在python中使用sklearn.preprocessing中的OneHotEncoder时，在输出中获得意外的\n和\t

我正在使用

onehotcoder

将字符串列转换为数字。但是，在输出矩阵中，它给出了一些意想不到的

\n

和

\t

字符。我的代码的最后5行导致了错误

import pandas as pd
import numpy as np

car_sales_missing = pd.read_csv("Data/car-sales-extended-missing-data.csv")
X = car_sales_missing.drop("Price",axis=1)
y = car_sales_missing["Price"]

from sklearn.model_selection import train_test_split as splt
X_train, X_test, y_train, y_test = splt(X,y,test_size=0.2)

from sklearn.impute import SimpleImputer
from sklearn.compose import ColumnTransformer
cat_imputer = SimpleImputer(strategy="constant",fill_value="missing")
door_imputer = SimpleImputer(strategy="constant",fill_value=4)
num_imputer =  SimpleImputer(strategy="mean")

cat_features = ["Make","Colour"]
door_features = ["Doors"]
num_features = ["Odometer (KM)"]

imputer = ColumnTransformer([("cat_imputer",cat_imputer,cat_features), 
("num_imputer",num_imputer,num_features),("door_imputer",door_imputer,door_features)])

filled_X = imputer.fit_transform(X)

car_sales_filled = pd.DataFrame(filled_X,columns=["Make","Colour","Odometer (KM)","Doors"])
X = car_sales_filled

from sklearn.preprocessing import OneHotEncoder

categorical_features = ["Make","Colour","Doors"]
one_hot = OneHotEncoder()
transformer = ColumnTransformer([("one_hot",one_hot,categorical_features)],remainder="passthrough")
transformed_X = transformer.fit_transform(X)
pd.DataFrame(transformed_X)