Given start date and end date, reshape/expand data for each day between (each day on a row) [duplicate]

Answer 1

Using data.table

library(data.table)
setDT(x)[, list(DATE=seq(START_DAY, END_DAY, by = 'day')), PER_COST]
#    PER_COST       DATE
# 1:  3451380 2013-02-26
# 2:  3451380 2013-02-27
# 3:  3451380 2013-02-28
# 4:  3451380 2013-03-01
# 5:  3451380 2013-03-02
#---                    
#116:  3575311 2013-06-21
#117:  3575311 2013-06-22
#118:  3575311 2013-06-23
#119:  3575311 2013-06-24
#120:  3575311 2013-06-25

If there are duplicate PER_COST, then it may be better to use 1:nrow(x) as the grouping variable

setDT(x)[, list(DATE=seq(START_DAY, END_DAY, by = 'day'), 
      PER_COST=rep(PER_COST, END_DAY-START_DAY+1)), 1:nrow(x)]

Update

Using dplyr

library(dplyr)
  x %>% 
    rowwise() %>% 
    do(data.frame(DATE=seq(.$START_DAY, .$END_DAY, by='day'),
       PER_COST= rep(.$PER_COST, .$END_DAY-.$START_DAY+1)))

Answer 2

You could do something like

do.call(rbind, apply(df, 1, function(x) 
  data.frame(DATE = seq.Date(from = as.Date(x[1]), to = as.Date(x[2]), by = "day"), 
             PER_COST = x[3], row.names = NULL))
)
# 1.1  2013-02-26  3451380
# 1.2  2013-02-27  3451380
# 1.3  2013-02-28  3451380
# 1.4  2013-03-01  3451380
# 1.5  2013-03-02  3451380
# 1.6  2013-03-03  3451380
# 1.7  2013-03-04  3451380