Error with nulls in categorical columns

[SuryaThiru]

Description

Error thrown when loading penguins dataset:
ValueError: Categorical categories cannot be null

Steps/Code to Reproduce

import openml
openml.datasets.get_dataset('penguins')

Expected Results

Dataset loads without issue.

Actual Results

>>> openml.datasets.get_dataset('penguins')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/suryak/Projects/sandbox/mlgauge/env/lib/python3.8/site-packages/openml/datasets/functions.py", line 519, in get_dataset
    dataset = _create_dataset_from_description(
  File "/home/suryak/Projects/sandbox/mlgauge/env/lib/python3.8/site-packages/openml/datasets/functions.py", line 1132, in _create_dataset_from_description
    return OpenMLDataset(
  File "/home/suryak/Projects/sandbox/mlgauge/env/lib/python3.8/site-packages/openml/datasets/dataset.py", line 241, in __init__
    ) = self._create_pickle_in_cache(data_file)
  File "/home/suryak/Projects/sandbox/mlgauge/env/lib/python3.8/site-packages/openml/datasets/dataset.py", line 526, in _create_pickle_in_cache
    X, categorical, attribute_names = self._parse_data_from_arff(data_file)
  File "/home/suryak/Projects/sandbox/mlgauge/env/lib/python3.8/site-packages/openml/datasets/dataset.py", line 457, in _parse_data_from_arff
    self._unpack_categories(X[column_name], categories_names[column_name])
  File "/home/suryak/Projects/sandbox/mlgauge/env/lib/python3.8/site-packages/openml/datasets/dataset.py", line 686, in _unpack_categories
    raw_cat = pd.Categorical(col, ordered=True, categories=categories)
  File "/home/suryak/Projects/sandbox/mlgauge/env/lib/python3.8/site-packages/pandas/core/arrays/categorical.py", line 304, in __init__
    dtype = CategoricalDtype._from_values_or_dtype(
  File "/home/suryak/Projects/sandbox/mlgauge/env/lib/python3.8/site-packages/pandas/core/dtypes/dtypes.py", line 273, in _from_values_or_dtype
    dtype = CategoricalDtype(categories, ordered)
  File "/home/suryak/Projects/sandbox/mlgauge/env/lib/python3.8/site-packages/pandas/core/dtypes/dtypes.py", line 160, in __init__
    self._finalize(categories, ordered, fastpath=False)
  File "/home/suryak/Projects/sandbox/mlgauge/env/lib/python3.8/site-packages/pandas/core/dtypes/dtypes.py", line 314, in _finalize
    categories = self.validate_categories(categories, fastpath=fastpath)
  File "/home/suryak/Projects/sandbox/mlgauge/env/lib/python3.8/site-packages/pandas/core/dtypes/dtypes.py", line 508, in validate_categories
    raise ValueError("Categorical categories cannot be null")
ValueError: Categorical categories cannot be null

Versions

Linux-5.9.16-1-MANJARO-x86_64-with-glibc2.10
Python 3.8.5 (default, Sep 4 2020, 07:30:14)
[GCC 7.3.0]
Pandas 1.2.2
NumPy 1.20.1
SciPy 1.6.0
Scikit-Learn 0.24.1
OpenML 0.11.0

[Neeratyoy]

Hi @SuryaThiru

openml.datasets.get_dataset("penguins") appears to work (for me) with the dev branch, with the dependencies (for numpy, pandas especially) as you listed under versions. Could you kindly confirm the same?

If it works, please use the dev branch. We are planning to release a new version soon which then should fix this issue!

