一种方法是使用
numpy.digitize来分类您的类别.
然后使用字典或列表推导来计算结果.
import numpy as np
chl = np.array([0.4,0.1,0.04,0.05,0.4,0.2,0.6,0.09,0.23,0.43,0.65,0.22,0.12,0.2,0.33])
depth = np.array([0.1,0.3,0.31,0.44,0.49,1.1,1.145,1.33,1.49,1.53,1.67,1.79,1.87,2.1,2.3])
bins = np.array([0,0.5,1.0,1.5,2.0,2.5])
A = np.vstack((np.digitize(depth, bins), chl)).T
res = {bins[int(i)]: np.mean(A[A[:, 0] == i, 1]) for i in np.unique(A[:, 0])}
# {0.5: 0.198, 1.5: 0.28, 2.0: 0.355, 2.5: 0.265}
或者您所追求的精确格式：
res_lst = [np.mean(A[A[:, 0] == i, 1]) for i in range(len(bins))]
# [nan, 0.198, nan, 0.28, 0.355, 0.265]