PGRdup (version 0.2.2.1)

ParseProbDup: Parse an object of class ProbDup to a data frame.

Description

ParseProbDup converts an object of class ProbDup to a data frame for export.

Usage

ParseProbDup(pdup, max.count = 30, insert.blanks = TRUE)

Arguments

pdup

An object of class ProbDup.

max.count

The maximum count of probable duplicate sets which are to be parsed to a data frame.

insert.blanks

logical. If TRUE, inserts a row of NAs after each set.

Value

A data frame of the long/narrow form of the probable duplicate sets data with the following core columns:

SET_NO

The set number.

TYPE

The type of probable duplicate set. 'F' for fuzzy, 'P' for phonetic and 'S' for semantic matching sets.

K

The KWIC index or database of origin of the record. The method is specified within the square brackets in the column name.

PRIM_ID

The primary ID of the accession record from which the set could be identified.

IDKW

The 'matching' keywords along with the IDs.

COUNT

The number of elements in a set.

For the retrieved columns(fields) the prefix K* indicates the KWIC index of origin.

See Also

ProbDup,

Examples

## Not run: 
# 
# #' # Load PGR passport database
# GN <- GN1000
# 
# # Specify as a vector the database fields to be used
# GNfields <- c("NationalID", "CollNo", "DonorID", "OtherID1", "OtherID2")
# 
# # Clean the data
# GN[GNfields] <- lapply(GN[GNfields], function(x) DataClean(x))
# y1 <- list(c("Gujarat", "Dwarf"), c("Castle", "Cary"), c("Small", "Japan"),
# c("Big", "Japan"), c("Mani", "Blanco"), c("Uganda", "Erect"),
# c("Mota", "Company"))
# y2 <- c("Dark", "Light", "Small", "Improved", "Punjab", "SAM")
# y3 <- c("Local", "Bold", "Cary", "Mutant", "Runner", "Giant", "No.",
#         "Bunch", "Peanut")
# GN[GNfields] <- lapply(GN[GNfields], function(x) MergeKW(x, y1, delim = c("space", "dash")))
# GN[GNfields] <- lapply(GN[GNfields], function(x) MergePrefix(x, y2, delim = c("space", "dash")))
# GN[GNfields] <- lapply(GN[GNfields], function(x) MergeSuffix(x, y3, delim = c("space", "dash")))
# 
# # Generate KWIC index
# GNKWIC <- KWIC(GN, GNfields)
# 
# # Specify the exceptions as a vector
# exep <- c("A", "B", "BIG", "BOLD", "BUNCH", "C", "COMPANY", "CULTURE", 
#          "DARK", "E", "EARLY", "EC", "ERECT", "EXOTIC", "FLESH", "GROUNDNUT", 
#          "GUTHUKAI", "IMPROVED", "K", "KUTHUKADAL", "KUTHUKAI", "LARGE", 
#          "LIGHT", "LOCAL", "OF", "OVERO", "P", "PEANUT", "PURPLE", "R", 
#          "RED", "RUNNER", "S1", "SAM", "SMALL", "SPANISH", "TAN", "TYPE", 
#          "U", "VALENCIA", "VIRGINIA", "WHITE")
#           
# # Specify the synsets as a list
# syn <- list(c("CHANDRA", "AH114"), c("TG1", "VIKRAM"))
# 
# # Fetch probable duplicate sets
# GNdup <- ProbDup(kwic1 = GNKWIC, method = "a", excep = exep, fuzzy = TRUE,
#                  phonetic = TRUE, encoding = "primary", 
#                  semantic = TRUE, syn = syn)
#                  
# # Convert to data frame of sets               
# GNdupParsed <- ParseProbDup(GNdup)
# 
# ## End(Not run)