Date conversion

import pandas as pd
def convert_date_abbreviations(input_file, output_file):
    # Read the Excel file
    df = pd.read_excel(input_file)
    # Split the 'observed_date' column into 'Year' and 'Month' based on '/'
    df[['Year', 'Month']] = df['observed_date'].str.split('/', expand=True)
    # Define a dictionary mapping three-letter month abbreviations to two-digit numeric values
    month_mapping = {
        'Jan': '01',
        'Feb': '02',
        'Mar': '03',
        'Apr': '04',
        'May': '05',
        'Jun': '06',
        'Jul': '07',
        'Aug': '08',
        'Sep': '09',
        'Oct': '10',
        'Nov': '11',
        'Dec': '12'
    }
    # Convert three-letter abbreviations to two-digit numeric values
    df['Month'] = df['Month'].map(month_mapping)
    # Replace "/" with "-"
    df['observed_date'] = df['Year'] + '-' + df['Month']
    # Drop unnecessary columns
    df = df[['observed_date', 'Weekly_Hours']]
    # Write the result DataFrame to a new Excel file
    df.to_excel(output_file, index=False)