[SuryaThiru]

Installed 0.11.1dev using this command on colab (internet a bit slow to clone openml repo locally):

pip install git+https://github.com/openml/openml-python@develop

Now this command seems to work:

import openml
data = openml.datasets.get_dataset('penguins')
data

==============
Name..........: penguins
Version.......: 1
Format........: ARFF
Upload Date...: 2020-07-22 18:34:52
Licence.......: CC0
Download URL..: https://www.openml.org/data/v1/download/21854866/penguins.arff
OpenML URL....: https://www.openml.org/d/42585
# of features.: 7
# of instances: 344

However, this throws the same error

>>> data.get_data()

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-10-b4e1f6df3b81> in <module>()
----> 1 data.get_data()

9 frames
/usr/local/lib/python3.7/dist-packages/openml/datasets/dataset.py in get_data(self, target, include_row_id, include_ignore_attribute, dataset_format)
    691             List of attribute names.
    692         """
--> 693         data, categorical, attribute_names = self._load_data()
    694 
    695         to_exclude = []

/usr/local/lib/python3.7/dist-packages/openml/datasets/dataset.py in _load_data(self)
    529 
    530             file_to_load = self.data_file if self.parquet_file is None else self.parquet_file
--> 531             return self._cache_compressed_file_from_file(file_to_load)
    532 
    533         # helper variable to help identify where errors occur

/usr/local/lib/python3.7/dist-packages/openml/datasets/dataset.py in _cache_compressed_file_from_file(self, data_file)
    486 
    487         if data_file.endswith(".arff"):
--> 488             data, categorical, attribute_names = self._parse_data_from_arff(data_file)
    489         elif data_file.endswith(".pq"):
    490             try:

/usr/local/lib/python3.7/dist-packages/openml/datasets/dataset.py in _parse_data_from_arff(self, arff_file_path)
    443                 if attribute_dtype[column_name] in ("categorical", "boolean"):
    444                     col.append(
--> 445                         self._unpack_categories(X[column_name], categories_names[column_name])
    446                     )
    447                 elif attribute_dtype[column_name] in ("floating", "integer"):

/usr/local/lib/python3.7/dist-packages/openml/datasets/dataset.py in _unpack_categories(series, categories)
    648         # We require two lines to create a series of categories as detailed here:
    649         # https://pandas.pydata.org/pandas-docs/version/0.24/user_guide/categorical.html#series-creation  # noqa E501
--> 650         raw_cat = pd.Categorical(col, ordered=True, categories=categories)
    651         return pd.Series(raw_cat, index=series.index, name=series.name)
    652 

/usr/local/lib/python3.7/dist-packages/pandas/core/arrays/categorical.py in __init__(self, values, categories, ordered, dtype, fastpath)
    306 
    307         dtype = CategoricalDtype._from_values_or_dtype(
--> 308             values, categories, ordered, dtype
    309         )
    310         # At this point, dtype is always a CategoricalDtype, but

/usr/local/lib/python3.7/dist-packages/pandas/core/dtypes/dtypes.py in _from_values_or_dtype(cls, values, categories, ordered, dtype)
    275             # Note: This could potentially have categories=None and
    276             # ordered=None.
--> 277             dtype = CategoricalDtype(categories, ordered)
    278 
    279         return dtype

/usr/local/lib/python3.7/dist-packages/pandas/core/dtypes/dtypes.py in __init__(self, categories, ordered)
    162 
    163     def __init__(self, categories=None, ordered: Ordered = False):
--> 164         self._finalize(categories, ordered, fastpath=False)
    165 
    166     @classmethod

/usr/local/lib/python3.7/dist-packages/pandas/core/dtypes/dtypes.py in _finalize(self, categories, ordered, fastpath)
    316 
    317         if categories is not None:
--> 318             categories = self.validate_categories(categories, fastpath=fastpath)
    319 
    320         self._categories = categories

/usr/local/lib/python3.7/dist-packages/pandas/core/dtypes/dtypes.py in validate_categories(categories, fastpath)
    490 
    491             if categories.hasnans:
--> 492                 raise ValueError("Categorical categories cannot be null")
    493 
    494             if not categories.is_unique:

ValueError: Categorical categories cannot be null

[PGijsbers]

For those that experience this issue, the dataset is still downloaded to ~\.openml\cache\org\openml\www\datasets\42585. So if you only care about the arff file that might be of help. I'll do my best to set up a PR this afternoon.

[PGijsbers]

Fixed in #1037. Please use the develop branch for now, we plan to do a new PyPI release soon.