python 3.x - TypeError while handling missing data using SimpleImputer

Question

I am trying to handle the missing data in my dataset using SimpleImputer from sklearn.imputer and my code is as follows :

from sklearn.impute import SimpleImputer
imputer = SimpleImputer(missing_values=np.nan, strategy='mean', verbose=0)
imputer = imputer.fit(X[:,1:3])
X[:,1:3] = imputer.transform(X[:,1:3])

and when imputer.fit line is executed I get the following TypeError :

Exception has occurred: TypeError '(slice(0, None, None), slice(1, 3, None))' is an invalid key

Answer 1

The above error can be resolved by using iloc/loc as follows :

 from sklearn.impute import SimpleImputer
imputer = SimpleImputer(missing_values=np.nan, strategy='mean', verbose=0)
imputer = imputer.fit(X.iloc[:,1:3])
X.iloc[:,1:3] = imputer.transform(X.iloc[:,1:3])

This works now!