Abnormal data processing

[Zas169]

def drop_outlier(array,count,bins):
index = []
range_ = np.arange(1,count,bins)
for i in range_[:-1]:
array_lim = array[i:i+bins]
sigma = np.std(array_lim)
mean = np.mean(array_lim)
th_max,th_min = mean + sigma2, mean - sigma2
idx = np.where((array_lim < th_max) & (array_lim > th_min))
idx = idx[0] + i
index.extend(list(idx))
return np.array(index)。这段代码中为啥range_ = np.arange(1,count,bins)这行代码从1开始，而不是从0开始