Coefficient 0 for categories in statsmodels GLM Is there a way to obtain the coefficient value 0 for the reference categories of categorical variables in statsmodels GLM.
    import statsmodels.api as sm 
    import statsmodels.formula.api as smf

    model = smf.glm( formula = "cost_tarif_median ~  age + 
            anc_veh + C(formule) + C(veh_usage) + C(categorie) + 
            C(groupe_sra) + C(zonier)" , family = 
            sm.families.Gamma( link = 
            sm.genmod.families.links.log() ) , data = df_train )

    model_fit = model.fit()

 A: It should certainly be possible to obtain an output coefficient table with the value 0 for these coefficients, as the corresponding problem in R is solved with the package gtsummary.  But I would not know if there is something in Python!  See What to do in a multinomial logistic regression when all levels of DV are of interest?
As for some of the comments:

Why do you want the coefficients that are by definition zero? What's the use case?

One use case is fewer questions from naive users --- there is quite a lot of related questions on this site! So then main use case is improved communication.

I am not sure it’s helpful to think of them as zero. They are just not separately identified from the intercept term, and likely non-zero.

NO, as the model is defined (and here I take the definition of categorical encoding as part of the model. Of course one could get an equivalent model with other encodings, but for matters of parameter interpretation, they must of course be relative to the used encoding) this coefficients are zero, period. Since they are zero by definition, there is now sampling variation, so their standard errors are also 0.
