I’m looking for some references on creating effective graphs/data visualizations.

I’ve found a bunch of books that show how to create data visualizations using certain tools (like R/ggplot vs python/pandas) but that’s not really what I’m looking for. I’m looking for a reference that explains different types of charts with respect to stats/math. I want more theory than process.

I want to know the different types of charts and how to use them. Anything helps!

**Answer**

I think that the work of William Cleveland is going to be closer to what you want that that of Tufte. Cleveland wrote two books:

- Visualizing Data (1993)
- The Elements of Graphing Data (1985)

The first book, in particular, may be what you want. Here is a publisher’s description:

Visualizing Data is about visualization tools that provide deep

insight into the structure of data. There are graphical tools such as

coplots, multiway dot plots, and the equal count algorithm. There are

fitting tools such as loess and bisquare that fit equations,

nonparametric curves, and nonparametric surfaces to data. But the book

is much more than just a compendium of useful tools. It conveys a

strategy for data analysis that stresses the use of visualization to

thoroughly study the structure of data and to check the validity of

statistical models fitted to data. The result of the tools and the

strategy is a vast increase in what you can learn from your data. The

book demonstrates this by reanalyzing many data sets from the

scientific literature, revealing missed effects and inappropriate

models fitted to data.

An even more theoretical book is *The Grammar of Graphics* by Leland Wilkinson. The description:

This book was written for statisticians, computer scientists,

geographers, researchers, and others interested in visualizing data.

It presents a unique foundation for producing almost every

quantitative graphic found in scientific journals, newspapers,

statistical packages, and data visualization systems. While the

tangible results of this work have been several visualization software

libraries, this book focuses on the deep structures involved in

producing quantitative graphics from data. What are the rules that

underlie the production of pie charts, bar charts, scatterplots,

function plots, maps, mosaics, and radar charts? Those less interested

in the theoretical and mathematical foundations can still get a sense

of the richness and structure of the system by examining the numerous

and often unique color graphics it can produce. The second edition is

almost twice the size of the original, with six new chapters and

substantial revision. Much of the added material makes this book

suitable for survey courses in visualization and statistical graphics.

This book is *very* theoretical.

**Attribution***Source : Link , Question Author : Community , Answer Author :
Peter Flom
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