dplyr - How can I calculate the percentage change within a group for multiple columns in R? -

i have data frame id column, date column (12 months each id), , have 23 numeric variables. obtain percentage change month within each id. using quantmod package in order obtain percent change.

here example 3 columns (for simplicity):

id date v1 v2 v3 1  jan   2  3  5 1  feb   3  4  6 1  mar   7  8  9 2  jan   1  1  1 2  feb   2  3  4 2  mar   7  8   8 

i tried use dplyr , summarise_each function, unsuccessful. more specifically, tried following (train name of data set):

library(dplyr) library(quantmod)  group1<-group_by(train,examid)  foo<-function(x){   return(delt(x)) }  summarise_each(group1,funs(foo)) 

i tried use function in dplyr, not successful either (having bad night guess!).

i think issue delt function. when replace delt sum function:

foo<-function(x){       return(sum(x))     } summarise_each(group1,funs(foo)) 

the result every variable summed across date each id. how can percentage change month-over-month each id?

how using pct <- function(x) x/lag(x)? e.g.,

pct(1:3) [1]  na 2.0 1.5 

edit: adding frank's suggestion

pct <- function(x) {x/lag(x)}  dt %>% group_by(id) %>% mutate_each(funs(pct), c(v1, v2, v3))  id date       v1       v2  v3 1  jan       na       na  na 1  feb 1.500000 1.333333 1.2 1  mar 2.333333 2.000000 1.5 2  jan       na       na  na 2  feb 2.000000 3.000000 4.0 2  mar 3.500000 2.666667 2.0