bigframes.pandas.DataFrame.kurtosis

DataFrame.kurtosis(*, numeric_only: bool = False)

Return unbiased kurtosis over columns.

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

Examples:

>>> df = bpd.DataFrame({"A": [1, 2, 3, 4, 5],
...                     "B": [3, 4, 3, 2, 1],
...                     "C": [2, 2, 3, 2, 2]})
>>> df
    A       B       C
0   1       3       2
1   2       4       2
2   3       3       3
3   4       2       2
4   5       1       2

[5 rows x 3 columns]

Calculating the kurtosis value of each column:

>>> df.kurt()
A        -1.2
B   -0.177515
C         5.0
dtype: Float64

Parameters:

numeric_only (bool, default False) – Include only float, int, boolean columns.

Returns:

Series.

Return type:

bigframes.pandas.Series