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CSViewer

CSViewer is a web-based application designed for visualizing CSV data through interactive charts. The application supports both pre-loaded climate datasets and user-uploaded CSV files, making it a versatile tool for data analysis and visualization.

Overview​

The application provides a straightforward interface for exploring tabular data through various chart types. It automatically detects the structure of your CSV files and selects appropriate visualization methods, though users can manually adjust the chart type as needed.

Key Features​

Pre-loaded Climate Datasets​

The application comes with several example climate datasets that demonstrate its visualization capabilities:

  • CO2 concentration levels over time
  • Glacier mass balance data
  • Historical temperature records
  • Ice sheet measurements

These datasets serve as both examples and tools for exploring climate change trends.

Custom File Upload​

Users can upload their own CSV files for visualization. The application accepts files up to 10MB in size, which is sufficient for most standard datasets. Files larger than this limit may need to be filtered or processed before upload.

Automatic Chart Type Detection​

When a CSV file is loaded, CSViewer analyzes its structure to determine the most appropriate visualization:

  • Line charts for time-series data
  • Bar charts for categorical comparisons
  • Area charts for cumulative data
  • Scatter plots for correlation analysis

The system examines the first column (typically used as the x-axis) and subsequent columns (y-axis data) to make this determination.

Multiple Data Columns​

CSViewer can handle CSV files with multiple data columns, plotting each as a separate series on the same chart. This allows for:

  • Comparing multiple metrics side by side
  • Viewing related datasets in context
  • Identifying correlations between different data series

CSV File Format​

Structure Requirements​

For optimal results, CSV files should follow this structure:

Year,Temperature,Precipitation
2020,14.9,850
2021,15.1,920
2022,15.3,780

Key points:

  • First row contains column headers
  • First column typically represents the independent variable (x-axis)
  • Subsequent columns contain dependent variables (y-axis)
  • Data should be properly formatted (numbers without extra characters)

Data Types​

The parser handles several data types:

  • Numeric values (integers and decimals)
  • Date strings (various formats)
  • Text labels (for categorical data)
  • Empty cells (treated as null values)

Character Encoding​

The application handles UTF-8 encoded files by default. If you encounter issues with special characters, ensure your CSV is saved with UTF-8 encoding.

Technical Architecture​

Frontend Stack​

The application is built with modern web technologies:

  • React provides the component architecture and state management
  • Vite handles the build process and development server
  • Recharts renders the interactive charts
  • Tailwind CSS manages the styling system
  • TypeScript ensures type safety throughout the codebase

Component Structure​

The application follows a modular component structure:

  • Upload Component handles file selection and processing
  • Data Viewer manages the display of parsed CSV data
  • Chart Components render different visualization types
  • Dataset Selector enables switching between pre-loaded examples

State Management​

React's built-in state management handles:

  • Currently loaded dataset
  • Selected chart type
  • User preferences
  • View configurations

Security Considerations​

The application has undergone comprehensive security hardening:

Input Validation​

All user inputs are validated using Zod schemas, ensuring:

  • File sizes remain within acceptable limits
  • CSV structure meets requirements
  • No malicious content is processed

Dependency Security​

All dependencies are kept up to date, with:

  • Regular vulnerability scans
  • Automated update checks
  • No known CVE issues in dependencies

Client-Side Processing​

All data processing occurs entirely in the browser. No data is sent to external servers, ensuring:

  • Privacy of uploaded data
  • No server-side vulnerabilities
  • Reduced attack surface

Strict TypeScript​

The codebase uses strict TypeScript configuration to catch potential issues at compile time rather than runtime.

Development​

Local Development Setup​

To run CSViewer locally:

  1. Install dependencies:
npm install
  1. Start the development server:
npm run dev
  1. Open your browser to http://localhost:8080

The development server includes hot module replacement, so changes to the code are reflected immediately without a full page reload.

Building for Production​

To create a production build:

npm run build

This generates optimized assets in the dist/ directory. The build process includes:

  • Code minification
  • Tree shaking to remove unused code
  • Asset optimization
  • Source map generation

Project Structure​

CSViewer/
├── public/          # Static assets
│   └── data/        # Pre-loaded datasets
├── src/
│   ├── components/  # React components
│   ├── hooks/       # Custom React hooks
│   ├── lib/         # Utility functions
│   └── pages/       # Page components
├── package.json     # Dependencies and scripts
└── vite.config.ts   # Build configuration

Browser Compatibility​

CSViewer works with all modern browsers that support:

  • ES2020 JavaScript features
  • CSS Grid and Flexbox
  • HTML5 File API
  • Canvas rendering (for charts)

Tested browsers:

  • Chrome 90+
  • Firefox 88+
  • Safari 14+
  • Edge 90+

Known Limitations​

File Size​

The 10MB file size limit is a practical constraint based on browser memory handling. Files larger than this may cause:

  • Slow rendering performance
  • Browser memory warnings
  • Potential crashes on low-end devices

For larger datasets, consider:

  • Filtering data before export
  • Sampling every nth row
  • Splitting into multiple files

Multi-Column Clarity​

While the application handles multiple data columns, the interface could be improved to make it clearer which series corresponds to which column. This is an area for future enhancement.

Console Warnings​

During development, some console warnings may appear that don't affect functionality. These are typically related to:

  • React development mode checks
  • Third-party library verbosity
  • Browser extension interference

Future Enhancements​

Planned improvements include:

  • Enhanced multi-column visualization controls
  • Export functionality for modified charts
  • Additional chart types (pie charts, heat maps)
  • Data filtering and transformation tools
  • Responsive mobile interface improvements

License​

CSViewer is released under the MIT License, allowing free use, modification, and distribution with proper attribution.

Support and Contribution​

For issues, feature requests, or contributions, please visit the project repository. The codebase welcomes contributions that align with the project's goals of simplicity and usability.