I am running a program on Python and I try to generate statistics outputs from an array.
The code line:
regressor_OLS = sm.OLS(y,X_opt).fit()
is given an elaborate error.

This is the code

Multiple Linear Regression

Importing Libraries

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

importing the dataset

dataset = pd.read_csv('50_Startups.csv')

Getting the independent variables

X = dataset.iloc[:,:-1].values
y = dataset.iloc[:,4].values
print (dataset)

Encoding categorical data

Encoding the Independent Variable

from sklearn.preprocessing import OneHotEncoder
from sklearn.compose import ColumnTransformer
ct = ColumnTransformer([("Country", 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 Model 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

Add columns of 1

X= np.append(arr = np.ones((50,1)).astype(int), values = X, axis =1)
X_opt = X[:,[0,1,2,3,4,5]]

Multiple Linear Regression Model --- OLS

regressor_OLS = sm.OLS(y,X_opt).fit()
regressor_OLS.summary()

Reproducing code example:

```python
import numpy as np

Error message:

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''

File "C:UsersmoranaDocumentsAIUDEMYMachine Learning A-ZPart 2 - RegressionSection 5 - Multiple Linear Regressionmultiple linear regression.py", line 46, in
regressor_OLS = sm.OLS(y,X_opt).fit()

File "C:UsersmoranaAppDataLocalContinuumanaconda3libsite-packagesstatsmodelsregressionlinear_model.py", line 838, in __init__
hasconst=hasconst, **kwargs)

File "C:UsersmoranaAppDataLocalContinuumanaconda3libsite-packagesstatsmodelsregressionlinear_model.py", line 684, in __init__
weights=weights, hasconst=hasconst, **kwargs)

File "C:UsersmoranaAppDataLocalContinuumanaconda3libsite-packagesstatsmodelsregressionlinear_model.py", line 196, in __init__
super(RegressionModel, self).__init__(endog, exog, **kwargs)

File "C:UsersmoranaAppDataLocalContinuumanaconda3libsite-packagesstatsmodelsbasemodel.py", line 216, in __init__
super(LikelihoodModel, self).__init__(endog, exog, **kwargs)

File "C:UsersmoranaAppDataLocalContinuumanaconda3libsite-packagesstatsmodelsbasemodel.py", line 68, in __init__
**kwargs)

File "C:UsersmoranaAppDataLocalContinuumanaconda3libsite-packagesstatsmodelsbasemodel.py", line 91, in _handle_data
data = handle_data(endog, exog, missing, hasconst, **kwargs)

File "C:UsersmoranaAppDataLocalContinuumanaconda3libsite-packagesstatsmodelsbasedata.py", line 635, in handle_data
**kwargs)

File "C:UsersmoranaAppDataLocalContinuumanaconda3libsite-packagesstatsmodelsbasedata.py", line 80, in __init__
self._handle_constant(hasconst)

File "C:UsersmoranaAppDataLocalContinuumanaconda3libsite-packagesstatsmodelsbasedata.py", line 125, in _handle_constant
if not np.isfinite(ptp_).all():

TypeError: 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''

Numpy/Python version information:

Spyder 4.0.0
1.17.4 3.7.3 (default, Apr 24 2019, 15:29:51) [MSC v.1915 64 bit (AMD64)]