How to Convert Numeric Values to Date Format in Python Similar to SAS with timedelta

Learn how to convert numeric date values from SAS format to Python's date format efficiently, including tips for handling DataFrame columns in PySpark.
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Converting Numeric Values to Date Format in Python Like SAS

When working with data imported from SAS, you may encounter numeric values that represent dates, but these values often appear incorrectly formatted. This is particularly the case when SAS dates, which are calculated as the number of days since a specific epoch (January 1, 1960), are transferred to Python.

In this post, we will explore how to convert these numeric date values into a proper date format using Python and PySpark.

Understanding SAS Date Values

SAS interprets dates as the number of days since January 1, 1960. For example, the numeric value 5893 correlates with February 19, 1976. If you try using Python's fromtimestamp method with this value, you might find that you get an incorrect date, which is rooted in the different epoch used by Python (January 1, 1970).

The Problem

When attempting to convert the SAS date value to Python's datetime format, you might experience unexpected results. For instance:

[[See Video to Reveal this Text or Code Snippet]]

The above code gives a date that makes little sense in the context of SAS.

The Solution: Using timedelta

To correctly convert a SAS date value to a Python date, you will need to add the number of days to Python's epoch start date. Here's how you can achieve that:

[[See Video to Reveal this Text or Code Snippet]]

How It Works

Imports: We import timedelta and date from the datetime module.

Define SAS Date Value: We define another variable sas_date_value with our SAS numeric value.

Calculating: Using timedelta, we add the number of days since the SAS epoch (January 1, 1960) to get the equivalent Python date.

Applying This to a DataFrame Column

If you're using a DataFrame in PySpark or Pandas and want to convert an entire column containing SAS date values, you can use a similar approach. Here’s how to do it with Pandas:

[[See Video to Reveal this Text or Code Snippet]]

Key Takeaways

Correct Epoch: Remember that SAS dates are calculated from January 1, 1960.

Use timedelta: To convert numeric SAS date values properly, calculate and add the days since the SAS epoch.

DataFrame Compatibility: If working with a column in a DataFrame, leverage the apply function to handle the conversion across all values seamlessly.

By following these steps, you can successfully convert SAS numeric date values into a readable date format in Python, allowing for better data analysis and utilization. Happy coding!