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amueller opened this issue Jun 1, 2018 · 3 comments · Fixed by #11197
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Add mixed categorical / continuous example with ColumnTransformer #11185

amueller opened this issue Jun 1, 2018 · 3 comments · Fixed by #11197
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@amueller
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amueller commented Jun 1, 2018

As mentioned in #9012 we should have an example in the gallery that shows how to use ColumnTransformer to deal with a mix of categorical and continuous data. I guess it should use CategoricalEncoder in the first iteration and we can change it back to OneHotEncoder once #10523 is merged.
@amueller amueller added Easy Well-defined and straightforward way to resolve help wanted labels Jun 1, 2018
@partmor
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partmor commented Jun 1, 2018

@amueller I'd be more than happy to help with this.

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amueller commented Jun 1, 2018

@partmor go for it :)

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partmor commented Jun 2, 2018 •
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From the "real world" datasets in sklearn.datasets the only one with mixed types is Boston housing, but I find it not to be very representative (1 categorical variable, already encoded).

I will build a randomly generated dataset with mixed types for the illustration. I think this would keep the example more focused on the usage of the transformer, rather than filling lines of code to read data from a UCI database url, for instance.

Any thoughts?

@partmor partmor mentioned this issue Jun 4, 2018
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[MRG] DOC add mixed categorical / continuous example with ColumnTransformer partmor/scikit-learn
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@amueller @partmor