I have a numpy 1D array:

```
import numpy as np
arr = np.array([1, 1, 3, -2, -1, 2, 0, 2, 1, 1, -3, -1, 2])
```

I want split it into another two-dimensional array, based on changes in positive and negative values of array’s elements(0 is placed in the range of positive values). But the original order of elements should be maintained.

The desired result is:

```
new_arr = [[1, 1, 3], [-2, -1], [2, 0, 2, 1, 1], [-3, -1], [2]]
```

### >Solution :

You could use `array_split`

, `diff`

, `nonzero`

:

```
np.array_split(arr, np.nonzero(np.diff(arr>=0))[0]+1)
```

Ouptut:

```
[array([1, 1, 3]),
array([-2, -1]),
array([2, 0, 2, 1, 1]),
array([-3, -1]),
array([2])]
```

Intermediates:

```
# arr>0
[ True True True False False True False True True True False False True]
# np.diff(arr>=0)
[False False True False True False False False False True False True]
# np.nonzero(np.diff(arr>=0))[0]+1
[ 3 5 10 12]
```

And for lists as output:

```
out = list(map(list, np.array_split(arr, np.nonzero(np.diff(arr>=0))[0]+1)))
```

Output:

```
[[1, 1, 3], [-2, -1], [2, 0, 2, 1, 1], [-3, -1], [2]]
```

Or using `itertools.groupby`

:

```
from itertools import groupby
out = [list(g) for _,g in groupby(arr, key=lambda x: x>=0)]
```

Output:

```
[[1, 1], [3, -2], [-1, 2, 0, 2, 1], [1, -3], [-1, 2]]
```