a b/WESAD/WESAD_Analysis.ipynb
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{
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 "cells": [
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  {
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   "cell_type": "markdown",
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   "metadata": {},
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   "source": [
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    "# WESAD Dataset Analysis"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "import numpy as np\n",
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    "import matplotlib as mpl\n",
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    "import matplotlib.pyplot as plt\n",
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    "import seaborn as sns\n",
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    "import pandas as pd"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "df = pd.read_csv(\"../../WESAD/allchest.csv\")"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "df = df[df['ID'] == 2]"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "df.reset_index(inplace=True, drop=True)"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "df['label'].unique()"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "sns.set_context(\"paper\", rc={\"lines.linewidth\": 2.5})\n",
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    "sns.set_palette(\"binary_d\")"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "# Neutral\n",
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    "sns.lineplot(data=df[df['label'] == 1].reset_index(drop=True)['chestResp'])\n",
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    "plt.ylabel('RESP')\n",
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    "plt.xlabel('Sequential Data-Points')\n",
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    "plt.show()"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {
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    "scrolled": false
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   },
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   "outputs": [],
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   "source": [
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    "# Stress\n",
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    "sns.lineplot(data=df[df['label'] == 2].reset_index(drop=True)['chestResp'])\n",
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    "plt.ylabel('RESP')\n",
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    "plt.xlabel('Sequential Data-Points')\n",
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    "plt.show()"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "# Neutral\n",
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    "sns.lineplot(data=df[df['label'] == 1].reset_index(drop=True).iloc[400000:420000]['chestResp'])\n",
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    "plt.ylabel('RESP')\n",
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    "plt.xlabel('Sequential Data-Points')\n",
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    "plt.show()"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "# Stress\n",
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    "sns.lineplot(data=df[df['label'] == 2].reset_index(drop=True).iloc[50000:70000]['chestResp'])\n",
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    "plt.ylabel('RESP')\n",
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    "plt.xlabel('Sequential Data-Points')\n",
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    "plt.show()"
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   ]
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  }
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 ],
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 "metadata": {
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  "kernelspec": {
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   "display_name": "Python 3",
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   "language": "python",
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   "name": "python3"
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  },
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  "language_info": {
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   "codemirror_mode": {
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    "name": "ipython",
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    "version": 3
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   },
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   "file_extension": ".py",
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   "mimetype": "text/x-python",
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   "name": "python",
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   "nbconvert_exporter": "python",
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   "pygments_lexer": "ipython3",
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   "version": "3.7.3"
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  }
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 },
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 "nbformat": 4,
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 "nbformat_minor": 2
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}