       "6537   6538         0     272.375         0.93         1   0.326869   \n",
       "6538   6539         0     272.417         0.98         1   0.335902   \n",
       "6539   6540         0     272.458         0.93         1   0.339839   \n",
       "6540   6541         0     272.500         0.93         1   0.345396   \n",
       "6541   6542         0     272.542         0.93         1   0.354721   \n",
       "6542   6543         0     272.583         0.93         1   0.370091   \n",
       "6543   6544         0     272.625         0.93         1   0.346260   \n",
       "6544   6545         0     272.667         0.93         1   0.374852   \n",
       "6545   6546         0     272.708         0.93         1   0.287790   \n",
       "6546   6547         0     272.750         0.93         1   0.342689   \n",
       "6547   6548         0     272.792         0.98         1   0.263855   \n",
       "6548   6549         0     272.833         0.93         1   0.311539   \n",
       "6549   6550         0     272.875         0.93         1   0.332144   \n",
       "6550   6551         0     272.917         0.98         1   0.324841   \n",
       "6551   6552         0     272.958         0.98         1   0.304509   \n",
       "6552   6553         0     273.000         0.98         1   0.312529   \n",
       "6553   6554         0     273.042         0.98         1   0.294600   \n",
       "6554   6555         0     273.083         0.98         1   0.296551   \n",
       "6555   6556         0     273.125         0.98         1   0.292875   \n",
       "6556   6557         0     273.167         0.98         1   0.379342   \n",
       "6557   6558         0     273.208         0.93         1   0.342119   \n",
       "6558   6559         0     273.250         0.98         1   0.355195   \n",
       "6559   6560         0     273.292         0.93         1   0.357529   \n",
       "6560   6561         0     273.333         0.98         1   0.342333   \n",
       "6561   6562         0     273.375         0.98         1   0.379890   \n",
       "6562   6563         0     273.417         0.93         1   0.374965   \n",
       "6563   6564         0     273.458         0.93         1   0.381179   \n",
       "6564   6565         0     273.500         0.93         1   0.347725   \n",
       "6565   6566         0     273.542         0.93         1   0.351760   \n",
       "\n",
       "       gaze_0_y   gaze_0_z   gaze_1_x   gaze_1_y   ...      AU12_c   AU14_c  \\\n",
       "0      0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "1      0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "2      0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "3      0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "4      0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "5      0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "6      0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "7      0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "8      0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "9      0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "10     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "11     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "12     0.518060  -0.701000  -0.110569   0.437534   ...         0.0      0.0   \n",
       "13     0.604145  -0.618272   0.192178   0.474315   ...         0.0      0.0   \n",
       "14     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "15     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "16     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "17     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "18     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "19     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "20     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "21     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "22     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "23     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "24     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "25     0.000000   0.000000   0.000000   0.000000   ...         1.0      1.0   \n",
       "26     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "27     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "28     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "29     0.000000   0.000000   0.000000   0.000000   ...         0.0      0.0   \n",
       "...         ...        ...        ...        ...   ...         ...      ...   \n",
       "6536   0.468742  -0.823790  -0.421208   0.742920   ...         0.0      0.0   \n",
       "6537   0.478771  -0.814822  -0.402046   0.732414   ...         0.0      0.0   \n",
       "6538   0.470934  -0.815715  -0.469190   0.700496   ...         0.0      1.0   \n",
       "6539   0.465885  -0.816983  -0.405154   0.606846   ...         0.0      1.0   \n",
       "6540   0.486849  -0.802297  -0.426202   0.712371   ...         0.0      1.0   \n",
       "6541   0.495150  -0.793095  -0.398843   0.703926   ...         0.0      1.0   \n",
       "6542   0.484333  -0.792751  -0.294535   0.595303   ...         0.0      1.0   \n",
       "6543   0.512075  -0.786056  -0.241335   0.570379   ...         0.0      1.0   \n",
       "6544   0.513227  -0.772065  -0.253287   0.607272   ...         0.0      1.0   \n",
       "6545   0.598376  -0.747745  -0.303277   0.662635   ...         0.0      1.0   \n",
       "6546   0.601672  -0.721495  -0.306269   0.662499   ...         0.0      1.0   \n",
       "6547   0.613817  -0.744049  -0.301051   0.657583   ...         0.0      1.0   \n",
       "6548   0.630902  -0.710567  -0.295961   0.660575   ...         0.0      1.0   \n",
       "6549   0.633465  -0.698858  -0.297534   0.661657   ...         0.0      1.0   \n",
       "6550   0.638554  -0.697658  -0.255620   0.671209   ...         0.0      1.0   \n",
       "6551   0.637509  -0.707712  -0.283503   0.655675   ...         0.0      1.0   \n",
       "6552   0.614242  -0.724591  -0.290768   0.633221   ...         0.0      1.0   \n",
       "6553   0.611432  -0.734412  -0.263335   0.644378   ...         0.0      1.0   \n",
       "6554   0.599050  -0.743772  -0.248604   0.656992   ...         0.0      1.0   \n",
       "6555   0.598764  -0.745457  -0.249262   0.663020   ...         0.0      1.0   \n",
       "6556   0.588466  -0.714008  -0.249613   0.651480   ...         0.0      1.0   \n",
       "6557   0.610894  -0.713977  -0.231250   0.666951   ...         0.0      1.0   \n",
       "6558   0.601119  -0.715886  -0.223241   0.680350   ...         0.0      1.0   \n",
       "6559   0.591812  -0.722448  -0.200448   0.688256   ...         0.0      1.0   \n",
       "6560   0.597744  -0.724920  -0.205528   0.696781   ...         0.0      1.0   \n",
       "6561   0.594685  -0.708543  -0.198039   0.703676   ...         0.0      1.0   \n",
       "6562   0.587188  -0.717364  -0.150392   0.706571   ...         0.0      1.0   \n",
       "6563   0.574120  -0.724630  -0.146471   0.702237   ...         0.0      1.0   \n",
       "6564   0.598589  -0.721650  -0.152610   0.706106   ...         0.0      1.0   \n",
       "6565   0.578569  -0.735883  -0.164034   0.689540   ...         0.0      0.0   \n",
       "\n",
       "       AU15_c   AU17_c   AU20_c   AU23_c   AU25_c   AU26_c   AU28_c   AU45_c  \n",
       "0         0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "1         0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "2         0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "3         0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "4         0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "5         0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6         0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "7         0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "8         0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "9         0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "10        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "11        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "12        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "13        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "14        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "15        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "16        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "17        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "18        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "19        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "20        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "21        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "22        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "23        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "24        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "25        0.0      1.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "26        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "27        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "28        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "29        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "...       ...      ...      ...      ...      ...      ...      ...      ...  \n",
