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Author: ch-garcia

Diff for: introduction-pandas/2890-reshape-melt.py

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+"""
+2890. Reshape Data: Melt
+Solved
+Easy
+Companies
+Hint
+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."
+"""
+
+import pandas as pd
+
+def meltTable(report: pd.DataFrame) -> pd.DataFrame:
+    return report.melt(id_vars='product', var_name='quarter', value_name='sales')