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Leetcode #1308: Running Total for Different Genders

In this guide, we solve Leetcode #1308 Running Total for Different Genders 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.

Leetcode

Problem Statement

Table: Scores +---------------+---------+ | Column Name | Type | +---------------+---------+ | player_name | varchar | | gender | varchar | | day | date | | score_points | int | +---------------+---------+ (gender, day) is the primary key (combination of columns with unique values) for this table. A competition is held between the female team and the male team.

Quick Facts

  • Difficulty: Medium
  • 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 | +---------------+---------+ | player_name | varchar | | gender | varchar | | day | date | | score_points | int | +---------------+---------+ (gender, day) is the primary key (combination of columns with unique values) for this table. A competition is held between the female team and the male team. Each row of this table indicates that a player_name and with gender has scored score_point in someday. Gender is 'F' if the player is in the female team and 'M' if the player is in the male team.

Python Solution

import duckdb import pandas as pd def solution(scores: pd.DataFrame) -> pd.DataFrame: con = duckdb.connect() con.register("Scores", scores) return con.execute("""SELECT gender, day, SUM(score_points) OVER ( PARTITION BY gender ORDER BY gender, day ) AS total FROM Scores;""").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.


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