Calculating growth rates in a loop (subsets) in R

Question

I am trying to compute the overall growth rate of each NUTS2 region (column NUTS_CODE) for the years 2000-2006 (REF_YEAR).

My dataset looks like this:

  NUTS_CODE NUTS_LEVEL SCENARIO_ID REF_YEAR IND_VALUE NUTS_C
  <chr>          <dbl>       <dbl>    <dbl>     <dbl> <chr> 
1 BE10               2           1     2000     49434 BE    
2 BE21               2           1     2000     29019 BE    
3 BE22               2           1     2000     20646 BE    
4 BE23               2           1     2000     21155 BE    
5 BE24               2           1     2000     24963 BE    
6 BE25               2           1     2000     22912 BE  

So I am trying to compute something like

(BE10(which(REF_YEAR == 2006 - BE10(which(REF_YEAR==2000))/BE10(which(REF_YEAR==2000)

(this is not my actual code - I just want to explain what I want to achieve) and this Needs to be done for each and every NUTS_CODE.

I have tried to achieve this by using both a for loop as well as the dplyr function, but somehow it does not work.

library(dplyr)

data$growth<-NA

for(i in 1:nrow(data))
{
  if((data%>%filter(NUTS_CODE == data$NUTS_CODE[i] &
                   SCENARIO_ID == data$SCENARIO_ID[i] &
                   REF_YEAR == (data$REF_YEAR[i]-1)
                   )%>%nrow()
      ) == 0
  )
  {
    data$growth[i]<-0
  } else {
    data$growth[i]<-(((data$IND_VALUE[i]-
                         (data%>%filter(NUTS_CODE == data$NUTS_CODE[i] &
                                          SCENARIO_ID == data$SCENARIO_ID[i] &
                                          REF_YEAR == (data$REF_YEAR[i]==2006) 
                         )
                         )[,"IND_VALUE"]
    )/
      (
        (data%>%filter(NUTS_CODE == data$NUTS_CODE[i] &
                         SCENARIO_ID == data$SCENARIO_ID[i] &
                         REF_YEAR == (data$REF_YEAR[i]==2000) 
        )
        )[,"IND_VALUE"]
      )
    )
    *100)
  }
  print(paste("",i,sep = " "))
}

I do not get an error or a warning, but in data$growth I get a full column of numeric(0) instead of actual values.

Help is appreciated!

Answer 1

library(dplyr)

data %>%
  group_by(NUTS_CODE) %>% 
  summarise(growth_rate = (IND_VALUE[REF_YEAR == 2006] -IND_VALUE[REF_YEAR == 2000]) / IND_VALUE[REF_YEAR == 2000] )