ENH: Checking gaps for time series

[ncooder]

Feature Type

• Adding new functionality to pandas

• Changing existing functionality in pandas

• Removing existing functionality in pandas

Problem Description

Add built-in schema validation capabilities to pandas, similar to those provided by pandera. It should check time series gaps based on datestamp gaps.

Feature Description

Time series data typically requires continuous timestamps without gaps. Currently, users have to implement their own custom solutions to check for missing periods. A built-in method would be useful to verify the continuity of timestamps. For example, if you have a time series with daily data from 2010-01-01 to 2020-01-01, there shouldn't be any gaps, such as a missing entry for 2019-01-02 or any other date. This method should work for various frequencies, not just daily data.

Alternative Solutions

When gaps are detected, the function should automatically fill them using various interpolation methods or give an error.

Additional Context

No response

[rhshadrach]

Thanks for the request!

To determine if there are missing values, you can generate a DateTimeIndex that is not missing any and then use .difference(your_index) to determine if any are missing (see this SO question).

When gaps are detected, the function should automatically fill them using various interpolation methods or give an error.

This can be achieved using reindex and interpolate.

This feature request seems duplicative of methods already available in pandas.

[mroeschke]

Agreed, since this can be accomplished with existing APIs, closing