特征锦囊：怎么定义一个方法去填充分类变量的空值？

# 本次案例使用的数据集
import pandas as pd
X = pd.DataFrame({'city':['tokyo',None,'london','seattle','san fancisco','tokyo'],
                  'boolean':['y','n',None,'n','n','y'],
                  'ordinal_column':['somewhat like','like','somewhat like','like','somewhat like','dislike'],
                  'quantitative_column':[1,11,-.5,10,None,20]})
X

# 填充分类变量（基于TransformerMixin的自定义填充器，用众数填充）
from sklearn.base import TransformerMixin
class CustomCategoryzImputer(TransformerMixin):
    def __init__(self, cols=None):
        self.cols = cols
        
    def transform(self, df):
        X = df.copy()
        for col in self.cols:
            X[col].fillna(X[col].value_counts().index[0], inplace=True)
        return X
    
    def fit(self, *_):
        return self
    
# 调用自定义的填充器
cci = CustomCategoryzImputer(cols=['city','boolean'])
cci.fit_transform(X)