{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "ecg = pd.read_csv(\"ECG.csv\")\n",
    "eeg = pd.read_csv(\"EEG.csv\")\n",
    "labels = pd.read_csv(\"Labels.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "Arousal = labels[labels['Label'] == 'Arousal']\n",
    "Dominance = labels[labels['Label'] == 'Dominance']\n",
    "Valence = labels[labels['Label'] == 'Valence']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "labels.shape[0] == Arousal.shape[0] + Dominance.shape[0] + Valence.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "Arousal = Arousal.rename({'Score':'Arousal'}, axis=1)\n",
    "Dominance = Dominance.rename({'Score':'Dominance'}, axis=1)\n",
    "Valence = Valence.rename({'Score':'Valence'}, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['ECG1', 'ECG2', 'Person', 'Movie'], dtype='object')\n",
      "Index(['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12',\n",
      "       '13', 'Person', 'Movie'],\n",
      "      dtype='object')\n",
      "Index(['Score', 'Person', 'Movie', 'Label'], dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(ecg.columns)\n",
    "print(eeg.columns)\n",
    "print(labels.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10975232, 16)\n",
      "(21950464, 4)\n"
     ]
    }
   ],
   "source": [
    "print(eeg.shape)\n",
    "print(ecg.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "ecg = pd.merge(ecg, Arousal.drop('Label', axis=1), how='left', on=['Person', 'Movie'])\n",
    "ecg = pd.merge(ecg, Dominance.drop('Label', axis=1), how='left', on=['Person', 'Movie'])\n",
    "ecg = pd.merge(ecg, Valence.drop('Label', axis=1), how='left', on=['Person', 'Movie'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "eeg = pd.merge(eeg, Arousal.drop('Label', axis=1), how='left', on=['Person', 'Movie'])\n",
    "eeg = pd.merge(eeg, Dominance.drop('Label', axis=1), how='left', on=['Person', 'Movie'])\n",
    "eeg = pd.merge(eeg, Valence.drop('Label', axis=1), how='left', on=['Person', 'Movie'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10975232, 19)\n"
     ]
    }
   ],
   "source": [
    "print(eeg.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10975232, 19)\n",
      "(21950464, 7)\n"
     ]
    }
   ],
   "source": [
    "print(eeg.shape)\n",
    "print(ecg.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>Person</th>\n",
       "      <th>Movie</th>\n",
       "      <th>Arousal</th>\n",
       "      <th>Dominance</th>\n",
       "      <th>Valence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4388.2</td>\n",
       "      <td>4102.6</td>\n",
       "      <td>4219.5</td>\n",
       "      <td>4465.1</td>\n",
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       "      <td>3953.8</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4375.9</td>\n",
       "      <td>4093.8</td>\n",
       "      <td>4252.8</td>\n",
       "      <td>4522.6</td>\n",
       "      <td>4435.9</td>\n",
       "      <td>4411.8</td>\n",
       "      <td>4488.7</td>\n",
       "      <td>4108.7</td>\n",
       "      <td>4399.5</td>\n",
       "      <td>4384.6</td>\n",
       "      <td>4007.7</td>\n",
       "      <td>4466.7</td>\n",
       "      <td>4372.8</td>\n",
       "      <td>4247.2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4378.5</td>\n",
       "      <td>4091.3</td>\n",
       "      <td>4230.3</td>\n",
       "      <td>4488.2</td>\n",
       "      <td>4370.3</td>\n",
       "      <td>4402.6</td>\n",
       "      <td>4461.0</td>\n",
       "      <td>4077.4</td>\n",
       "      <td>4378.5</td>\n",
       "      <td>4328.7</td>\n",
       "      <td>3986.2</td>\n",
       "      <td>4461.0</td>\n",
       "      <td>4328.2</td>\n",
       "      <td>4203.6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4393.8</td>\n",
       "      <td>4101.0</td>\n",
       "      <td>4193.3</td>\n",
       "      <td>4419.0</td>\n",
       "      <td>4270.3</td>\n",
       "      <td>4392.3</td>\n",
       "      <td>4411.3</td>\n",
       "      <td>3982.6</td>\n",
       "      <td>4336.4</td>\n",
       "      <td>4213.3</td>\n",
       "      <td>3930.3</td>\n",
       "      <td>4442.6</td>\n",
       "      <td>4261.0</td>\n",
       "      <td>4100.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4396.4</td>\n",
       "      <td>4108.7</td>\n",
       "      <td>4210.8</td>\n",
       "      <td>4436.4</td>\n",
       "      <td>4310.8</td>\n",
       "      <td>4401.0</td>\n",
