#Loading Libraries
from sklearn.impute import KNNImputer
import numpy as np
# create a dataset with missing values
X = np.array([[1, 2, np.nan], [3, 4, 5], [np.nan, 6, 7], [8, 9, 10]])
# instantiate a KNNImputer object with k=3
imputer = KNNImputer(n_neighbors=3)
# impute the missing values in X
X_imputed = imputer.fit_transform(X)
# print the imputed dataset
print(X_imputed)