Skip to content

DOC: Clarify is_scalar docstring to specify scalar vs non-scalar and add Enum example (GH#62063) #62143

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 1 commit into from
Closed

DOC: Clarify is_scalar docstring to specify scalar vs non-scalar and add Enum example (GH#62063) #62143

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
53 changes: 32 additions & 21 deletions pandas/core/series.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@
TYPE_CHECKING,
Any,
Literal,
Self,
cast,
overload,
)
Expand All @@ -40,6 +41,7 @@
from pandas.errors import (
ChainedAssignmentError,
InvalidIndexError,
Pandas4Warning,
)
from pandas.errors.cow import (
_chained_assignment_method_msg,
Expand Down Expand Up @@ -191,7 +193,6 @@
ReindexMethod,
Renamer,
Scalar,
Self,
SortKind,
StorageOptions,
Suffixes,
Expand Down Expand Up @@ -764,11 +765,13 @@ def values(self):
array([1, 2, 3])

>>> pd.Series(list("aabc")).values
array(['a', 'a', 'b', 'c'], dtype=object)
<ArrowStringArrayNumpySemantics>
['a', 'a', 'b', 'c']
Length: 4, dtype: str

>>> pd.Series(list("aabc")).astype("category").values
['a', 'a', 'b', 'c']
Categories (3, object): ['a', 'b', 'c']
Categories (3, str): ['a', 'b', 'c']

Timezone aware datetime data is converted to UTC:

Expand Down Expand Up @@ -1471,7 +1474,7 @@ def to_string(
) -> None: ...

@deprecate_nonkeyword_arguments(
version="4.0", allowed_args=["self", "buf"], name="to_string"
Pandas4Warning, allowed_args=["self", "buf"], name="to_string"
)
def to_string(
self,
Expand Down Expand Up @@ -1629,7 +1632,7 @@ def to_markdown(
),
)
@deprecate_nonkeyword_arguments(
version="4.0", allowed_args=["self", "buf"], name="to_markdown"
Pandas4Warning, allowed_args=["self", "buf"], name="to_markdown"
)
def to_markdown(
self,
Expand Down Expand Up @@ -1970,7 +1973,7 @@ def groupby(
as_index: bool = True,
sort: bool = True,
group_keys: bool = True,
observed: bool = False,
observed: bool = True,
dropna: bool = True,
) -> SeriesGroupBy:
from pandas.core.groupby.generic import SeriesGroupBy
Expand Down Expand Up @@ -2144,12 +2147,12 @@ def unique(self) -> ArrayLike:

>>> pd.Series(pd.Categorical(list("baabc"))).unique()
['b', 'a', 'c']
Categories (3, object): ['a', 'b', 'c']
Categories (3, str): ['a', 'b', 'c']
>>> pd.Series(
... pd.Categorical(list("baabc"), categories=list("abc"), ordered=True)
... ).unique()
['b', 'a', 'c']
Categories (3, object): ['a' < 'b' < 'c']
Categories (3, str): ['a' < 'b' < 'c']
"""
return super().unique()

Expand Down Expand Up @@ -3109,7 +3112,8 @@ def combine(
Function that takes two scalars as inputs and returns an element.
fill_value : scalar, optional
The value to assume when an index is missing from
one Series or the other. The default specifies to use the
one Series or the other. Scalars are any value that is not a numpy.ndarray,
list, tuple or Series. The default specifies to use the
appropriate NaN value for the underlying dtype of the Series.

Returns
Expand Down Expand Up @@ -6070,6 +6074,11 @@ def eq(
Equivalent to ``series == other``, but with support to substitute a fill_value
for missing data in either one of the inputs.

By default, comparisons with missing values (e.g. ``np.nan``, ``pd.NA``) will
return ``False`` for those positions, even when comparing missing values to
themselves. If ``fill_value`` is specified, missing values are replaced before
comparison.