       "6536      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6537      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6538      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6539      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6540      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6541      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6542      1.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6543      1.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6544      1.0      1.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6545      1.0      1.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6546      1.0      1.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6547      1.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6548      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6549      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6550      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6551      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6552      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6553      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6554      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6555      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6556      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6557      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6558      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6559      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6560      0.0      0.0      1.0      0.0      0.0      1.0      0.0      1.0  \n",
       "6561      0.0      0.0      1.0      0.0      0.0      1.0      0.0      1.0  \n",
       "6562      0.0      0.0      1.0      0.0      0.0      1.0      0.0      1.0  \n",
       "6563      0.0      0.0      1.0      0.0      0.0      1.0      0.0      1.0  \n",
       "6564      0.0      0.0      1.0      0.0      0.0      1.0      0.0      1.0  \n",
       "6565      0.0      0.0      0.0      0.0      0.0      1.0      0.0      1.0  \n",
       "\n",
       "[6566 rows x 714 columns]"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_data = data[data[' confidence'] > .70] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [],
   "source": [
    "removed_data = data[data[' confidence'] <= .70] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels =  pd.read_csv(\"annos_s17_2017-09-30_3.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "#align the data\n",
    "aligned_labels = []\n",
    "\n",
    "\n",
    "\n",
    "#labels.drop(removed_data[\"frame\"])\n",
    "newFrames = []\n",
    "for index, row in removed_data.iterrows():\n",
    "    newFrames.append(int(row[\"frame\"]) - 1)\n",
    "labels = labels.drop(newFrames)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>C_Gaze</th>\n",
       "      <th>Env</th>\n",
       "      <th>C_Movement</th>\n",
       "      <th>Unnamed: 4</th>\n",
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       "      <th>12</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
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       "      <td>0.541667</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1.333333</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>44</th>\n",
       "      <td>1.833333</td>\n",
       "      <td>away</td>\n",
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       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>45</th>\n",
       "      <td>1.875000</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>1.916667</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>1.958333</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2.041667</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2.083333</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>2.125000</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2.166667</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2.208333</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2.250000</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2.291667</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>2.333333</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>2.375000</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2.416667</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2.458333</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2.500000</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2.541667</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2.583333</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2.625000</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2.666667</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2.708333</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2.750000</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2.791667</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2.833333</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2.875000</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2.916667</td>\n",
       "      <td>away</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>6532</th>\n",
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       "      <th>6533</th>\n",
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       "      <th>6534</th>\n",
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       "      <th>6538</th>\n",
       "      <td>272.416667</td>\n",
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       "    <tr>\n",
       "      <th>6539</th>\n",
       "      <td>272.458333</td>\n",
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       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6540</th>\n",
       "      <td>272.500000</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
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       "    <tr>\n",
       "      <th>6541</th>\n",
       "      <td>272.541667</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>6542</th>\n",
       "      <td>272.583333</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6543</th>\n",
       "      <td>272.625000</td>\n",
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       "      <td>people</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>6544</th>\n",
       "      <td>272.666667</td>\n",
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       "    <tr>\n",
       "      <th>6545</th>\n",
       "      <td>272.708333</td>\n",
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       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6546</th>\n",
       "      <td>272.750000</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6547</th>\n",
       "      <td>272.791667</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6548</th>\n",
       "      <td>272.833333</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6549</th>\n",
       "      <td>272.875000</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6550</th>\n",
       "      <td>272.916667</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>6551</th>\n",
       "      <td>272.958333</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6552</th>\n",
       "      <td>273.000000</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6553</th>\n",
       "      <td>273.041667</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6554</th>\n",
       "      <td>273.083333</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6555</th>\n",
       "      <td>273.125000</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6556</th>\n",
       "      <td>273.166667</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6557</th>\n",
       "      <td>273.208333</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6558</th>\n",
       "      <td>273.250000</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6559</th>\n",
       "      <td>273.291667</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6560</th>\n",
       "      <td>273.333333</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6561</th>\n",
       "      <td>273.375000</td>\n",
       "      <td>tablet</td>\n",
       "      <td>people</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6137 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Timestamp  C_Gaze     Env C_Movement  Unnamed: 4\n",
       "12      0.500000    away  people     active         NaN\n",
       "13      0.541667    away  people     active         NaN\n",
       "32      1.333333    away  people     active         NaN\n",
       "44      1.833333    away  people     active         NaN\n",
       "45      1.875000    away  people     active         NaN\n",
       "46      1.916667    away  people     active         NaN\n",
       "47      1.958333    away  people     active         NaN\n",
