Average net revenue per order, by channel
A per-order average, not a total: the channel with the most revenue and the channel with the most valuable order are usually not the same channel.
How it decided
Sales orders: 11,316 rows, 10 columns. channel and net_amount; order counts come from the grouping itself.
11,316 rows in, 6 out across 2 columns. A per-order average, not a total: the channel with the most revenue and the channel with the most valuable order are usually not the same channel.
bar. A handful of named categories being compared on one measure is a bar chart, sorted so the ranking is the shape.
Palette, spacing, axis titles and legend placement applied. 0 issues found.
The transformation
This is the code, not a description of it — the chart above was drawn from what it returns, and the notebook download runs the same lines against the same file.
result = df.groupby("channel", as_index=False)["net_amount"].mean().sort_values("net_amount", ascending=False)What it charted
6 rows out of 11,316, 2 columns. First 6 shown.
| channel | net_amount |
|---|---|
| Referral | 1198.0452 |
| Social | 1145.2531 |
| Paid search | 1145.0665 |
| Organic | 1131.3771 |
| 1120.5744 | |
| Partner | 1096.7414 |