join {analogue} | R Documentation |
Merges any number of species matrices on their common columns to create a new data set with number of columns equal to the number of unqiue columns across all data frames. Needed for analysis of fossil data sets with respect to training set samples.
join(..., verbose = FALSE, na.replace = TRUE, split = TRUE)
... |
data frames containing the data sets to be merged |
verbose |
logical; if TRUE , the function prints out the
dimensions of the data frames in "..." , as well as those of
the returned, merged data frame. |
na.replace |
logical; samples where a column in one data frame
that have no matching column in the other will contain missing
values (NA ). If na.replace is TRUE , these
missing values are replaced with zeros. This is standard practice in
ecology and palaeoecology. If you want to replace with another
value, then set na.replace to FALSE and do the
replacement later. |
split |
logical; should the merged data sets samples be split back into individual data frames, but now with common columns (i.e. species)? |
If split = TRUE
, a list of data frames, with as many components
as the number of data frames originally merged.
Otherwise, a data frame containing the merged data sets.
Gavin L. Simpson
## load the example data data(swapdiat) data(swappH) data(rlgh) ## merge training and test set on columns dat <- join(swapdiat, rlgh, verbose = TRUE) ## extract the merged data sets and convert to proportions swapdiat <- dat[[1]] / 100 rlgh <- dat[[2]] / 100