Average values on duplicate records

[chandramouliarun]

I have the following input table

| Custid | transactions | price | revenue |
| ------ | ------------ | ----- | ------- |
| 12456 | 2300 | 21 | 48300 |
| 12456 | 5200 | 29 | 150800 |
| 78901 | 3000 | 30 | 90000 |
| 676512 | 5200 | 24 | 124800 |
| 676512 | 7400 | 18 | 133200 |

where the custid has duplicates . There is a need to remove the duplicates and find the average of the transactions field and the price field for the custid that has more than 1 record and recalculate the revenue as ((new avg)transactions *(newavg) price)

Output table

| Custid | transactions | price | revenue |
| ------ | ------------ | ----- | ------- |
| 12456 | 3750 | 25 | 93750 |
| 78901 | 3000 | 30 | 90000 |
| 676512 | 6300 | 21 | 132300 |

[b]Python code tried


import pandas as pd

df1 .pd.read_csv("file1.csv")

df2=df1[custid].value_counts()

df1[transactions]=np.where(df2[count]>1,df1[transactions].mean())
df1[price]=np.where(df2[count]>1,df1[price].mean())
df1[revenue]=df1[transactions]*df1[price]

[/b]