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Learn Fundamentals Of Data Visualization Step By Step

Download Fundamental of data Visualization free in PDF. This notes  is the best practical guide to visualization for anyone with a scientific deposit. This notes help you move beyond the standard line, bar and pie chart that you know and use.

This notes takes you through many commonly encounter visualization problem. It provides guidelines on how to turn large dataset into clear and compelling figure. This book is very helpful for anyone who is interested in data science, practicing data science and interesting in good data visualization.

You Learn These Topics From This Notes: 

1. Introduction

  • Ugly, Bad and Wrong Figure

2. Visualizing Data: Mapping Data on to Aesthetics

  • Aesthetic and Types of Data
  • Scales Map Data Value on to Aesthetic

3. Coordinate System and Axes

  • Cartesian Coordinates
  • Nonlinear Axes
  • Coordinate with System Axes

4. Color Scales

  • Color as a Tool to Distinguish
  • Color to Represent Data Values
  • Color as a Tool to Highlights

5. Directory of Visualization

  • Amounts
  • Distribution
  • proportions
  • X-Y Relationships

6. Visualizing Amount

  • Bar Plots
  • Grouped and Stacked Bar
  • Dot Plots and Heat maps

7. Visualizing Distribution: Histogram and Density Plots

  • Visualizing a Single Distribution
  • Visualizing Multiple Distribution at a Same Time

8. Visualizing Distribution: Empirical Cumulative Distribution Functions and Q-Q Plots

  • Empirical Cumulative Distribution Functions
  • Highly Skewed Distribution
  • Quantile-Quantile Plots

9. Visualizing Many Distribution at Once

  • Visualizing Distributing Along The Vertical Axes
  • Visualizing Distributing Along The Horizontal Axes

10. Visualizing Proportion

  • A Case for Pie Chart
  • A Case for Side by Side Bar
  • A Case for Stacked Bar and Stacked Densities

11. Visualizing Nested Proportions

  • Nested Proportion Gone Wrong
  • Nested Pies
  • Parallel Sets

12. Visualizing Associations Among Two or More Quantitative Variables 

  • Scatter Plots
  • Correlograms
  • Dimension Reduction

13. Visualizing Time Series and Other Functions on an Independent Variables

  • Individual Time Series
  • Multiple Time Series and Does Response Curve

14. Visualizing Trends

  • Smoothing
  • Showing Trend with a Defined Functional Forms
  • Trending and Time Series Decomposition

15. Visualizing Geospatial Data

  • Projections
  • Layers
  • Cartograms

16. Visualizing Uncertainty

  • Farming Probabilities as Frequencies
  • Visualizing the Uncertainty of Point Estimation
  • Visualizing the Uncertainty of Curve Fit

17. The Principal of Proportional lnk

  • Visualizing Along Linear Axes
  • Visualizing Along Logarithmic Axes
  • Direct Area Visualizing

18. Handling Overlapping Points

  • Partial Transparency and Jittering
  • 2D Histogram
  • Contour Lines

19. Common Pitfalls of Color Use

  • Encoding to Much or Irrelevant Information
  • Using Non monotonic Colors Scale to Encode Data Values
  • Not Designing for Color Vision Deficiency

20. Redundant Coding

  • Designing Legends For Redundant Coding
  • Designing Figure without Legends

21. Multipanel Figure

  • Small Multiples
  • Compound Figure

22. Titles, Captions and Tables

  • Figure, Title and Captions
  • Axis and Legends Titles
  • Tables

23. Balance the Data and the Context

  • Providing the Appropriate Amount of Context
  • Background Grids
  • Paired Data

24. Use Large Axes Labels

25. Avoid Line Drawing

26. Don’t Go 3D

  • Avoid 3D Position Scale
  • Avoid Gratuities 3D

27. Understanding the Most Commonly Use Image File Format

  • Bit Map and Vector Graphics
  • Lossless and Lossy Compression of Bit Map Graphics
  • Converting Between Image Format

28. Choosing the Right Visualizing Software

  • Reproductability and Repeatability
  • Data Exploration Versus Data Presentation

29. Telling a Story and Making a Point

  • What is a Story?
  • Make a Figure for the Generals
  • Build Up towards Complex Figure





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