🗺️ Tourism Big Data Visualization Project

📌 Project Overview

This project presents a comprehensive data visualization and analysis of tourism data across China. Using Python (Pandas + Pyecharts), we visualize various dimensions such as sales volume, scenic spot distribution, pricing, and holiday travel trends. The final output includes interactive charts and maps that aid tourism planning, decision-making, and public understanding of the tourism market structure.

📊 Key Features

• 📌 Top 20 Most Popular Scenic Spots — Horizontal bar chart based on ticket sales
• 🏞️ City-Level 4A/5A Attractions Distribution — Bar chart for city tourism resource density
• 🗺️ National Map of High-Level Attractions — Heat map showing spatial distribution
• 🌸 Rose Charts — Ticket price ranges & number of 4A/5A attractions per province
• 💬 Word Cloud — Scenic spot introduction highlights
• 🔍 Scatter Plots — Relationships between price levels, sales, and attraction quantity
• 🚗 Holiday Travel Distribution — Geographical distribution of tourist flow

🧾 Dataset Description

• Format: Excel (.xlsm)

• Fields: Name, City, Ticket Price, Grade (4A/5A), Sales, Description, Address

• Preprocessing:

  • Removed duplicates by scenic spot name
  • Filled missing grades and descriptions with mode/defaults
  • Divided ticket price into defined intervals using pd.cut()

🛠️ Technologies Used

• Language: Python 3.x

• Libraries:

  • pandas: Data handling and preprocessing
  • pyecharts: Interactive charts and maps
  • matplotlib & seaborn: Auxiliary visual checks

• Output Format: Interactive HTML reports

🔎 Data Mining Techniques

• Preprocessing:

  • Duplicate removal
  • Null value filling
  • Type normalization

• Clustering:

  • Price range segmentation

• Aggregation:

  • Scenic spot count per city
  • Grade-level distribution per region

📁 Project Structure

Tourism-Visualization/
├── data/
│   └── 旅游景点.xlsm
├── figures/
│   ├── top20_sales_bar.html
│   ├── city_grade_bar.html
│   └── ...
├── src/
│   └── main_visualization.py
├── README.md
└── requirements.txt

🚀 How to Run

1. Clone the repository:

   git clone https://github.com/yourusername/Tourism-Visualization.git
   cd Tourism-Visualization

2. Install dependencies:

   pip install -r requirements.txt

3. Run the visualization script:

   python src/main_visualization.py

4. Open the generated .html files in the figures/ directory with any web browser.

📈 Sample Visualization

🙋 Author

• Name: Zhong Zhuohua
• Major: Computer Science and Technology 22(3)
• College: School of International Education
• ID: 3122010011
• Instructor: Prof. Lin Zhiyi

📅 Date

May 1, 2025