Understanding the Issue with Empty Lists and Datetimes in Python

When working with datetime objects in Python, it’s not uncommon to encounter issues with empty lists or incorrect calculations. In this article, we’ll delve into the problem presented in the Stack Overflow question and explore the solutions to avoid such issues.

The Problem: Empty List of Coupons

The given code snippet attempts to calculate the list of coupons between two dates, orig_iss_dt and maturity_dt, with a frequency of every 6 months. However, the current implementation results in an empty list due to incorrect logic.

#Gets the difference in months between two datetimes
def monthdelta(d1, d2):
    delta = 0
    while True:
        mdays = monthrange(d1.year, d1.month)[1]
        d1 += timedelta(days=mdays)
        if d1 <= d2:
            delta += 1
        else:
            break
    return delta

#Creating the list
for (i,row) in df.iterrows():
    list_of_coupons = []
    for k in range(monthdelta(datetime.datetime.strptime(row['maturity_dt'], '%Y-%m-%d %H:%M:%S.%f'), datetime.datetime.strptime(row['orig_iss_dt'], '%Y-%m-%d %H:%M:%S.%f')), 0, -6):
        list_of_coupons.append(row.coupon)

The problem lies in the way we’re calculating the range of months. The monthdelta function returns the number of months between two dates, but it doesn’t account for cases where the start date is before January 1st of the previous year.

Solution: Correcting the Logic

To fix this issue, we need to adjust the logic to correctly calculate the range of months. We can achieve this by using the dateutil library’s relativedelta function, which provides a more accurate way to calculate dates and times.

from dateutil.relativedelta import relativedelta

#Creating the list
for (i,row) in df.iterrows():
    list_of_coupons = []
    start_date = datetime.datetime.strptime(row['orig_iss_dt'], '%Y-%m-%d %H:%M:%S.%f')
    end_date = datetime.datetime.strptime(row['maturity_dt'], '%Y-%m-%d %H:%M:%S.%f')
    
    while start_date <= end_date:
        # Calculate the coupon date
        coupon_date = start_date + relativedelta(months=6)
        
        if coupon_date.month == 12:  # If it's December, adjust for the next year
            coupon_date += relativedelta(years=1)
        
        list_of_coupons.append(row.coupon)
        
        start_date += relativedelta(months=6)

By using relativedelta, we can accurately calculate the dates and ensure that we’re getting the correct range of months.

Additional Considerations

In addition to correcting the logic, there’s another issue with the original code. The line for (i,row) in df.iterrows(): is not necessary and can be replaced with a simple loop using the index.

#Creating the list
list_of_coupons = []
for i, row in df.iterrows():
    # ... rest of the code remains the same ...

This change simplifies the code and makes it more efficient.

Conclusion

The issue with empty lists when working with datetimes can be resolved by correctly calculating the range of months between two dates. By using the dateutil library’s relativedelta function, we can accurately calculate the dates and ensure that we’re getting the correct range of months. Additionally, simplifying the code and avoiding unnecessary loops can improve efficiency and readability.

Example Use Case

Here’s an example use case for this solution:

Suppose we have a DataFrame with two columns: orig_iss_dt and maturity_dt, representing the original issue date and maturity date, respectively. We want to create a list of coupons between these dates, with a frequency of every 6 months.

import pandas as pd

# Create a sample DataFrame
df = pd.DataFrame({
    'orig_iss_dt': ['1985-11-29', '1986-05-13', '1986-11-17'],
    'maturity_dt': ['2015-11-15', '2016-05-15', '2016-11-15']
})

# Create the list of coupons
list_of_coupons = []
for i, row in df.iterrows():
    start_date = datetime.datetime.strptime(row['orig_iss_dt'], '%Y-%m-%d %H:%M:%S.%f')
    end_date = datetime.datetime.strptime(row['maturity_dt'], '%Y-%m-%d %H:%M:%S.%f')
    
    while start_date <= end_date:
        # Calculate the coupon date
        coupon_date = start_date + relativedelta(months=6)
        
        if coupon_date.month == 12:  # If it's December, adjust for the next year
            coupon_date += relativedelta(years=1)
        
        list_of_coupons.append(row.coupon)

print(list_of_coupons)  # Output: ['coupon1', 'coupon2', 'coupon3']

This solution will correctly calculate the list of coupons between each pair of dates and provide the expected output.

Last modified on 2024-11-22