{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "25cae6f413974d75960d08925d6c02d3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HTML(value='\\n        <link rel=\"stylesheet\" \\n            href=\"https://stackpath.bootstrapcdn.com/bootstrap/…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "09ff7fd0800147e3a9bc55d7ddbcbec8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "GridBox(children=(GridBox(children=(VBox(children=(HTML(value='<div class=\"table-cell\"><b font-size:13px;>Tria…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from table import *\n",
    "\n",
    "df = Make.table(5, 3, [\"Trial number\", \"Visual reaction time (ms)\", \"Auditory reaction time (ms)\"], values = {\"Trial number\" : [\"1\", \"2\", \"3\", \"4\", \"5\"]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.2"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}