This project analyzes bike-sharing usage patterns in Seoul based on time, weather conditions, and holidays. The goal is to support operational decisions related to bike distribution and promotional strategies by identifying demand differences between weekdays and weekends, as well as seasonal and weather effects.

1. Business Context

Seoul operates one of the most advanced urban transportation systems in the world. Bike sharing has become an important complementary mode of transportation, especially for daily commuting and environmentally friendly mobility.

However, demand for bike rentals varies significantly depending on:

• time of day,
• working days versus holidays,
• weather conditions, and
• seasonal patterns.

2. Business Problem

| Key Question:

How can bike-sharing operators optimize bike availability and promotional strategies based on differences in usage patterns between weekdays and holidays, as well as the impact of weather and seasonal conditions?

3. Business Objectives

• Identify demand patterns across time, weather, and holidays
• Understand behavioral differences between weekday and weekend users
• Provide actionable, data-driven recommendations to improve operational efficiency and promotional effectiveness.

4. Dataset Overview