Aggregations on matrix in Python

               Aggregations are the data transformation techniques which produces scalar values from arrays. Let us implement this two ways

• 1.      Using python code
• 2.      Using Numpy

The code is given below…

1.Using python code:

              This method creates a matrix.It calculates the row wise sum,column wise sum and overall sum. It also finds the maximum value in row wise and column wise.

Finally,it displays the values.

Code:

s_matrix = [

    [2, 2, 1],

    [6, 5, 4],

    [3, 8, 9]

]

# Let us find Row-wise sum

row_sums = [sum(row) for row in s_matrix]

# Let us find Column-wise sum

col_sums = [sum(s_matrix[r][c] for r in range(len(s_matrix))) for c in range(len(s_matrix[0]))]

# Sum of all the elements

total_sum = sum(sum(row) for row in s_matrix)

# To find maximum value in Row-wise

row_max = [max(row) for row in s_matrix]

# To find maximum value in Column-wise

col_max = [max(s_matrix[r][c] for r in range(len(s_matrix))) for c in range(len(s_matrix[0]))]

print("Row elements sums:", row_sums)

print("Column elements sums:", col_sums)

print("Overall elements sum:", total_sum)

print("Row max Value:", row_max)

print("Column max Value:", col_max)

Output:

Row elements sums: [5, 15, 20]

Column elements sums: [11, 15, 14]

Overall elements sum: 40

Row max Value: [2, 6, 9]

Column max Value: [6, 8, 9]

This is the first method. Second method is given below.

2. Using numpy

               This method uses the built-in numpy package.

import numpy as np1

# Create a NumPy sample matrix

s_matrix = np1.array([

    [3, 2, 1],

    [9, 5, 4],

    [6, 8, 7]

])

# let us perform Aggregations

row_sums = np1.sum(s_matrix, axis=1)  

col_sums = np1.sum(s_matrix, axis=0)  

total_sum = np1.sum(s_matrix)        

row_max = np1.max(s_matrix, axis=1)   

col_max = np1.max(s_matrix, axis=0)  

print("Sum of Row elements:", row_sums)

print("Sum of Column elements:", col_sums)

print("Sum of Total elements:", total_sum)

print("Maximum value in the Row:", row_max)

print("Maximum value in the Column:", col_max)

Output:

Sum of Row elements: [ 6 18 21]

Sum of Column elements: [18 15 12]

Sum of Total elements: 45

Maximum value in the Row: [3 9 8]

Maximum value in the Column: [9 8 7]

This method is suitable for large matrices.

These are the methods to implement Aggregations on matrix in python. Hope, this code is useful to you. Keep coding!!!