ufunc 'isfinite' not supported for the input types

Question

# Multiple Linear Regression

# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

# Importing the dataset
dataset = pd.read_csv('50_Startups.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 4].values

# Encoding categorical data
# Encoding the Independent Variable
# Encoding categorical data
# Encoding the Independent Variable
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
from sklearn.compose import ColumnTransformer
ct = ColumnTransformer([("State", OneHotEncoder(),[3])], remainder = 'passthrough')
X = ct.fit_transform(X)


# Avoiding the Dummy Variable Trap
X = X[:, 1:]


# Splitting the dataset into the Training set and Test set
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 = 0)


# Fitting Multiple Linear Regression to the Training set
from sklearn.linear_model import LinearRegression
regressor = LinearRegression()
regressor.fit(X_train, y_train)

# Predicting the Test set results
y_pred = regressor.predict(X_test)



# Building the optimal model using Backward Elimination
import statsmodels.api as sm
X_train = np.append(arr = np.ones((40, 1)).astype(int), values = X_train, axis = 1)
X_opt = X_train [:, [0,  3]]

regressor_OLS = sm.OLS(endog = y_train, exog = X_opt).fit()
regressor_OLS.summary()

报错：

ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

Answer 1

我也出现这个问题，借楼求回答~