Nikolay Ambartsumov - 1 year ago 67

Python Question

Let's assume I have an array like this:

`a = np.array([5, 2, 13, 13, 222])`

I want to convert it to an array like this:

`b = np.array([1, 0, 2, 2, 3])`

I've tried np.argsort, but returns

`np.argsort(np.array([5, 2, 13, 13, 222])) # = array([1, 0, 2, 3, 4])`

which doesn't do exactly what I need it to do (it still assigns different indexes to identical elements.

So far I've written this little function to do what I want:

`def indexate_array(v):`

v_unique = np.unique(v)

result = shape_like(v)

dic = {value: result for value, result in zip(v_unique, np.argsort(v_unique))}

for i, val in enumerate(v):

result[i] = dic[val]

return result

Is there an elegant way to perform the operation I want using numpy/scipy?

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Answer Source

This is what the `return_inverse`

parameter to `numpy.unique`

does:

```
In [5]: np.unique(a, return_inverse=True)
Out[5]: (array([ 2, 5, 13, 222]), array([1, 0, 2, 2, 3]))
```