including Zeros counts categories with pandas value_counts() What i want is including zero counts categories while generating frequencies for categorical variables
example: 

col1   col2 
a       x
c       y
a       y
f       z

what i want is to generate a frequency table with counts and percentages including zero counts categories
results
  Counts   Cercentage
a  2          50.0%
b  0          0.0%
c  1          25.0%
d  0          0.0%
e  1          25.0%

what i have done is generating the frequency table with counts and percentages but i need to include also the zero counts categories like b and d as illustrated above
here is what i have tried
pd.concat([df.col1.value_counts(dropna=False),
           df.col1.value_counts(normalize=True,
                                dropna=False).mul(100).round(1).astype(str) + '%'],
          axis=1,
          keys=('Counts','Percentage'))

any help please
I got the answer use of Series.reindex with a list of all categories and if not match replace to 0
  categories = ['a', 'b', 'c', 'd', 'e']
  pd.concat([df.col1.value_counts().reindex(categories[::-1], fill_value=0),        df.col1.value_counts(normalize=True).reindex(categories[::-1], fill_value=0).mul(100).round(1).astype(str) + '%'],axis=1, keys=('Counts','Percentage'))

This worked for me