{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6eee3ddd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import camelot\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d95cd8b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "tables = camelot.read_pdf('data/KM6479696509 _ Keirstyn_Moran_SingleViewWithExplanation_2025-07-29.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "759fd46e",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_dfs = []\n",
    "\n",
    "# Append each table's dataframe to the list\n",
    "for table in tables:\n",
    "    all_dfs.append(table.df)\n",
    "\n",
    "# Concatenate all dataframes into one\n",
    "combined_df = pd.concat(all_dfs, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e9c3b9f0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                   0 1 2 3  \\\n",
      "0  ← FM →\\nLow Fat\\nHigh Fat\\nBody Composition Ch...         \n",
      "1                                                            \n",
      "2                                                            \n",
      "3                                                            \n",
      "4                                                            \n",
      "5                                                            \n",
      "6                                                            \n",
      "\n",
      "                                                   4 5  \n",
      "0  muscle  mass  in  a  coordinate  system.  A  d...    \n",
      "1                                                       \n",
      "2                                                       \n",
      "3                                                       \n",
      "4                                                       \n",
      "5                                                       \n",
      "6                                                       \n"
     ]
    }
   ],
   "source": [
    "print(combined_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6bbc907f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "report_generation",
   "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": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}