Social Data Hackerton - Seoul Taxi Demand Analysis

This project analyzes and visualizes taxi demand in Seoul using real-world data. It provides interactive maps and data analysis tools to help understand taxi usage patterns across different regions and times.

Project Structure

• Final_Map.py
  Generates the final interactive map visualizing taxi demand data.

• map.py
  Contains core logic for processing taxi data and generating map visualizations.

• map.html
  Output HTML file displaying the interactive map.

• population_example.ipynb
  Jupyter notebook demonstrating population data analysis and its relation to taxi demand.

• taxi data.png
  Image visualizing taxi data statistics.

• README.md
  Project documentation.

• 발표 자료.pdf
  Presentation slides (PDF) summarizing the project.

• 발표자료_최종.pptx
  Final presentation slides (PowerPoint).

Features

• Data preprocessing and analysis of Seoul taxi demand.
• Interactive map visualization of taxi demand hotspots.
• Integration of population data for deeper insights.
• Presentation materials for sharing findings.

Getting Started

1. Install Dependencies
   Make sure you have Python 3.x and Jupyter Notebook installed.
   Install required packages:

   pip install pandas folium jupyter matplotlib

2. Run Data Analysis
   Open and run population_example.ipynb for population data analysis.

3. Generate Map
   Run Final_Map.py or map.py to generate the interactive map.
   The output will be saved as map.html.

4. View Results
   Open map.html in your browser to explore the interactive map.

Usage

• Modify map.py or Final_Map.py to analyze different datasets or customize the map.
• Use the Jupyter notebook for exploratory data analysis.