Sum the max of each element index in list

I have two lists

task=[1,1,1,1,2,2,3,4,5,5]
hours=[1,7,6,2,3,6,5,2,4,6]

-.suppose the value in index are 1,2,3,4,5 without diplicated. I want to. sum (the max of first four index in hours (because number 1 repeated 4 times in task), the max of 5,6 index in hours(because number 2 repeated 2 times in task), the max of 7 index in hours, the max of 8 index in hours, the max of 9,10 index in hours).
.
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So I need to find the sum of max each value in task with it index in hours

>Solution :

You can create a dictionary/Dataframe from your lists and group by task and aggregate to sum:

import pandas as pd
task=[1,1,1,1,2,2,3,4,5,5]
hours=[1,7,6,2,3,6,5,2,4,6]
df = pd.DataFrame({'task': task, 'hours': hours})
print(df.groupby('task').agg(sum))

Output:

      hours
task       
1        16
2         9
3         5
4         2
5        10

Edit: Seems that I misunderstood the question.

You can use the same logic to find max values and then sum them:

max_val = df.groupby('task').agg(max)
print(int(max_val.sum()))

Output:

# max_val:
      hours
task       
1         7
2         6
3         5
4         2
5         6
# sum : 26