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Unable to reproduce OneHotEncoder example from the docs

See original GitHub issue

This example from the API reference returns an error:

from dask_ml.preprocessing import OneHotEncoder
import numpy as np
import dask.array as da
enc = OneHotEncoder()
X = da.from_array(np.array([['A'], ['B'], ['A'], ['C']]), chunks=2)
enc.fit(X)
enc.categories_
enc.transform(X)

This is the traceback:

ValueErrorTraceback (most recent call last)
<ipython-input-1-f54891b18539> in <module>
      6 enc.fit(X)
      7 enc.categories_
----> 8 enc.transform(X)

~/myenv/lib/python3.7/site-packages/dask_ml/preprocessing/_encoders.py in transform(self, X)
    211         self, X: Union[ArrayLike, DataFrameType]
    212     ) -> Union[ArrayLike, DataFrameType]:
--> 213         return self._transform(X)
    214 
    215     def _transform_new(

~/myenv/lib/python3.7/site-packages/dask_ml/preprocessing/_encoders.py in _transform(self, X, handle_unknown)
    243                 for i in range(n_features)
    244             ]
--> 245             X = da.concatenate(Xs, axis=1)
    246 
    247             if not self.sparse:

~/myenv/lib/python3.7/site-packages/dask/array/core.py in concatenate(seq, axis, allow_unknown_chunksizes)
   3480         raise ValueError("Need array(s) to concatenate")
   3481 
-> 3482     meta = np.concatenate([meta_from_array(s) for s in seq], axis=axis)
   3483 
   3484     # Promote types to match meta

<__array_function__ internals> in concatenate(*args, **kwargs)

ValueError: zero-dimensional arrays cannot be concatenated

Environment:

Dask version: 2.19.0
numpy version: 1.18.5
Python version: 3.7.6
Install method (conda, pip, source): conda

Issue Analytics

State:
Created 3 years ago
Comments:6 (4 by maintainers)

Top GitHub Comments

1reaction

TomAugspurgercommented, Jun 23, 2020

https://github.com/dask/dask/pull/6339 was just merged, so going to go ahead and close.

For now, you can install Dask from GitHub, or we’ll have a release in a week or two.

1reaction

TomAugspurgercommented, Jun 22, 2020

Just FYI @SultanOrazbayev, this may be being fixed upstream in https://github.com/dask/dask/pull/6339.

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