Python中的 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值(平均值)。
Parameters :
arr : [array_like]input array.
axis : [int or tuples of int]axis along which we want to calculate the arithmetic mean. Otherwise, it will consider arr to be flattened(works on all
the axis). axis = 0 means along the column and axis = 1 means working along the row.
out : [ndarray, optional]Different array in which we want to place the result. The array must have the same dimensions as expected output.
dtype : [data-type, optional]Type we desire while computing mean.
Results : Arithmetic mean of the array (a scalar value if axis is none) or array with mean values along specified axis.
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]