Show zero values for a column after performing conditional groupby count in pandas

Question

I've a dataframe as mentioned below:

I'm using the following code to get the count of resolved for all the items in column A :

resolved = df[df['B']== 'resolved'].groupby('A', as_index=False)['B'].size()

and similarly for unresolved :

unresolved = df[df['B']== 'unresolved'].groupby('A', as_index=False)['B'].size()

For unresolved , SRVCAM-AM BI-Data doesn't have unresolved value in column B . So, the resulting dataframe will not have it

The result obtained for unresolved is as below:

work_queue count SRVCAM-AM BI-Reports Admin 1

but I want the result as follows:

work_queue count SRVCAM-AM BI-Reports Admin 1 SRVCAM-AM BI-Data 0

Answer 1

You can compare column B and aggregate sum - True s are processes like 1 s:

resolved = (df['B'] == 'resolved').groupby(df['A'], as_index=False).sum().astype(int)

If want all columns by B use crosstab :

resolved = pd.crosstab(df['A'], df['B'])