dsTypeError: 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''

[moranavni]

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:

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''

<!-- Full error message, if any (starting from line Traceback: ...) -->


  File "C:\Users\morana\Documents\AI\UDEMY\Machine Learning A-Z\Part 2 - Regression\Section 5 - Multiple Linear Regression\multiple linear regression.py", line 46, in <module>
    regressor_OLS = sm.OLS(y,X_opt).fit()

  File "C:\Users\morana\AppData\Local\Continuum\anaconda3\lib\site-packages\statsmodels\regression\linear_model.py", line 838, in __init__
    hasconst=hasconst, **kwargs)

  File "C:\Users\morana\AppData\Local\Continuum\anaconda3\lib\site-packages\statsmodels\regression\linear_model.py", line 684, in __init__
    weights=weights, hasconst=hasconst, **kwargs)

  File "C:\Users\morana\AppData\Local\Continuum\anaconda3\lib\site-packages\statsmodels\regression\linear_model.py", line 196, in __init__
    super(RegressionModel, self).__init__(endog, exog, **kwargs)

  File "C:\Users\morana\AppData\Local\Continuum\anaconda3\lib\site-packages\statsmodels\base\model.py", line 216, in __init__
    super(LikelihoodModel, self).__init__(endog, exog, **kwargs)

  File "C:\Users\morana\AppData\Local\Continuum\anaconda3\lib\site-packages\statsmodels\base\model.py", line 68, in __init__
    **kwargs)

  File "C:\Users\morana\AppData\Local\Continuum\anaconda3\lib\site-packages\statsmodels\base\model.py", line 91, in _handle_data
    data = handle_data(endog, exog, missing, hasconst, **kwargs)

  File "C:\Users\morana\AppData\Local\Continuum\anaconda3\lib\site-packages\statsmodels\base\data.py", line 635, in handle_data
    **kwargs)

  File "C:\Users\morana\AppData\Local\Continuum\anaconda3\lib\site-packages\statsmodels\base\data.py", line 80, in __init__
    self._handle_constant(hasconst)

  File "C:\Users\morana\AppData\Local\Continuum\anaconda3\lib\site-packages\statsmodels\base\data.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)]

[filip-stolinski]

Hey!
Your X_opt array has a dtype of object and this may be causing an error. Try changing it to float. For example you can use this:
X= np.append(arr = np.ones((50,1)).astype(int), values = X, axis =1)
X_opt = X[:,[0,1,2,3,4,5]]
X_opt = np.array(X_opt, dtype=float)

Have fun :D

[riderman10000]

Thanks @filip-stolinski for your solution

[aliraza-aa]

@filip-stolinski Thank you very much for your solution. It definitely Works

[mattip]

Closing. Please reopen or open a new issue if needed.

[Dev-Gaju]

Thanks @filip-stolinski

[shashankchakrawarty98]

thanks

[sidalikharef]

@filip-stolinski thank you that works for me <3

[SamuelOsondu]

Thanks so much!!