This book presents a wide array of methods applicable for reading data into R, and efficiently manipulating that data. In addition to the built-in functions, a number of readily available packages from CRAN (the Comprehensive R Archive Network) are also covered. All of the methods presented take advantage of the core features of R: vectorization, efficient use of subscripting, and the proper use of the varied functions in R that are provided for common data management tasks. Most experienced R users discover that, especially when working with large data sets, it may be helpful to use other programs, notably databases, in conjunction with R. Accordingly, the use of databases in R is covered in detail, along with methods for extracting data from spreadsheets and datasets created by other programs. Character manipulation, while sometimes overlooked within R, is also covered in detail, allowing problems that are traditionally solved by scripting languages to be carried out entirely within R. For users with experience in other languages, guidelines for the effective use of programming constructs like loops are provided. Since many statistical modeling and graphics functions need their data presented in a data frame, techniques for converting the output of commonly used functions to data frames are provided throughout the book.Among its arguments are --local, which specifies that the data is local, and not on the server, --delete, which insures that the contents ... of the machine on which the MySQL server is running, and the -p option, to tell the server to prompt for a password, may be required ... shell command could be entered in a terminal window: mysqlimport -u sqluser -p --delete --local \ --fields-terminated-by=a#39;, a#39; test mydata.txt Notice that mysqlimport determines the table name by removing any suffix fromanbsp;...
|Title||:||Data Manipulation with R|
|Publisher||:||Springer Science & Business Media - 2008-03-19|