Predicting missing values with scikit-learn's Imputer module

Question

I am writing a very basic program to predict missing values in a dataset using scikit-learn\'s Imputer class.

I have made a NumPy array, created an Imp

Answer 1

Note: Due to the change in the sklearn library 'NaN' has to be replaced with np.nan as shown below.

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