       "48      2.000000    away  people     active         NaN\n",
       "49      2.041667    away  people     active         NaN\n",
       "50      2.083333    away  people     active         NaN\n",
       "51      2.125000    away  people     active         NaN\n",
       "52      2.166667    away  people     active         NaN\n",
       "53      2.208333    away  people     active         NaN\n",
       "54      2.250000    away  people     active         NaN\n",
       "55      2.291667    away  people     active         NaN\n",
       "56      2.333333    away  people     active         NaN\n",
       "57      2.375000    away  people     active         NaN\n",
       "58      2.416667    away  people     active         NaN\n",
       "59      2.458333    away  people     active         NaN\n",
       "60      2.500000    away  people     active         NaN\n",
       "61      2.541667    away  people     active         NaN\n",
       "62      2.583333    away  people     active         NaN\n",
       "63      2.625000    away  people     active         NaN\n",
       "64      2.666667    away  people     active         NaN\n",
       "65      2.708333    away  people     active         NaN\n",
       "66      2.750000    away  people     active         NaN\n",
       "67      2.791667    away  people     active         NaN\n",
       "68      2.833333    away  people     active         NaN\n",
       "69      2.875000    away  people     active         NaN\n",
       "70      2.916667    away  people     active         NaN\n",
       "...          ...     ...     ...        ...         ...\n",
       "6532  272.166667  tablet  people     active         NaN\n",
       "6533  272.208333  tablet  people     active         NaN\n",
       "6534  272.250000  tablet  people     active         NaN\n",
       "6535  272.291667  tablet  people     active         NaN\n",
       "6536  272.333333  tablet  people     active         NaN\n",
       "6537  272.375000  tablet  people     active         NaN\n",
       "6538  272.416667  tablet  people     active         NaN\n",
       "6539  272.458333  tablet  people     active         NaN\n",
       "6540  272.500000  tablet  people     active         NaN\n",
       "6541  272.541667  tablet  people     active         NaN\n",
       "6542  272.583333  tablet  people     active         NaN\n",
       "6543  272.625000  tablet  people     active         NaN\n",
       "6544  272.666667  tablet  people     active         NaN\n",
       "6545  272.708333  tablet  people     active         NaN\n",
       "6546  272.750000  tablet  people     active         NaN\n",
       "6547  272.791667  tablet  people     active         NaN\n",
       "6548  272.833333  tablet  people     active         NaN\n",
       "6549  272.875000  tablet  people     active         NaN\n",
       "6550  272.916667  tablet  people     active         NaN\n",
       "6551  272.958333  tablet  people     active         NaN\n",
       "6552  273.000000  tablet  people     active         NaN\n",
       "6553  273.041667  tablet  people     active         NaN\n",
       "6554  273.083333  tablet  people     active         NaN\n",
       "6555  273.125000  tablet  people     active         NaN\n",
       "6556  273.166667  tablet  people     active         NaN\n",
       "6557  273.208333  tablet  people     active         NaN\n",
       "6558  273.250000  tablet  people     active         NaN\n",
       "6559  273.291667  tablet  people     active         NaN\n",
       "6560  273.333333  tablet  people     active         NaN\n",
       "6561  273.375000  tablet  people     active         NaN\n",
       "\n",
       "[6137 rows x 5 columns]"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_data = new_data[:-4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
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       "      <td>1</td>\n",
       "      <td>0.217933</td>\n",
       "      <td>0.445631</td>\n",
       "      <td>-0.868285</td>\n",
       "      <td>-0.057812</td>\n",
       "      <td>0.164489</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>1.833</td>\n",
       "      <td>0.73</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>46</td>\n",
       "      <td>0</td>\n",
       "      <td>1.875</td>\n",
       "      <td>0.88</td>\n",
       "      <td>1</td>\n",
       "      <td>0.001631</td>\n",
       "      <td>0.571123</td>\n",
       "      <td>-0.820863</td>\n",
       "      <td>-0.251735</td>\n",
       "      <td>0.323956</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>1.917</td>\n",
       "      <td>0.82</td>\n",
       "      <td>1</td>\n",
       "      <td>0.051677</td>\n",
       "      <td>0.687563</td>\n",
       "      <td>-0.724284</td>\n",
       "      <td>-0.138799</td>\n",
       "      <td>0.465378</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>1.958</td>\n",
       "      <td>0.88</td>\n",
       "      <td>1</td>\n",
       "      <td>0.150175</td>\n",
       "      <td>0.813878</td>\n",
       "      <td>-0.561293</td>\n",
       "      <td>-0.143064</td>\n",
       "      <td>0.347823</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>2.000</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.078123</td>\n",
       "      <td>0.826184</td>\n",
       "      <td>-0.557958</td>\n",
       "      <td>-0.227640</td>\n",
       "      <td>0.478376</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>2.042</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.012497</td>\n",
       "      <td>0.812299</td>\n",
       "      <td>-0.583107</td>\n",
       "      <td>-0.328687</td>\n",
       "      <td>0.521661</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>51</td>\n",
       "      <td>0</td>\n",
       "      <td>2.083</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.009666</td>\n",
       "      <td>0.813891</td>\n",
       "      <td>-0.580937</td>\n",
       "      <td>-0.326907</td>\n",
       "      <td>0.572618</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>52</td>\n",
       "      <td>0</td>\n",
       "      <td>2.125</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.048428</td>\n",
       "      <td>0.784492</td>\n",
       "      <td>-0.618246</td>\n",
       "      <td>-0.278237</td>\n",
       "      <td>0.628173</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "      <td>2.167</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.004113</td>\n",
       "      <td>0.806096</td>\n",
       "      <td>-0.591771</td>\n",
       "      <td>-0.363057</td>\n",
       "      <td>0.574826</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>2.208</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.013404</td>\n",
       "      <td>0.760601</td>\n",
       "      <td>-0.649082</td>\n",
       "      <td>-0.316235</td>\n",
       "      <td>0.578942</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>2.250</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.060351</td>\n",
       "      <td>0.763783</td>\n",
       "      <td>-0.642645</td>\n",
       "      <td>-0.314020</td>\n",
       "      <td>0.571981</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>2.292</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.064842</td>\n",
       "      <td>0.749218</td>\n",
       "      <td>-0.659142</td>\n",
       "      <td>-0.312687</td>\n",
       "      <td>0.620587</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>2.333</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.084957</td>\n",
       "      <td>0.740457</td>\n",
       "      <td>-0.666712</td>\n",
       "      <td>-0.300326</td>\n",
       "      <td>0.642258</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>2.375</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.095222</td>\n",
       "      <td>0.788293</td>\n",
       "      <td>-0.607887</td>\n",
       "      <td>-0.344359</td>\n",
       "      <td>0.631019</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>2.417</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.035841</td>\n",
       "      <td>0.797743</td>\n",
       "      <td>-0.601931</td>\n",
       "      <td>-0.331173</td>\n",
       "      <td>0.614157</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>2.458</td>\n",
       "      <td>0.88</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.064122</td>\n",
       "      <td>0.816204</td>\n",
       "      <td>-0.574195</td>\n",
       "      <td>-0.336924</td>\n",
       "      <td>0.614932</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>2.500</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.052078</td>\n",
       "      <td>0.810919</td>\n",
       "      <td>-0.582837</td>\n",
       "      <td>-0.350467</td>\n",
       "      <td>0.615993</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>2.542</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.128134</td>\n",
       "      <td>0.818532</td>\n",
       "      <td>-0.559988</td>\n",
       "      <td>-0.375479</td>\n",
