A visual guide to multidimensional NumPy array aggregation

A visual guide to multidimensional NumPy array aggregation

A visual guide to multidimensional NumPy array aggregation. If you are just learning to use the aggregate functions in NumPy like sum, mean or median, understanding what the axis parameter does can be difficult. In the following article I provide an intuitive…

An intuitive way of thinking about axis numbering

If you are just learning to use the aggregate functions in NumPy like sum, mean or median, understanding what the axis parameter does can be difficult. In the following article I provide an intuitive visual guide to axis numbering so you can always make sure that your code works as intended.

Aggregating a 1-dimensional array is straightforward since there is only one axis to consider. With 2 or more dimensions, however, we must think about the direction along which we wish to aggregate our array. In this guide we will discuss one-, two- and three-dimensional problems using the numpy.sum() function. (Note: other aggregate functions like mean, median, amin, amax use the same logic.)

data-science python numpy arrays

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