I am working with this dataset in R. I am hoping to create a new tow for each region and age, with student type being "Part time" and values being the values of "Any" - "Full time". It seems I can use lag in the process, but I was hoping to be more explicit, specifying it is "Any" - "Full time", as while this dataset is well organized there may be data sets where entries are reversed.

Ideally the result would look something like

Thank you!

CodePudding user response：

You may try

library(dplyr)
df %>%
  group_by(Region, Age) %>%
  summarize(Student.Type = "Part time",
            Values = abs(diff(Values))) %>%
  rbind(., df) %>%
  arrange(Region, Age, Student.Type)

   Region   Age Student.Type Values
   <chr>  <int> <chr>         <int>
 1 A         17 Any              32
 2 A         17 Full time        24
 3 A         17 Part time         8
 4 A         18 Any              27
 5 A         18 Full time        19
 6 A         18 Part time         8
 7 B         17 Any              22
 8 B         17 Full time        14
 9 B         17 Part time         8
10 B         18 Any              80
11 B         18 Full time        75
12 B         18 Part time         5

CodePudding user response：

With dplyr, you could use group_modify() add_row().

df %>%
  group_by(Region, Age) %>%
  group_modify(~ {
    .x %>%
      summarise(StudentType = "Part time", Values = -diff(Values)) %>%
      add_row(.x, .)
  }) %>%
  ungroup()

# # A tibble: 12 × 4
#    Region   Age StudentType    Values
#    <chr>  <int> <chr>           <int>
#  1 A         17 Any                32
#  2 A         17 Full time          24
#  3 A         17 Part time           8
#  4 A         18 Any                27
#  5 A         18 Full time          19
#  6 A         18 Part time           8
#  7 B         17 Any                22
#  8 B         17 Full time          14
#  9 B         17 Part time           8
# 10 B         18 Any                80
# 11 B         18 Full time          75
# 12 B         18 Part time           5