I am trying to calculate the absolute difference between lagged values over several columns. The first row of the resulting data set is NA, which is correct because there is no previous value to calculate the lag. What I don't understand is why the lag isn't calculated for the last value. Note that the last value in the example below (temp) is the lag between the 2nd to last and the 3rd to last values, the lag value between the last and 2nd to last value is missing.
library(tidyverse)
library(purrr)
dim(mtcars) # 32 rows
temp <- map_df(mtcars, ~ abs(diff(lag(.x))))
names(temp) <- paste(names(temp), '.abs.diff.lag', sep= '')
dim(temp) # 31 rows
It would be an awesome bonus if someone could show me how to pipe the renaming step, I played around with paste and enquo. The real dataset is too long to do a gather/newcolumnname/spread approach.
Thanks in advance!
EDIT: libraries need to run the script added
I think the lag call in your existing code is unnecessary as diff calculates the lagged difference automatically (although perhaps I don't understand properly what you are trying to do). You can also use rename_all to add a suffix to all the variable names.
library(purrr)
library(dplyr)
mtcars %>%
map_df(~ abs(diff(.x))) %>%
rename_all(funs(paste0(., ".abs.diff.lag")))
#> # A tibble: 31 x 11
#> mpg.abs.diff.lag cyl.abs.diff.lag disp.abs.diff.lag hp.abs.diff.lag
#> <dbl> <dbl> <dbl> <dbl>
#> 1 0.0 0 0.0 0
#> 2 1.8 2 52.0 17
#> 3 1.4 2 150.0 17
#> 4 2.7 2 102.0 65
#> 5 0.6 2 135.0 70
#> 6 3.8 2 135.0 140
#> 7 10.1 4 213.3 183
#> 8 1.6 0 5.9 33
#> 9 3.6 2 26.8 28
#> 10 1.4 0 0.0 0
#> # ... with 21 more rows, and 7 more variables: drat.abs.diff.lag <dbl>,
#> # wt.abs.diff.lag <dbl>, qsec.abs.diff.lag <dbl>, vs.abs.diff.lag <dbl>,
#> # am.abs.diff.lag <dbl>, gear.abs.diff.lag <dbl>,
#> # carb.abs.diff.lag <dbl>