Consider a data frame with results of multi-objective stochastic optimizers on a set of problems from different categories/groups (say indicated by column group ). Occasionally, it is useful to unite the results of several groups into a meta-group. The function addUnionGroup aids in generation of such a meta-group while function addAllGroup is a wrapper around the former which generates a union of all groups.
addUnionGroup(df, col, group, values)addAllGroup(df, col, group ="all")
Arguments
df: [data.frame]
Data frame.
col: [character(1)]
Column name of group-column.
group: [character(1)]
Name for new group.
values: [character(1)]
Subset of values within the value range of column col.
Returns
[data.frame] Modified data frame.
Examples
df = data.frame( group = c("A1","A1","A2","A2","B"), perf = runif(5), stringsAsFactors =FALSE)df2 = addUnionGroup(df, col ="group", group ="A", values = c("A1","A2"))df3 = addAllGroup(df, col ="group", group ="ALL")