Replicating predictive margins for a categorical variable

General Usage
1

I am new with Julia, my background is Stata. I am looking a way for get marginal mean for a categorical variable (Stata: margins i.group).

I am using categorical variable for variable group, then my goal its get probabilities for each level of variable group, but lamentably I get for all model.

example:

using Margins, DataFrames, GLM, CategoricalArrays, Random   

n = 10000
Random.seed!(06515)
y = rand([0,1], n)

data = DataFrame(y=y, x1 = randn(n), 
       x2 = randn(n), 
       bino =rand([1,2], n), 
       group = rand(["A", "B", "C"], n))

model = glm(@formula(y ~ x1+ x2+ bino+ group), data, Binomial(), LogitLink())


population_margins(model, data; type=:predictions)

PredictionsResult: 1 population predictions (N=10000)
────────────────────────────────────────────────────
  Prediction   Std. Err.  [95% Conf.   Interval]
────────────────────────────────────────────────────
      0.4952       0.005      0.4854       0.505
────────────────────────────────────────────────────

My goal its get this Stata result but using Julia:
------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
      group  |
          A  |   .4845861   .0086549    55.99   0.000     .4676229    .5015493
          B  |   .5056282   .0087316    57.91   0.000     .4885145    .5227418
          C  |   .4955554   .0085923    57.67   0.000     .4787148    .5123959
------------------------------------------------------------------------------

.