# Numpy array dimensions

### Question

I'm currently trying to learn Numpy and Python. Given the following array:

``````import numpy as np
a = np.array([[1,2],[1,2]])
``````

Is there a function that returns the dimensions of `a` (e.g.a is a 2 by 2 array)?

`size()` returns 4 and that doesn't help very much.

1
325
12/21/2018 3:43:19 AM

It is `.shape`:

ndarray.shape
Tuple of array dimensions.

Thus:

``````>>> a.shape
(2, 2)
``````
445
6/17/2010 12:59:46 PM

## First:

By convention, in Python world, the shortcut for `numpy` is `np`, so:

``````In [1]: import numpy as np

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

## Second：

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

### 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 (or the range) 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
``````