📊 Comprehensive Data Visualization Tool

A powerful Python-based data visualization tool that supports 60+ different chart types including area graphs, bar charts, heatmaps, network diagrams, geographic visualizations, and much more.

🚀 Features

Chart Types Supported

Basic Charts:

• Area Graph
• Bar Chart
• Line Graph
• Scatterplot
• Pie Chart
• Donut Chart
• Histogram
• Box & Whisker Plot

Advanced Charts:

• Heatmap
• Violin Plot
• Radar Chart
• Sunburst Diagram
• Treemap
• Sankey Diagram
• Parallel Coordinates Plot

Geographic Visualizations:

• Choropleth Map
• Bubble Map
• Dot Map
• Flow Map

Network & Relationship Charts:

• Network Diagram
• Connection Map
• Chord Diagram
• Non-ribbon Chord Diagram

Specialized Charts:

• Candlestick Chart
• OHLC Chart
• Gantt Chart
• Timeline
• Population Pyramid
• Word Cloud
• Venn Diagram

Radial & Polar Charts:

• Radial Bar Chart
• Radial Column Chart
• Nightingale Rose Chart
• Spiral Plot

Statistical Charts:

• Error Bars
• Density Plot
• Stem & Leaf Plot
• Kagi Chart
• Point & Figure Chart

Hierarchical Charts:

• Tree Diagram
• Circle Packing
• Brainstorm Diagram
• Flow Chart
• Illustration Diagram

Time-based Charts:

• Calendar Heatmap
• Timetable
• Stream Graph
• Span Chart

Special Purpose Charts:

• Bullet Graph
• Marimekko Chart
• Pictogram Chart
• Tally Chart
• Proportional Area Chart

🛠️ Installation

1. Clone or download the project files

2. Install dependencies:

   pip install -r requirements.txt

3. Run the application:

   streamlit run app.py

4. Open your browser and navigate to http://localhost:8501

📁 Project Structure

Data Visualization Tools/
├── app.py                 # Main Streamlit application
├── advanced_charts.py     # Additional chart implementations
├── requirements.txt       # Python dependencies
└── README.md             # This file

🎯 Usage

1. Data Upload

• Upload your CSV file using the file uploader in the sidebar
• The tool will automatically generate sample data if no file is uploaded
• Supported format: CSV files

2. Chart Selection

• Choose from 60+ different chart types from the dropdown menu
• Each chart type is optimized for specific data patterns

3. Data Preview

• View your data structure and content in the expandable "Data Preview" section
• Check data shape and column information

4. Interactive Visualizations

• All charts are interactive and responsive
• Hover over elements for detailed information
• Zoom, pan, and explore your data

📊 Sample Data Structure

The tool works with CSV files containing columns like:

• date: Time series data
• category: Categorical data
• subcategory: Sub-categories
• value: Numerical values
• value2: Secondary numerical values
• size: Size values for bubble charts
• color: Color categories
• region: Geographic regions
• open, high, low, close: OHLC data
• volume: Volume data
• text: Text data for word clouds

🔧 Customization

Adding New Chart Types

1. Create a new function in advanced_charts.py
2. Add the function to the chart_functions dictionary in app.py
3. Update the chart types list in the sidebar

Data Format Requirements

• Time Series Charts: Require date column
• Geographic Charts: Require latitude/longitude or country names
• Network Charts: Work with relationship data
• Statistical Charts: Require numerical data

🎨 Chart Categories

Basic Analytics

• Bar, Line, Area, Scatter plots
• Histograms, Box plots
• Pie and Donut charts

Advanced Analytics

• Heatmaps, Violin plots
• Radar charts, Sunburst diagrams
• Parallel coordinates, Sankey diagrams

Geographic Visualization

• Choropleth maps
• Bubble maps, Dot maps
• Flow maps

Network Analysis

• Network diagrams
• Connection maps
• Chord diagrams

Time Series

• Candlestick charts
• Gantt charts
• Calendar heatmaps

Statistical Analysis

• Error bars
• Density plots
• Stem & leaf plots

🚀 Advanced Features

• Interactive Charts: All charts support zoom, pan, and hover interactions
• Responsive Design: Works on desktop and mobile devices
• Data Export: Download charts as images
• Real-time Updates: Charts update automatically when data changes
• Multiple Chart Types: Switch between different visualizations instantly

🔍 Troubleshooting

Common Issues:

1. Chart not rendering: Check if your data has the required columns
2. Missing dependencies: Run pip install -r requirements.txt
3. Port already in use: Change the port with streamlit run app.py --server.port 8502

Data Requirements:

• Ensure your CSV file has the necessary columns
• Check data types (dates should be in datetime format)
• Remove any missing values if needed

📈 Examples

Sample CSV Format:

date,category,subcategory,value,value2,size,color,region
2023-01-01,A,X,100,50,25,Red,North
2023-01-02,B,Y,120,60,30,Blue,South
2023-01-03,C,Z,90,45,20,Green,East

🤝 Contributing

Feel free to contribute by:

• Adding new chart types
• Improving existing visualizations
• Enhancing the user interface
• Adding new data processing features

📄 License

This project is open source and available under the MIT License.

🆘 Support

For issues or questions:

1. Check the troubleshooting section
2. Review the data format requirements
3. Ensure all dependencies are installed

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Built with ❤️ using Streamlit, Plotly, and Python