       "      <td>0.628269</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>2.583</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.118655</td>\n",
       "      <td>0.826225</td>\n",
       "      <td>-0.550702</td>\n",
       "      <td>-0.429335</td>\n",
       "      <td>0.626095</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>2.625</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.057599</td>\n",
       "      <td>0.813390</td>\n",
       "      <td>-0.578861</td>\n",
       "      <td>-0.367048</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>2.667</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.050359</td>\n",
       "      <td>0.826329</td>\n",
       "      <td>-0.560932</td>\n",
       "      <td>-0.329420</td>\n",
       "      <td>0.611442</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>66</td>\n",
       "      <td>0</td>\n",
       "      <td>2.708</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.072139</td>\n",
       "      <td>0.786550</td>\n",
       "      <td>-0.613299</td>\n",
       "      <td>-0.307827</td>\n",
       "      <td>0.604353</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>67</td>\n",
       "      <td>0</td>\n",
       "      <td>2.750</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.023048</td>\n",
       "      <td>0.808965</td>\n",
       "      <td>-0.587405</td>\n",
       "      <td>-0.264372</td>\n",
       "      <td>0.592010</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>2.792</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.074834</td>\n",
       "      <td>0.826053</td>\n",
       "      <td>-0.558602</td>\n",
       "      <td>-0.213845</td>\n",
       "      <td>0.594617</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>69</td>\n",
       "      <td>0</td>\n",
       "      <td>2.833</td>\n",
       "      <td>0.88</td>\n",
       "      <td>1</td>\n",
       "      <td>0.099313</td>\n",
       "      <td>0.845649</td>\n",
       "      <td>-0.524418</td>\n",
       "      <td>-0.217906</td>\n",
       "      <td>0.601011</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>2.875</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.067165</td>\n",
       "      <td>0.844065</td>\n",
       "      <td>-0.532017</td>\n",
       "      <td>-0.227579</td>\n",
       "      <td>0.566541</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>71</td>\n",
       "      <td>0</td>\n",
       "      <td>2.917</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.044946</td>\n",
       "      <td>0.807528</td>\n",
       "      <td>-0.588114</td>\n",
       "      <td>-0.280023</td>\n",
       "      <td>0.579284</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</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>6532</th>\n",
       "      <td>6533</td>\n",
       "      <td>0</td>\n",
       "      <td>272.167</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.358192</td>\n",
       "      <td>0.328583</td>\n",
       "      <td>-0.873918</td>\n",
       "      <td>-0.506456</td>\n",
       "      <td>0.728760</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6533</th>\n",
       "      <td>6534</td>\n",
       "      <td>0</td>\n",
       "      <td>272.208</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.317517</td>\n",
       "      <td>0.394480</td>\n",
       "      <td>-0.862304</td>\n",
       "      <td>-0.465632</td>\n",
       "      <td>0.754687</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6534</th>\n",
       "      <td>6535</td>\n",
       "      <td>0</td>\n",
       "      <td>272.250</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.365567</td>\n",
       "      <td>0.388149</td>\n",
       "      <td>-0.845991</td>\n",
       "      <td>-0.464314</td>\n",
       "      <td>0.752721</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6535</th>\n",
       "      <td>6536</td>\n",
       "      <td>0</td>\n",
       "      <td>272.292</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.324768</td>\n",
       "      <td>0.414295</td>\n",
       "      <td>-0.850227</td>\n",
       "      <td>-0.518245</td>\n",
       "      <td>0.758292</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6536</th>\n",
       "      <td>6537</td>\n",
       "      <td>0</td>\n",
       "      <td>272.333</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.318829</td>\n",
       "      <td>0.468742</td>\n",
       "      <td>-0.823790</td>\n",
       "      <td>-0.421208</td>\n",
       "      <td>0.742920</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6537</th>\n",
       "      <td>6538</td>\n",
       "      <td>0</td>\n",
       "      <td>272.375</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.326869</td>\n",
       "      <td>0.478771</td>\n",
       "      <td>-0.814822</td>\n",
       "      <td>-0.402046</td>\n",
       "      <td>0.732414</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6538</th>\n",
       "      <td>6539</td>\n",
       "      <td>0</td>\n",
       "      <td>272.417</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.335902</td>\n",
       "      <td>0.470934</td>\n",
       "      <td>-0.815715</td>\n",
       "      <td>-0.469190</td>\n",
       "      <td>0.700496</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6539</th>\n",
       "      <td>6540</td>\n",
       "      <td>0</td>\n",
       "      <td>272.458</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.339839</td>\n",
       "      <td>0.465885</td>\n",
       "      <td>-0.816983</td>\n",
       "      <td>-0.405154</td>\n",
       "      <td>0.606846</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6540</th>\n",
       "      <td>6541</td>\n",
       "      <td>0</td>\n",
       "      <td>272.500</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.345396</td>\n",
       "      <td>0.486849</td>\n",
       "      <td>-0.802297</td>\n",
       "      <td>-0.426202</td>\n",
       "      <td>0.712371</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6541</th>\n",
       "      <td>6542</td>\n",
       "      <td>0</td>\n",
       "      <td>272.542</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.354721</td>\n",
       "      <td>0.495150</td>\n",
       "      <td>-0.793095</td>\n",
       "      <td>-0.398843</td>\n",
       "      <td>0.703926</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6542</th>\n",
       "      <td>6543</td>\n",
       "      <td>0</td>\n",
       "      <td>272.583</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.370091</td>\n",
       "      <td>0.484333</td>\n",
       "      <td>-0.792751</td>\n",
       "      <td>-0.294535</td>\n",
       "      <td>0.595303</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6543</th>\n",
       "      <td>6544</td>\n",
       "      <td>0</td>\n",
       "      <td>272.625</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.346260</td>\n",
       "      <td>0.512075</td>\n",
       "      <td>-0.786056</td>\n",
       "      <td>-0.241335</td>\n",
       "      <td>0.570379</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6544</th>\n",
       "      <td>6545</td>\n",
       "      <td>0</td>\n",
       "      <td>272.667</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.374852</td>\n",
       "      <td>0.513227</td>\n",
       "      <td>-0.772065</td>\n",
       "      <td>-0.253287</td>\n",
       "      <td>0.607272</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6545</th>\n",
       "      <td>6546</td>\n",
       "      <td>0</td>\n",
       "      <td>272.708</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.287790</td>\n",
       "      <td>0.598376</td>\n",
       "      <td>-0.747745</td>\n",
       "      <td>-0.303277</td>\n",
       "      <td>0.662635</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6546</th>\n",
       "      <td>6547</td>\n",
       "      <td>0</td>\n",
       "      <td>272.750</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.342689</td>\n",
       "      <td>0.601672</td>\n",
       "      <td>-0.721495</td>\n",
       "      <td>-0.306269</td>\n",
       "      <td>0.662499</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6547</th>\n",
       "      <td>6548</td>\n",
       "      <td>0</td>\n",
       "      <td>272.792</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.263855</td>\n",
       "      <td>0.613817</td>\n",
       "      <td>-0.744049</td>\n",
       "      <td>-0.301051</td>\n",
       "      <td>0.657583</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6548</th>\n",
       "      <td>6549</td>\n",
       "      <td>0</td>\n",
       "      <td>272.833</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.311539</td>\n",
       "      <td>0.630902</td>\n",
       "      <td>-0.710567</td>\n",
       "      <td>-0.295961</td>\n",
       "      <td>0.660575</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6549</th>\n",
       "      <td>6550</td>\n",
       "      <td>0</td>\n",
       "      <td>272.875</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.332144</td>\n",
