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Data Visualization

Visualization Principles and Design​

  • What you Need to Know

    • Visual Perception and Cognitive Principles

    • Chart Types and Selection Criteria

      • Bar charts, line plots, and scatter plots
      • Histograms, box plots, and distribution visualization
      • Heatmaps, treemaps, and specialized chart types
      • Resources:

    • Dashboard Design and Layout

Python Visualization Libraries​

  • What you Need to Know

    • Matplotlib for Static Plots

    • Seaborn for Statistical Visualization

      • Statistical plot types and distribution visualization
      • Categorical data visualization techniques
      • Multi-variable relationships and correlation plots
      • Resources:

    • Plotly for Interactive Visualization

Advanced Visualization Techniques​

  • What you Need to Know

    • Statistical Visualization Methods

      • Regression plots and confidence intervals
      • Distribution comparison and probability plots
      • Residual plots and diagnostic visualization
      • Resources:

    • Multivariate Data Visualization

    • Geographic and Spatial Visualization

      • Choropleth maps and geographic data visualization
      • Spatial analysis and coordinate systems
      • Interactive maps and location-based analytics
      • Resources:

Business Intelligence and Dashboard Development​

  • What you Need to Know

    • Executive Dashboard Design

      • KPI visualization and executive reporting
      • Real-time data integration and updates
      • Mobile-responsive dashboard layouts
      • Resources:

    • Interactive Dashboard Frameworks

      • Streamlit for rapid prototyping
      • Dash for production dashboards
      • Jupyter widgets for notebook interactivity
      • Resources:

    • Data Storytelling and Presentation

      • Narrative structure for data presentations
      • Annotation and highlighting techniques
      • Audience-specific visualization strategies
      • Resources:

Web-Based Visualization and Deployment​

  • What you Need to Know

    • D3.js and JavaScript Visualization

      • D3.js fundamentals and data binding
      • Custom visualization creation
      • Interactive web-based charts
      • Resources:

    • Web Deployment and Sharing

      • GitHub Pages for static visualizations
      • Heroku and cloud deployment for interactive dashboards
      • Embedding visualizations in web applications
      • Resources:

Specialized Visualization Domains​

  • What you Need to Know

    • Financial and Business Data Visualization

    • Scientific and Research Visualization

    • Network and Graph Visualization

      • Network analysis and graph visualization
      • Social network analysis visualization
      • Hierarchical and tree visualization
      • Resources:

Performance and Optimization​

  • What you Need to Know

    • Large Dataset Visualization

      • Data sampling and aggregation for visualization
      • Progressive rendering and lazy loading
      • Performance optimization techniques
      • Resources:

    • Interactive Visualization Optimization

      • Client-side vs server-side rendering
      • Caching strategies for dashboard performance
      • User experience optimization
      • Resources:

Accessibility and Inclusive Design​

  • What you Need to Know

    • Color Accessibility and Universal Design

      • Color-blind friendly palettes and contrast ratios
      • Alternative text and screen reader compatibility
      • Universal design principles for data visualization
      • Resources:

    • Multi-Modal Data Communication

Ready for Advanced Analytics? Continue to Module 5: Advanced Analytics to master specialized techniques, domain applications, and cutting-edge data science methods.