Add as_frame='auto' option in datasets.fetch_openml#17396
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rth merged 5 commits intoscikit-learn:masterfrom Jun 10, 2020
Merged
Add as_frame='auto' option in datasets.fetch_openml#17396rth merged 5 commits intoscikit-learn:masterfrom
rth merged 5 commits intoscikit-learn:masterfrom
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ping |
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Sounds good to me aside from a few comments below. I would also be +1 to make "auto" the default since fetch_openml is experimental.
| data. If ``return_X_y`` is True, then ``(data, target)`` will be pandas | ||
| DataFrames or Series as describe above. | ||
| If as_frame is 'auto', the data and target will be converted to | ||
| DataFrame or Series as if as_frame is set to True, unless the dataset |
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data.target may be a Series. For example:
data_id = 61 # iris dataset version 1
data = fetch_openml(data_id=data_id, as_frame=True)
>>> type(data.target)
<class 'pandas.core.series.Series'>Co-authored-by: Roman Yurchak <rth.yurchak@gmail.com>
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Thanks!
I would also be +1 to make "auto" the default since fetch_openml is experimental.
Let's see what other reviewers think about doing that.
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I'm okay with making it default. If the occasional user needs to change
their code to add .values, so be it.
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Could you propose that change to default in another pull request? |
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Sure. Do you want to merge this first? Or do I branch out from here? |
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Thanks! Please open a new PR for changing the default. |
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Reference Issues/PRs
Closes #14888
What does this implement/fix? Explain your changes.
This PR adds an
'auto'option for argumentas_framein functiondatasets.fetch_openml.When
as_frameis set to be'auto', returned data will be converted to pandas DataFrame or Series unless data is sparse.Any other comments?
This PR doesn't fully close #14888. The team still need to discuss and decide whether to make
'auto'the default option.