lerner adams - 1 month ago 5

Python Question

I have a very sparse array, for illustration like the following:

`arr = array([[0, 1, 0, 0, 0, 2],`

[0, 0, 2, 0, 0, 0],

[0, 0, 0, 0, 0, 0],

[0, 7, 0, 0, 4, 0]])

Since the columns indexed 0 and 3 are all zeros I want to delete them and get the result as this:

`array([[1, 0, 0, 2],`

[0, 2, 0, 0],

[0, 0, 0, 0],

[7, 0, 4, 0]])

I thought I can check every column by

`for i in len(arr):`

if arr[:, i] != 0:

newarr = np.column_stack((newarr, arr[:, i]))

But I encounter an error which teaches me to use a.all()..

Answer

Use a simple indexing, by picking the columns that have at least one non-zero item (using `any()`

over the first axis):

```
In [9]: arr[:, arr.any(0)]
Out[9]:
array([[1, 0, 0, 2],
[0, 2, 0, 0],
[0, 0, 0, 0],
[7, 0, 4, 0]])
```

Source (Stackoverflow)

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