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.

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]])
```

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

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
```

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)
```

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
```

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