data preprocessing.ipynb

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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import nltk\n",
    "from nltk.sentiment.vader import SentimentIntensityAnalyzer\n",
    "import matplotlib.pyplot as plt\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Filter articles based on year & time periods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "csv_directory = '1973'\n",
    "csv_files = [file for file in os.listdir(csv_directory) if file.endswith('.csv')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_dataframes = []\n",
    "for file in csv_files:\n",
    "    file_path = os.path.join(csv_directory, file)\n",
    "    df = pd.read_csv(file_path)\n",
    "    all_dataframes.append(df)\n",
    "\n",
    "merged_df = pd.concat(all_dataframes, ignore_index=True)\n",
    "merged_df.to_csv('1973/1973_file.csv', index=False)"
   ]
  }
 ],
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