bigframes.pandas.Series.kurt

Series.kurt()

Return unbiased kurtosis over requested axis.

Kurtosis obtained using Fisher’s definition of kurtosis (kurtosis of normal == 0.0). Normalized by N-1.

Examples:

>>> s = bpd.Series([1, 2, 2, 3], index=['cat', 'dog', 'dog', 'mouse'])
>>> s
cat      1
dog      2
dog      2
mouse    3
dtype: Int64

>>> s.kurt()
np.float64(1.5)

With a DataFrame

>>> df = bpd.DataFrame({'a': [1, 2, 2, 3], 'b': [3, 4, 4, 4]},
...                    index=['cat', 'dog', 'dog', 'mouse'])
>>> df
       a  b
cat    1  3
dog    2  4
dog    2  4
mouse  3  4

[4 rows x 2 columns]

>>> df.kurt()
a    1.5
b    4.0
dtype: Float64

Returns:

Unbiased kurtosis over requested axis.

Return type:

scalar or scalar