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Improve lookup documentation #61471

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Follows from #61185

Examples available at https://colab.research.google.com/drive/1MGWX6JVJL5yHyK7BeEBPQAW4tLM3TZL9#scrollTo=DjWfk4i1SiOY

stevenae added 2 commits May 21, 2025 10:46
@stevenae
Update indexing.rst
f17b96c 
Add pd_lookup_het() and pd_lookup_hom()
@stevenae
Update indexing.rst
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This was referenced May 21, 2025
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@mroeschke mroeschke requested a review from rhshadrach May 21, 2025 16:02
@mroeschke mroeschke added the Docs label May 21, 2025
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rhshadrach requested changes May 21, 2025
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Thanks for the PR! No strong opposition to having both functions, but the performance gain of the _het version does not seem significant to me.

doc/source/user_guide/indexing.rst
idx, cols = pd.factorize(df['col'])
df.reindex(cols, axis=1).to_numpy()[np.arange(len(df)), idx]
def pd_lookup_hom(df, row_labels, col_labels):
rows = df.index.get_indexer(row_labels)
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Can you add df = df.loc[:, sorted(set(col_labels))] here.

doc/source/user_guide/indexing.rst
result = values[flat_index]
return result

For homogeneous column types, it is fastest to skip column subsetting and go directly to numpy:
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Nit: NumPy

doc/source/user_guide/indexing.rst

.. ipython:: python
For heterogeneous column types, we subset columns to avoid unnecessary numpy conversions:
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NumPy again.

@rhshadrach rhshadrach added the Indexing Related to indexing on series/frames, not to indexes themselves label May 21, 2025
@rhshadrach rhshadrach added this to the 3.0 milestone May 21, 2025
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ENH: re-implement DataFrame.lookup.
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