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DOC: Fixing EX03 - Removing flake8 errors in docstrings #55401

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merged 2 commits into from
Oct 4, 2023
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DOC: Fixing EX03 - Removing flake8 errors in docstrings #55401

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74b1911
fixing EX03 errors
DeaMariaLeon Oct 4, 2023
3237f64
Merge remote-tracking branch 'upstream/main' into ex03
DeaMariaLeon Oct 4, 2023
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10 changes: 0 additions & 10 deletions ci/code_checks.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -63,16 +63,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then

MSG='Partially validate docstrings (EX03)' ; echo $MSG
$BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=EX03 --ignore_functions \
pandas.Series.loc \
pandas.Series.iloc \
pandas.Series.pop \
pandas.Series.describe \
pandas.Series.skew \
pandas.Series.var \
pandas.Series.last \
pandas.Series.tz_convert \
pandas.Series.tz_localize \
pandas.Series.dt.month_name \
pandas.Series.dt.day_name \
pandas.Series.str.len \
pandas.Series.cat.set_categories \
Expand Down
2 changes: 1 addition & 1 deletion pandas/core/arrays/datetimes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1276,7 +1276,7 @@ def month_name(self, locale=None) -> npt.NDArray[np.object_]:
>>> idx
DatetimeIndex(['2018-01-31', '2018-02-28', '2018-03-31'],
dtype='datetime64[ns]', freq='ME')
>>> idx.month_name(locale='pt_BR.utf8') # doctest: +SKIP
>>> idx.month_name(locale='pt_BR.utf8') # doctest: +SKIP
Index(['Janeiro', 'Fevereiro', 'Março'], dtype='object')
"""
values = self._local_timestamps()
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20 changes: 10 additions & 10 deletions pandas/core/generic.py
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Expand Up @@ -9684,7 +9684,7 @@ def last(self, offset) -> Self:

Get the rows for the last 3 days:

>>> ts.last('3D') # doctest: +SKIP
>>> ts.last('3D') # doctest: +SKIP
A
2018-04-13 3
2018-04-15 4
Expand Down Expand Up @@ -11194,7 +11194,7 @@ def tz_convert(
Pass None to convert to UTC and get a tz-naive index:

>>> s = pd.Series([1],
... index=pd.DatetimeIndex(['2018-09-15 01:30:00+02:00']))
... index=pd.DatetimeIndex(['2018-09-15 01:30:00+02:00']))
>>> s.tz_convert(None)
2018-09-14 23:30:00 1
dtype: int64
Expand Down Expand Up @@ -11312,7 +11312,7 @@ def tz_localize(
Pass None to convert to tz-naive index and preserve local time:

>>> s = pd.Series([1],
... index=pd.DatetimeIndex(['2018-09-15 01:30:00+02:00']))
... index=pd.DatetimeIndex(['2018-09-15 01:30:00+02:00']))
>>> s.tz_localize(None)
2018-09-15 01:30:00 1
dtype: int64
Expand Down Expand Up @@ -11555,10 +11555,10 @@ def describe(
Describing a ``DataFrame``. By default only numeric fields
are returned.

>>> df = pd.DataFrame({'categorical': pd.Categorical(['d','e','f']),
>>> df = pd.DataFrame({'categorical': pd.Categorical(['d', 'e', 'f']),
... 'numeric': [1, 2, 3],
... 'object': ['a', 'b', 'c']
... })
... })
>>> df.describe()
numeric
count 3.0
Expand Down Expand Up @@ -12674,9 +12674,9 @@ def last_valid_index(self) -> Hashable | None:
Examples
--------
>>> df = pd.DataFrame({'person_id': [0, 1, 2, 3],
... 'age': [21, 25, 62, 43],
... 'height': [1.61, 1.87, 1.49, 2.01]}
... ).set_index('person_id')
... 'age': [21, 25, 62, 43],
... 'height': [1.61, 1.87, 1.49, 2.01]}
... ).set_index('person_id')
>>> df
age height
person_id
Expand Down Expand Up @@ -13502,7 +13502,7 @@ def make_doc(name: str, ndim: int) -> str:
With a DataFrame

>>> df = pd.DataFrame({'a': [1, 2, 3], 'b': [2, 3, 4], 'c': [1, 3, 5]},
... index=['tiger', 'zebra', 'cow'])
... index=['tiger', 'zebra', 'cow'])
>>> df
a b c
tiger 1 2 1
Expand All @@ -13526,7 +13526,7 @@ def make_doc(name: str, ndim: int) -> str:
getting an error.

