Mathematica Data Visualization was written with one goal in mind—teaching the reader how to write interactive visualization programs seamlessly using Mathematica. Mathematica is the programming language of choice for many data analysts, mathematicians, scientists, engineers, and business analysts. It offers a powerful suite of data analysis and data mining packages, along with a very rich data visualization framework for its users.
After reading this book and working with the code examples provided, you will be proficient in building your own interactive data visualizations. You will have a good understanding of the different kinds of data that you may encounter as a data visualization expert, along with a solid foundation on the techniques of visualizing such data using Mathematica.
Whenever needed, this book teaches the essential theory behind any advanced concept, so a beginner in data visualization will not feel uncomfortable tackling the material. Other than traditional plots, this book teaches how to build advanced visualizations from scratch, such as chord diagrams, maps, protein molecule visualizations, and so on.
Chapter 1, Visualization as a Tool to Understand Data, introduces the reader to the world of data visualization. The importance of visualization is discussed, along with the description of different datasets that will be covered.
Chapter 2, Dissecting Data Using Mathematica, gives a short introduction to Mathematica programming in the context of data analysis and operations. It also introduces the readers to basic plots.
Chapter 3, Time Series and Scientific Visualization, deals with time series and scalar fields, detailing some methods of visualizing these types of data in Mathematica.
Chapter 4, Statistical and Information Visualization, teaches some methods of statistical and information visualization using several mini projects.
Chapter 5, Maps and Aesthetics, develops a map visualization using a geographic shape file. Some essential data visualization aesthetics are also discussed.
You will require a computer with an installation of the latest version (10) of Mathematica. The notebooks were tested only with Versions 9 and 10. There are a small number of functions that are only present in Version 10, but almost all of the code listings will work in Versions 8 and 9 otherwise. The codes will work with both the student and Pro versions. If you do not have access to Mathematica, you can still view the code and interact with the visualizations using the freely downloadable CDF player from the Wolfram Mathematica website (http://www.wolfram.com/cdf-player/).
This book is aimed at people who are familiar with basic programming and high school mathematics, and are enthusiastic to learn about data visualization and Mathematica. It does not assume any prior knowledge of advanced data analysis or statistical techniques. Familiarity with a programming language may prove to be useful, but it is not essential. For beginners in Mathematica, Chapter 2, Dissecting Data Using Mathematica, provides a short primer on the essentials of Mathematica programming. Readers who are already familiar with Mathematica may skip the first half of Chapter 2, Dissecting Data Using Mathematica.
In this book, you will find a number of styles of text that distinguish between different kinds of information. Here are some examples of these styles, and an explanation of their meaning.
Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "The EdgeForm[None] function is used to ask Graphics to not render the polygon boundaries."
A block of code is set as follows:
SetDirectory[ NotebookDirectory[] ]
shpdat = Import["data/usa_state_shapefile.shp", "Data"]
names = shpdat[[1, 4, 2, 2, 2]];
polys = "Geometry" /. shpdat[[1]]
filenames = Table["data/usgs_state_" <> ToString[i] <> ".csv", {i, 2001, 2010}]When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
SectorChart[{data1, data2, …}, options]New terms and important words are shown in bold. Words that you see on the screen, in menus or dialog boxes for example, appear in the text like this: "The surface will represent the points in 3D space that has the same potential, the potential value of interest being selectable from the drop-down menu named Contour."
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