Python numpy.mean()
numpy.mean(arr, axis = None) :计算给定数据(数组元素)沿指定轴的算术平均数(平均值)。
参数 :
arr :[array_like]输入阵列。
axis :[int或int的tuples]轴,我们想沿着这个轴计算算术平均值。否则,它将认为arr是被压扁的(对所有的
axis = 0表示沿着列工作, axis = 1表示沿着行工作。
out :[ndarray, optional]不同的数组,我们想把结果放在其中。该数组必须具有与预期输出相同的尺寸。
dtype :[数据类型,可选]我们在计算平均值时希望的类型。
结果s :数组的算术平均值(如果没有轴,则为标量值)或沿指定轴的平均值的数组。
代码 #1:
# Python Program illustrating
# numpy.mean() method
import numpy as np
# 1D array
arr = [20, 2, 7, 1, 34]
print("arr : ", arr)
print("mean of arr : ", np.mean(arr))
输出 :
arr : [20, 2, 7, 1, 34]
mean of arr : 12.8
代码 #2:
# Python Program illustrating
# numpy.mean() method
import numpy as np
# 2D array
arr = [[14, 17, 12, 33, 44],
[15, 6, 27, 8, 19],
[23, 2, 54, 1, 4, ]]
# mean of the flattened array
print("\nmean of arr, axis = None : ", np.mean(arr))
# mean along the axis = 0
print("\nmean of arr, axis = 0 : ", np.mean(arr, axis = 0))
# mean along the axis = 1
print("\nmean of arr, axis = 1 : ", np.mean(arr, axis = 1))
out_arr = np.arange(3)
print("\nout_arr : ", out_arr)
print("mean of arr, axis = 1 : ",
np.mean(arr, axis = 1, out = out_arr))
输出 :
mean of arr, axis = None : 18.6
mean of arr, axis = 0 : [17.33333333 8.33333333 31. 14. 22.33333333]
mean of arr, axis = 1 : [24. 15. 16.8]
out_arr : [0 1 2]
mean of arr, axis = 1 : [24 15 16]