{

 "cells": [

  {

   "cell_type": "code",

   "execution_count": 1,

   "metadata": {},

   "outputs": [],

   "source": [

    "import numpy as np\n",

    "import matplotlib as mpl\n",

    "import matplotlib.pyplot as plt\n",

    "import seaborn as sns\n",

    "import pandas as pd"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 3,

   "metadata": {},

   "outputs": [],

   "source": [

    "dfeda = pd.read_csv(\"../EDA_New.csv\")"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 4,

   "metadata": {},

   "outputs": [

    {

     "data": {

      "text/plain": [

       "array(['no stress', 'time pressure', 'interruption'], dtype=object)"

      ]

     },

     "execution_count": 4,

     "metadata": {},

     "output_type": "execute_result"

    }

   ],

   "source": [

    "dfeda['condition'].unique()"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 5,

   "metadata": {},

   "outputs": [],

   "source": [

    "dfeda['condition'].replace('time pressure', 'interruption', inplace=True)\n",

    "dfeda['condition'].replace('interruption', 1, inplace=True)\n",

    "dfeda['condition'].replace('no stress', 0, inplace=True)"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 162,

   "metadata": {},

   "outputs": [],

   "source": [

    "a = dfeda[dfeda['condition']==0].reset_index()[5000:20001].reset_index()['SC']"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 173,

   "metadata": {},

   "outputs": [

    {

     "data": {

      "text/plain": [

       "Text(0.5, 0, 'Sequential Data-Points')"

      ]

     },

     "execution_count": 173,

     "metadata": {},

     "output_type": "execute_result"

    },

    {

     "data": {

      "image/png": "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\n",

      "text/plain": [

       "<Figure size 432x288 with 1 Axes>"

      ]

     },

     "metadata": {

      "needs_background": "light"

     },

     "output_type": "display_data"

    },

    {

     "data": {

      "image/png": 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\n",

      "text/plain": [

       "<Figure size 432x288 with 1 Axes>"

      ]

     },

     "metadata": {

      "needs_background": "light"

     },

     "output_type": "display_data"

    }

   ],

   "source": [

    "sns.set_context(\"paper\", rc={\"lines.linewidth\": 2.5})\n",

    "sns.set_palette(\"binary_d\")\n",

    "fig, ax = plt.subplots()\n",

    "ax.tick_params('x', labelbottom=False, bottom=False)\n",

    "ax.tick_params()\n",

    "g = sns.lineplot(data=a)\n",

    "g.set_ylim(0, 0.12)\n",

    "plt.ylabel('Electrodermal Activity')\n",

    "plt.xlabel('Sequential Data-Points')"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 43,

   "metadata": {},

   "outputs": [],

   "source": [

    "a = pd.concat([dfeda[dfeda['condition']==1].reset_index()['SC'][40175:40200], dfeda[dfeda['condition']==1].reset_index()['SC'][40375:40400], dfeda[dfeda['condition']==1].reset_index()['SC'][50280:50300]], axis=0)"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 46,

