Apply function to pandas DataFrame that can return multiple rows

You could use groupby:

def f(group):
    row = group.irow(0)
    return DataFrame({'class': [row['class']] * row['count']})
df.groupby('class', group_keys=False).apply(f)

so you get

In [25]: df.groupby('class', group_keys=False).apply(f)
Out[25]: 
  class
0     A
0     C
1     C

You can fix the index of the result however you like