       "      <td>0.633465</td>\n",
       "      <td>-0.698858</td>\n",
       "      <td>-0.297534</td>\n",
       "      <td>0.661657</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6550</th>\n",
       "      <td>6551</td>\n",
       "      <td>0</td>\n",
       "      <td>272.917</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.324841</td>\n",
       "      <td>0.638554</td>\n",
       "      <td>-0.697658</td>\n",
       "      <td>-0.255620</td>\n",
       "      <td>0.671209</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6551</th>\n",
       "      <td>6552</td>\n",
       "      <td>0</td>\n",
       "      <td>272.958</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.304509</td>\n",
       "      <td>0.637509</td>\n",
       "      <td>-0.707712</td>\n",
       "      <td>-0.283503</td>\n",
       "      <td>0.655675</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6552</th>\n",
       "      <td>6553</td>\n",
       "      <td>0</td>\n",
       "      <td>273.000</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.312529</td>\n",
       "      <td>0.614242</td>\n",
       "      <td>-0.724591</td>\n",
       "      <td>-0.290768</td>\n",
       "      <td>0.633221</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6553</th>\n",
       "      <td>6554</td>\n",
       "      <td>0</td>\n",
       "      <td>273.042</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.294600</td>\n",
       "      <td>0.611432</td>\n",
       "      <td>-0.734412</td>\n",
       "      <td>-0.263335</td>\n",
       "      <td>0.644378</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6554</th>\n",
       "      <td>6555</td>\n",
       "      <td>0</td>\n",
       "      <td>273.083</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.296551</td>\n",
       "      <td>0.599050</td>\n",
       "      <td>-0.743772</td>\n",
       "      <td>-0.248604</td>\n",
       "      <td>0.656992</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6555</th>\n",
       "      <td>6556</td>\n",
       "      <td>0</td>\n",
       "      <td>273.125</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.292875</td>\n",
       "      <td>0.598764</td>\n",
       "      <td>-0.745457</td>\n",
       "      <td>-0.249262</td>\n",
       "      <td>0.663020</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6556</th>\n",
       "      <td>6557</td>\n",
       "      <td>0</td>\n",
       "      <td>273.167</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.379342</td>\n",
       "      <td>0.588466</td>\n",
       "      <td>-0.714008</td>\n",
       "      <td>-0.249613</td>\n",
       "      <td>0.651480</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6557</th>\n",
       "      <td>6558</td>\n",
       "      <td>0</td>\n",
       "      <td>273.208</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.342119</td>\n",
       "      <td>0.610894</td>\n",
       "      <td>-0.713977</td>\n",
       "      <td>-0.231250</td>\n",
       "      <td>0.666951</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6558</th>\n",
       "      <td>6559</td>\n",
       "      <td>0</td>\n",
       "      <td>273.250</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.355195</td>\n",
       "      <td>0.601119</td>\n",
       "      <td>-0.715886</td>\n",
       "      <td>-0.223241</td>\n",
       "      <td>0.680350</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6559</th>\n",
       "      <td>6560</td>\n",
       "      <td>0</td>\n",
       "      <td>273.292</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0.357529</td>\n",
       "      <td>0.591812</td>\n",
       "      <td>-0.722448</td>\n",
       "      <td>-0.200448</td>\n",
       "      <td>0.688256</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6560</th>\n",
       "      <td>6561</td>\n",
       "      <td>0</td>\n",
       "      <td>273.333</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.342333</td>\n",
       "      <td>0.597744</td>\n",
       "      <td>-0.724920</td>\n",
       "      <td>-0.205528</td>\n",
       "      <td>0.696781</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6561</th>\n",
       "      <td>6562</td>\n",
       "      <td>0</td>\n",
       "      <td>273.375</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1</td>\n",
       "      <td>0.379890</td>\n",
       "      <td>0.594685</td>\n",
       "      <td>-0.708543</td>\n",
       "      <td>-0.198039</td>\n",
       "      <td>0.703676</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6137 rows × 714 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      frame   face_id   timestamp   confidence   success   gaze_0_x  \\\n",
       "12       13         0       0.500         0.88         1   0.490115   \n",
       "13       14         0       0.542         0.98         1   0.502741   \n",
       "32       33         0       1.333         0.77         1   0.217933   \n",
       "44       45         0       1.833         0.73         0   0.000000   \n",
       "45       46         0       1.875         0.88         1   0.001631   \n",
       "46       47         0       1.917         0.82         1   0.051677   \n",
       "47       48         0       1.958         0.88         1   0.150175   \n",
       "48       49         0       2.000         0.93         1   0.078123   \n",
       "49       50         0       2.042         0.98         1  -0.012497   \n",
       "50       51         0       2.083         0.98         1  -0.009666   \n",
       "51       52         0       2.125         0.98         1  -0.048428   \n",
       "52       53         0       2.167         0.98         1  -0.004113   \n",
       "53       54         0       2.208         0.98         1  -0.013404   \n",
       "54       55         0       2.250         0.98         1  -0.060351   \n",
       "55       56         0       2.292         0.98         1  -0.064842   \n",
       "56       57         0       2.333         0.98         1  -0.084957   \n",
       "57       58         0       2.375         0.98         1  -0.095222   \n",
       "58       59         0       2.417         0.98         1  -0.035841   \n",
       "59       60         0       2.458         0.88         1  -0.064122   \n",
       "60       61         0       2.500         0.98         1  -0.052078   \n",
       "61       62         0       2.542         0.98         1  -0.128134   \n",
       "62       63         0       2.583         0.98         1  -0.118655   \n",
       "63       64         0       2.625         0.98         1  -0.057599   \n",
       "64       65         0       2.667         0.98         1  -0.050359   \n",
       "65       66         0       2.708         0.98         1  -0.072139   \n",
       "66       67         0       2.750         0.98         1  -0.023048   \n",
       "67       68         0       2.792         0.98         1   0.074834   \n",
       "68       69         0       2.833         0.88         1   0.099313   \n",
       "69       70         0       2.875         0.98         1   0.067165   \n",
       "70       71         0       2.917         0.98         1  -0.044946   \n",
       "...     ...       ...         ...          ...       ...        ...   \n",
       "6532   6533         0     272.167         0.98         1   0.358192   \n",
       "6533   6534         0     272.208         0.93         1   0.317517   \n",
       "6534   6535         0     272.250         0.98         1   0.365567   \n",
       "6535   6536         0     272.292         0.93         1   0.324768   \n",
       "6536   6537         0     272.333         0.93         1   0.318829   \n",
       "6537   6538         0     272.375         0.93         1   0.326869   \n",
       "6538   6539         0     272.417         0.98         1   0.335902   \n",
       "6539   6540         0     272.458         0.93         1   0.339839   \n",
       "6540   6541         0     272.500         0.93         1   0.345396   \n",
       "6541   6542         0     272.542         0.93         1   0.354721   \n",
       "6542   6543         0     272.583         0.93         1   0.370091   \n",
       "6543   6544         0     272.625         0.93         1   0.346260   \n",
       "6544   6545         0     272.667         0.93         1   0.374852   \n",
       "6545   6546         0     272.708         0.93         1   0.287790   \n",
       "6546   6547         0     272.750         0.93         1   0.342689   \n",
       "6547   6548         0     272.792         0.98         1   0.263855   \n",
       "6548   6549         0     272.833         0.93         1   0.311539   \n",
       "6549   6550         0     272.875         0.93         1   0.332144   \n",
       "6550   6551         0     272.917         0.98         1   0.324841   \n",
       "6551   6552         0     272.958         0.98         1   0.304509   \n",
       "6552   6553         0     273.000         0.98         1   0.312529   \n",
       "6553   6554         0     273.042         0.98         1   0.294600   \n",
