Leetcode #1384: Total Sales Amount by Year
In this guide, we solve Leetcode #1384 Total Sales Amount by Year in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
Table: Product +---------------+---------+ | Column Name | Type | +---------------+---------+ | product_id | int | | product_name | varchar | +---------------+---------+ product_id is the primary key (column with unique values) for this table. product_name is the name of the product.
Quick Facts
- Difficulty: Hard
- Premium: Yes
- Tags: Database
Intuition
The task is relational in nature, which maps cleanly to DataFrame operations in Python.
By treating tables as DataFrames, joins and group-bys become concise and readable.
Approach
Load the inputs as DataFrames and apply the appropriate merge, filter, or group-by.
Select or rename the columns to match the required output.
Steps:
- Load inputs as DataFrames.
- Apply merge/groupby/filter operations.
- Select the output columns.
Example
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| product_id | int |
| product_name | varchar |
+---------------+---------+
product_id is the primary key (column with unique values) for this table.
product_name is the name of the product.
Python Solution
import duckdb
import pandas as pd
def solution(product: pd.DataFrame, sales: pd.DataFrame) -> pd.DataFrame:
con = duckdb.connect()
con.register("Product", product)
con.register("Sales", sales)
return con.execute("""SELECT
s.product_id,
p.product_name,
y.YEAR report_year,
s.average_daily_sales * (
IF(
YEAR(s.period_end) > y.YEAR,
y.days_of_year,
DAYOFYEAR(s.period_end)
) - IF(
YEAR(s.period_start) < y.YEAR,
1,
DAYOFYEAR(s.period_start)
) + 1
) total_amount
FROM
Sales s
INNER JOIN (
SELECT
'2018' YEAR,
365 days_of_year
UNION
ALL
SELECT
'2019' YEAR,
365 days_of_year
UNION
ALL
SELECT
'2020' YEAR,
366 days_of_year
) y ON YEAR(s.period_start) <= y.YEAR
AND YEAR(s.period_end) >= y.YEAR
INNER JOIN Product p ON p.product_id = s.product_id
ORDER BY
s.product_id,
y.YEAR""").df()
Complexity
The time complexity is O(n log n) (typical). The space complexity is O(n).
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.