性别列中有一些缺失值，希望使用KNN插补来插补这些值。但是我没有得到填充的结果！有人可以帮助吗？

import pandas as pd
import numpy as np
from sklearn.impute import KNNImputer

data = {'ID': [1, 2, 3, 4, 5],
        'Age': [20, 25, 30, 35, 40],
        'Gender': ['M', 'F', np.nan, 'F', np.nan]}
df = pd.DataFrame(data)
imputer = KNNImputer(n_neighbors=2)
df['Gendermap'] = pd.factorize(df['Gender'])[0]
df['Gender_imputed_factorized'] = imputer.fit_transform(df[['Gendermap']])
df['Gender_imputed'] = pd.unique(df['Gender'])[df['Gender_imputed_factorized'].astype(int)]
df

输出：

ID  Age Gender  Gendermap  Gender_imputed_factorized Gender_imputed
0   1   20      M          0                        0.0              M
1   2   25      F          1                        1.0              F
2   3   30    NaN         -1                       -1.0            NaN
3   4   35      F          1                        1.0              F
4   5   40    NaN         -1                       -1.0            NaN

“性别插补”列不应包含Nan值。