       "6554   6555         0     273.083         0.98         1   0.296551   \n",
       "6555   6556         0     273.125         0.98         1   0.292875   \n",
       "6556   6557         0     273.167         0.98         1   0.379342   \n",
       "6557   6558         0     273.208         0.93         1   0.342119   \n",
       "6558   6559         0     273.250         0.98         1   0.355195   \n",
       "6559   6560         0     273.292         0.93         1   0.357529   \n",
       "6560   6561         0     273.333         0.98         1   0.342333   \n",
       "6561   6562         0     273.375         0.98         1   0.379890   \n",
       "\n",
       "       gaze_0_y   gaze_0_z   gaze_1_x   gaze_1_y   ...      AU12_c   AU14_c  \\\n",
       "12     0.518060  -0.701000  -0.110569   0.437534   ...         0.0      0.0   \n",
       "13     0.604145  -0.618272   0.192178   0.474315   ...         0.0      0.0   \n",
       "32     0.445631  -0.868285  -0.057812   0.164489   ...         0.0      0.0   \n",
       "44     0.000000   0.000000   0.000000   0.000000   ...         1.0      0.0   \n",
       "45     0.571123  -0.820863  -0.251735   0.323956   ...         0.0      1.0   \n",
       "46     0.687563  -0.724284  -0.138799   0.465378   ...         0.0      1.0   \n",
       "47     0.813878  -0.561293  -0.143064   0.347823   ...         0.0      1.0   \n",
       "48     0.826184  -0.557958  -0.227640   0.478376   ...         0.0      1.0   \n",
       "49     0.812299  -0.583107  -0.328687   0.521661   ...         0.0      1.0   \n",
       "50     0.813891  -0.580937  -0.326907   0.572618   ...         0.0      1.0   \n",
       "51     0.784492  -0.618246  -0.278237   0.628173   ...         0.0      1.0   \n",
       "52     0.806096  -0.591771  -0.363057   0.574826   ...         0.0      1.0   \n",
       "53     0.760601  -0.649082  -0.316235   0.578942   ...         0.0      1.0   \n",
       "54     0.763783  -0.642645  -0.314020   0.571981   ...         0.0      1.0   \n",
       "55     0.749218  -0.659142  -0.312687   0.620587   ...         0.0      1.0   \n",
       "56     0.740457  -0.666712  -0.300326   0.642258   ...         0.0      1.0   \n",
       "57     0.788293  -0.607887  -0.344359   0.631019   ...         0.0      1.0   \n",
       "58     0.797743  -0.601931  -0.331173   0.614157   ...         0.0      1.0   \n",
       "59     0.816204  -0.574195  -0.336924   0.614932   ...         0.0      1.0   \n",
       "60     0.810919  -0.582837  -0.350467   0.615993   ...         0.0      1.0   \n",
       "61     0.818532  -0.559988  -0.375479   0.628269   ...         0.0      1.0   \n",
       "62     0.826225  -0.550702  -0.429335   0.626095   ...         0.0      0.0   \n",
       "63     0.813390  -0.578861  -0.367048   0.614610   ...         0.0      0.0   \n",
       "64     0.826329  -0.560932  -0.329420   0.611442   ...         0.0      0.0   \n",
       "65     0.786550  -0.613299  -0.307827   0.604353   ...         0.0      0.0   \n",
       "66     0.808965  -0.587405  -0.264372   0.592010   ...         0.0      0.0   \n",
       "67     0.826053  -0.558602  -0.213845   0.594617   ...         0.0      0.0   \n",
       "68     0.845649  -0.524418  -0.217906   0.601011   ...         0.0      0.0   \n",
       "69     0.844065  -0.532017  -0.227579   0.566541   ...         0.0      0.0   \n",
       "70     0.807528  -0.588114  -0.280023   0.579284   ...         0.0      0.0   \n",
       "...         ...        ...        ...        ...   ...         ...      ...   \n",
       "6532   0.328583  -0.873918  -0.506456   0.728760   ...         0.0      0.0   \n",
       "6533   0.394480  -0.862304  -0.465632   0.754687   ...         0.0      0.0   \n",
       "6534   0.388149  -0.845991  -0.464314   0.752721   ...         0.0      0.0   \n",
       "6535   0.414295  -0.850227  -0.518245   0.758292   ...         0.0      0.0   \n",
       "6536   0.468742  -0.823790  -0.421208   0.742920   ...         0.0      0.0   \n",
       "6537   0.478771  -0.814822  -0.402046   0.732414   ...         0.0      0.0   \n",
       "6538   0.470934  -0.815715  -0.469190   0.700496   ...         0.0      1.0   \n",
       "6539   0.465885  -0.816983  -0.405154   0.606846   ...         0.0      1.0   \n",
       "6540   0.486849  -0.802297  -0.426202   0.712371   ...         0.0      1.0   \n",
       "6541   0.495150  -0.793095  -0.398843   0.703926   ...         0.0      1.0   \n",
       "6542   0.484333  -0.792751  -0.294535   0.595303   ...         0.0      1.0   \n",
       "6543   0.512075  -0.786056  -0.241335   0.570379   ...         0.0      1.0   \n",
       "6544   0.513227  -0.772065  -0.253287   0.607272   ...         0.0      1.0   \n",
       "6545   0.598376  -0.747745  -0.303277   0.662635   ...         0.0      1.0   \n",
       "6546   0.601672  -0.721495  -0.306269   0.662499   ...         0.0      1.0   \n",
       "6547   0.613817  -0.744049  -0.301051   0.657583   ...         0.0      1.0   \n",
       "6548   0.630902  -0.710567  -0.295961   0.660575   ...         0.0      1.0   \n",
       "6549   0.633465  -0.698858  -0.297534   0.661657   ...         0.0      1.0   \n",
       "6550   0.638554  -0.697658  -0.255620   0.671209   ...         0.0      1.0   \n",
       "6551   0.637509  -0.707712  -0.283503   0.655675   ...         0.0      1.0   \n",
       "6552   0.614242  -0.724591  -0.290768   0.633221   ...         0.0      1.0   \n",
       "6553   0.611432  -0.734412  -0.263335   0.644378   ...         0.0      1.0   \n",
       "6554   0.599050  -0.743772  -0.248604   0.656992   ...         0.0      1.0   \n",
       "6555   0.598764  -0.745457  -0.249262   0.663020   ...         0.0      1.0   \n",
       "6556   0.588466  -0.714008  -0.249613   0.651480   ...         0.0      1.0   \n",
       "6557   0.610894  -0.713977  -0.231250   0.666951   ...         0.0      1.0   \n",
       "6558   0.601119  -0.715886  -0.223241   0.680350   ...         0.0      1.0   \n",
       "6559   0.591812  -0.722448  -0.200448   0.688256   ...         0.0      1.0   \n",
       "6560   0.597744  -0.724920  -0.205528   0.696781   ...         0.0      1.0   \n",
       "6561   0.594685  -0.708543  -0.198039   0.703676   ...         0.0      1.0   \n",
       "\n",
       "       AU15_c   AU17_c   AU20_c   AU23_c   AU25_c   AU26_c   AU28_c   AU45_c  \n",
       "12        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "13        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "32        0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "44        1.0      1.0      0.0      1.0      0.0      0.0      1.0      0.0  \n",
       "45        1.0      1.0      0.0      1.0      0.0      0.0      1.0      0.0  \n",
       "46        1.0      1.0      0.0      1.0      0.0      0.0      1.0      0.0  \n",
       "47        1.0      1.0      0.0      1.0      0.0      0.0      0.0      0.0  \n",
       "48        1.0      1.0      0.0      1.0      0.0      0.0      1.0      0.0  \n",
       "49        1.0      1.0      0.0      1.0      0.0      0.0      0.0      0.0  \n",
       "50        1.0      1.0      1.0      1.0      0.0      0.0      0.0      0.0  \n",
       "51        1.0      1.0      1.0      1.0      0.0      0.0      0.0      0.0  \n",
       "52        1.0      1.0      1.0      1.0      0.0      0.0      1.0      0.0  \n",
       "53        1.0      1.0      1.0      1.0      0.0      0.0      1.0      0.0  \n",
       "54        1.0      1.0      1.0      1.0      0.0      0.0      1.0      0.0  \n",
       "55        1.0      1.0      1.0      1.0      0.0      0.0      1.0      0.0  \n",
       "56        1.0      1.0      1.0      1.0      0.0      1.0      1.0      0.0  \n",
       "57        1.0      1.0      1.0      1.0      0.0      1.0      0.0      0.0  \n",
       "58        1.0      1.0      1.0      1.0      0.0      1.0      0.0      0.0  \n",
       "59        0.0      1.0      1.0      1.0      0.0      1.0      0.0      0.0  \n",
       "60        0.0      1.0      1.0      1.0      1.0      1.0      0.0      0.0  \n",
       "61        0.0      1.0      1.0      1.0      1.0      1.0      1.0      0.0  \n",
       "62        0.0      1.0      1.0      1.0      1.0      1.0      1.0      0.0  \n",
       "63        0.0      1.0      1.0      1.0      1.0      1.0      1.0      0.0  \n",
       "64        1.0      1.0      1.0      1.0      1.0      1.0      1.0      0.0  \n",
       "65        1.0      1.0      1.0      1.0      1.0      1.0      1.0      0.0  \n",
       "66        1.0      1.0      1.0      1.0      1.0      1.0      1.0      0.0  \n",
       "67        1.0      1.0      0.0      1.0      1.0      1.0      1.0      0.0  \n",
       "68        1.0      1.0      0.0      1.0      1.0      1.0      1.0      0.0  \n",
       "69        1.0      1.0      0.0      1.0      1.0      1.0      1.0      0.0  \n",
       "70        1.0      1.0      0.0      1.0      1.0      0.0      1.0      0.0  \n",
