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# Stack and Split
# Stack and Split, Compress
{:.no_toc}
<nav markdown="1" class="toc-class">
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[18 19]]
```
## [numpy.compress](https://numpy.org/doc/stable/reference/generated/numpy.compress.html)
```python
numpy.compress(condition, a, axis=None, out=None)
```
> Return selected slices of an array along given axis.
>
> When working along a given axis, a slice along that axis is returned in output for each index where condition evaluates to True. When working on a 1-D array, compress is equivalent to extract.
```python
import numpy as np
a = np.arange(0, 20).reshape(5, 4)
print(a)
print(a.shape) # -> (5, 4)
print()
b = np.compress([True, False, False, True, True], a, axis=0)
print(b)
print(b.shape) # -> (3, 4)
print()
b = np.compress([False, True, False, True], a, axis=1)
print(b)
print(b.shape) # -> (5, 2)
```
Output:
```python
[[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]
[12 13 14 15]
[16 17 18 19]]
[[ 0 1 2 3]
[12 13 14 15]
[16 17 18 19]]
[[ 1 3]
[ 5 7]
[ 9 11]
[13 15]
[17 19]]
```