我使用scikit learn进行线性回归，我尝试了各种方法，通过重塑它们，导致代码中的整个错误。

R&D Spend  Administration  Marketing Spend       State     Profit
0   165349.20       136897.80        471784.10    New York  192261.83
1   162597.70       151377.59        443898.53  California  191792.06
2   153441.51       101145.55        407934.54     Florida  191050.39
3   144372.41       118671.85        383199.62    New York  182901.99
4   142107.34        91391.77        366168.42     Florida  166187.94
5   131876.90        99814.71        362861.36    New York  156991.12
6   134615.46       147198.87        127716.82  California  156122.51
7   130298.13       145530.06        323876.68     Florida  155752.60
8   120542.52       148718.95        311613.29    New York  152211.77
9   123334.88       108679.17        304981.62  California  149759.96
10  101913.08       110594.11        229160.95     Florida  146121.95
11  100671.96        91790.61        249744.55  California  144259.40
12   93863.75       127320.38        249839.44     Florida  141585.52
13   91992.39       135495.07        252664.93  California  134307.35
14  119943.24       156547.42        256512.92     Florida  132602.65

我试过以下代码

#Dataset
dataset=pd.read_csv(r'50_Startups.csv')
X=dataset.iloc[:,:-1]
y=dataset.iloc[:,-1]
#Encoding Categorical Data
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import OneHotEncoder
oHe=OneHotEncoder()
ct=ColumnTransformer(transformers=[('encoder',oHe,[3])],remainder='passthrough')
X = np.array(ct.fit_transform(X), dtype = np.str)
#Splitting into Training and Test sets 
from sklearn.model_selection import train_test_split
X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2,random_state=1)
#Training the Multiple Linear Regression
from sklearn.linear_model import LinearRegression
regressor=LinearRegression()
regressor.fit(X_train,y_train)

错误是：

ValueError: dtype='numeric' is not compatible with arrays of bytes/strings.
Convert your data to numeric values explicitly instead.