Practice / reshaping
The Daily Grind keeps two regional revenue tables, east and west, with the same three columns — but the two teams happened to list their columns in a different order. Stack them into one DataFrame, safely.
east
west (note the column order)
Your task: return one DataFrame with all rows from both regions, using a name-safe union so the columns line up by name rather than position.
Assign your answer DataFrame to result. Row order doesn't matter.
eastinput DataFrame| column | type |
|---|---|
| store | string |
| amount | double |
| tax | double |
| store | amount | tax |
|---|---|---|
| Boston | 10 | 1 |
| Miami | 8 | 0.8 |
westinput DataFrame| column | type |
|---|---|
| store | string |
| tax | double |
| amount | double |
| store | tax | amount |
|---|---|---|
| Denver | 0.6 | 6 |
| Reno | 0.4 | 4 |
storeamounttax· 4 rowseast.unionByName(west) stacks the two tables by column name, so it lines up
correctly even though west lists its columns in a different order.
This problem builds on Reshaping Data (~7 min). Pop it open in a new tab if you want a quick recap.