Pandas GroupBy.apply Duplicates First Group: Understanding the Behavior

When using the groupby function in Pandas, the apply method may appear to apply a function twice to the first row of a data frame. This behavior, though seemingly unexpected, is by design.

The Purpose of the Double Application

The apply function needs to determine the shape of the data it will combine. To achieve this, it calls the designated function—in this case, checkit—twice. The first call helps infer the output's shape, while the second executes the operation on the group.

Avoiding the Double Effect

Depending on your use case, you can avoid the double application by using alternative functions:

• aggregate: Requires the return value to be a summary statistic, such as the mean or sum.
• transform: Requires the return value to have the same shape as the input group.
• filter: Requires the return value to be a boolean index indicating which rows to keep.

These functions enforce specific shapes for the return value, eliminating the need for the double application.

Side-Effect Considerations

If the function you are applying has no side effects—that is, it does not modify the original data frame—then the double application likely does not matter. However, if the function performs any data manipulation, the double application on the first row may lead to unintended consequences.