如何在熊猫中正确找到偏度和峰度？

Question

我想知道如何在熊猫中正确计算偏度和峰度。Pandas 给出了一些值skew()和kurtosis()值，但它们似乎与值大不相同scipy.stats。哪个信任熊猫或scipy.stats？

这是我的代码：

import numpy as np
import scipy.stats as stats
import pandas as pd

np.random.seed(100)
x = np.random.normal(size=(20))

kurtosis_scipy = stats.kurtosis(x)
kurtosis_pandas = pd.DataFrame(x).kurtosis()[0]

print(kurtosis_scipy, kurtosis_pandas)
# -0.5270409758168872
# -0.31467107631025604

skew_scipy = stats.skew(x)
skew_pandas = pd.DataFrame(x).skew()[0]

print(skew_scipy, skew_pandas)
# -0.41070929017558555
# -0.44478877631598901

版本：

print(np.__version__, pd.__version__, scipy.__version__)
1.11.0 0.20.0 0.19.0

Answer 1

bias=False

print(
    stats.kurtosis(x, bias=False), pd.DataFrame(x).kurtosis()[0],
    stats.skew(x, bias=False), pd.DataFrame(x).skew()[0],
    sep='\n'
)

-0.31467107631025515
-0.31467107631025604
-0.4447887763159889
-0.444788776315989