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fixed 'Double line break found' error reported by the docstrings check
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pandas/core/generic.py

+16-20
Original file line numberDiff line numberDiff line change
@@ -5037,8 +5037,7 @@ def pipe(self, func, *args, **kwargs):
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`agg` is an alias for `aggregate`. Use the alias.
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A passed user-defined-function will be passed a Series for evaluation.
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{examples}
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"""
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{examples}"""
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)
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# ----------------------------------------------------------------------
@@ -10992,8 +10991,7 @@ def stat_func(
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Returns
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-------
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{name1} or {name2} (if level specified)\n
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"""
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{name1} or {name2} (if level specified)\n"""
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nv.validate_stat_ddof_func(tuple(), kwargs, fname=name)
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if skipna is None:
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skipna = True
@@ -11062,8 +11060,7 @@ def cum_func(self, axis=None, skipna=True, *args, **kwargs):
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{name2}.cumsum : Return cumulative sum over {name2} axis.
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{name2}.cumprod : Return cumulative product over {name2} axis.
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{examples}
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"""
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{examples}"""
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skipna = nv.validate_cum_func_with_skipna(skipna, args, kwargs, name)
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if axis is None:
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axis = self._stat_axis_number
@@ -11112,11 +11109,11 @@ def _make_logical_function(
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)
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def logical_func(self, axis=0, bool_only=None, skipna=True, level=None, **kwargs):
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"""
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{desc}
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{desc}
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Parameters
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----------
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axis : {{0 or 'index', 1 or 'columns', None}}, default 0
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Parameters
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----------
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axis : {{0 or 'index', 1 or 'columns', None}}, default 0
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Indicate which axis or axes should be reduced.
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* 0 / 'index' : reduce the index, return a Series whose index is the
@@ -11125,30 +11122,29 @@ def logical_func(self, axis=0, bool_only=None, skipna=True, level=None, **kwargs
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original index.
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* None : reduce all axes, return a scalar.
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11128-
bool_only : bool, default None
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bool_only : bool, default None
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Include only boolean columns. If None, will attempt to use everything,
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then use only boolean data. Not implemented for Series.
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skipna : bool, default True
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skipna : bool, default True
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Exclude NA/null values. If the entire row/column is NA and skipna is
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True, then the result will be {empty_value}, as for an empty row/column.
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If skipna is False, then NA are treated as True, because these are not
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equal to zero.
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level : int or level name, default None
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level : int or level name, default None
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If the axis is a MultiIndex (hierarchical), count along a
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particular level, collapsing into a {name1}.
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**kwargs : any, default None
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**kwargs : any, default None
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Additional keywords have no effect but might be accepted for
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compatibility with NumPy.
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11143-
Returns
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-------
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{name1} or {name2}
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Returns
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-------
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{name1} or {name2}
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If level is specified, then, {name2} is returned; otherwise, {name1}
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is returned.
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11149-
{see_also}
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{examples}
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"""
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{see_also}
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{examples}"""
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nv.validate_logical_func(tuple(), kwargs, fname=name)
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if level is not None:
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if bool_only is not None:

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