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### Effective Data Visualization with R: Volume II - lattice

Charts and graphs are meant to give us a condensed view of a given phenomenon or situation from data. That is, they enable us to extract the maximum amount of information from data as we can. At times, this entails dealing with a single variable (univariate charts), two variables (bivariate charts) or three variables (trivariate charts). But what happens when we have more than three variables (multivariate and Hypervariate charts). In such cases, the centre can no longer hold, and we need a different paradigm from which to visualize these variables. This is the premise of the lattice package. The package lattice is a data visualization package that allows us to produce multipanel plots that is many plots arranged by columns and rows on the same sheet or multiple sheets. It was developed by Deepayan Sarkar as R's implementation of trellis graphics which was implemented in S and S-PLUS.

The goal of this book then is to explore the nooks and crannies of chart production with the lattice package and is the second in a series of books on data visualization with R.

• R
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fru kingsly

FRU Kingsly is a seasoned Business Intelligence developer, with more than ten years in the field of data management and analysis. He has worked with various applications and software including R, Python, Power BI, Tableau, MS SQL Server, MS Excel, MySQL etc. He is passionate about data and analytics and always encourages others around him to take the data analysis route. You can contact him at frukingsly@live.com.

• Part1: Introduces you to plotting and multipanel plotting with lattice (Chapter 1 and 3)
Chapter 1: Introduction to plotting with lattice
Chapter 2: Multivariate plots
Chapter 3: Plot Elements
• Part2: Producing different chart types (Chapter 4 to 7)
Chapter 4: Bar chart and dot plot
Chapter 5: Histogram, Density plot and Q-Q plot
Chapter 6: Box plot, strip plot and violin plot
Chapter 7: Scatter plot matrix, parallel coordinates plot and 3D Scatter Plot
• Part3: Map visualization with the maps package (Chapter 8 to 10)
Chapter 8: Base maps with the maps package
Chapter 9: Qualitative Maps
Chapter 10: Quantitative maps

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