%\VignetteIndexEntry{Working with Unknown Values} %\VignettePackage{gdata} %\VignetteKeywords{unknown, missing, manip} \documentclass[a4paper]{report} \usepackage{Rnews} \usepackage[round]{natbib} \bibliographystyle{abbrvnat} \usepackage{Sweave} \SweaveOpts{strip.white=all, keep.source=TRUE} \SweaveOpts{concordance=TRUE} \begin{document} \begin{article} \title{Working with Unknown Values} \subtitle{The \pkg{gdata} package} \author{by Gregor Gorjanc} \maketitle This vignette has been published as \cite{Gorjanc}. \section{Introduction} Unknown or missing values can be represented in various ways. For example SAS uses \code{.}~(dot), while \R{} uses \code{NA}, which we can read as Not Available. When we import data into \R{}, say via \code{read.table} or its derivatives, conversion of blank fields to \code{NA} (according to \code{read.table} help) is done for \code{logical}, \code{integer}, \code{numeric} and \code{complex} classes. Additionally, the \code{na.strings} argument can be used to specify values that should also be converted to \code{NA}. Inversely, there is an argument \code{na} in \code{write.table} and its derivatives to define value that will replace \code{NA} in exported data. There are also other ways to import/export data into \R{} as described in the {\emph R Data Import/Export} manual \citep{RImportExportManual}. However, all approaches lack the possibility to define unknown value(s) for some particular column. It is possible that an unknown value in one column is a valid value in another column. For example, I have seen many datasets where values such as 0, -9, 999 and specific dates are used as column specific unknown values. This note describes a set of functions in package \pkg{gdata}\footnote{ package version 2.3.1} \citep{WarnesGdata}: \code{isUnknown}, \code{unknownToNA} and \code{NAToUnknown}, which can help with testing for unknown values and conversions between unknown values and \code{NA}. All three functions are generic (S3) and were tested (at the time of writing) to work with: \code{integer}, \code{numeric}, \code{character}, \code{factor}, \code{Date}, \code{POSIXct}, \code{POSIXlt}, \code{list}, \code{data.frame} and \code{matrix} classes. \section{Description with examples} The following examples show simple usage of these functions on \code{numeric} and \code{factor} classes, where value \code{0} (beside \code{NA}) should be treated as an unknown value: <>= library("gdata") xNum <- c(0, 6, 0, 7, 8, 9, NA) isUnknown(x=xNum) @ The default unknown value in \code{isUnknown} is \code{NA}, which means that output is the same as \code{is.na} --- at least for atomic classes. However, we can pass the argument \code{unknown} to define which values should be treated as unknown: <>= isUnknown(x=xNum, unknown=0) @ This skipped \code{NA}, but we can get the expected answer after appropriately adding \code{NA} into the argument \code{unknown}: <>= isUnknown(x=xNum, unknown=c(0, NA)) @ Now, we can change all unknown values to \code{NA} with \code{unknownToNA}. There is clearly no need to add \code{NA} here. This step is very handy after importing data from an external source, where many different unknown values might be used. Argument \code{warning=TRUE} can be used, if there is a need to be warned about ``original'' \code{NA}s: <>= (xNum2 <- unknownToNA(x=xNum, unknown=0)) @ Prior to export from \R{}, we might want to change unknown values (\code{NA} in \R{}) to some other value. Function \code{NAToUnknown} can be used for this: <>= NAToUnknown(x=xNum2, unknown=999) @ Converting \code{NA} to a value that already exists in \code{x} issues an error, but \code{force=TRUE} can be used to overcome this if needed. But be warned that there is no way back from this step: <>= NAToUnknown(x=xNum2, unknown=7, force=TRUE) @ Examples below show all peculiarities with class \code{factor}. \code{unknownToNA} removes \code{unknown} value from levels and inversely \code{NAToUnknown} adds it with a warning. Additionally, \code{"NA"} is properly distinguished from \code{NA}. It can also be seen that the argument \code{unknown} in functions \code{isUnknown} and \code{unknownToNA} need not match the class of \code{x} (otherwise factor should be used) as the test is internally done with \code{\%in\%}, which nicely resolves coercing issues. <>= (xFac <- factor(c(0, "BA", "RA", "BA", NA, "NA"))) isUnknown(x=xFac) isUnknown(x=xFac, unknown=0) isUnknown(x=xFac, unknown=c(0, NA)) isUnknown(x=xFac, unknown=c(0, "NA")) isUnknown(x=xFac, unknown=c(0, "NA", NA)) (xFac <- unknownToNA(x=xFac, unknown=0)) (xFac <- NAToUnknown(x=xFac, unknown=0)) @ These two examples with classes \code{numeric} and \code{factor} are fairly simple and we could get the same results with one or two lines of \R{} code. The real benefit of the set of functions