Parameters
----------
other : Series or scalar value
Expand Down Expand Up @@ -6683,7 +6692,7 @@ def any( # type: ignore[override]
filter_type="bool",
)

@deprecate_nonkeyword_arguments(version="4.0", allowed_args=["self"], name="all")
@deprecate_nonkeyword_arguments(Pandas4Warning, allowed_args=["self"], name="all")
@Appender(make_doc("all", ndim=1))
def all(
self,
Expand All @@ -6703,7 +6712,7 @@ def all(
filter_type="bool",
)

@deprecate_nonkeyword_arguments(version="4.0", allowed_args=["self"], name="min")
@deprecate_nonkeyword_arguments(Pandas4Warning, allowed_args=["self"], name="min")
def min(
self,
axis: Axis | None = 0,
Expand Down Expand Up @@ -6774,7 +6783,7 @@ def min(
self, axis=axis, skipna=skipna, numeric_only=numeric_only, **kwargs
)

@deprecate_nonkeyword_arguments(version="4.0", allowed_args=["self"], name="max")
@deprecate_nonkeyword_arguments(Pandas4Warning, allowed_args=["self"], name="max")
def max(
self,
axis: Axis | None = 0,
Expand Down Expand Up @@ -6845,7 +6854,7 @@ def max(
self, axis=axis, skipna=skipna, numeric_only=numeric_only, **kwargs
)

@deprecate_nonkeyword_arguments(version="4.0", allowed_args=["self"], name="sum")
@deprecate_nonkeyword_arguments(Pandas4Warning, allowed_args=["self"], name="sum")
def sum(
self,
axis: Axis | None = None,
Expand Down Expand Up @@ -6946,7 +6955,7 @@ def sum(
**kwargs,
)

@deprecate_nonkeyword_arguments(version="4.0", allowed_args=["self"], name="prod")
@deprecate_nonkeyword_arguments(Pandas4Warning, allowed_args=["self"], name="prod")
@doc(make_doc("prod", ndim=1))
def prod(
self,
Expand All @@ -6965,7 +6974,7 @@ def prod(
**kwargs,
)

@deprecate_nonkeyword_arguments(version="4.0", allowed_args=["self"], name="mean")
@deprecate_nonkeyword_arguments(Pandas4Warning, allowed_args=["self"], name="mean")
def mean(
self,
axis: Axis | None = 0,
Expand Down Expand Up @@ -7019,7 +7028,9 @@ def mean(
self, axis=axis, skipna=skipna, numeric_only=numeric_only, **kwargs
)

@deprecate_nonkeyword_arguments(version="4.0", allowed_args=["self"], name="median")
@deprecate_nonkeyword_arguments(
Pandas4Warning, allowed_args=["self"], name="median"
)
def median(
self,
axis: Axis | None = 0,
Expand Down Expand Up @@ -7100,7 +7111,7 @@ def median(
self, axis=axis, skipna=skipna, numeric_only=numeric_only, **kwargs
)

@deprecate_nonkeyword_arguments(version="4.0", allowed_args=["self"], name="sem")
@deprecate_nonkeyword_arguments(Pandas4Warning, allowed_args=["self"], name="sem")
@doc(make_doc("sem", ndim=1))
def sem(
self,
Expand All @@ -7119,7 +7130,7 @@ def sem(
**kwargs,
)

@deprecate_nonkeyword_arguments(version="4.0", allowed_args=["self"], name="var")
@deprecate_nonkeyword_arguments(Pandas4Warning, allowed_args=["self"], name="var")
def var(
self,
axis: Axis | None = None,
Expand Down Expand Up @@ -7206,7 +7217,7 @@ def var(
**kwargs,
)

@deprecate_nonkeyword_arguments(version="4.0", allowed_args=["self"], name="std")
@deprecate_nonkeyword_arguments(Pandas4Warning, allowed_args=["self"], name="std")
@doc(make_doc("std", ndim=1))
def std(
self,
Expand All @@ -7225,7 +7236,7 @@ def std(
**kwargs,
)

@deprecate_nonkeyword_arguments(version="4.0", allowed_args=["self"], name="skew")
@deprecate_nonkeyword_arguments(Pandas4Warning, allowed_args=["self"], name="skew")
@doc(make_doc("skew", ndim=1))
def skew(
self,
Expand All @@ -7238,7 +7249,7 @@ def skew(
self, axis=axis, skipna=skipna, numeric_only=numeric_only, **kwargs
)

@deprecate_nonkeyword_arguments(version="4.0", allowed_args=["self"], name="kurt")
@deprecate_nonkeyword_arguments(Pandas4Warning, allowed_args=["self"], name="kurt")
def kurt(
self,
axis: Axis | None = 0,
Expand Down