Effective awk Programming,3rd Edition, focuses entirely on awk, exploring it in the greatest depth of the three awk titles we carry. It's an excellent companion piece to the more broadly focused second edition. This book provides complete coverage of the gawk 3.1 language as well as the most up-to-date coverage of the POSIX standard for awk available anywhere. Author Arnold Robbins clearly distinguishes standard awk features from GNU awk (gawk)-specific features, shines light into many of the "dark corners" of the language (areas to watch out for when programming), and devotes two full chapters to example programs. A brand new chapter is devoted to TCP/IP networking with gawk. He includes a summary of how the awk language evolved. The book also covers: Internationalization of gawk Interfacing to i18n at the awk level Two-way pipes TCP/IP networking via the two-way pipe interface The new PROCINFO array, which provides information about running gawk Profiling and pretty-printing awk programs In addition to covering the awk language, this book serves as the official "User's Guide" for the GNU implementation of awk (gawk), describing in an integrated fashion the extensions available to the System V Release 4 version of awk that are also available in gawk. As the official gawk User's Guide, this book will also be available electronically, and can be freely copied and distributed under the terms of the Free Software Foundation's Free Documentation License (FDL). A portion of the proceeds from sales of this book will go to the Free Software Foundation to support further development of free and open source software. The third edition of Effective awk Programming is a GNU Manual and is published by O'Reilly & Associates under the Free Software Foundation's Free Documentation License (FDL). A portion of the proceeds from the sale of this book is donated to the Free Software Foundation to further development of GNU software. This book is also available in electronic form; you have the freedom to modify this GNU Manual, like GNU software. Copies published by the Free Software Foundation raise funds for GNU development.

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.

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

"Spurious Correlations ... is the most fun you'll ever have with graphs." -- Bustle Military intelligence analyst and Harvard Law student Tyler Vigen illustrates the golden rule that "correlation does not equal causation" through hilarious graphs inspired by his viral website. Is there a correlation between Nic Cage films and swimming pool accidents? What about beef consumption and people getting struck by lightning? Absolutely not. But that hasn't stopped millions of people from going to tylervigen.com and asking, "Wait, what?" Vigen has designed software that scours enormous data sets to find unlikely statistical correlations. He began pulling the funniest ones for his website and has since gained millions of views, hundreds of thousands of likes, and tons of media coverage. Subversive and clever, Spurious Correlations is geek humor at its finest, nailing our obsession with data and conspiracy theory.