{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0327aa17",
   "metadata": {},
   "source": [
    "# Data Preprocessing for NLP Project\n",
    "\n",
    "This notebook contains the data preprocessing steps for our NLP project."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a4c43313",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import necessary libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import nltk\n",
    "from sklearn.model_selection import train_test_split\n",
    "import re\n",
    "import string"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d4c2a2b",
   "metadata": {},
   "source": [
    "## Load Raw Data\n",
    "\n",
    "Load the raw data from the data/raw directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9b2784d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load your raw data here\n",
    "df = pd.read_csv('../data/raw/your_dataset.csv')\n",
    "print(df.head())"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "name": "python",
   "version": "3.13.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}