From the reviews: "This comprehensive, compact and concise book provides all R users with a reference and guide to the mundane but terribly important topic of data manipulation in R. ... This is a book that should be read and kept close at hand by everyone who uses R regularly."(Douglas M. Bates, International Statistical Reviews, Vol. 76 (2), 2008) "Presents a wide array of methods applicable for reading statistical data into the R program and efficiently manipulating that data." (Journal of Economic Literature, Vol. 46, no. 3, September 2008) "R is a programming language particularly suitable for statistical computing and data analysis. ... Using a variety of examples based on data sets included with R, along with easily stimulated data sets, the book is recommended to anyone using R who wishes to advance from simple examples to practical real-life data manipulation solutions." (Christina Diakaki, Zentralblatt MATH, Vol. 1154, 2009) "The book contains much good information regarding the unique way in which R manipulates data objects. lt provides a complement to the many books illustrating statistical applications of R. It is clear that the author is very familiar with R. and the explanations and illustrations are generally helpful. Personally, I found the chapters on reading and writing data and on data aggregation most helpful, because these topics are essential in exploring data." (Jim Albert, The American Statistician, May 2009, Vol. 63, no. 2) "Readers of this book will receive a focused treatment of data manipulation ... . This book has lots of examples which are helpful. ... provides more depth to understand the data structure/objects within R and how to better take advantage of this structure. ... I found this book very helpful to my understanding of the structure and will be using it as a reference tool in my work." (Roger M. Sauter, Technometrics, Vol. 52 (3), August, 2010)

• Data in R.- Reading and Writing Data.- R and Databases.- Dates.- Factors.- Subscripting.- Character Manipulation.- Data Aggregation.- Reshaping Data.

From the reviews: "This comprehensive, compact and concise book provides all R users with a reference and guide to the mundane but terribly important topic of data manipulation in R. ... This is a book that should be read and kept close at hand by everyone who uses R regularly."(Douglas M. Bates, International Statistical Reviews, Vol. 76 (2), 2008) "Presents a wide array of methods applicable for reading statistical data into the R program and efficiently manipulating that data." (Journal of Economic Literature, Vol. 46, no. 3, September 2008) "R is a programming language particularly suitable for statistical computing and data analysis. ... Using a variety of examples based on data sets included with R, along with easily stimulated data sets, the book is recommended to anyone using R who wishes to advance from simple examples to practical real-life data manipulation solutions." (Christina Diakaki, Zentralblatt MATH, Vol. 1154, 2009) "The book contains much good information regarding the unique way in which R manipulates data objects. lt provides a complement to the many books illustrating statistical applications of R. It is clear that the author is very familiar with R. and the explanations and illustrations are generally helpful. Personally, I found the chapters on reading and writing data and on data aggregation most helpful, because these topics are essential in exploring data." (Jim Albert, The American Statistician, May 2009, Vol. 63, no. 2) "Readers of this book will receive a focused treatment of data manipulation ... . This book has lots of examples which are helpful. ... provides more depth to understand the data structure/objects within R and how to better take advantage of this structure. ... I found this book very helpful to my understanding of the structure and will be using it as a reference tool in my work." (Roger M. Sauter, Technometrics, Vol. 52 (3), August, 2010)

• Data in R.- Reading and Writing Data.- R and Databases.- Dates.- Factors.- Subscripting.- Character Manipulation.- Data Aggregation.- Reshaping Data.

From the reviews: "This comprehensive, compact and concise book provides all R users with a reference and guide to the mundane but terribly important topic of data manipulation in R. ... This is a book that should be read and kept close at hand by everyone who uses R regularly."(Douglas M. Bates, International Statistical Reviews, Vol. 76 (2), 2008) "Presents a wide array of methods applicable for reading statistical data into the R program and efficiently manipulating that data." (Journal of Economic Literature, Vol. 46, no. 3, September 2008) "R is a programming language particularly suitable for statistical computing and data analysis. ... Using a variety of examples based on data sets included with R, along with easily stimulated data sets, the book is recommended to anyone using R who wishes to advance from simple examples to practical real-life data manipulation solutions." (Christina Diakaki, Zentralblatt MATH, Vol. 1154, 2009) "The book contains much good information regarding the unique way in which R manipulates data objects. lt provides a complement to the many books illustrating statistical applications of R. It is clear that the author is very familiar with R. and the explanations and illustrations are generally helpful. Personally, I found the chapters on reading and writing data and on data aggregation most helpful, because these topics are essential in exploring data." (Jim Albert, The American Statistician, May 2009, Vol. 63, no. 2) "Readers of this book will receive a focused treatment of data manipulation ... . This book has lots of examples which are helpful. ... provides more depth to understand the data structure/objects within R and how to better take advantage of this structure. ... I found this book very helpful to my understanding of the structure and will be using it as a reference tool in my work." (Roger M. Sauter, Technometrics, Vol. 52 (3), August, 2010)

• Data in R.- Reading and Writing Data.- R and Databases.- Dates.- Factors.- Subscripting.- Character Manipulation.- Data Aggregation.- Reshaping Data.