Datasets:
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{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"id": "SFEUqifXS0At"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Processing CSV files: 100%|██████████| 16573/16573 [01:14<00:00, 222.34it/s]\n"
]
}
],
"source": [
"import os\n",
"import pandas as pd\n",
"from tqdm import tqdm\n",
"\n",
"# Create an empty DataFrame\n",
"df = pd.DataFrame()\n",
"df['context'] = None\n",
"df['answer'] = None\n",
"\n",
"# Read all CSV files from the folder 'all_csv'\n",
"folder_path = 'all_csv' # Path to the folder containing CSV files\n",
"paths = [os.path.join(folder_path, filename) for filename in os.listdir(folder_path) if filename.endswith('.csv')]\n",
"for i, path in enumerate(tqdm(paths, desc=\"Processing CSV files\")):\n",
" data = pd.read_csv(path, sep='#')\n",
" df.loc[i, 'context'] = data.to_string()\n",
" df.loc[i, 'answer'] = data.to_json(force_ascii=False)\n",
"\n",
"# Write the DataFrame to a CSV file\n",
"df.to_csv('table_extract.csv', index=False)"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"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": "3.10.4"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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