presented here is in \code{list} and \code{data.frame} methods, where \code{data.frame} methods are merely wrappers for \code{list} methods. We need additional flexibility for \code{list}/\code{data.frame} methods, due to possibly having multiple unknown values that can be different among \code{list} components or \code{data.frame} columns. For these two methods, the argument \code{unknown} can be either a \code{vector} or \code{list}, both possibly named. Of course, greater flexibility (defining multiple unknown values per component/column) can be achieved with a \code{list}. When a \code{vector}/\code{list} object passed to the argument \code{unknown} is not named, the first value/component of a \code{vector}/\code{list} matches the first component/column of a \code{list}/\code{data.frame}. This can be quite error prone, especially with \code{vectors}. Therefore, I encourage the use of a \code{list}. In case \code{vector}/\code{list} passed to argument \code{unknown} is named, names are matched to names of \code{list} or \code{data.frame}. If lengths of \code{unknown} and \code{list} or \code{data.frame} do not match, recycling occurs. The example below illustrates the application of the described functions to a list which is composed of previously defined and modified numeric (\code{xNum}) and factor (\code{xFac}) classes. First, function \code{isUnknown} is used with \code{0} as an unknown value. Note that we get \code{FALSE} for \code{NA}s as has been the case in the first example. <>= (xList <- list(a=xNum, b=xFac)) isUnknown(x=xList, unknown=0) @ We need to add \code{NA} as an unknown value. However, we do not get the expected result this way! <>= isUnknown(x=xList, unknown=c(0, NA)) @ This is due to matching of values in the argument \code{unknown} and components in a \code{list}; i.e., \code{0} is used for component \code{a} and \code{NA} for component \code{b}. Therefore, it is less error prone and more flexible to pass a \code{list} (preferably a named list) to the argument \code{unknown}, as shown below. <>= (xList1 <- unknownToNA(x=xList, unknown=list(b=c(0, "NA"), a=0))) @ Changing \code{NA}s to some other value (only one per component/column) can be accomplished as follows: <>= NAToUnknown(x=xList1, unknown=list(b="no", a=0)) @ A named component \code{.default} of a \code{list} passed to argument \code{unknown} has a special meaning as it will match a component/column with that name and any other not defined in \code{unknown}. As such it is very useful if the number of components/columns with the same unknown value(s) is large. Consider a wide \code{data.frame} named \code{df}. Now \code{.default} can be used to define unknown value for several columns: <>= df <- data.frame(col1=c(0, 1, 999, 2), col2=c("a", "b", "c", "unknown"), col3=c(0, 1, 2, 3), col4=c(0, 1, 2, 2)) @ <>= tmp <- list(.default=0, col1=999, col2="unknown") (df2 <- unknownToNA(x=df, unknown=tmp)) @ If there is a need to work only on some components/columns you can of course ``skip'' columns with standard \R{} mechanisms, i.e., by subsetting \code{list} or \code{data.frame} objects: <>= df2 <- df cols <- c("col1", "col2") tmp <- list(col1=999, col2="unknown") df2[, cols] <- unknownToNA(x=df[, cols], unknown=tmp) df2 @ \section{Summary} Functions \code{isUnknown}, \code{unknownToNA} and \code{NAToUnknown} provide a useful interface to work with various representations of unknown/missing values. Their use is meant primarily for shaping the data after importing to or before exporting from \R{}. I welcome any comments or suggestions. % \bibliography{refs} \begin{thebibliography}{1} \providecommand{\natexlab}[1]{#1} \providecommand{\url}[1]{\texttt{#1}} \expandafter\ifx\csname urlstyle\endcsname\relax \providecommand{\doi}[1]{doi: #1}\else \providecommand{\doi}{doi: \begingroup \urlstyle{rm}\Url}\fi \bibitem[Gorjanc(2007)]{Gorjanc} G.~Gorjanc. \newblock Working with unknown values: the gdata package. \newblock \emph{R News}, 7\penalty0 (1):\penalty0 24--26, 2007. \newblock URL \url{http://CRAN.R-project.org/doc/Rnews/Rnews_2007-1.pdf}. \bibitem[{R Development Core Team}(2006)]{RImportExportManual} {R Development Core Team}. \newblock \emph{R Data Import/Export}, 2006. \newblock URL \url{http://cran.r-project.org/manuals.html}. \newblock ISBN 3-900051-10-0. \bibitem[Warnes (2006)]{WarnesGdata} G.~R. Warnes. \newblock \emph{gdata: Various R programming tools for data manipulation}, 2006. \newblock URL \url{http://cran.r-project.org/src/contrib/Descriptions/gdata.html}. \newblock R package version 2.3.1. Includes R source code and/or documentation contributed by Ben Bolker, Gregor Gorjanc and Thomas Lumley. \end{thebibliography} \address{Gregor Gorjanc\\ University of Ljubljana, Slovenia\\ \email{gregor.gorjanc@bfro.uni-lj.si}} \end{article} \end{document}