       "...       ...      ...      ...      ...      ...      ...      ...      ...  \n",
       "6532      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6533      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6534      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6535      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6536      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6537      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6538      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6539      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6540      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6541      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6542      1.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6543      1.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6544      1.0      1.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6545      1.0      1.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6546      1.0      1.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6547      1.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6548      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "6549      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6550      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6551      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6552      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6553      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6554      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6555      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6556      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6557      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6558      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6559      0.0      0.0      1.0      0.0      0.0      0.0      0.0      1.0  \n",
       "6560      0.0      0.0      1.0      0.0      0.0      1.0      0.0      1.0  \n",
       "6561      0.0      0.0      1.0      0.0      0.0      1.0      0.0      1.0  \n",
       "\n",
       "[6137 rows x 714 columns]"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels = labels[\"C_Gaze\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "label_bools = []\n",
    "for i in range(len(labels)):\n",
    "    if labels.values[i] == \"away\":\n",
    "        label_bools.append(False)\n",
    "    else: \n",
    "        label_bools.append(True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(False, 784), (True, 5353)]\n"
     ]
    }
   ],
   "source": [
    "from collections import Counter\n",
    "c = Counter( label_bools )\n",
    "\n",
    "print( c.items() )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegression(C=1.0, class_weight='balanced', dual=False,\n",
       "          fit_intercept=True, intercept_scaling=1, max_iter=10000,\n",
       "          multi_class='warn', n_jobs=None, penalty='l2', random_state=None,\n",
       "          solver='warn', tol=0.0001, verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#new_data is data\n",
    "#labels is annotations\n",
    "\n",
    "new_data_test = new_data[5261:]\n",
    "new_data_train = new_data[:5260]\n",
    "\n",
    "#trains vanilla log reg with unmodified data using l2 regularization\n",
    "labels_test = label_bools[5261:]\n",
    "labels_train = label_bools[:5260]\n",
    "LogReg = LogisticRegression(max_iter=10000, penalty='l2', tol=.0001, class_weight=\"balanced\")\n",
    "\n",
    "LogReg.fit(new_data_train, labels_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [],
   "source": [
    "#uses model to predict on test data\n",
    "y_pred = LogReg.predict(new_data_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 66,  48],\n",
       "       [ 64, 698]])"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#evaluates results\n",
    "from sklearn.metrics import confusion_matrix\n",
    "confusion_matrix = confusion_matrix(labels_test, y_pred)\n",
    "confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 74,  40],\n",
       "       [ 50, 712]])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#shortens the data to only take leftmost n features\n",
    "new_data_train_short = new_data_train.iloc[:,0:160]\n",
    "new_data_test_short = new_data_test.iloc[:,0:160]\n",
    "#uses fewer featured data to train log reg\n",
    "LogReg = LogisticRegression(max_iter=10000, penalty='l2', tol=.0001, class_weight=\"balanced\")\n",
    "\n",
    "LogReg.fit(new_data_train_short, labels_train)\n",
    "\n",
    "y_pred = LogReg.predict(new_data_test_short)\n",
    "\n",
    "from sklearn.metrics import confusion_matrix\n",
    "confusion_matrix = confusion_matrix(labels_test, y_pred)\n",
    "confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(C=0.1, cache_size=200, class_weight=None, coef0=0.0,\n",
       "  decision_function_shape='ovr', degree=3, gamma=1e-11, kernel='rbf',\n",
       "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
       "  tol=1e-05, verbose=False)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#fits svm to data\n",
    "from sklearn import svm\n",
    "clf = svm.SVC(gamma=0.00000000001, C=.1, tol=.00001)\n",
    "clf.fit(new_data_train_short, labels_train)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  0, 114],\n",
       "       [  0, 762]])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#evaluates svm\n",
    "y_pred = clf.predict(new_data_test_short)\n",
    "\n",
    "from sklearn.metrics import confusion_matrix\n",
    "confusion_matrix = confusion_matrix(labels_test, y_pred)\n",
    "confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/site-packages/sklearn/preprocessing/data.py:617: DataConversionWarning: Data with input dtype int64, float64 were all converted to float64 by StandardScaler.\n",
      "  return self.partial_fit(X, y)\n",
      "/usr/local/lib/python2.7/site-packages/sklearn/base.py:462: DataConversionWarning: Data with input dtype int64, float64 were all converted to float64 by StandardScaler.\n",
      "  return self.fit(X, **fit_params).transform(X)\n"
     ]
    }
   ],
   "source": [
    "#reduces data dimensionality\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "pca = PCA(n_components=200)\n",
    "new_data_train_pca = pca.fit_transform(StandardScaler().fit_transform(new_data_train))\n",
    "new_data_test_pca = pca.fit_transform(StandardScaler().fit_transform(new_data_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 50,  64],\n",
       "       [168, 594]])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#runs log reg on pca dimensionaity reduced data\n",
    "LogReg = LogisticRegression(max_iter=10000, penalty='l2', tol=.0001)\n",
    "\n",
    "LogReg.fit(new_data_train_pca, labels_train)\n",
    "\n",
    "y_pred = LogReg.predict(new_data_test_pca)\n",
    "\n",
    "from sklearn.metrics import confusion_matrix\n",
    "confusion_matrix = confusion_matrix(labels_test, y_pred)\n",
    "confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Length mismatch: Expected axis has 201 elements, new values have 3 elements",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-22-410600c30a5b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mtest_pd2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnew_data_train_pca\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mgraph_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconcat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mtest_pd2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtest_pd\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mgraph_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'principal component 1'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'principal component 2'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'label'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python2.7/site-packages/pandas/core/generic.pyc\u001b[0m in \u001b[0;36m__setattr__\u001b[0;34m(self, name, value)\u001b[0m\n\u001b[1;32m   4383\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4384\u001b[0m             \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4385\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4386\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4387\u001b[0m             \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/properties.pyx\u001b[0m in \u001b[0;36mpandas._libs.properties.AxisProperty.__set__\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python2.7/site-packages/pandas/core/generic.pyc\u001b[0m in \u001b[0;36m_set_axis\u001b[0;34m(self, axis, labels)\u001b[0m\n\u001b[1;32m    643\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    644\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_set_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 645\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    646\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_clear_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    647\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python2.7/site-packages/pandas/core/internals.pyc\u001b[0m in \u001b[0;36mset_axis\u001b[0;34m(self, axis, new_labels)\u001b[0m\n\u001b[1;32m   3321\u001b[0m             raise ValueError(\n\u001b[1;32m   3322\u001b[0m                 \u001b[0;34m'Length mismatch: Expected axis has {old} elements, new '\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3323\u001b[0;31m                 'values have {new} elements'.format(old=old_len, new=new_len))\n\u001b[0m\u001b[1;32m   3324\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3325\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnew_labels\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Length mismatch: Expected axis has 201 elements, new values have 3 elements"
