CODEWITHSUNDEEP
pythonscikit-learnneural-networkone-hot-encoding
Fikile
Fikile

Reputation: 117

OneHotEncoding Categorical data

I am trying to use OneHotEncoding to transform the second column of my csv file, which consists of company names.

from sklearn.preprocessing import OneHotEncoder
ct = ColumnTransformer(transformers=[('encoder', OneHotEncoder(), [1])]), remainder='passthrough'
X = np.array(ct.fit_transform(X))

and I received this error:

    ct = ColumnTransformer(transformers=[('encoder', OneHotEncoder(), [1])]), remainder='passthrough'
                  ^
SyntaxError: can't assign to function call

Where did i go wrong? I understand that perhaps there is an error with how I wrote the ct line, but i do not know exactly what I did wrong.

Upvotes: 0

Views: 159

Answers (2)

jahed sunny
jahed sunny

Reputation: 1

you can call columntransformer from sklearn.compose first write the code like this from sklearn.compose import ColumnTransformer from sklearn.preprocessing import OneHotEncoder ct = ColumnTransformer(transformers=[('encoder', OneHotEncoder(), [1])]), remainder='passthrough' X = np.array(ct.fit_transform(X))

Upvotes: 0

Kim Tang
Kim Tang

Reputation: 2478

I think you set a bracket incorrectly and it should probably be like this:

ct = ColumnTransformer(transformers=[('encoder', OneHotEncoder(), [1])], remainder='passthrough')

Upvotes: 1

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