percentage change for all columns in a row except one

Question

ciao guys,

i have the following dataframe

  obj <- data.frame (degree2 = c(1, 1, 2, 2, 3, 3, 4, 4),
      yr = c(1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997),
      degree = c(1, 1, 1, 2, 1, 1, 0, 0), degree3 = c(1, 1, 6, 7, 5, 1, 0, 0)
   )

what I would like to do is to create the percentage change for the variables degree degree2 degree3 per year. Note that my real dataframe is quite long.

I guess the code must by something like in the sense of: "for every row compute percentual change for all variables except yr

many thanks in advance!

Answer 1

Update with correct function to calculate the percentage change:

Thanks to ThoamslsCoding:

The function to calculate: Divide x by the lag of x substract 1 and then multiple by 100

pct_change <- function(x) {(x/lag(x) -1) * 100}

obj %>% 
  mutate(across(c(degree2, degree, degree3), pct_change, .names = "pct_change_{.col}"))

Output:

  degree2   yr degree degree3 pct_change_degree2 pct_change_degree pct_change_degree3
1       1 1990      1       1                 NA                NA                 NA
2       1 1991      1       1                0.0                 0                0.0
3       2 1992      1       6              100.0                 0              500.0
4       2 1993      2       7                0.0               100               16.7
5       3 1994      1       5               50.0               -50              -28.6
6       3 1995      1       1                0.0                 0              -80.0
7       4 1996      0       0               33.3              -100             -100.0
8       4 1997      0       0                0.0               NaN                NaN

First answer: not correct:

# function to calculate percentage change
pct_change <- function(x) {x/lag(x)}

obj %>% 
  mutate(across(c("degree2", "degree", "degree3"), pct_change)) 

output:

   degree2   yr degree degree3 degree2_perc_change degree_perc_change degree3_perc_change
1      NA 1990     NA      NA                 0.0                  0                 0.0
2    1.00 1991    1.0   1.000                 0.0                  0                 0.0
3    2.00 1992    1.0   6.000                50.0                  0                83.3
4    1.00 1993    2.0   1.167                 0.0                 50                14.3
5    1.50 1994    0.5   0.714                33.3               -100               -40.0
6    1.00 1995    1.0   0.200                 0.0                  0              -400.0
7    1.33 1996    0.0   0.000                25.0               -Inf                -Inf
8    1.00 1997    NaN     NaN                 0.0                NaN                 NaN