# [SOLVED] What does a numpy shape starting with zero mean

## Issue

Okay, so I found out that you can have arrays with 0s in their shape.
For the case where you have 0 as the only dimension, this makes sense to me. It is an empty array.

``````np.zeros(0)
``````

But the case where you have something like this:

``````np.zeros((0, 100))
``````

Is confusing for me. Why is it defined like this?

## Solution

As far as I know it’s just a redundant way to express an empty array. It doesn’t seems to matter for python if you have rows of “emptiness”.

Let’s say we have a give array a:

``````import numpy as np

a = np.zeros((0,100))
``````

If we print a all we get is the empty array itself:

``````print(a)

>>> []
``````

Moreover we can actually see that despite this a maintain it’s shape”

``````np.shape(a)

>>> (0, 100)
``````

But if you try to access a given element by position, e.g:

``````print(a[0])
``````

or

``````print(a[0][0])
``````

You get an IndexError :

``````IndexError: index 0 is out of bounds for axis 0 with size 0
``````

Therefore I believe that the mathematical meaning of the empty arrays, despite the shape you assign to them, is the same.