中国健康与养老追踪调查(CHARLS)数据可视化系统是一个基于Streamlit的交互式数据可视化平台，用于展示和管理CHARLS调查数据，包含多维度健康指标分析、问卷管理功能和系统功能模块。
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📊 多维度数据可视化
- 样本数量与跟踪率变化趋势
- 各年龄段健康状况分析
- 教育水平分布
- 家庭年收入分布
- 医疗保险覆盖情况
- 主要慢性病患病率趋势
- 城乡健康差异对比
- 养老方式分析
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📋 问卷管理系统
- 问卷数据的添加、编辑、删除功能
- 分页展示问卷列表
- 直观的数据卡片展示
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⚙️ 系统功能模块
- 多个核心功能模块概览与详情
- 系统信息摘要与状态监控
- 功能模块状态跟踪（已上线/开发中/计划中）
- 系统使用统计和性能监控
- 数据备份与系统维护功能
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📈 关键指标概览
- 基线调查样本量
- 受访者平均年龄
- 慢性病患病率
- 医保覆盖率
- Python 3.7+
- Streamlit
- Plotly
- Pandas
- Numpy
- PyEcharts
- Streamlit-Echarts
- 克隆仓库
git clone https://github.com/MilesSG/charls-data-visualization.git
cd charls-data-visualization- 安装依赖
pip install -r requirements.txt- 运行应用
streamlit run app.py- 2023-03-06: 添加系统功能模块，提供系统状态监控和功能概览
- 2023-02-15: 更新2020年CHARLS数据集
- 2022-11-20: 新增健康指标横向对比功能
- 2022-09-05: 更新数据清洗算法
The China Health and Retirement Longitudinal Study (CHARLS) Data Visualization System is a Streamlit-based interactive platform for visualizing and managing CHARLS survey data, featuring multi-dimensional health indicators analysis, questionnaire management, and system function modules.
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📊 Multi-dimensional Data Visualization
- Sample Size and Tracking Rate Trends
- Health Status Analysis by Age Groups
- Education Level Distribution
- Annual Household Income Distribution
- Medical Insurance Coverage
- Chronic Disease Prevalence Trends
- Urban-Rural Health Disparities
- Elderly Care Methods Analysis
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📋 Questionnaire Management System
- CRUD Operations for Survey Data
- Paginated Survey List
- Intuitive Data Card Display
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⚙️ System Function Modules
- Overview and details of multiple core function modules
- System information summary and status monitoring
- Function module status tracking (Active/In Development/Planned)
- System usage statistics and performance monitoring
- Data backup and system maintenance functions
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📈 Key Metrics Overview
- Baseline Survey Sample Size
- Average Age of Respondents
- Chronic Disease Prevalence
- Medical Insurance Coverage Rate
- Python 3.7+
- Streamlit
- Plotly
- Pandas
- Numpy
- PyEcharts
- Streamlit-Echarts
- Clone Repository
git clone https://github.com/MilesSG/charls-data-visualization.git
cd charls-data-visualization- Install Dependencies
pip install -r requirements.txt- Run Application
streamlit run app.py- 2023-03-06: Added System Function Modules for status monitoring and feature overview
- 2023-02-15: Updated 2020 CHARLS dataset
- 2022-11-20: Added health indicators comparative analysis
- 2022-09-05: Updated data cleaning algorithms
This project is licensed under the MIT License - see the LICENSE file for details.
MilesSG