以下是MatLab中的偏度和峰度代码：

clc; clear all
% Generate "N" data points
N = 1:1:2000;                   
% Set sampling frequency 
Fs = 1000;          
% Set time step value
dt = 1/Fs;
% Frequency of the signal 
f = 5;
% Generate time array
t = N*dt;
% Generate sine wave
y = 10 + 5*sin(2*pi*f*t);  
% Skewness 
y_skew = skewness(y);
% Kurtosis 
y_kurt = kurtosis(y);

在MatLab中得到的答案是：
Y_skew=4.4686810415491e-15
Y_kurt=1.500000000000001(在matlab中为正值)
现在，以下是用Python编写的代码：

import numpy as np
from scipy.stats import skew
from scipy.stats import kurtosis
# Generate "N" data points
N = np.linspace(1,2000,2000)
# Set sampling frequency 
Fs = 1000          
# Set time step value
dt = 1/Fs
# Frequency of the signal 
f = 5
# Generate time array
t = N*dt
# Generate sine wave
y = 10 + 5*np.sin(2*np.pi*f*t);
# Skewness 
y_skew = skew(y)                                            
# Kurtosis 
y_kurt = kurtosis(y)

在Python中得到的答案是：
Y_SKEW=-1.8521564287013977e-16
Y_Kurt=**-**1.5(在Python中，值原来是负数)
谁能解释一下，为什么在MatLab和Python语言中，偏度和峰度有不同的答案？
具体地说，在峰度的情况下，该值已从正值变为负值。有谁能帮我理解一下这一点。