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DOC: GH5456 Adding workaround info on NA / NaT handling for groupby #47337

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DOC: GH5456 Adding workaround info on NA / NaT handling for groupby #47337

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5 changes: 5 additions & 0 deletions doc/source/user_guide/groupby.rst
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Expand Up @@ -1268,6 +1268,11 @@ automatically excluded. In other words, there will never be an "NA group" or
generally discarding the NA group anyway (and supporting it was an
implementation headache).

.. note::
If you need to include NaN or NaT values in your grouping, you can workaround the automatic exclusion by replacing
the NaN / NaT values with a placeholder string. For example, you can use ``df.fillna("default", inplace=True)`` to
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Thanks for the PR!

  1. Could you demonstrate this by including a .. ipython:: python example (like above)
  2. In the example, could you exclude inplace=True? We are trying to discourage that keyword generally

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Can do on both!

Do you think it makes sense to pull it out of a note and just include it in line with the rest of the text if we're including an ipython?

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Yeah sure that sounds reasonable

create a **default** group in your dataframe that captures NaN / NaT values.

Grouping with ordered factors
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

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