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Type 'q()' to quit R. > pkgname <- "DDIwR" > source(file.path(R.home("share"), "R", "examples-header.R")) > options(warn = 1) > library('DDIwR') Also attaching packages: admisc, declared > > base::assign(".oldSearch", base::search(), pos = 'CheckExEnv') > base::assign(".old_wd", base::getwd(), pos = 'CheckExEnv') > cleanEx() > nameEx("clearFormats") > ### * clearFormats > > flush(stderr()); flush(stdout()) > > ### Name: clearFormats > ### Title: Clear statistical variable formats and widths > ### Aliases: clearFormats clearWidths > > ### ** Examples > > x <- structure(c(1, 2), format.spss = "F12.3", width = 8L) > attr(x, "spss_metadata") <- list(format = "F16.4", measure = "scale") > clearFormats(x) [1] 1 2 attr(,"width") [1] 8 attr(,"spss_metadata") attr(,"spss_metadata")$measure [1] "scale" > clearWidths(x) [1] 1 2 attr(,"format.spss") [1] "F12.3" attr(,"spss_metadata") attr(,"spss_metadata")$format [1] "F16.4" attr(,"spss_metadata")$measure [1] "scale" > > > > > cleanEx() > nameEx("convert") > ### * convert > > flush(stderr()); flush(stdout()) > > ### Name: convert > ### Title: Converts a dataset from one statistical software to another > ### Aliases: convert > > ### ** Examples > > ## Not run: > ##D # Assuming an SPSS file called test.sav is located in the working directory > ##D # The following command imports the file into the R environment: > ##D test <- convert("test.sav") > ##D > ##D # The following command will extract the metadata in a DDI Codebook and > ##D # produce a test.xml file in the same directory > ##D convert("test.sav", to = "DDI") > ##D > ##D # The data may be saved separately from the DDI file, using: > ##D convert("test.sav", to = "DDI", embed = FALSE) > ##D > ##D # Format-specific options are supplied through the three dots. For example, > ##D # import the English labels from a multilingual DDI Codebook using: > ##D test <- convert("test.xml", language = "en") > ##D > ##D # To produce a Stata file: > ##D convert("test.sav", to = "Stata") > ##D > ##D # To produce an R file: > ##D convert("test.sav", to = "R") > ##D > ##D # To produce an Excel file: > ##D convert("test.sav", to = "Excel") > ## End(Not run) > > > > > cleanEx() > nameEx("exportCodebook") > ### * exportCodebook > > flush(stderr()); flush(stdout()) > > ### Name: exportCodebook > ### Title: Export a DDI Codebook to an XML file. > ### Aliases: exportCodebook > > ### ** Examples > > ## Not run: > ##D exportCodebook(codeBook, to = "codebook.xml") > ##D > ##D # using a namespace > ##D exportCodebook(codeBook, to = "codebook.xml", xmlns = "ddi") > ## End(Not run) > > > > > cleanEx() > nameEx("getCodebook") > ### * getCodebook > > flush(stderr()); flush(stdout()) > > ### Name: getCodebook > ### Title: Extract metadata information > ### Aliases: getCodebook > > ### ** Examples > > x <- data.frame( + A = declared( + c(1:5, -92), + labels = c(Good = 1, Bad = 5, NR = -92), + na_values = -92 + ), + C = declared( + c(1, -91, 3:5, -92), + labels = c(DK = -91, NR = -92), + na_values = c(-91, -92) + ) + ) > > getCodebook(from = x) $fileDscr $fileDscr$fileTxt $fileDscr$fileTxt$fileName $fileDscr$fileTxt$fileName[[1]] [1] "x" $fileDscr$fileTxt$fileName$.extra $fileDscr$fileTxt$fileName$.extra$name [1] "fileName" $fileDscr$fileTxt$fileName$.extra$index [1] 1 $fileDscr$fileTxt$fileType $fileDscr$fileTxt$fileType[[1]] [1] "R" $fileDscr$fileTxt$fileType$.extra $fileDscr$fileTxt$fileType$.extra$name [1] "fileType" $fileDscr$fileTxt$fileType$.extra$index [1] 1 $fileDscr$fileTxt$.extra $fileDscr$fileTxt$.extra$name [1] "fileTxt" $fileDscr$fileTxt$.extra$index [1] 1 $fileDscr$.extra $fileDscr$.extra$name [1] "fileDscr" $fileDscr$.extra$index [1] 1 $dataDscr $dataDscr$var $dataDscr$var$valrng $dataDscr$var$valrng$range $dataDscr$var$valrng$range$.extra $dataDscr$var$valrng$range$.extra$name [1] "range" $dataDscr$var$valrng$range$.extra$index [1] 1 attr(,"UNITS") [1] "INT" attr(,"min") [1] "1" attr(,"max") [1] "5" $dataDscr$var$valrng$.extra $dataDscr$var$valrng$.extra$name [1] "valrng" $dataDscr$var$valrng$.extra$index [1] 1 $dataDscr$var$sumStat $dataDscr$var$sumStat[[1]] [1] "5" $dataDscr$var$sumStat$.extra $dataDscr$var$sumStat$.extra$name [1] "sumStat" $dataDscr$var$sumStat$.extra$index [1] 1 attr(,"type") [1] "vald" attr(,"wgtd") [1] "not-wgtd" $dataDscr$var$sumStat $dataDscr$var$sumStat[[1]] [1] "1" $dataDscr$var$sumStat$.extra $dataDscr$var$sumStat$.extra$name [1] "sumStat" $dataDscr$var$sumStat$.extra$index [1] 2 attr(,"type") [1] "invd" attr(,"wgtd") [1] "not-wgtd" $dataDscr$var$catgry $dataDscr$var$catgry$catValu $dataDscr$var$catgry$catValu[[1]] [1] "1" $dataDscr$var$catgry$catValu$.extra $dataDscr$var$catgry$catValu$.extra$name [1] "catValu" $dataDscr$var$catgry$catValu$.extra$index [1] 1 $dataDscr$var$catgry$labl $dataDscr$var$catgry$labl[[1]] [1] "Good" $dataDscr$var$catgry$labl$.extra $dataDscr$var$catgry$labl$.extra$name [1] "labl" $dataDscr$var$catgry$labl$.extra$index [1] 1 $dataDscr$var$catgry$catStat $dataDscr$var$catgry$catStat[[1]] [1] "1" $dataDscr$var$catgry$catStat$.extra $dataDscr$var$catgry$catStat$.extra$name [1] "catStat" $dataDscr$var$catgry$catStat$.extra$index [1] 1 attr(,"type") [1] "freq" $dataDscr$var$catgry$.extra $dataDscr$var$catgry$.extra$name [1] "catgry" $dataDscr$var$catgry$.extra$index [1] 1 $dataDscr$var$catgry $dataDscr$var$catgry$catValu $dataDscr$var$catgry$catValu[[1]] [1] "5" $dataDscr$var$catgry$catValu$.extra $dataDscr$var$catgry$catValu$.extra$name [1] "catValu" $dataDscr$var$catgry$catValu$.extra$index [1] 1 $dataDscr$var$catgry$labl $dataDscr$var$catgry$labl[[1]] [1] "Bad" $dataDscr$var$catgry$labl$.extra $dataDscr$var$catgry$labl$.extra$name [1] "labl" $dataDscr$var$catgry$labl$.extra$index [1] 1 $dataDscr$var$catgry$catStat $dataDscr$var$catgry$catStat[[1]] [1] "1" $dataDscr$var$catgry$catStat$.extra $dataDscr$var$catgry$catStat$.extra$name [1] "catStat" $dataDscr$var$catgry$catStat$.extra$index [1] 1 attr(,"type") [1] "freq" $dataDscr$var$catgry$.extra $dataDscr$var$catgry$.extra$name [1] "catgry" $dataDscr$var$catgry$.extra$index [1] 2 $dataDscr$var$catgry $dataDscr$var$catgry$catValu $dataDscr$var$catgry$catValu[[1]] [1] "-92" $dataDscr$var$catgry$catValu$.extra $dataDscr$var$catgry$catValu$.extra$name [1] "catValu" $dataDscr$var$catgry$catValu$.extra$index [1] 1 $dataDscr$var$catgry$labl $dataDscr$var$catgry$labl[[1]] [1] "NR" $dataDscr$var$catgry$labl$.extra $dataDscr$var$catgry$labl$.extra$name [1] "labl" $dataDscr$var$catgry$labl$.extra$index [1] 1 $dataDscr$var$catgry$catStat $dataDscr$var$catgry$catStat[[1]] [1] "0" $dataDscr$var$catgry$catStat$.extra $dataDscr$var$catgry$catStat$.extra$name [1] "catStat" $dataDscr$var$catgry$catStat$.extra$index [1] 1 attr(,"type") [1] "freq" $dataDscr$var$catgry$.extra $dataDscr$var$catgry$.extra$name [1] "catgry" $dataDscr$var$catgry$.extra$index [1] 3 attr(,"missing") [1] "Y" $dataDscr$var$varFormat $dataDscr$var$varFormat[[1]] [1] "F1.0" $dataDscr$var$varFormat$.extra $dataDscr$var$varFormat$.extra$name [1] "varFormat" $dataDscr$var$varFormat$.extra$index [1] 1 attr(,"type") [1] "numeric" $dataDscr$var$.extra $dataDscr$var$.extra$name [1] "var" $dataDscr$var$.extra$index [1] 1 attr(,"ID") [1] "DAh8WqNR6ygUUp1t" attr(,"name") [1] "A" attr(,"dcml") [1] "0" $dataDscr$var $dataDscr$var$valrng $dataDscr$var$valrng$range $dataDscr$var$valrng$range$.extra $dataDscr$var$valrng$range$.extra$name [1] "range" $dataDscr$var$valrng$range$.extra$index [1] 1 attr(,"UNITS") [1] "INT" attr(,"min") [1] "1" attr(,"max") [1] "5" $dataDscr$var$valrng$.extra $dataDscr$var$valrng$.extra$name [1] "valrng" $dataDscr$var$valrng$.extra$index [1] 1 $dataDscr$var$sumStat $dataDscr$var$sumStat[[1]] [1] "4" $dataDscr$var$sumStat$.extra $dataDscr$var$sumStat$.extra$name [1] "sumStat" $dataDscr$var$sumStat$.extra$index [1] 1 attr(,"type") [1] "vald" attr(,"wgtd") [1] "not-wgtd" $dataDscr$var$sumStat $dataDscr$var$sumStat[[1]] [1] "2" $dataDscr$var$sumStat$.extra $dataDscr$var$sumStat$.extra$name [1] "sumStat" $dataDscr$var$sumStat$.extra$index [1] 2 attr(,"type") [1] "invd" attr(,"wgtd") [1] "not-wgtd" $dataDscr$var$catgry $dataDscr$var$catgry$catValu $dataDscr$var$catgry$catValu[[1]] [1] "-91" $dataDscr$var$catgry$catValu$.extra $dataDscr$var$catgry$catValu$.extra$name [1] "catValu" $dataDscr$var$catgry$catValu$.extra$index [1] 1 $dataDscr$var$catgry$labl $dataDscr$var$catgry$labl[[1]] [1] "DK" $dataDscr$var$catgry$labl$.extra $dataDscr$var$catgry$labl$.extra$name [1] "labl" $dataDscr$var$catgry$labl$.extra$index [1] 1 $dataDscr$var$catgry$catStat $dataDscr$var$catgry$catStat[[1]] [1] "0" $dataDscr$var$catgry$catStat$.extra $dataDscr$var$catgry$catStat$.extra$name [1] "catStat" $dataDscr$var$catgry$catStat$.extra$index [1] 1 attr(,"type") [1] "freq" $dataDscr$var$catgry$.extra $dataDscr$var$catgry$.extra$name [1] "catgry" $dataDscr$var$catgry$.extra$index [1] 1 attr(,"missing") [1] "Y" $dataDscr$var$catgry $dataDscr$var$catgry$catValu $dataDscr$var$catgry$catValu[[1]] [1] "-92" $dataDscr$var$catgry$catValu$.extra $dataDscr$var$catgry$catValu$.extra$name [1] "catValu" $dataDscr$var$catgry$catValu$.extra$index [1] 1 $dataDscr$var$catgry$labl $dataDscr$var$catgry$labl[[1]] [1] "NR" $dataDscr$var$catgry$labl$.extra $dataDscr$var$catgry$labl$.extra$name [1] "labl" $dataDscr$var$catgry$labl$.extra$index [1] 1 $dataDscr$var$catgry$catStat $dataDscr$var$catgry$catStat[[1]] [1] "0" $dataDscr$var$catgry$catStat$.extra $dataDscr$var$catgry$catStat$.extra$name [1] "catStat" $dataDscr$var$catgry$catStat$.extra$index [1] 1 attr(,"type") [1] "freq" $dataDscr$var$catgry$.extra $dataDscr$var$catgry$.extra$name [1] "catgry" $dataDscr$var$catgry$.extra$index [1] 2 attr(,"missing") [1] "Y" $dataDscr$var$varFormat $dataDscr$var$varFormat[[1]] [1] "F1.0" $dataDscr$var$varFormat$.extra $dataDscr$var$varFormat$.extra$name [1] "varFormat" $dataDscr$var$varFormat$.extra$index [1] 1 attr(,"type") [1] "numeric" $dataDscr$var$.extra $dataDscr$var$.extra$name [1] "var" $dataDscr$var$.extra$index [1] 2 attr(,"ID") [1] "mJGIOUkoYtkkhp9Y" attr(,"name") [1] "C" attr(,"dcml") [1] "0" $dataDscr$.extra $dataDscr$.extra$name [1] "dataDscr" $dataDscr$.extra$index [1] 1 $.extra $.extra$name [1] "codeBook" attr(,"source") [1] "producer" attr(,"xsi:schemaLocation") [1] "ddi:codebook:2_6 codebook.xsd" attr(,"xmlns:xsi") [1] "http://www.w3.org/2001/XMLSchema-instance" attr(,"xmlns:xsd") [1] "http://www.w3.org/2001/XMLSchema" attr(,"xmlns") [1] "ddi:codebook:2_6" > > > > > cleanEx() > nameEx("inspectFile") > ### * inspectFile > > flush(stderr()); flush(stdout()) > > ### Name: inspectFile > ### Title: Inspect statistical file metadata without importing observations > ### Aliases: inspectFile > > ### ** Examples > > ## Not run: > ##D info <- inspectFile("survey.sav") > ##D info$row_count > ##D info$columns > ##D info$metadata$label > ## End(Not run) > > > > > cleanEx() > nameEx("makeElement") > ### * makeElement > > flush(stderr()); flush(stdout()) > > ### Name: makeElement > ### Title: Make a DDI Codebook element > ### Aliases: makeElement > > ### ** Examples > > stdyDscr <- makeElement("stdyDscr", fill = TRUE) > > # easier to extract with: > getChildren("citation/titlStmt/titl", from = stdyDscr) [[1]] [1] "Generic title" $.extra $.extra$name [1] "titl" $.extra$index [1] 1 > > > > > cleanEx() > nameEx("recodeCharcat") > ### * recodeCharcat > > flush(stderr()); flush(stdout()) > > ### Name: recodeCharcat > ### Title: Recode character categorical variables > ### Aliases: recodeCharcat > > ### ** Examples > > x <- declared( + c(letters[1:5], -91), + labels = c(Good = "a", Bad = "e", NR = -91), + na_values = -91 + ) > > recodeCharcat(x) [6]> [1] 1 3 4 5 2 NA(-91) Missing values: -91 Labels: value label -91 NR 1 Good 2 Bad > > > > > cleanEx() > nameEx("recodeMissings") > ### * recodeMissings > > flush(stderr()); flush(stdout()) > > ### Name: recodeMissings > ### Title: Consistent recoding of (extended) missing values > ### Aliases: recodeMissings > > ### ** Examples > > # x <- data.frame( > # A = declared( > # c(1:5, -92), > # labels = c(Good = 1, Bad = 5, NR = -92), > # na_values = -92 > # ), > # B = labelled( > # c(1:5, tagged_na('a')), > # labels = c(DK = tagged_na('a')) > # ), > # C = declared( > # c(1, -91, 3:5, -92), > # labels = c(DK = -91, NR = -92), > # na_values = c(-91, -92) > # ) > # ) > > # xrec <- recodeMissings(x, to = "Stata") > > # attr(xrec, "dictionary") > > # Supply a dictionary to harmonize missing meanings across variables > # dictionary <- data.frame( > # old = c(-91, -92, "a"), > # new = c("c", "d", "c") > # ) > # recodeMissings(x, to = "Stata", dictionary = dictionary) > > # recodeMissings(x, to = "SPSS") > > # dictionary$new <- c(-97, -98, -97) > > # recodeMissings(x, to = "SPSS", dictionary = dictionary) > > # recodeMissings(x, to = "SPSS", start = 991) > > # recodeMissings(x, to = "SPSS", start = -8) > > > > > cleanEx() > nameEx("setupfile") > ### * setupfile > > flush(stderr()); flush(stdout()) > > ### Name: setupfile > ### Title: Create setup files for