## Issue

I have a numpy array and want to add a row to it and modify one column. This is my array:

```
import numpy as np
small_array = np.array ([[[3., 2., 5.],
[3., 2., 2.]],
[[3., 2., 7.],
[3., 2., 5.]]])
```

Then, firstly I wnat to add a fixed value (e.g. `2.`

) to last column. I did it this way:

```
chg = 2.
small_array[:,:,-1] += chg
```

next thing that I want to do is adding another row to each aubarray. Added row should have the same first and second columns but third column shold be different. This time chg x 2. should be subtracted from the existing value in third column:

```
big_array = np.array ([[[3., 2., 7.],
[3., 2., 4.],
[3., 2., 0.]], # this row is added
[[3., 2., 9.],
[3., 2., 7.],
[3., 2., 3.]]]) # this row is added
```

I very much appreciate any help to do it.

## Solution

I believe the operation you are looking for is `np.concatenate`

, which can construct a new array by concatenating two arrays.

Simple example, we can add a row of zeroes like this:

```
>>> np.concatenate((small_array, np.zeros((2,1,3))), axis=1)
array([[[3., 2., 7.],
[3., 2., 4.],
[0., 0., 0.]],
[[3., 2., 9.],
[3., 2., 7.],
[0., 0., 0.]]])
```

Now, instead of zeros, we can get the values from the first row in each matrix:

```
>>> np.concatenate((small_array, small_array[:,:1,:]), axis=1)
array([[[3., 2., 7.],
[3., 2., 4.],
[3., 2., 7.]],
[[3., 2., 9.],
[3., 2., 7.],
[3., 2., 9.]]])
```

At this point, you can modify the value in the third column of the new rows as needed.

The `axis`

parameter is important here, it tells `concatenate()`

along which axis I want to concatenate the two input arrays.

Documentation: https://numpy.org/doc/stable/reference/generated/numpy.concatenate.html

Answered By – joanis

Answer Checked By – Timothy Miller (BugsFixing Admin)