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Backport PR #42110 on branch 1.3.x (DOC-Modified documentation for the issue GH42106) #42161

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Jun 21, 2021
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Backport PR #42110 on branch 1.3.x (DOC-Modified documentation for the issue GH42106) #42161

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9 changes: 4 additions & 5 deletions doc/source/user_guide/indexing.rst
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Expand Up @@ -1523,18 +1523,17 @@ Looking up values by index/column labels
----------------------------------------

Sometimes you want to extract a set of values given a sequence of row labels
and column labels, this can be achieved by ``DataFrame.melt`` combined by filtering the corresponding
rows with ``DataFrame.loc``. For instance:
and column labels, this can be achieved by ``pandas.factorize`` and NumPy indexing.
For instance:

.. ipython:: python

df = pd.DataFrame({'col': ["A", "A", "B", "B"],
'A': [80, 23, np.nan, 22],
'B': [80, 55, 76, 67]})
df
melt = df.melt('col')
melt = melt.loc[melt['col'] == melt['variable'], 'value']
melt.reset_index(drop=True)
idx, cols = pd.factorize(df['col'])
df.reindex(cols, axis=1).to_numpy()[np.arange(len(df)), idx]

Formerly this could be achieved with the dedicated ``DataFrame.lookup`` method
which was deprecated in version 1.2.0.
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