Sales Analysis I

Problem

Table: Product

+--------------+---------+
| Column Name  | Type    |
+--------------+---------+
| product_id   | int     |
| product_name | varchar |
| unit_price   | int     |
+--------------+---------+
product_id is the primary key (column with unique values) of this table.
Each row of this table indicates the name and the price of each product.

Table: Sales

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| seller_id   | int     |
| product_id  | int     |
| buyer_id    | int     |
| sale_date   | date    |
| quantity    | int     |
| price       | int     |
+-------------+---------+
This table can have repeated rows.
product_id is a foreign key (reference column) to the Product table.
Each row of this table contains some information about one sale.

Write a solution that reports the best seller by total sales price, If there is a tie, report them all.

Return the result table in any order.

The result format is in the following example.

Examples

Example 1:

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Input: 
Product table:
+------------+--------------+------------+
| product_id | product_name | unit_price |
+------------+--------------+------------+
| 1          | S8           | 1000       |
| 2          | G4           | 800        |
| 3          | iPhone       | 1400       |
+------------+--------------+------------+
Sales table:
+-----------+------------+----------+------------+----------+-------+
| seller_id | product_id | buyer_id | sale_date  | quantity | price |
+-----------+------------+----------+------------+----------+-------+
| 1         | 1          | 1        | 2019-01-21 | 2        | 2000  |
| 1         | 2          | 2        | 2019-02-17 | 1        | 800   |
| 2         | 2          | 3        | 2019-06-02 | 1        | 800   |
| 3         | 3          | 4        | 2019-05-13 | 2        | 2800  |
+-----------+------------+----------+------------+----------+-------+
Output: 
+-------------+
| seller_id   |
+-------------+
| 1           |
| 3           |
+-------------+
Explanation: Both sellers with id 1 and 3 sold products with the most total price of 2800.

Solution

Method 1 - Group and Max

Intuition

We want the seller(s) with the highest total sales price. We can group by seller_id, sum the price, and select those with the maximum sum.

Approach

Group Sales by seller_id, sum the price for each seller.
Find the maximum total price.
Select all seller_ids with that total.

Code

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SELECT seller_id
FROM (
  SELECT seller_id, SUM(price) AS total
  FROM Sales
  GROUP BY seller_id
) t
WHERE total = (SELECT MAX(total) FROM (SELECT SUM(price) AS total FROM Sales GROUP BY seller_id) x);

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SELECT seller_id
FROM (
  SELECT seller_id, SUM(price) AS total
  FROM Sales
  GROUP BY seller_id
) t
WHERE total = (SELECT MAX(total) FROM (SELECT SUM(price) AS total FROM Sales GROUP BY seller_id) x);

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# Sales is a pandas DataFrame
import pandas as pd
def sales_analysis_i(Sales):
    totals = Sales.groupby('seller_id')['price'].sum()
    max_total = totals.max()
    result = totals[totals == max_total].index.to_frame(index=False)
    return result
# result = sales_analysis_i(Sales)

Complexity

⏰ Time complexity: O(N) (N = number of sales)
🧺 Space complexity: O(S) (S = number of sellers)

Problem#

Examples#

Solution#

Method 1 - Group and Max#

Intuition#

Approach#

Code#

Complexity#