Partitions from by values in grouping column, and returns list. Only advised for a moderate number of groups and better if grouping column is an index. This plus lapply and replyr::bind_rows is powerful enough to implement "The Split-Apply-Combine Strategy for Data Analysis" https://www.jstatsoft.org/article/view/v040i01

replyr_split(df, gcolumn, ..., ocolumn = NULL, decreasing = FALSE,
partitionMethod = "extract", maxgroups = 100, eagerCompute = FALSE)

## Arguments

df remote dplyr data item grouping column force later values to be bound by name ordering column (optional) if TRUE sort in decreasing order by ocolumn method to partition the data, one of 'split' (only works over local data frames), or 'extract' maximum number of groups to work over if TRUE call compute on split results

## Value

list of data items

## Examples


d <- data.frame(group=c(1,1,2,2,2),
order=c(.1,.2,.3,.4,.5),
values=c(10,20,2,4,8))