   "metadata": {},

   "outputs": [],

   "source": [

    "a = a.reset_index()"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 49,

   "metadata": {},

   "outputs": [

    {

     "data": {

      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXMAAADwCAYAAADy6YRQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAJgklEQVR4nO3cQaideXnH8d9j0qJYnXAXihuhURsXBZtRs+gMzqqb4q7DuCjYgTTUXSk1IBb0SrtoXUjFjUsHsdBq6XK60PaGmWYIoRTKlI7GNnWRlkLJnTK1I5ObPl3kZnJyvfecc+feq+PD5wMv5D3/9z3vP+/iy8v/nHOruwPAz7a3/LQnAMDRiTnAAGIOMICYAwwg5gADiDnAACtjXlU/V1V/V1UvV9WT+4x/vKpeqKqrVfXRk5kmAMucXuOYnSRPJvmdvQNVdSrJHyb5WJJ3JvnzJI8f5wQBWG1lzPver4r+o6r2G/5Aku919ytJXtl9in9rd//omOcJwBLrPJkvs5Fke2H/5d3X/v3+C1W1meTzR7wOAEm6e98n66PGfDvJmYX9R5Lc3nPhzSSbi69VVfszAgCHc8AKSZKjx/xGkl+qqrcneUeSHUssAD95a8W8qv4iyUeS/E9VXci9p++/6u7v7i6jfDtJJ/m9k5ooAAern8Zyh2UWgMOrqgPXzP1oCGAAMQcYQMwBBhBzgAHEHGAAMQcYQMwBBhBzgAHEHGAAMQcYQMwBBhBzgAHEHGAAMQcYQMwBBhBzgAHEHGAAMQcYQMwBBhBzgAHEHGAAMQcYQMwBBhBzgAHEHGAAMQcYQMwBBhBzgAHEHGAAMQcYQMwBBhBzgAHEHGAAMQcYQMwBBhBzgAHWinlVXaqqq1W1VVVn94z9VlVdr6prVfW7JzNNAJap7l5+QNVGkmeTPJbkfJLL3f3UwvhLST6c5NUkLyb5le5+bcV79qrrAvCwqkp3135j6zyZX0iy1d073X09ybk94y8l+YUkb8u9oN/dc/HNqurF7fD/BQCWWSfmG0m2l5zzrST/kHtRf6a7H4p5d292dy1uR5oxAD9mnZhvJzmzsP96rKvqHUk+m3tP6+9L8htV9d5jnSEAK60T82tJnqiqU1X1aJIbC2P/l+S1JD/cXSf/3yTvPP5pArDM6VUHdPftqnomyXNJ7iS5WFVPJ7nZ3Veq6mtJXthdC3+hu188yQkD8ONWfpvlRC7q2ywAh3bUb7MA8CYn5gADiDnAAGIOMICYAwwg5gADiDnAAGIOMICYAwwg5gADiDnAAGIOMICYAwwg5gADiDnAAGIOMICYAwwg5gADiDnAAGIOMICYAwwg5gADiDnAAGIOMICYAwwg5gADiDnAAGIOMICYAwwg5gADiDnAAGIOMICYAwwg5gADiDnAAGvFvKouVdXVqtqqqrN7xt5VVd+sqr+pqj87mWkCsEx19/IDqjaSPJvksSTnk1zu7qcWxr+eZLO7/2Xti1b1qusC8LCqSnfXfmPrPJlfSLLV3TvdfT3JuYU3PpXkg0k2q+pKVX3iWGYMwKGsE/ONJNsHnPOuJB9K8kdJfj3JZ3af5F9XVZtV1YvbUScNwMPWifl2kjML+3f3jP2gu7/b3T9M8vdJ3r94cndvdnctbkeeNQAPWSfm15I8UVWnqurRJDfuD3T3j5Lcqqp37y65/HKSH5zMVAE4yOlVB3T37ap6JslzSe4kuVhVTye52d1Xknw6yTeT/HySb3T3f57gfAHYx8pvs5zIRX2bBeDQjvptFgDe5MQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGWCvmVXWpqq5W1VZVnd1n/JGq+q+qevL4pwjAKitjXlUbSX47yceSXE7yx/sc9ukk1453agCsa50n8wtJtrp7p7uvJzm3OFhV705yNsn1/U6uqs2q6sXtyLMG4CHrxHwjyfaSc/4gyZ8cdHJ3b3Z3LW5vYJ4ALLFOzLeTnFnYv3v/H1X1i0nOdPc/HvfEAFjf6TWOuZbkc1V1KsmHktxYGDuf5H1V9ddJ3p/klar65+7+p+OfKgAHqe7VS9hV9akkn0xyJ8nFJI8nudndVxaO2UzyYnd/a43363WuC8ADVZWDlqrXivlxE3OAw1sWcz8aAhhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAcQcYAAxBxhAzAEGEHOAAdaKeVVdqqqrVbVVVWcXXj9TVd+pqueq6vmqevTkpgrAQaq7lx9QtZHk2SSPJTmf5HJ3P7U79rYkG919q6o+mOQr3f1rKy9a1auuC8DDqirdXfuNnV7j/AtJtrp7J8n1qjp3f6C7X01ya3f3tSQ7R50sAIe3zjLLRpLtZedUVSX5UpIv7jO2WVW9uL3h2QKwr3Vivp3kzML+3X2O+XLuPb3/7d6B7t7s7lrc3uBcATjAOjG/luSJqjq1+wHnjcXBqvpskp3u/tOTmCAAq638ADRJqupTST6Z5E6Si0keT3Izyb8m+bckzyfpJLe6+zfXeD8fgAIc0rIPQNeK+XETc4DDWxZzPxoCGEDMAQYQc4ABxBxgADEHGEDMAQYQc4ABxBxgADEHGEDMAQYQc4ABxBxgADEHGEDMAQYQc4ABxBxgADEHGEDMAQYQc4ABxBxgADEHGEDMAQYQc4ABxBxgADEHGEDMAQYQc4ABxBxgADEHGEDMAQYQc4ABxBxgADEHGEDMAQYQc4ABxBxggLViXlWXqupqVW1V1dk9Yx/dHXuhqj5+MtMEYJnq7uUHVG0keTbJY0nOJ7nc3U8tjD+f5BNJ/jvJc0k+0t13V7xnr7ouAA+rqnR37Td2eo3zLyTZ6u6dJNer6tzCG781yenuvrW7/70kH0jy0sIxm0k+v9+kADge68R8I8n2wv5b9oy9vLD/8u5rr+vuzSSbi6/tPpmredyLRe7FA+7FA+7FA1V14JLGOmvm20nOLOzfXTL2SJLbh5odAEe2TsyvJXmiqk5V1aNJbtwf6O5Xk+xU1Xuq6u25t8Ty/ZOZKgAHWbnM0t23q+qZ3Ptw806Si1X1dJKb3X0lye8n+cskleQLu2vrAPwErbNmnu7+apKvLrz0/YWxa0l+9ZDX/cIhj5/MvXjAvXjAvXjAvXjgwHux8quJALz5+QUowABiDjCAmAMMIOYAA4g5wABiDjDA/wNIvEzuP5cGYAAAAABJRU5ErkJggg==\n",