SPSS, Stata, SAS and R > ### Aliases: setupfile > > ### ** Examples > > # A small dataset with variable and value labels > survey <- data.frame( + age = declared( + c(28, 35, 42), + label = "Age in years" + ), + device = declared( + c(1, 2, 1), + label = "Device used", + labels = c(Desktop = 1, Mobile = 2) + ) + ) > > # Use a temporary directory for the files created in this example > temp_dir <- tempdir() > csv_file <- file.path(temp_dir, "survey.csv") > admisc::export(undeclare(survey, drop = TRUE), file = csv_file) > > # codeBook is an R object containing DDI metadata extracted from survey. > # It describes the variables and their labels; the observations are in the CSV. > codeBook <- getCodebook(survey) > > # Create Stata commands to import the CSV and apply the metadata > # Edit the generated file's configuration paths before running it in Stata. > setupfile(codeBook, file = file.path(temp_dir, "survey.do"), csv = csv_file) > > # A labelled data frame can also be supplied directly > setupfile(survey, file = file.path(temp_dir, "survey.sps")) recode_native.c:521:5: runtime error: null pointer passed as argument 1, which is declared to never be null #0 0x7b99f1a04e34 in build_dictionary_ /data/localhost/ripley/R/packages/tests-gcc-SAN/DDIwR/src/recode_native.c:521 #1 0x00000075f63a in R_doDotCall /data/localhost/ripley/R/svn/R-devel/src/main/dotcode.c:760 #2 0x0000007640aa in do_dotcall /data/localhost/ripley/R/svn/R-devel/src/main/dotcode.c:1437 #3 0x0000008f09db in bcEval_loop /data/localhost/ripley/R/svn/R-devel/src/main/eval.c:8154 #4 0x0000008db8eb in bcEval /data/localhost/ripley/R/svn/R-devel/src/main/eval.c:7537 #5 0x00000087979a in Rf_eval /data/localhost/ripley/R/svn/R-devel/src/main/eval.c:1167 #6 0x000000892c1a in R_execClosure /data/localhost/ripley/R/svn/R-devel/src/main/eval.c:2400 #7 0x00000089691d in applyClosure_core /data/localhost/ripley/R/svn/R-devel/src/main/eval.c:2316 #8 0x000000879e48 in Rf_applyClosure /data/localhost/ripley/R/svn/R-devel/src/main/eval.c:2335 #9 0x000000879e48 in Rf_eval /data/localhost/ripley/R/svn/R-devel/src/main/eval.c:1278 #10 0x000000a253f8 in Rf_ReplIteration /data/localhost/ripley/R/svn/R-devel/src/main/main.c:264 #11 0x000000a253f8 in R_ReplConsole /data/localhost/ripley/R/svn/R-devel/src/main/main.c:319 #12 0x000000a4315a in run_Rmainloop /data/localhost/ripley/R/svn/R-devel/src/main/main.c:1239 #13 0x000000a431f2 in Rf_mainloop /data/localhost/ripley/R/svn/R-devel/src/main/main.c:1246 #14 0x0000004122df in main /data/localhost/ripley/R/svn/R-devel/src/main/Rmain.c:29 #15 0x7f9a0020a680 in __libc_start_call_main (/lib64/libc.so.6+0x3680) (BuildId: 85075e2ae2e13352a1413d41c327dacf6461526c) #16 0x7f9a0020a797 in __libc_start_main@GLIBC_2.2.5 (/lib64/libc.so.6+0x3797) (BuildId: 85075e2ae2e13352a1413d41c327dacf6461526c) #17 0x000000412ca4 in _start (/data/localhost/ripley/R/gcc-SAN3/bin/exec/R+0x412ca4) (BuildId: 907e1509d4ba549f1da5b9155d05c31aa6f3d368) > > # The file extension selects the software: .do, .sps, .sas or .R. > # A setup file contains import commands, not the observations themselves. > > ## Not run: > ##D # Alternatively, read metadata from an existing DDI XML file > ##D setupfile("/path/to/metadata.xml", file = "survey.do", > ##D csv = "/path/to/survey.csv") > ##D > ##D # Batch processing: read metadata and CSV files from matching directories > ##D setupfile("/path/to/metadata/directory", csv = "/path/to/csv/directory") > ## End(Not run) > > > > > cleanEx() > nameEx("showDetails") > ### * showDetails > > flush(stderr()); flush(stdout()) > > ### Name: showDetails > ### Title: Describe what a DDI element is > ### Aliases: showDetails showDescription showAttributes globalAttributes > ### showExamples showRelations showLineages > > ### ** Examples > > showDetails("codeBook") Codebook (mandatory, non-repeatable) Every element in the DDI DTD/Schema has the following attributes: ID - This uniquely identifies each element. The DDI contains a linking mechanism permitting arbitrary links between internal elements (See Link) and from internal elements to external sources (See ExtLink). Note that the use of these two elements has been DEPRECATED in version 2.6. Specific attributes, use globalAttributes() for the rest: - xsi:schemaLocation (mandatory): string URL or URN containing the location of the XML file schema. - xmlns:xsi (mandatory): string URL or URN containing the location of the XML Schema Instance. - xmlns:xsd (mandatory): string URL or URN containing the location of the XML Schema Instance. - xmlns (mandatory): string The DDI Codebook XML namespace. - xmlang (recommended): language Specifies the language used in the contents and attribute values of any element in the XML document. Use of ISO (www.iso.org) language codes is recommended. - source (optional): (archive | producer) : producer Identifies the source that provided information in the element. If the documentation contains two differing sets of information on Sampling Procedure -- one provided by the data producer and one by the archive where the data is deposited -- this information can be distinguished through the use of the source attribute. - version (optional): string Version number of the DDI specification. - codeBookAgency (optional): NCName Agency name of the creator or maintainer of the codeBook instance as a whole. This is designed to support forward compatibility with DDI-Lifecycle. Recommend the agency name as filed with the DDI Agency ID Registry with optional additional sub-agency extensions. - access (optional): IDREFS Records the ID values of all elements in the Data Access and Metadata Access section that describe access conditions for this codebook instance. Children: - docDscr [0..n]: Document Description - stdyDscr [1..n]: Study Description - fileDscr [0..n]: Data Files Description - dataDscr [0..n]: Variable Description - otherMat [0..n]: Other Study-Related Materials This element has no examples. > > showAttributes("catgry") Specific attributes, use globalAttributes() for the rest: - missing (optional): (Y | N) : N Indicates whether this category group contains missing data or not. - missType (optional): string Type of missing data, e.g., inap., don't know, no answer, etc. - country (optional): string Allows for the denotation of country-specific category values - sdatrefs (optional): IDREFS Summary data description references that record the ID values of all elements within the summary data description section of the Study Description that might apply to this element. These