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DOC: update the DataFrame.pivot docstring #20250

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merged 7 commits into from
Mar 12, 2018
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DOC: update the DataFrame.pivot docstring #20250

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75cb343
DOC: DataFrame.pivot
amuta Mar 10, 2018
0d1efb8
DOC: grammar
amuta Mar 10, 2018
e880c47
Fixing pivot
amuta Mar 10, 2018
3dbafa1
Added Raises and example
TomAugspurger Mar 12, 2018
b13cbd0
Say what to do
TomAugspurger Mar 12, 2018
fb80f04
Refer to user guide
TomAugspurger Mar 12, 2018
d454a30
Fixed name
TomAugspurger Mar 12, 2018
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28 changes: 16 additions & 12 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4341,27 +4341,31 @@ def last_valid_index(self):

def pivot(self, index=None, columns=None, values=None):
"""
Return reshaped DataFrame summarized by given index / column values.
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I think "summarized" is misleading here, as there is no "summary" (aggregation) calculation happening.

(I don't directly have the "better" wording in mind though. And the "reshaping" is important, as you already mention)


Reshape data (produce a "pivot" table) based on column values. Uses
unique values from index / columns to form axes of the resulting
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can you add single backtick around index and column ? (to reference them as parameters).

I would maybe also say "from specified index / columns" to make it clear it is not the existing index / columns

DataFrame.
DataFrame. This function does not support data aggregation, multiple
values will result in hierarchically indexed columns.
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in multiindexed columns.


Parameters
----------
index : string or object, optional
Column name to use to make new frame's index. If None, uses
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Would it be clearer to just say "Column" instead of "Column name". I know the value you specify is the name, but what you actually use to make the new frame's index is the actual column, not the column name ...

existing index.
columns : string or object
Column name to use to make new frame's columns
columns : string or object, optional
Column name to use to make new frame's columns.
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What happens in this case if you do not specify it?

values : string or object, optional
Column name to use for populating new frame's values. If not
specified, all remaining columns will be used and the result will
have hierarchically indexed columns
have hierarchically indexed columns.

Returns
-------
pivoted : DataFrame
DataFrame
Returns reshaped DataFrame.

See also
See Also
--------
DataFrame.pivot_table : generalization of pivot that can handle
duplicate values for one index/column pair
Expand All @@ -4377,8 +4381,8 @@ def pivot(self, index=None, columns=None, values=None):
--------

>>> df = pd.DataFrame({'foo': ['one','one','one','two','two','two'],
'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
'baz': [1, 2, 3, 4, 5, 6]})
... 'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
... 'baz': [1, 2, 3, 4, 5, 6]})
>>> df
foo bar baz
0 one A 1
Expand All @@ -4389,16 +4393,16 @@ def pivot(self, index=None, columns=None, values=None):
5 two C 6

>>> df.pivot(index='foo', columns='bar', values='baz')
A B C
bar A B C
foo
one 1 2 3
two 4 5 6

>>> df.pivot(index='foo', columns='bar')['baz']
A B C
bar A B C
foo
one 1 2 3
two 4 5 6


"""
from pandas.core.reshape.reshape import pivot
return pivot(self, index=index, columns=columns, values=values)
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