# [Solved] numpy array TypeError: only integer scalar arrays can be converted to a scalar index

Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error numpy array TypeError: only integer scalar arrays can be converted to a scalar index in python. So Here I am Explain to you all the possible solutions here.

## How numpy array TypeError: only integer scalar arrays can be converted to a scalar index Error Occurs?

Today I get the following error numpy array TypeError: only integer scalar arrays can be converted to a scalar index in python.

## How To Solve numpy array TypeError: only integer scalar arrays can be converted to a scalar index Error ?

1. How To Solve numpy array TypeError: only integer scalar arrays can be converted to a scalar index Error ?

To Solve numpy array TypeError: only integer scalar arrays can be converted to a scalar index Error I ran into the problem when venturing to use numpy.concatenate to emulate a C++ like pushback for 2D-vectors; If A and B are two 2D numpy.arrays, then numpy.concatenate(A,B) yields the error.

2. numpy array TypeError: only integer scalar arrays can be converted to a scalar index

To Solve numpy array TypeError: only integer scalar arrays can be converted to a scalar index Error I ran into the problem when venturing to use numpy.concatenate to emulate a C++ like pushback for 2D-vectors; If A and B are two 2D numpy.arrays, then numpy.concatenate(A,B) yields the error.

## Solution 1

I ran into the problem when venturing to use numpy.concatenate to emulate a C++ like pushback for 2D-vectors; If A and B are two 2D numpy.arrays, then numpy.concatenate(A,B) yields the error.

The fix was to simply to add the missing brackets: numpy.concatenate( ( A,B ) ), which are required because the arrays to be concatenated constitute to a single argument

## Solution 2

This could be unrelated to this specific problem, but I ran into a similar issue where I used NumPy indexing on a Python list and got the same exact error message:

```# incorrect
weights = list(range(1, 129)) + list(range(128, 0, -1))
mapped_image = weights[image[:, :, band]] # image.shape = [800, 600, 3]
# TypeError: only integer scalar arrays can be converted to a scalar index
```

It turns out I needed to turn `weights`, a 1D Python list, into a NumPy array before I could apply multi-dimensional NumPy indexing. The code below works:

```# correct
weights = np.array(list(range(1, 129)) + list(range(128, 0, -1)))
mapped_image = weights[image[:, :, band]] # image.shape = [800, 600, 3]```

## Summery

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you? Thank You.