## Question

Asked By – Ben

I want to create an empty array and append items to it, one at a time.

```
xs = []
for item in data:
xs.append(item)
```

Can I use this list-style notation with NumPy arrays?

**Now we will see solution for issue: How do I create an empty array and then append to it in NumPy? **

## Answer

That is the wrong mental model for using NumPy efficiently. NumPy arrays are stored in contiguous blocks of memory. To append rows or columns to an existing array, the entire array needs to be copied to a new block of memory, creating gaps for the new elements to be stored. This is very inefficient if done repeatedly.

Instead of appending rows, allocate a suitably sized array, and then assign to it row-by-row:

```
>>> import numpy as np
>>> a = np.zeros(shape=(3, 2))
>>> a
array([[ 0., 0.],
[ 0., 0.],
[ 0., 0.]])
>>> a[0] = [1, 2]
>>> a[1] = [3, 4]
>>> a[2] = [5, 6]
>>> a
array([[ 1., 2.],
[ 3., 4.],
[ 5., 6.]])
```

This question is answered By – Stephen Simmons

**This answer is collected from stackoverflow and reviewed by FixPython community admins, is licensed under cc by-sa 2.5 , cc by-sa 3.0 and cc by-sa 4.0 **