Difference of skew values in scipy and pandas

Beginners
1

Now i am developing the system for data cleaning, I can notice one thing.
The value of skew in scipy and pandas are totally different.
Of course I found the formula of skew and then calculate manually.
The result is the same as pandas.
Then what is the result of scipy skew?
And what is the formula and what does it stand for?
Help me!

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

data = [2, 3, 4, 24, 31]

# Scipy skew
scipy_skew = skew(data)

# Pandas skew
pandas_skew = pd.Series(data).skew()

print(f'Scipy Skewness: {scipy_skew}')
print(f'Pandas Skewness: {pandas_skew}')
1 Like
2

Solved.

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

data = [2, 3, 4, 24, 31]

# Scipy skew
scipy_skew = skew(data)
scipy_skew_biasfalse = skew(data, bias=False)

# Pandas skew
pandas_skew = pd.Series(data).skew()

print(f'Scipy Skewness: {scipy_skew}')
print(f'Scipy Skewness (bias=False): {scipy_skew_biasfalse}')
print(f'Pandas Skewness: {pandas_skew}')

Scipy Skewness: 0.4986511500628641
Scipy Skewness (bias=False): 0.7433452457326751
Pandas Skewness: 0.7433452457326751