Impute categorical missing values in scikit-learn

Question

I\'ve got pandas data with some columns of text type. There are some NaN values along with these text columns. What I\'m trying to do is to impute those NaN\'s by skle

Answer 1

There is a package sklearn-pandas which has option for imputation for categorical variable https://github.com/scikit-learn-contrib/sklearn-pandas#categoricalimputer

>>> from sklearn_pandas import CategoricalImputer
>>> data = np.array(['a', 'b', 'b', np.nan], dtype=object)
>>> imputer = CategoricalImputer()
>>> imputer.fit_transform(data)
array(['a', 'b', 'b', 'b'], dtype=object)