Extract regressions coefficient from statsmodels

Question

I'm estimating an OLS model, as seen below. I need the coefficients on the categorical variable along with their values.

Here's my code:

import pandas as pd
import numpy as np
import statsmodels.formula.api as smf

np.random.seed(12345)
df = pd.DataFrame(np.random.randn(25, 1), columns=list('A'))

df['groupid'] = [1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,5,5,5,5,5,6,6,6,6,6]
df['groupid'] = df['groupid'].astype('int')

###Fixed effects models

FE_ols = smf.ols(formula = 'A ~ C(groupid) - 1', data=df).fit()

FE_coeffs = FE_ols.params #Save coeffs
FE_coeffs.GroupID = FE_coeffs.index #Extract value of GroupID
FE_coeffs.GroupID = FE_coeffs.GroupID.str.extract('(\d+)') #Parse number from string

I'm able to extract the coefficients on the dummy variables. I put them in a new data frame.

C(groupid)[1]   0.2329694463342642
C(groupid)[2]   0.7567034333090062
C(groupid)[3]   0.31355791920072623
C(groupid)[5]   -0.05131898650395289
C(groupid)[6]   0.31757453138500547

However, I want the data frame to be like:

1   0.2329694463342642
2   0.7567034333090062
3   0.31355791920072623
5   -0.05131898650395289
6   0.31757453138500547    

The code seems to work, including the parsing. When I do this on Jupyter, it even shows the correct output. But the change isn't saved onto the data frame. There doesn't seem to be a inplace=True kind of command.

Will appreciate any help.

Answer 1

FE_coeffs is a Series, so adding an attribute GroupID as if it's adding a column is the wrong direction. Instead, just overwrite the index with the extracted integer values:

In [80]: FE_coeffs = FE_ols.params.copy()

In [81]: FE_coeffs.index = FE_coeffs.index.str.extract("(\d+)", expand=False).astype(int)

In [82]: FE_coeffs
Out[82]: 
1    0.232969
2    0.756703
3    0.313558
5   -0.051319
6    0.317575
dtype: float64