Visualizing Categorical Data

by Michael Friendly
Visualizing Categorical Data
Author: Michael Friendly
Publisher: SAS Press
Total Pages: 0
Release: 2000
Genre: Computer graphics
ISBN: 9781580256605
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Graphical methods for quantitative data are well developed and widely used. However, until now with this comprehensive treatment, few graphical methods existed for categorical data. In this innovative book, the author presents many aspects of the relationships among variables, the adequacy of a fitted model, and possibly unusual features of the data that can best be seen and appreciated in an informative graphical display.

Visualization of Categorical Data

by Jörg Blasius
Visualization of Categorical Data
Author: Jörg Blasius
Publisher: Academic Press
Total Pages: 615
Release: 1998-02-09
Genre: Mathematics
ISBN: 0080543626
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A unique and timely monograph, Visualization of Categorical Data contains a useful balance of theoretical and practical material on this important new area. Top researchers in the field present the books four main topics: visualization, correspondence analysis, biplots and multidimensional scaling, and contingency table models.This volume discusses how surveys, which are employed in many different research areas, generate categorical data. It will be of great interest to anyone involved in collecting or analyzing categorical data.* Correspondence Analysis* Homogeneity Analysis* Loglinear and Association Models* Latent Class Analysis* Multidimensional Scaling* Cluster Analysis* Ideal Point Discriminant Analysis* CHAID* Formal Concept Analysis* Graphical Models

Tableau Strategies

by Ann Jackson
Tableau Strategies
Author: Ann Jackson
Publisher: "O'Reilly Media, Inc."
Total Pages: 578
Release: 2021-07-28
Genre: Business & Economics
ISBN: 1492080055
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If you want to increase Tableau's value to your organization, this practical book has your back. Authors Ann Jackson and Luke Stanke guide data analysts through recipes for solving real-world analytics problems using Tableau. Starting with the basics and building toward advanced topics such as multidimensional analysis and user experience, you'll explore pragmatic and creative examples that you can apply to your own data. Staying competitive today requires the ability to quickly analyze, visualize, and make data-driven decisions. With this guide, data practitioners and leaders alike will learn strategies for building compelling and purposeful visualizations, dashboards, and data products. Every chapter contains the why behind the solution and the technical knowledge you need to make it work. Visualize different data types and tackle specific data challenges Create compelling data visualizations, dashboards, and data products Learn how to generate industry-specific analytics Use this book as a high-value on-the-job reference guide to Tableau Explore categorical and quantitative analysis and comparisons Understand geospatial, dynamic, and statistical and multivariate analysis Communicate the value of the Tableau platform to your team and to stakeholders.

Discrete Data Analysis with R

by Michael Friendly
Discrete Data Analysis with R
Author: Michael Friendly
Publisher: CRC Press
Total Pages: 700
Release: 2015-12-16
Genre: Mathematics
ISBN: 1498725864
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An Applied Treatment of Modern Graphical Methods for Analyzing Categorical DataDiscrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and frequency data. It explains how to use graphical meth

Feature Engineering and Selection

by Max Kuhn
Feature Engineering and Selection
Author: Max Kuhn
Publisher: CRC Press
Total Pages: 266
Release: 2019-07-25
Genre: Business & Economics
ISBN: 1351609467
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The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

Data Visualization

by Kieran Healy
Data Visualization
Author: Kieran Healy
Publisher: Princeton University Press
Total Pages: 292
Release: 2018-12-18
Genre: Social Science
ISBN: 0691181624
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An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions

R for Data Science

by Hadley Wickham
R for Data Science
Author: Hadley Wickham
Publisher: "O'Reilly Media, Inc."
Total Pages: 521
Release: 2016-12-12
Genre: Computers
ISBN: 1491910364
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Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Visualization Analysis and Design

by Tamara Munzner
Visualization Analysis and Design
Author: Tamara Munzner
Publisher: CRC Press
Total Pages: 422
Release: 2014-12-01
Genre: Business & Economics
ISBN: 1466508930
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Learn How to Design Effective Visualization SystemsVisualization Analysis and Design provides a systematic, comprehensive framework for thinking about visualization in terms of principles and design choices. The book features a unified approach encompassing information visualization techniques for abstract data, scientific visualization techniques

The Grammar of Graphics

by Leland Wilkinson
The Grammar of Graphics
Author: Leland Wilkinson
Publisher: Springer Science & Business Media
Total Pages: 415
Release: 2013-03-09
Genre: Computers
ISBN: 1475731000
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Written for statisticians, computer scientists, geographers, research and applied scientists, and others interested in visualizing data, this book presents a unique foundation for producing almost every quantitative graphic found in scientific journals, newspapers, statistical packages, and data visualization systems. It was designed for a distributed computing environment, with special attention given to conserving computer code and system resources. While the tangible result of this work is a Java production graphics library, the text focuses on the deep structures involved in producing quantitative graphics from data. It investigates the rules that underlie pie charts, bar charts, scatterplots, function plots, maps, mosaics, and radar charts. These rules are abstracted from the work of Bertin, Cleveland, Kosslyn, MacEachren, Pinker, Tufte, Tukey, Tobler, and other theorists of quantitative graphics.