Drop duplicates keeping the row with the highest value in another column

Question

a = [[\'John\', \'Mary\', \'John\'], [10,22,50]])
df1 = pd.DataFrame(a, columns=[\'Name\', \'Count\'])

Given a data frame like this I want to compa

Answer 1

Either sort_values and drop_duplicates,

df1.sort_values('Count').drop_duplicates('Name', keep='last')

   Name  Count
1  Mary     22
2  John     50

Or, like miradulo said, groupby and max.

df1.groupby('Name')['Count'].max().reset_index()

   Name  Count
0  John     50
1  Mary     22