Value Matching for Data Frames
match-like classification for data.frames; returns a
vector of row numbers of (first) matches of its first argument in its
second, across shared column names. This is unlikely to be useful to
casual TRAMP users, but see the final example for a relevant
usage.
classify(x, table, ...)
x |
data.frame: containing columns with the values to be matched. |
table |
data.frame: where all columns contain the values to be matched against. |
... |
Additional arguments to |
As with duplicated.data.frame, this works by pasting
together a character representation of the rows separated by
\r (a carriage return), so may be imperfect if the data.frame
has characters with embedded carriage returns or columns which do not
reliably map to characters.
Cases in x with NA values in any column shared with
table will not be matched (and will return the value of
nomatch). Cases in table with any NA values in
any row will match nothing.
All columns in table must be present in x, but x
may have additional columns that will be ignored.
A vector of length nrow(x), with each element giving the row
number in table where all elements match across shared
columns.
match, on which this is based.
table <- data.frame(a=letters[1:3], b=rep(1:2, each=3))
x <- cbind(table[sample(nrow(table), 20, TRUE),], x=runif(20))
classify(x, table)
all.equal(table[classify(x, table),], x[names(table)])
## Select only a few cases from a TRAMPsamples data object,
## corresponding with 4 enzyme/primer combinations.
data(demo.samples)
d <- demo.samples$data
use <- expand.grid(primer=c("ITS1F", "ITS4"),
enzyme=c("HpyCH4IV", "BsuRI"))
classify(d, use)
d[!is.na(classify(d, use)),]Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.