Electron microscopy
 
Methods of Data and Information Visualization
- Python Automation and Machine Learning for ICs -
- An Online Book -
Python Automation and Machine Learning for ICs                                                    http://www.globalsino.com/ICs/        


Chapter/Index: Introduction | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | Appendix

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There are various methods of data and information visualization, each suited to different types of data and communication goals:

  1. Bar Charts: Display data using rectangular bars. Useful for comparing quantities across different categories.

  2. Line Charts: Show trends and patterns over a continuous interval or time. Useful for displaying data points in a chronological order.

  3. Pie Charts: Represent parts of a whole. Useful for showing the distribution of a dataset.

  4. Scatter Plots: Display individual data points on a two-dimensional graph to show the relationship between two variables.

  5. Heatmaps: Use color variations to represent values in a matrix. Useful for showing patterns in large datasets.

  6. Tree Maps: Display hierarchical data using nested rectangles, with each branch represented by a smaller rectangle.

  7. Bubble Charts: Similar to a scatter plot but with an additional dimension represented by the size of the markers.

  8. Network Diagrams: Visualize relationships between nodes (points) and edges (connections) in a network.

  9. Choropleth Maps: Represent data using color variations on a map to show regional patterns.

  10. Word Clouds: Display words where the size of each word indicates its frequency or importance.

  11. Gantt Charts: Used in project management to illustrate a project schedule, including start and finish dates of elements.

  12. Radar Charts: Display multivariate data in the form of a two-dimensional chart with three or more quantitative variables.

  13. Box Plots (Box-and-Whisker Plots): Show the distribution of a dataset and highlight statistical measures like median and quartiles.

  14. Sankey Diagrams: Represent the flow of resources or information between different entities.

  15. Pictograms: Use icons or pictures to represent data, where the size or quantity of icons corresponds to the value being conveyed.

  16. 3D Visualizations: Represent data in three-dimensional space for a more immersive experience.

  17. Sparklines: Small, simple charts placed within a cell to provide a visual representation of data trends.

  18. Sunburst Charts: Display hierarchical data using concentric rings, where each ring represents a level of the hierarchy.

  19. Streamgraphs: Show the cumulative values of different data series over time.

  20. Parallel Coordinates: Represent multivariate data by plotting each variable on a separate vertical axis.

When choosing a visualization method, it's essential to consider the type of data you have, the message you want to convey, and the audience you are targeting.

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