Retail revenue trends
Question
Given the table below, called 'orders', write code to show the average revenue by month by channel. The format of the result should look like the following:
- Month | Channel | Avg. Revenue
| order_id | channel | date | month | revenue | |
|---|---|---|---|---|---|
| 0 | 1 | Online | 2018-09-01 | 09 | 100 |
| 1 | 2 | Online | 2018-09-03 | 09 | 125 |
| 2 | 3 | In_store | 2018-10-11 | 10 | 200 |
| 3 | 4 | In_store | 2018-08-21 | 08 | 80 |
| 4 | 5 | Online | 2018-08-13 | 08 | 200 |
| 5 | 6 | Online | 2018-10-29 | 10 | 100 |
Here is code to create the above dataframe, to help get you started:
import pandas as pd
raw_data = {'order_id': [1, 2, 3, 4, 5, 6],'channel': ['Online', 'Online', 'In_Store', 'In_Store', 'Online', 'Online'], 'date': ['2018-09-01', '2018-09-03', '2018-10-11', '2018-08-21', '2018-08-13', '2018-10-29'], 'month': ['09', '09', '10', '08', '08', '10'],'revenue' :[100, 125, 200, 80, 200, 100]}
df = pd.DataFrame(raw_data, columns = ['order_id', 'channel', 'date', 'month', 'revenue'])