remove the first row for each group

Question

suppose I have a dataset like this

df <- data.frame(group = c(rep(1,3),rep(2,2), rep(3,2),rep(4,3),rep(5, 2)), score = c(30, 10, 22, 44, 6, 5, 20, 35, 2,         


        

Answer 1

An option with dplyr is to select rows ignoring 1st row

library(dplyr)
df %>%
  group_by(group) %>%
  slice(2:n())

#  group score
#  <dbl> <dbl>
#1  1.00 10.0 
#2  1.00 22.0 
#3  2.00  6.00
#4  3.00 20.0 
#5  4.00  2.00
#6  4.00 60.0 
#7  5.00  5.00

---

Another way is shown by @Rich Scriven in now deleted answer

df %>%
  group_by(group) %>%
  slice(-1)

Answer 2

Quite simple with duplicated

df[duplicated(df$group),]

   group score
2      1    10
3      1    22
5      2     6
7      3    20
9      4     2
10     4    60
12     5     5

Answer 3

dplyr::filter(df, group == lag(group))
   group score
1     1    10
2     1    22
3     2     6
4     3    20
5     4     2
6     4    60
7     5     5

See lead and lag of package dplyr for more information:

https://dplyr.tidyverse.org/reference/lead-lag.html

Answer 4

Another base R option would be to check the adjacent elements

df[c(FALSE,df$group[-1]==df$group[-nrow(df)]),]
#   group score
#2      1    10
#3      1    22
#5      2     6
#7      3    20
#9      4     2
#10     4    60
#12     5     5

Here I removed the first observation in 'group' (df$group[-1]) and compared (==) with the vector in which last observation is removed (df$group[-nrow(df)])). As the length of the comparison is one less than the nrow of the dataset, we pad with FALSE at the top and use this as logical index to subset the dataset.