LeetCode-in-Java
2890. Reshape Data: Melt
Easy
DataFrame report
+-------------+--------+
| Column Name | Type |
+-------------+--------+
| product | object |
| quarter_1 | int |
| quarter_2 | int |
| quarter_3 | int |
| quarter_4 | int |
+-------------+--------+
Write a solution to reshape the data so that each row represents sales data for a product in a specific quarter.
The result format is in the following example.
Example 1:
Input:
+-------------+-----------+-----------+-----------+-----------+
| product | quarter_1 | quarter_2 | quarter_3 | quarter_4 |
+-------------+-----------+-----------+-----------+-----------+
| Umbrella | 417 | 224 | 379 | 611 |
| SleepingBag | 800 | 936 | 93 | 875 |
+-------------+-----------+-----------+-----------+-----------+
Output:
+-------------+-----------+-------+
| product | quarter | sales |
+-------------+-----------+-------+
| Umbrella | quarter_1 | 417 |
| SleepingBag | quarter_1 | 800 |
| Umbrella | quarter_2 | 224 |
| SleepingBag | quarter_2 | 936 |
| Umbrella | quarter_3 | 379 |
| SleepingBag | quarter_3 | 93 |
| Umbrella | quarter_4 | 611 |
| SleepingBag | quarter_4 | 875 |
+-------------+-----------+-------+
Explanation: The DataFrame is reshaped from wide to long format. Each row represents the sales of a product in a quarter.
Solution
import pandas as pd
def meltTable(report: pd.DataFrame) -> pd.DataFrame:
return report.melt(id_vars='product', var_name='quarter', value_name='sales')