Axes in Numpy arrays

In Numpy arrays, the axis is the direction along the rows and columns. A two-dimensional numpy array has the following two corresponding axes:

vertical axis (axis 0)
horizontal axis (axis 1)

Let us see an example to understand the concept of axis:

Getting minimum value with axes

Specifying axes will calculate values along that specific axes only. Let us see an example. We have used the min() method and the axis attribute:

import numpy as np

# Create a numpy 3x5 array
n = np.array([[2, 5, 7, 9, 6], [15, 25, 35, 45, 55], [100, 200, 300, 400, 500]])

print("Iterating 2D array...")
for a in n:
    print(a)

print("\nMinimum value = ", n.min())
print("\nMinimum value with axis 0 (vertical axes) = ", n.min(axis=0))
print("\nMinimum value with axis 1 (horizontal axes) = ", n.min(axis=1))

Output

Iterating 2D array...
[2 5 7 9 6]
[15 25 35 45 55]
[100 200 300 400 500]

Minimum value =  2

Minimum value with axis 0 (vertical axes) =  [2 5 7 9 6]

Minimum value with axis 1 (horizontal axes) =  [  2  15 100]

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Read More:

Sorting Numpy Arrays
Intersection of Numpy Arrays
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