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DOC Fix EX01 issues in docstrings #51593

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Merged
merged 2 commits into from
Feb 23, 2023
Merged

DOC Fix EX01 issues in docstrings #51593

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e8334df
DOC Fix EX01 issues plus line too long
DeaMariaLeon Feb 23, 2023
0ff2b67
Merge
DeaMariaLeon Feb 23, 2023
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4 changes: 0 additions & 4 deletions ci/code_checks.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -92,8 +92,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.Series.keys \
pandas.Series.item \
pandas.Series.pipe \
pandas.Series.mean \
pandas.Series.median \
pandas.Series.mode \
pandas.Series.sem \
pandas.Series.skew \
Expand Down Expand Up @@ -543,8 +541,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.DataFrame.keys \
pandas.DataFrame.iterrows \
pandas.DataFrame.pipe \
pandas.DataFrame.mean \
pandas.DataFrame.median \
pandas.DataFrame.sem \
pandas.DataFrame.skew \
pandas.DataFrame.backfill \
Expand Down
72 changes: 70 additions & 2 deletions pandas/core/generic.py
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Expand Up @@ -11516,7 +11516,41 @@ def prod(
axis_descr=axis_descr,
min_count="",
see_also="",
examples="",
examples="""

Examples
--------
>>> s = pd.Series([1, 2, 3])
>>> s.mean()
2.0

With a DataFrame

>>> df = pd.DataFrame({'a': [1, 2], 'b': [2, 3]}, index=['tiger', 'zebra'])
>>> df
a b
tiger 1 2
zebra 2 3
>>> df.mean()
a 1.5
b 2.5
dtype: float64

Using axis=1

>>> df.mean(axis=1)
tiger 1.5
zebra 2.5
dtype: float64

In this case, `numeric_only` should be set to `True` to avoid
getting an error.

>>> df = pd.DataFrame({'a': [1, 2], 'b': ['T', 'Z']},
... index=['tiger', 'zebra'])
>>> df.mean(numeric_only=True)
a 1.5
dtype: float64""",
)
def mean(
self,
Expand Down Expand Up @@ -11624,7 +11658,41 @@ def kurt(
axis_descr=axis_descr,
min_count="",
see_also="",
examples="",
examples="""

Examples
--------
>>> s = pd.Series([1, 2, 3])
>>> s.median()
2.0

With a DataFrame

>>> df = pd.DataFrame({'a': [1, 2], 'b': [2, 3]}, index=['tiger', 'zebra'])
>>> df
a b
tiger 1 2
zebra 2 3
>>> df.median()
a 1.5
b 2.5
dtype: float64

Using axis=1

>>> df.median(axis=1)
tiger 1.5
zebra 2.5
dtype: float64

In this case, `numeric_only` should be set to `True`
to avoid getting an error.

>>> df = pd.DataFrame({'a': [1, 2], 'b': ['T', 'Z']},
... index=['tiger', 'zebra'])
>>> df.median(numeric_only=True)
a 1.5
dtype: float64""",
)
def median(
self,
Expand Down