Value Count with List in New Column that Comprised it Pandas

Question

I have a dataframe with individuals who called a variety of numbers. As so:

Person          Called
A                 123
B                 123
C                 234

I need to create a new dataframe that makes a list of people who called that number and the count. Like this:

Persons         Called         Count
A, B             123             2
C                234             1

I'm pretty sure I can just create a for loop that counts the number of times and appends them to a list, but I was wondering if there's a more efficient way to do this without a for loop. Apologies if the formatting is incorrect. I'm new to the forum.

Answer 1

Use name aggregations with GroupBy.agg:

df1 = (df.groupby('Called')
         .agg(Persons = ('Person',','.join), 
              Count=('Person','size'))
         .reset_index())
print (df1)
   Called Persons  Count
0     123     A,B      2
1     234       C      1

Because processing only one column is possible use alternative with tuples and column after groupby:

df1 = (df.groupby('Called')['Person']
         .agg([('Persons', ','.join), 
               ('Count','size')])
         .reset_index())
print (df1)
   Called Persons  Count
0     123     A,B      2
1     234       C      1