{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "779a5d6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install emoji"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3bf0d6c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import ast\n",
    "import emoji\n",
    "\n",
    "DELIMITERS = (\"__pythonji_\", \"__\")\n",
    "\n",
    "def demoji_raw_source(lines):\n",
    "    demojized_lines = []\n",
    "    for line in lines:\n",
    "        demojized_lines.append(emoji.demojize(line, delimiters=DELIMITERS))\n",
    "    return demojized_lines\n",
    "\n",
    "class EmojiNodeTransformer(ast.NodeTransformer):\n",
    "    def visit_Str(self, node):\n",
    "        return ast.copy_location(\n",
    "            ast.Str(s=emoji.emojize(node.s, delimiters=DELIMITERS)), node\n",
    "        )\n",
    "\n",
    "ip = get_ipython()\n",
    "ip.input_transformers_post = [demoji_raw_source]\n",
    "ip.ast_transformers = [EmojiNodeTransformer()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8f12773f",
   "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>animal</th>\n",
       "      <th>scale</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>🦊</td>\n",
       "      <td>0.841312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>🪲</td>\n",
       "      <td>0.264566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>🪲</td>\n",
       "      <td>0.655013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>🦊</td>\n",
       "      <td>0.458347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>🪲</td>\n",
       "      <td>0.539141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>🦞</td>\n",
       "      <td>0.791464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>🪲</td>\n",
       "      <td>0.086120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>🦊</td>\n",
       "      <td>0.048357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>🪲</td>\n",
       "      <td>0.104178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>🦞</td>\n",
       "      <td>0.125664</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  animal     scale\n",
       "0      🦊  0.841312\n",
       "1      🪲  0.264566\n",
       "2      🪲  0.655013\n",
       "3      🦊  0.458347\n",
       "4      🪲  0.539141\n",
       "5      🦞  0.791464\n",
       "6      🪲  0.086120\n",
       "7      🦊  0.048357\n",
       "8      🪲  0.104178\n",
       "9      🦞  0.125664"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as 🐼\n",
    "import random as 🔀\n",
    "\n",
    "📊 = 🐼.DataFrame([{'animal': 🔀.choice(['🦊', '🪲', '🦞']), 'scale': 🔀.random()} for _ in range(10)])\n",
    "📊"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ed587c39",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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