group.columns: Merge pairs of grouping columns

In ctkremer/priceTools: Tools for analyzing biodiversity-ecosystem function relationships

Description

Take a pair of columns, distinguished with suffix .x and .y, and merge them into a single column without suffixes. This is helpful for post-processing the output of pairwise price calculations.

Usage

group.columns(x, gps, drop = F)

Arguments

x	A data frame
gps	A list of grouping column(s)
drop	Drop original, unpaired columns after grouping? TRUE/FALSE

Value

This function returns a data frame

Examples

# Data frame containing multiple communities we want to compare
set.seed(36)
cms1<-data.frame(comm.id=sort(rep(seq(1,3),6)),
                species=rep(LETTERS[seq(1,6)],3),
                func=rpois(6*3,lambda = 2))
cms2<-data.frame(comm.id=sort(rep(seq(1,3),6)),
                species=rep(LETTERS[seq(1,6)],3),
                func=rpois(6*3,lambda = 2))
cms1$site<-'site1'
cms2$site<-'site2'
cms<-rbind(cms1,cms2)
                                
#Identify one grouping columns
cmsA<-group_by(cms,comm.id)

# Perform pairwise comparisons of all communities in cms identified by comm.id
ppA<-pairwise.price(cmsA,species='species',func='func')

# Process results using group.columns
group.columns(ppA,gps='comm.id')
group.columns(ppA,gps='comm.id',drop=T)

# Or with two grouping columns:
cmsB<-group_by(cms,comm.id,site)
ppB<-pairwise.price(cmsB,species='species',func='func')

# Process results using group.columns
group.columns(ppB,gps=c('comm.id'))
group.columns(ppB,gps=c('comm.id','site'))
group.columns(ppB,gps=c('comm.id','site'),drop=T)

ctkremer/priceTools documentation built on May 28, 2019, 7:49 p.m.