Python Forum

Dear all,
I’m beginning with Python that I need to use to run a linear model for the dataset below :

Output:
Location 	Y	X1	X2
1	             32	1	1
1          	44  	1	2
1          	58  	1	3
1	            76 	2	1
1	             73	2	2
1	             37	2	3
1           	52 	3	1
1	             78	3	2
1            	 60   3	3
2           	93	    1	1
2           	78     1	2
2	            25  	 1	3
2	             97	2	1
2	             85	2	2
2           	60 	2	3
2	            70	    3	1
2	            62	    3 	2
2   	        95	    3 	3

My target is to run a linear model as follows :
Y ~ X1 + X2
X1 and X2 are categorical variables
And for that the following code gave me exactly what I need :

import numpy as np
import pandas as pd
import statsmodels.api as sm
import matplotlib.pyplot as plt
from statsmodels.formula.api import ols
import scipy.stats as stats

df = pd.DataFrame(dataset)
reg = ols('Y ~ C(X1) + C(X2)', data=df).fit() 
df['fitted_values'] = reg.fittedvalues
result = reg.outlier_test()
df['student_resid'] = result.student_resid

What I’m not able to do is to run this code by ‘Location’, and get my columns 'fitted_values' and 'student_resid' accordingly.
Any help is highly appreciated.
Thanks a lot in advance.