我正在尝试使用onehotencoder转换我的分类数据，但是，我被困在这一步：

X =变压器.fit_transform（X）

我不确定我错过了什么，但是我对python不太了解，感谢任何愿意帮助的人，谢谢！

这是数据集： Data.csv

我正在尝试转换“国家/地区”列

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

#import dataset
dataset = pd.read_csv("Data.csv")
X = dataset.iloc[:,:-1].values
Y = dataset.iloc[:,3].values

#Taking care of Missing data
from sklearn.impute import SimpleImputer  
imputer = SimpleImputer(missing_values=np.nan,strategy='mean')
imputer = imputer.fit(X[:,1:3])
X[:,1:3] = imputer.transform(X[:,1:3])

#Encoding Categorical data
from sklearn.preprocessing import LabelEncoder,OneHotEncoder
from sklearn.compose import ColumnTransformer
labelencoder_X = LabelEncoder()
X[:,0] = labelencoder_X.fit_transform(X[:,0])

transformer = ColumnTransformer([('one_hot_encoder',OneHotEncoder(),[0])],remainder='passthrough')
X = transformer.fit_transform(X)
#X = np.array(transformer.fit_transform(X),dtype=np.float)
labelencoder_Y = LabelEncoder()
Y = labelencoder_Y.fit_transform(Y)

这是错误：

ValueError: all the input arrays must have same number of dimensions,but the array at index 0 has 1 dimension(s) and the array at index 1 has 2 dimension(s)