       "      <td>4426.7</td>\n",
       "      <td>3980.5</td>\n",
       "      <td>4349.7</td>\n",
       "      <td>4238.5</td>\n",
       "      <td>3945.1</td>\n",
       "      <td>4446.7</td>\n",
       "      <td>4289.7</td>\n",
       "      <td>4115.4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        0       1       2       3       4       5       6       7       8  \\\n",
       "0  4388.2  4102.6  4219.5  4465.1  4370.8  4399.5  4443.1  4023.1  4365.1   \n",
       "1  4375.9  4093.8  4252.8  4522.6  4435.9  4411.8  4488.7  4108.7  4399.5   \n",
       "2  4378.5  4091.3  4230.3  4488.2  4370.3  4402.6  4461.0  4077.4  4378.5   \n",
       "3  4393.8  4101.0  4193.3  4419.0  4270.3  4392.3  4411.3  3982.6  4336.4   \n",
       "4  4396.4  4108.7  4210.8  4436.4  4310.8  4401.0  4426.7  3980.5  4349.7   \n",
       "\n",
       "        9      10      11      12      13  Person  Movie  Arousal  Dominance  \\\n",
       "0  4310.3  3953.8  4454.4  4326.2  4165.1       1      1        3          2   \n",
       "1  4384.6  4007.7  4466.7  4372.8  4247.2       1      1        3          2   \n",
       "2  4328.7  3986.2  4461.0  4328.2  4203.6       1      1        3          2   \n",
       "3  4213.3  3930.3  4442.6  4261.0  4100.0       1      1        3          2   \n",
       "4  4238.5  3945.1  4446.7  4289.7  4115.4       1      1        3          2   \n",
       "\n",
       "   Valence  \n",
       "0        4  \n",
       "1        4  \n",
       "2        4  \n",
       "3        4  \n",
       "4        4  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eeg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "ecg.to_csv(\"ECG_Labelled.csv\")\n",
    "eeg.to_csv(\"EEG_Labelled.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Combine ECG and EEG"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/sf/.local/lib/python3.6/site-packages/numpy/lib/arraysetops.py:472: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "  mask |= (ar1 == a)\n"
     ]
    }
   ],
   "source": [
    "ecg = pd.read_csv(\"ECG_Labelled.csv\", index_col=0)\n",
    "eeg = pd.read_csv(\"EEG_Labelled.csv\", index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>Person</th>\n",
       "      <th>Movie</th>\n",
       "      <th>Arousal</th>\n",
       "      <th>Dominance</th>\n",
       "      <th>Valence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>4388.2</td>\n",
       "      <td>4102.6</td>\n",
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       "      <th>1</th>\n",
       "      <td>4375.9</td>\n",
       "      <td>4093.8</td>\n",
       "      <td>4252.8</td>\n",
       "      <td>4522.6</td>\n",
       "      <td>4435.9</td>\n",
       "      <td>4411.8</td>\n",
       "      <td>4488.7</td>\n",
       "      <td>4108.7</td>\n",
       "      <td>4399.5</td>\n",
       "      <td>4384.6</td>\n",
       "      <td>4007.7</td>\n",
       "      <td>4466.7</td>\n",
       "      <td>4372.8</td>\n",
       "      <td>4247.2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
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       "      <th>2</th>\n",
       "      <td>4378.5</td>\n",
       "      <td>4091.3</td>\n",
       "      <td>4230.3</td>\n",
       "      <td>4488.2</td>\n",
       "      <td>4370.3</td>\n",
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       "      <td>4077.4</td>\n",
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       "      <td>3986.2</td>\n",
       "      <td>4461.0</td>\n",
       "      <td>4328.2</td>\n",
       "      <td>4203.6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4393.8</td>\n",
       "      <td>4101.0</td>\n",
       "      <td>4193.3</td>\n",
       "      <td>4419.0</td>\n",
       "      <td>4270.3</td>\n",
       "      <td>4392.3</td>\n",
       "      <td>4411.3</td>\n",
       "      <td>3982.6</td>\n",
       "      <td>4336.4</td>\n",
       "      <td>4213.3</td>\n",
       "      <td>3930.3</td>\n",
       "      <td>4442.6</td>\n",
       "      <td>4261.0</td>\n",
       "      <td>4100.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4396.4</td>\n",
       "      <td>4108.7</td>\n",
       "      <td>4210.8</td>\n",
       "      <td>4436.4</td>\n",
       "      <td>4310.8</td>\n",
       "      <td>4401.0</td>\n",
       "      <td>4426.7</td>\n",
       "      <td>3980.5</td>\n",
       "      <td>4349.7</td>\n",
       "      <td>4238.5</td>\n",
