How to do Onehotencoding in Sklearn Pipeline

Question

I am trying to oneHotEncode the categorical variables of my Pandas dataframe, which includes both categorical and continues variables. I realise this can be done easily with the

Answer 1

OneHotEncoder doesn't support string features, and with [(d, OneHotEncoder()) for d in dummies] you are applying it to all dummies columns. Use LabelBinarizer instead:

mapper = DataFrameMapper(
    [(d, LabelBinarizer()) for d in dummies]
)

An alternative would be to use the LabelEncoder with a second OneHotEncoder step.

mapper = DataFrameMapper(
    [(d, LabelEncoder()) for d in dummies]
)

lm = PMMLPipeline([("mapper", mapper),
                   ("onehot", OneHotEncoder()),
                   ("regressor", LinearRegression())])