>>> df = pd.DataFrame({'a': [1, 2, 3], 'b': ['T', 'Z', 'X']},
... index=['tiger', 'zebra', 'cow'])
... index=['tiger', 'zebra', 'cow'])
>>> df.skew(numeric_only=True)
a 0.0
dtype: float64"""
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24 changes: 12 additions & 12 deletions pandas/core/indexing.py
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Expand Up @@ -187,7 +187,7 @@ def iloc(self) -> _iLocIndexer:
--------
>>> mydict = [{'a': 1, 'b': 2, 'c': 3, 'd': 4},
... {'a': 100, 'b': 200, 'c': 300, 'd': 400},
... {'a': 1000, 'b': 2000, 'c': 3000, 'd': 4000 }]
... {'a': 1000, 'b': 2000, 'c': 3000, 'd': 4000}]
>>> df = pd.DataFrame(mydict)
>>> df
a b c d
Expand Down Expand Up @@ -328,16 +328,16 @@ def loc(self) -> _LocIndexer:
DataFrame.at : Access a single value for a row/column label pair.
DataFrame.iloc : Access group of rows and columns by integer position(s).
DataFrame.xs : Returns a cross-section (row(s) or column(s)) from the
Series/DataFrame.
Series/DataFrame.
Series.loc : Access group of values using labels.

Examples
--------
**Getting values**

>>> df = pd.DataFrame([[1, 2], [4, 5], [7, 8]],
... index=['cobra', 'viper', 'sidewinder'],
... columns=['max_speed', 'shield'])
... index=['cobra', 'viper', 'sidewinder'],
... columns=['max_speed', 'shield'])
>>> df
max_speed shield
cobra 1 2
Expand Down Expand Up @@ -380,8 +380,8 @@ def loc(self) -> _LocIndexer:
Alignable boolean Series:

>>> df.loc[pd.Series([False, True, False],
... index=['viper', 'sidewinder', 'cobra'])]
max_speed shield
... index=['viper', 'sidewinder', 'cobra'])]
max_speed shield
sidewinder 7 8

Index (same behavior as ``df.reindex``)
Expand All @@ -407,7 +407,7 @@ def loc(self) -> _LocIndexer:
Multiple conditional using ``&`` that returns a boolean Series

>>> df.loc[(df['max_speed'] > 1) & (df['shield'] < 8)]
max_speed shield
max_speed shield
viper 4 5

Multiple conditional using ``|`` that returns a boolean Series
Expand Down Expand Up @@ -496,7 +496,7 @@ def loc(self) -> _LocIndexer:
Another example using integers for the index

>>> df = pd.DataFrame([[1, 2], [4, 5], [7, 8]],
... index=[7, 8, 9], columns=['max_speed', 'shield'])
... index=[7, 8, 9], columns=['max_speed', 'shield'])
>>> df
max_speed shield
7 1 2
Expand All @@ -517,13 +517,13 @@ def loc(self) -> _LocIndexer:
A number of examples using a DataFrame with a MultiIndex

>>> tuples = [
... ('cobra', 'mark i'), ('cobra', 'mark ii'),
... ('sidewinder', 'mark i'), ('sidewinder', 'mark ii'),
... ('viper', 'mark ii'), ('viper', 'mark iii')
... ('cobra', 'mark i'), ('cobra', 'mark ii'),
... ('sidewinder', 'mark i'), ('sidewinder', 'mark ii'),
... ('viper', 'mark ii'), ('viper', 'mark iii')
... ]
>>> index = pd.MultiIndex.from_tuples(tuples)
>>> values = [[12, 2], [0, 4], [10, 20],
... [1, 4], [7, 1], [16, 36]]
... [1, 4], [7, 1], [16, 36]]
>>> df = pd.DataFrame(values, columns=['max_speed', 'shield'], index=index)
>>> df
max_speed shield
Expand Down
2 changes: 1 addition & 1 deletion pandas/core/series.py
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Expand Up @@ -5186,7 +5186,7 @@ def pop(self, item: Hashable) -> Any:

Examples
--------
>>> ser = pd.Series([1,2,3])
>>> ser = pd.Series([1, 2, 3])

>>> ser.pop(0)
1
Expand Down