include: time period covered, date of collection, nation or country, geographic coverage, geographic unit, unit of analysis, universe, and kind of data. - access (optional): IDREFS ID values of all elements within the Data Access and etadata Access sections description that apply to this element. - excls (optional): (true | false) : true Exclusiveness, should be set to "false" if the category can appear in more than one place in the classification hierarchy. - catgry (optional): IDREFS References any child categories of this category element. Used to capture nested hierarchies of categories. - level (optional): IDREF Reference to the catLevel ID in which this category exists. > > showExamples("abstract") Examples: Data on labor force activity for the week prior to the survey are supplied in this collection. Information is available on the employment status, occupation, and industry of persons 15 years old and over. Demographic variables such as age, sex, race, marital status, veteran status, household relationship, educational background, and Hispanic origin are included. In addition to providing these core data, the May survey also contains a supplement on work schedules for all applicable persons aged 15 years and older who were employed at the time of the survey. This supplement focuses on shift work, flexible hours, and work at home for both main and second jobs. > > showLineages("titl") codeBook/docDscr/citation/notes/table/titl codeBook/docDscr/notes/table/titl codeBook/docDscr/docSrc/notes/table/titl codeBook/docDscr/citation/verStmt/notes/table/titl codeBook/docDscr/docSrc/verStmt/notes/table/titl codeBook/docDscr/citation/titlStmt/titl codeBook/docDscr/docSrc/titlStmt/titl codeBook/stdyDscr/othrStdyMat/othRefs/citation/notes/table/titl codeBook/stdyDscr/othrStdyMat/relMat/citation/notes/table/titl codeBook/stdyDscr/othrStdyMat/relPubl/citation/notes/table/titl codeBook/stdyDscr/othrStdyMat/relStdy/citation/notes/table/titl codeBook/stdyDscr/citation/notes/table/titl codeBook/stdyDscr/dataAccs/notes/table/titl codeBook/stdyDscr/metadataAccs/notes/table/titl codeBook/stdyDscr/method/notes/table/titl codeBook/stdyDscr/dataAccs/setAvail/notes/table/titl codeBook/stdyDscr/method/dataColl/sources/sourceCitation/notes/table/titl 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codeBook/dataDscr/nCubeGrp/universe/txt/table/titl codeBook/dataDscr/var/universe/txt/table/titl codeBook/dataDscr/varGrp/universe/txt/table/titl codeBook/dataDscr/var/txt/table/titl codeBook/dataDscr/varGrp/txt/table/titl codeBook/otherMat/citation/notes/table/titl codeBook/otherMat/notes/table/titl codeBook/otherMat/citation/verStmt/notes/table/titl codeBook/otherMat/table/titl codeBook/otherMat/txt/table/titl codeBook/otherMat/citation/titlStmt/titl > > > > > cleanEx() > nameEx("vendorMetadata") > ### * vendorMetadata > > flush(stderr()); flush(stdout()) > > ### Name: vendorMetadata > ### Title: Read and edit vendor-specific metadata > ### Aliases: vendorMetadata vendorMetadata<- > > ### ** Examples > > x <- c(1, 2) > vendorMetadata(x, "SAS", "format") <- "BEST12." > vendorMetadata(x, "SAS", "informat") <- "BEST32." > vendorMetadata(x, "SAS", "format") [1] "BEST12." > vendorMetadata(x, "SAS", "format") <- NULL > > > > ### *