Learn Aggregating in 2-D Arrays | Introduction to NumPy

All the aggregate functions learned in this section can be used along either columns, or rows. To do it, you need to specify the axis parameter within aggregate function.

For example, we can compute the sum of rows and columns elements separately.


              1234567
            
# Import the library
import numpy as np
# Creating array
arr = np.array([[5.2, 3.0, 4.5], [9.1, 0.1, 0.3]])
# Sum of rows and columns elements
print(arr.sum(axis = 0)) # columns
print(arr.sum(axis = 1)) # rows

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Thanks for your feedback!

Section 5. Chapter 6

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All the aggregate functions learned in this section can be used along either columns, or rows. To do it, you need to specify the axis parameter within aggregate function.

For example, we can compute the sum of rows and columns elements separately.


              1234567
            
# Import the library
import numpy as np
# Creating array
arr = np.array([[5.2, 3.0, 4.5], [9.1, 0.1, 0.3]])
# Sum of rows and columns elements
print(arr.sum(axis = 0)) # columns
print(arr.sum(axis = 1)) # rows

Everything was clear?

Thanks for your feedback!

Section 5. Chapter 6