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Lære Aggregating in 2-D Arrays | Introduction to NumPy
Introduction to Data Analysis in Python

bookAggregating in 2-D Arrays

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.

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# 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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Sektion 5. Kapitel 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
copy

Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 5. Kapitel 6
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