modin.pandas.Series.skew

Series.skew(axis: Axis = 0, skipna: bool = True, numeric_only=False, **kwargs) → Series | float[source] (https://github.com/snowflakedb/snowpark-python/blob/v1.33.0/.tox/docs/lib/python3.9/site-packages/modin/pandas/base.py#L3096-L3106)

Return unbiased skew, normalized over n-1

Parameters:

  • axis (Optional[int]) – Axis to calculate skew on, only 0 (columnar) is supported

  • skipna (Optional[bool]) – Exclude NA values when calculating result ( only True is supported )

  • numeric_only (Optional[bool]) – Include only the numeric columns ( only True is supported )

  • level (Optional[bool]) – Not Supported, included for compatibility with other stats calls

Return type:

A series ( or scalar if used on a series ) with the calculated skew

Examples

>>> df = pd.DataFrame({'A': [0, 1, 2],
...           'B': [1, 2, 1],
...           'C': [3, 4, 5]})
>>> df.skew()
A    0.000000
B    1.732059
C    0.000000
dtype: float64
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Language: English