from sklearn.preprocessing import Imputer

I'm sorry, but the `Imputer` module has been removed in the latest version of scikit-learn. Instead, you can use the `SimpleImputer` module which has similar functionalities. Here's an example of how to use it:

from sklearn.impute import SimpleImputer

# create an instance of SimpleImputer with the desired strategy (mean, median, most_frequent)
imputer = SimpleImputer(strategy='mean')

# fit the imputer to the data
imputer.fit(X)

# transform the data by filling in missing values with the imputer's strategy
X_imputed = imputer.transform(X)

Note that `X` is your input data with missing values. You can also specify which columns to impute by passing a boolean mask to the `fit` and `transform` methods.