{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <big><big><big>REST💀IN💀PXXXLS</big></big></big>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<iframe \n",
       "    src=\"https://cdn.knightlab.com/libs/timeline3/latest/embed/index.html?source=1Ffjucc5gnS2PLr5TCmECyfsXttm8ya0bT7nYAYZJkcc&font=Default&lang=en&initial_zoom=2&height=650\" width=\"100%\" height=\"650\" \n",
       "    webkitallowfullscreen \n",
       "    mozallowfullscreen \n",
       "    allowfullscreen \n",
       "    frameborder=\"0\"></iframe>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from deathbeds import Timeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[NbConvertApp] Converting notebook readme.ipynb to markdown\n",
      "[NbConvertApp] Writing 167 bytes to readme.md\n"
     ]
    }
   ],
   "source": [
    "    !jupyter nbconvert --to markdown --MarkdownExporter.exclude_input=True readme.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "p6",
   "language": "python",
   "name": "other-env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}