Add confidence intervals to countplot showing percentages (seaborn, python)

Question

I drew a plot showing the % of a categorical response (Categorical_DependentVar_xVSy) as a function of two binary categorical variables (called CategoricalVar1_aVSb and CategoricalVar3_cVSd) using teh seaborn package.

Would you know how to add the confidence interval to the percentgaes on the plot?

It is easy for means to have confidence intervals, but I do not find a way to add those for percentage/count plots.

Here is my code showing the % plot:

First I compute the percentages:

import seaborn as sns

DfInterpretation = (df.groupby(['CategoricalVar1_aVSb','CategoricalVar2_cVSd'])['Categorical_DependentVar_xVSy']
                     .value_counts(normalize=True)
                     .rename('percentage')
                     .mul(100)
                     .reset_index()
                     .sort_values('Categorical_DependentVar_xVSy'))

Then I plot the value from the table

g = sns.catplot(y = 'percentage', hue="CategoricalVar1_aVSb", x = "CategoricalVar2_cVSd",
                col = "Categorical_DependentVar_xVSy",
                data=DfInterpretation, kind="bar")

But I do not manage to get confidence intervals.

Any help would be greatly appreciated!

[[for information, it is possible with R - e.g.: https://stackoverflow.com/questions/58343088/how-to-add-95-confidence-intervals-to-graph-of-proportions-of-factor-levels-in but I could not find in python]]