计算二维 NumPy 数组中跨维度的平均值

我们可以使用 numpy 和函数np.mean() 找出二维数组的每一行和每一列的平均值。在这里，我们必须提供寻找均值的轴。

Syntax: numpy.mean(arr, axis = None)

For Row mean: axis=1

For Column mean: axis=0

例子：

Python3

# Importing Library
import numpy as np
  
# creating 2d array
arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
  
# Calculating mean across Rows
row_mean = np.mean(arr, axis=1)
  
row1_mean = row_mean[0]
print("Mean of Row 1 is", row1_mean)
  
row2_mean = row_mean[1]
print("Mean of Row 2 is", row2_mean)
  
row3_mean = row_mean[2]
print("Mean of Row 3 is", row3_mean)
  
  
# Calculating mean across Columns
column_mean = np.mean(arr, axis=0)
  
column1_mean = column_mean[0]
print("Mean of column 1 is", column1_mean)
  
column2_mean = column_mean[1]
print("Mean of column 2 is", column2_mean)
  
column3_mean = column_mean[2]
print("Mean of column 3 is", column3_mean)

输出：

Mean of Row 1 is 2.0
Mean of Row 2 is 5.0
Mean of Row 3 is 8.0
Mean of column 1 is 4.0
Mean of column 2 is 5.0
Mean of column 3 is 6.0