     ]
    }
   ],
   "source": [
    "#grabs data to graph\n",
    "#note: pca needs to reduce to 2 for this to work\n",
    "test_pd = pd.DataFrame(data=labels_train)\n",
    "test_pd2 = pd.DataFrame(data=new_data_train_pca)\n",
    "graph_data = pd.concat([test_pd2, test_pd], axis = 1)\n",
    "graph_data.columns = ['principal component 1', 'principal component 2', 'label']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#graphs pca data\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "fig = plt.figure(figsize = (8,8))\n",
    "ax = fig.add_subplot(1,1,1) \n",
    "ax.set_xlabel('Principal Component 1', fontsize = 15)\n",
    "ax.set_ylabel('Principal Component 2', fontsize = 15)\n",
    "ax.set_title('OpenFace Visualization', fontsize = 20)\n",
    "targets = ['OpenFace']\n",
    "ax.scatter(new_data_train_pca[:,0] , new_data_train_pca[:,1] , c = 'r' , s = 50)\n",
    "ax.legend(targets)\n",
    "ax.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#graphs pca data with colors for true and false, true on top\n",
    "fig = plt.figure(figsize = (8,8))\n",
    "ax = fig.add_subplot(1,1,1) \n",
    "ax.set_xlabel('Principal Component 1', fontsize = 15)\n",
    "ax.set_ylabel('Principal Component 2', fontsize = 15)\n",
    "ax.set_title('2 component PCA', fontsize = 20)\n",
    "targets = [False, True]\n",
    "colors = ['r', 'b']\n",
    "for target, color in zip(targets,colors):\n",
    "    indicesToKeep = graph_data['label'] == target\n",
    "    ax.scatter(graph_data.loc[indicesToKeep, 'principal component 1']\n",
    "               , graph_data.loc[indicesToKeep, 'principal component 2']\n",
    "               , c = color\n",
    "               , s = 50)\n",
    "ax.legend(targets)\n",
    "ax.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#graphs pca data with colors for true and false, false on top\n",
    "fig = plt.figure(figsize = (8,8))\n",
    "ax = fig.add_subplot(1,1,1) \n",
    "ax.set_xlabel('Principal Component 1', fontsize = 15)\n",
    "ax.set_ylabel('Principal Component 2', fontsize = 15)\n",
    "ax.set_title('2 component PCA', fontsize = 20)\n",
    "targets = [True, False]\n",
    "colors = ['r', 'b']\n",
    "for target, color in zip(targets,colors):\n",
    "    indicesToKeep = graph_data['label'] == target\n",
    "    ax.scatter(graph_data.loc[indicesToKeep, 'principal component 1']\n",
    "               , graph_data.loc[indicesToKeep, 'principal component 2']\n",
    "               , c = color\n",
    "               , s = 50)\n",
    "ax.legend(targets)\n",
    "ax.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#trys svm with pca data\n",
    "from sklearn import svm\n",
    "clf = svm.SVC(gamma=1)\n",
    "clf.fit(new_data_train_pca, labels_train)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#evaluates svm with pca data\n",
    "y_pred = clf.predict(new_data_test_pca)\n",
    "\n",
    "from sklearn.metrics import confusion_matrix\n",
    "confusion_matrix = confusion_matrix(labels_test, y_pred)\n",
    "confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#selects k most significant features\n",
    "from sklearn.feature_selection import SelectKBest\n",
    "from sklearn.feature_selection import f_classif\n",
    "\n",
    "new_data_train_feature_selection = SelectKBest(f_classif, k=80).fit_transform(new_data_train, labels_train)\n",
    "new_data_test_feature_selection = SelectKBest(f_classif, k=80).fit_transform(new_data_test, labels_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#trains log reg with k most significant features\n",
    "LogReg = LogisticRegression(max_iter=10000, penalty='l2', tol=.0001, class_weight=\"balanced\")\n",
    "\n",
    "LogReg.fit(new_data_train_feature_selection, labels_train)\n",
    "\n",
    "y_pred = LogReg.predict(new_data_test_feature_selection)\n",
    "\n",
    "from sklearn.metrics import confusion_matrix\n",
    "confusion_matrix = confusion_matrix(labels_test, y_pred)\n",
    "confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KernelPCA(alpha=1.0, coef0=1, copy_X=True, degree=3, eigen_solver='auto',\n",
       "     fit_inverse_transform=False, gamma=10, kernel='rbf',\n",
       "     kernel_params=None, max_iter=None, n_components=4, n_jobs=None,\n",
       "     random_state=None, remove_zero_eig=False, tol=0)"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#creates a kernel pca with gamma g and n components\n",
    "from sklearn.decomposition import KernelPCA\n",
    "kpca = KernelPCA(kernel=\"rbf\", gamma=10, n_components=4)\n",
    "kpca.fit(new_data_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_data_train_kpca = kpca.transform(new_data_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KernelPCA(alpha=1.0, coef0=1, copy_X=True, degree=3, eigen_solver='auto',\n",
       "     fit_inverse_transform=False, gamma=20, kernel='rbf',\n",
       "     kernel_params=None, max_iter=None, n_components=4, n_jobs=None,\n",
       "     random_state=None, remove_zero_eig=False, tol=0)"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kpca2 = KernelPCA(kernel=\"rbf\", gamma=20, n_components=4)\n",
    "kpca2.fit(new_data_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_data_test_kpca = kpca2.transform(new_data_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#sets up kernel pca data to be graphed\n",
    "test_pd = pd.DataFrame(data=labels_train)\n",
    "test_pd2 = pd.DataFrame(data=new_data_train_kpca)\n",
    "graph_data2 = pd.concat([test_pd2, test_pd], axis = 1)\n",
    "graph_data2.columns = ['principal component 1', 'principal component 2', 'label']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#graphs kernel pca data\n",
    "import matplotlib.pyplot as plt\n",
    "fig = plt.figure(figsize = (8,8))\n",
    "ax = fig.add_subplot(1,1,1) \n",
    "ax.set_xlabel('Principal Component 1', fontsize = 15)\n",
    "ax.set_ylabel('Principal Component 2', fontsize = 15)\n",
    "ax.set_title('2 component PCA', fontsize = 20)\n",
    "targets = [True, False]\n",
    "colors = ['r', 'b']\n",
    "for target, color in zip(targets,colors):\n",
    "    indicesToKeep = graph_data2['label'] == target\n",
    "    ax.scatter(graph_data2.loc[indicesToKeep, 'principal component 1']\n",
    "               , graph_data2.loc[indicesToKeep, 'principal component 2']\n",
    "               , c = color\n",
    "               , s = 50)\n",
    "ax.legend(targets)\n",
    "ax.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[LibSVM]"
     ]
    },
    {
     "data": {
      "text/plain": [
       "SVC(C=1.0, cache_size=10000, class_weight=None, coef0=0.0,\n",
       "  decision_function_shape='ovr', degree=10, gamma='scale', kernel='rbf',\n",
       "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
       "  tol=1e-05, verbose=True)"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#fits svm to kpca data\n",
    "from sklearn import svm\n",
    "clf = svm.SVC(gamma='scale', tol=.00001)\n",
    "clf.fit(new_data_train_kpca, labels_train) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  0, 114],\n",
       "       [  0, 762]])"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#evaluates kernel pca data svm\n",
    "y_pred = clf.predict(new_data_test_kpca)\n",
    "\n",
    "from sklearn.metrics import confusion_matrix\n",
    "confusion_matrix = confusion_matrix(labels_test, y_pred)\n",
    "confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegression(C=1.0, class_weight='balanced', dual=False,\n",
       "          fit_intercept=True, intercept_scaling=1, max_iter=10000,\n",
       "          multi_class='warn', n_jobs=None, penalty='l2', random_state=None,\n",
       "          solver='warn', tol=0.0001, verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#trains log reg with kernel pca data\n",
    "LogReg = LogisticRegression(max_iter=10000, penalty='l2', tol=.0001, class_weight=\"balanced\")\n",
    "\n",
    "LogReg.fit(new_data_train_kpca, labels_train)\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = LogReg.predict(new_data_test_kpca)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 63,  51],\n",
       "       [412, 350]])"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "confusion_matrix = confusion_matrix(labels_test, y_pred)\n",
    "confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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