      "text/plain": [

       "<Figure size 432x288 with 1 Axes>"

      ]

     },

     "metadata": {

      "needs_background": "light"

     },

     "output_type": "display_data"

    },

    {

     "data": {

      "image/png": 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\n",

      "text/plain": [

       "<Figure size 432x288 with 1 Axes>"

      ]

     },

     "metadata": {

      "needs_background": "light"

     },

     "output_type": "display_data"

    }

   ],

   "source": [

    "plt.gca().set_xticklabels(['']*100000)\n",

    "fig, ax = plt.subplots()\n",

    "# ax.tick_params('x', labelbottom=False, bottom=False)\n",

    "g = sns.lineplot(data=a['SC'])\n",

    "g.set_ylim(0, 0.12)\n",

    "g.set_xlim(0, 60)\n",

    "plt.ylabel('Electrodermal Activity')\n",

    "plt.xlabel('Sequential Data-Points')\n",

    "plt.show()"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 55,

   "metadata": {},

   "outputs": [

    {

     "data": {

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      "text/plain": [

       "<Figure size 432x288 with 1 Axes>"

      ]

     },

     "metadata": {

      "needs_background": "light"

     },

     "output_type": "display_data"

    },

    {

     "data": {

      "image/png": 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\n",

      "text/plain": [

       "<Figure size 432x288 with 1 Axes>"

      ]

     },

     "metadata": {

      "needs_background": "light"

     },

     "output_type": "display_data"

    }

   ],

   "source": [

    "sns.set_context(\"paper\", rc={\"lines.linewidth\": 2.5})\n",

    "sns.set_palette(\"binary_d\")\n",

    "fig, ax = plt.subplots()\n",

    "# ax.tick_params('x', labelbottom=False, bottom=False)\n",

    "g = sns.lineplot(data=dfeda[dfeda['condition']==1].reset_index().iloc[40379:40400].reset_index()['SC'])\n",

    "g.set_ylim(0, 0.12)\n",

    "g.set_xlim(0, 20)\n",

    "plt.ylabel('Electrodermal Activity')\n",

    "plt.xlabel('Sequential Data-Points')\n",

    "plt.show()"

   ]

  }

 ],

 "metadata": {

  "kernelspec": {

   "display_name": "Python 3",

   "language": "python",

   "name": "python3"

  },

  "language_info": {

   "codemirror_mode": {

    "name": "ipython",

    "version": 3

   },

   "file_extension": ".py",

   "mimetype": "text/x-python",

   "name": "python",

   "nbconvert_exporter": "python",

   "pygments_lexer": "ipython3",

   "version": "3.7.3"

  }

 },

 "nbformat": 4,

 "nbformat_minor": 2

}