tnabdb - 1 year ago 73

Python Question

Suppose I have a numpy array like: [11, 30, 25]. These numbers represent categories of the objects corresponding to the indices. I know there are just 20 categories but for some reason they are numbered from 11 to 29. I'd like to convert them to numbers in 0:19 and back. What would by a pythonic way to do this? Preferably in bumpy.

EDIT: this is just a small example of a bigger problem, where the number of categories are in the thousands, and some categories are never represented, so the maximum id will be the number of unique existing categories.

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Answer Source

To be able to easily convert back-and-forth, I would use the `sklearn.preprocessing`

module `LabelEncoder`

:

```
In [7]: from sklearn.preprocessing import LabelEncoder
In [8]: encoder = LabelEncoder()
In [9]: encoder.fit(range(11,31))
Out[9]: LabelEncoder()
In [10]: encoder.transform([11,30,25])
Out[10]: array([ 0, 19, 14])
In [11]: encoder.inverse_transform([18, 1, 15])
Out[11]: array([29, 12, 26])
```

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