We can find out the mean of each row and column of 2d array using numpy with the function np.mean(). Here we have to provide the axis for finding mean.
Syntax: numpy.mean(arr, axis = None)
For Row mean: axis=1
For Column mean: axis=0
Example:
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) |
Output:
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
