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DOC: Fixes PR01, PR02 for Series.cat and Series.dt #58912

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DOC: Fixes PR01, PR02 for Series.cat and Series.dt #58912

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e6f3a74
Fixed false negative PR01, PR02 errors in Series
Jun 3, 2024
01ad3f9
Fixed false negative PR01, PR02 errors in Series
Jun 3, 2024
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20 changes: 0 additions & 20 deletions ci/code_checks.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -130,31 +130,11 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.RangeIndex.start SA01" \
-i "pandas.RangeIndex.step SA01" \
-i "pandas.RangeIndex.stop SA01" \
-i "pandas.Series.cat.add_categories PR01,PR02" \
-i "pandas.Series.cat.as_ordered PR01" \
-i "pandas.Series.cat.as_unordered PR01" \
-i "pandas.Series.cat.remove_categories PR01,PR02" \
-i "pandas.Series.cat.remove_unused_categories PR01" \
-i "pandas.Series.cat.rename_categories PR01,PR02" \
-i "pandas.Series.cat.reorder_categories PR01,PR02" \
-i "pandas.Series.cat.set_categories PR01,PR02" \
-i "pandas.Series.dt.as_unit PR01,PR02" \
-i "pandas.Series.dt.ceil PR01,PR02" \
-i "pandas.Series.dt.day_name PR01,PR02" \
-i "pandas.Series.dt.floor PR01,PR02" \
-i "pandas.Series.dt.freq GL08" \
-i "pandas.Series.dt.microseconds SA01" \
-i "pandas.Series.dt.month_name PR01,PR02" \
-i "pandas.Series.dt.nanoseconds SA01" \
-i "pandas.Series.dt.normalize PR01" \
-i "pandas.Series.dt.qyear GL08" \
-i "pandas.Series.dt.round PR01,PR02" \
-i "pandas.Series.dt.seconds SA01" \
-i "pandas.Series.dt.strftime PR01,PR02" \
-i "pandas.Series.dt.to_period PR01,PR02" \
-i "pandas.Series.dt.total_seconds PR01" \
-i "pandas.Series.dt.tz_convert PR01,PR02" \
-i "pandas.Series.dt.tz_localize PR01,PR02" \
-i "pandas.Series.dt.unit GL08" \
-i "pandas.Series.ge SA01" \
-i "pandas.Series.gt SA01" \
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26 changes: 26 additions & 0 deletions scripts/validate_docstrings.py
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Original file line number Diff line number Diff line change
Expand Up @@ -240,6 +240,32 @@ def pandas_validate(func_name: str):
dict
Information about the docstring and the errors found.
"""

def _get_delegated_func_name(func_name: str) -> str:
method_name = func_name.rsplit(".", 1)[-1]

if "Series.cat" in func_name:
return "pandas.core.arrays.categorical.Categorical." + method_name
if "Series.dt" in func_name:
if method_name in ["as_unit", "ceil", "floor", "round"]:
return "pandas.core.arrays.datetimelike.TimelikeOps." + method_name
if method_name in [
"day_name",
"month_name",
"normalize",
"to_period",
"tz_convert",
"tz_localize"
]:
return "pandas.core.arrays.datetimes.DatetimeArray." + method_name
if method_name in ["strftime"]:
return "pandas.core.arrays.datetimelike.DatelikeOps." + method_name
if method_name in ["total_seconds"]:
return "pandas.core.arrays.timedeltas.TimedeltaArray." + method_name

return func_name

func_name = _get_delegated_func_name(func_name)
func_obj = Validator._load_obj(func_name)
# Some objects are instances, e.g. IndexSlice, which numpydoc can't validate
doc_obj = get_doc_object(func_obj, doc=func_obj.__doc__)
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