how to import imputer from sklearn code example

Example 1: sciket learn imputer code

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

Example 2: Multivariate feature imputation

# Multivariate feature imputation

import numpy as np
from sklearn.experimental import enable_iterative_imputer
from sklearn.impute import IterativeImputer
imp = IterativeImputer(max_iter=10, random_state=0)
imp.fit([[1, 2], [3, 6], [4, 8], [np.nan, 3], [7, np.nan]])
# IterativeImputer(random_state=0)
X_test = [[np.nan, 2], [6, np.nan], [np.nan, 6]]
# the model learns that the second feature is double the first
print(np.round(imp.transform(X_test)))
# [[ 1.  2.]
#  [ 6. 12.]
#  [ 3.  6.]]

Example 3: sklearn imputer

OneHotEncoder(categories=     total_bill   tip     sex smoker   day    time  size
0         16.99  1.01  Female     No   Sun  Dinner     2
1         10.34  1.66    Male     No   Sun  Dinner     3
2         21.01  3.50    Male     No   Sun  Dinner     3
3         23.68  3.31    Male     No   Sun  Dinner     2
4         24.59  3.61  Female     No   Sun  Dinner     4
..          ...   ...     ...    ...   ...     ...   ...
239       29.03  5.92    Male     No   Sat  Dinner     3
240       27.18  2.00  Female    Yes   Sat  Dinner     2
241       22.67  2.00    Male    Yes   Sat  Dinner     2
242       17.82  1.75    Male     No   Sat  Dinner     2
243       18.78  3.00  Female     No  Thur  Dinner     2

[244 rows x 7 columns],
              drop=None, dtype=<class 'numpy.float64'>, handle_unknown='error',
              sparse=True)