       "      <td>3945.1</td>\n",
       "      <td>4446.7</td>\n",
       "      <td>4289.7</td>\n",
       "      <td>4115.4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "        0       1       2       3       4       5       6       7       8  \\\n",
       "0  4388.2  4102.6  4219.5  4465.1  4370.8  4399.5  4443.1  4023.1  4365.1   \n",
       "1  4375.9  4093.8  4252.8  4522.6  4435.9  4411.8  4488.7  4108.7  4399.5   \n",
       "2  4378.5  4091.3  4230.3  4488.2  4370.3  4402.6  4461.0  4077.4  4378.5   \n",
       "3  4393.8  4101.0  4193.3  4419.0  4270.3  4392.3  4411.3  3982.6  4336.4   \n",
       "4  4396.4  4108.7  4210.8  4436.4  4310.8  4401.0  4426.7  3980.5  4349.7   \n",
       "\n",
       "        9      10      11      12      13  Person  Movie  Arousal  Dominance  \\\n",
       "0  4310.3  3953.8  4454.4  4326.2  4165.1       1      1        3          2   \n",
       "1  4384.6  4007.7  4466.7  4372.8  4247.2       1      1        3          2   \n",
       "2  4328.7  3986.2  4461.0  4328.2  4203.6       1      1        3          2   \n",
       "3  4213.3  3930.3  4442.6  4261.0  4100.0       1      1        3          2   \n",
       "4  4238.5  3945.1  4446.7  4289.7  4115.4       1      1        3          2   \n",
       "\n",
       "   Valence  \n",
       "0        4  \n",
       "1        4  \n",
       "2        4  \n",
       "3        4  \n",
       "4        4  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eeg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "ecg_downsampled = ecg[np.arange(len(ecg)) % 2 == 0] # deleting all odd indices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "44544"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecg_downsampled[(ecg_downsampled['Person'] == 1) & (ecg_downsampled['Movie'] == 3)].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "ecg_downsampled.reset_index(inplace=True, drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ECG1</th>\n",
       "      <th>ECG2</th>\n",
       "      <th>Person</th>\n",
       "      <th>Movie</th>\n",
       "      <th>Arousal</th>\n",
       "      <th>Dominance</th>\n",
       "      <th>Valence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2046</td>\n",
       "      <td>2056</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2039</td>\n",
       "      <td>2059</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2041</td>\n",
       "      <td>2060</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2039</td>\n",
       "      <td>2059</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2040</td>\n",
       "      <td>2056</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ECG1  ECG2  Person  Movie  Arousal  Dominance  Valence\n",
       "0  2046  2056       1      1        3          2        4\n",
       "1  2039  2059       1      1        3          2        4\n",
       "2  2041  2060       1      1        3          2        4\n",
       "3  2039  2059       1      1        3          2        4\n",
       "4  2040  2056       1      1        3          2        4"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecg_downsampled.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "44544"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eeg[(eeg['Person'] == 1) & (eeg['Movie'] == 3)].shape[0] # check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eeg.shape[0] == ecg_downsampled.shape[0] # check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12',\n",
       "       '13', 'Person', 'Movie', 'Arousal', 'Dominance', 'Valence'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eeg.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "del ecg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "combined = pd.concat([eeg, ecg_downsampled.drop(['Person', 'Movie', 'Arousal', 'Dominance', 'Valence'], axis=1)], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10975232, 7)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecg_downsampled.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10975232, 21)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12',\n",
       "       '13', 'Person', 'Movie', 'Arousal', 'Dominance', 'Valence', 'ECG1',\n",
       "       'ECG2'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "combined.to_csv(\"DREAMER_combined.csv\")"
   ]
  }
 ],
 "metadata": {
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   "display_name": "Python 3",
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