I have a data frame containing the values of weight. I have a create a new column, percentage change of weight wherein the denominator takes the value of every third row.
df <- data.frame(weight = c(30,30,109,30,309,10,20,20,14))
# expected output
change_of_weight = c(30/109, 30/109, 109/109, 30/10,309/10,10/10,20/14,20/14,14/14)
Subset weight column where it's position %% 3 is zero and repeat each value three times.
df <- transform(df, change_of_weight=weight / rep(weight[1:nrow(df) %% 3 == 0], each=3))
df
weight change_of_weight
1 30 0.2752294
2 30 0.2752294
3 109 1.0000000
4 30 3.0000000
5 309 30.9000000
6 10 1.0000000
7 20 1.4285714
8 20 1.4285714
9 14 1.0000000
You can create a group of every 3 rows and divide weight column by the last value in the group.
df$change <- with(df, ave(df$weight, ceiling(seq_len(nrow(df))/3),
FUN = function(x) x/x[length(x)]))
Or using dplyr :
library(dplyr)
df %>%
group_by(grp = ceiling(row_number()/3)) %>%
mutate(change = weight/last(weight))
# weight grp change
# <dbl> <dbl> <dbl>
#1 30 1 0.275
#2 30 1 0.275
#3 109 1 1
#4 30 2 3
#5 309 2 30.9
#6 10 2 1
#7 20 3 1.43
#8 20 3 1.43
#9 14 3 1
We can also use gl to create a grouping column
library(dplyr)
df %>%
group_by(grp = as.integer(gl(n(), 3, n()))) %>%
mutate(change = weight/last(weight))
# A tibble: 9 x 3
# Groups: grp [3]
# weight grp change
# <dbl> <int> <dbl>
#1 30 1 0.275
#2 30 1 0.275
#3 109 1 1
#4 30 2 3
#5 309 2 30.9
#6 10 2 1
#7 20 3 1.43
#8 20 3 1.43
#9 14 3 1
Or using data.table
library(data.table)
setDT(df)[, change := weight/last(weight), .(as.integer(gl(nrow(df), 3, nrow(df))))]