In Python NumPy what is a dimension and axis?

Question

I am coding with Pythons NumPy module. If coordinates of a point in 3D space are described as [1, 2, 1], wouldn\'t that be three dimensions, three

Answer 1

Just paste part of answer from this answer:

In Numpy, dimension, axis/axes, shape are related and sometimes similar concepts:

In [1]: import numpy as np

In [2]: a = np.array([[1,2],[3,4]])

dimension

In Mathematics/Physics, dimension or dimensionality is informally defined as the minimum number of coordinates needed to specify any point within a space. But in Numpy, according to the numpy doc, it's the same as axis/axes:

In Numpy dimensions are called axes. The number of axes is rank.

In [3]: a.ndim  # num of dimensions/axes, *Mathematics definition of dimension*
Out[3]: 2

axis/axes

the nth coordinate to index an array in Numpy. And multidimensional arrays can have one index per axis.

In [4]: a[1,0]  # to index `a`, we specific 1 at the first axis and 0 at the second axis.
Out[4]: 3  # which results in 3 (locate at the row 1 and column 0, 0-based index)

shape

describes how many data along each available axis.

In [5]: a.shape
Out[5]: (2, 2)  # both the first and second axis have 2 (columns/rows/pages/blocks/...) data