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DOC: add PR01,RT03,SA01 to pandas.Series.var docstring (#58735)
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* DOC: add PR01,RT03,SA01 to pandas.Series.var

* DOC: remove PR01,RT03,SA01 to pandas.Series.var
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tuhinsharma121 committed May 16, 2024
1 parent 58461fe commit 737c69c
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Showing 2 changed files with 69 additions and 2 deletions.
1 change: 0 additions & 1 deletion ci/code_checks.sh
Original file line number Diff line number Diff line change
Expand Up @@ -228,7 +228,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.Series.to_markdown SA01" \
-i "pandas.Series.to_string SA01" \
-i "pandas.Series.update PR07,SA01" \
-i "pandas.Series.var PR01,RT03,SA01" \
-i "pandas.Timedelta PR07,SA01" \
-i "pandas.Timedelta.as_unit SA01" \
-i "pandas.Timedelta.asm8 SA01" \
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70 changes: 69 additions & 1 deletion pandas/core/series.py
Original file line number Diff line number Diff line change
Expand Up @@ -6720,7 +6720,6 @@ def sem(
)

@deprecate_nonkeyword_arguments(version="3.0", allowed_args=["self"], name="var")
@doc(make_doc("var", ndim=1))
def var(
self,
axis: Axis | None = None,
Expand All @@ -6729,6 +6728,75 @@ def var(
numeric_only: bool = False,
**kwargs,
):
"""
Return unbiased variance over requested axis.
Normalized by N-1 by default. This can be changed using the ddof argument.
Parameters
----------
axis : {index (0)}
For `Series` this parameter is unused and defaults to 0.
.. warning::
The behavior of DataFrame.var with ``axis=None`` is deprecated,
in a future version this will reduce over both axes and return a scalar
To retain the old behavior, pass axis=0 (or do not pass axis).
skipna : bool, default True
Exclude NA/null values. If an entire row/column is NA, the result
will be NA.
ddof : int, default 1
Delta Degrees of Freedom. The divisor used in calculations is N - ddof,
where N represents the number of elements.
numeric_only : bool, default False
Include only float, int, boolean columns. Not implemented for Series.
**kwargs :
Additional keywords passed.
Returns
-------
scalar or Series (if level specified)
Unbiased variance over requested axis.
See Also
--------
numpy.var : Equivalent function in NumPy.
Series.std : Returns the standard deviation of the Series.
DataFrame.var : Returns the variance of the DataFrame.
DataFrame.std : Return standard deviation of the values over
the requested axis.
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")
>>> df
age height
person_id
0 21 1.61
1 25 1.87
2 62 1.49
3 43 2.01
>>> df.var()
age 352.916667
height 0.056367
dtype: float64
Alternatively, ``ddof=0`` can be set to normalize by N instead of N-1:
>>> df.var(ddof=0)
age 264.687500
height 0.042275
dtype: float64
"""
return NDFrame.var(
self,
axis=axis,
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