Creating a new data frame based on the range of numeric values of a specific column in R

Question

I am working with a dataset that looks like this...

group  col_2  col_3   col_4
A       TT     12      21
A       RR     11      21
A       LL     13      22
A       QQ     11      24
A       PP     14      25
A       RR     15      26
A       TT     17      28
A       LL     16      29
B       DD     12      23
B       QQ     14      23
B       PP     13      25 
B       HH     11      25
B       LL     15      26
B       DD     17      28
B       QQ     14      29
B       HH     13      30
C       MM     18      21
C       JJ     15      22
C       LL     17      23
C       NN     14      24
C       EE     19      25
C       KK     15      28
C       NN     17      28
C       UU     10      29 
D       II     14      21
D       OO     15      23
D       PP     16      24 
D       LL     17      25 
D       MM     18      26
D       AA     10      28
D       HH     12      29
D       JJ     13      30 

So, I need to create a new data frame grouping by the group column and using the values of col_4.

As you can see range of values in col_4 goes from 21-30. I need to select three values for each group. One value is supposed to be on the range from 21-22, the second value is supposed to be on the range from 25-26 and the third values needs to be a value on the range from 29-30. If there are two possibilities I need to randomly select one values and if there are no possibilities I need the output to be NA. For example, you can see that group A has three possible outputs for the first range with values in col_4 of 21, 21, 22. Then I need to select just one, randomly. You can also see that group B doe not has any values in column_4 between 21-22, so I need the output to be NA.

The second important issue is that I need to have only three rows per group. So I want my data (the output) to look like this.

group  col_2  col_3   col_4  range_2122 group col_2 col_3 col_4 range_2526 group col_2 col_3 col_4 range2930
A       TT     12      21     21          A     RR    15    26    26         A    LL   16      29      29
B       NA     NA      NA     NA          B     HH    11    25    25         B    HH   13      30      30
C etc.
D etc.

A second option is to get an output like this...

group  col_2  col_3   col_4  range
 A       TT     12      21     21
 A       RR     15      26     26
 A       LL     16      29     29
 B       NA     NA      NA     NA
 B       HH     11      25     25
 B       HH     13      30     30
 C  etc..

Answer 1

The below comes fairly close to what you want using dplyr and tidyr . As has been mentioned, the example output you gave has non-unique names which are not a good idea.

Hopefully you can use this as a starting point.

library(dplyr)

df %>%
  dplyr::mutate(grouping_col = case_when(
    col_4 %in% 21:22 ~ "range_2122",
    col_4 %in% 25:26 ~ "range_2526",
    col_4 %in% 29:30 ~ "range_2930",
    TRUE ~ NA_character_
  )) %>%
  # Get all combinations of group and range (ensures NAs where missing)
  right_join(tidyr::expand(., group, grouping_col), by = c("grouping_col", "group")) %>%
  filter(!is.na(grouping_col)) %>%
  # Group back and randomly select a row
  group_by(group, grouping_col) %>%
  slice_sample(n = 1)

Answer 2

Here's a dplyr suggestion:

library(dplyr)
# library(purrr) # map_dfc
set.seed(42)
dat %>%
  group_by(group) %>%
  summarize(purrr::map_dfc(L, function(z) {
    out <- filter(cur_data(), between(col_4, z[1], z[2])) %>%
      slice(sample(n(), 1))
    if (!nrow(out)) out <- out[NA,]
    out[[ paste0("range_", paste(z, collapse = "")) ]] <- out$col_4
    out
  })) %>%
  ungroup()
# New names:
# * col_2 -> col_2...1
# * col_3 -> col_3...2
# * col_4 -> col_4...3
# * col_2 -> col_2...5
# * col_3 -> col_3...6
# * ...
# New names:
# * col_2 -> col_2...1
# * col_3 -> col_3...2
# * col_4 -> col_4...3
# * col_2 -> col_2...5
# * col_3 -> col_3...6
# * ...
# New names:
# * col_2 -> col_2...1
# * col_3 -> col_3...2
# * col_4 -> col_4...3
# * col_2 -> col_2...5
# * col_3 -> col_3...6
# * ...
# New names:
# * col_2 -> col_2...1
# * col_3 -> col_3...2
# * col_4 -> col_4...3
# * col_2 -> col_2...5
# * col_3 -> col_3...6
# * ...
# # A tibble: 3 x 13
#   group col_2...1 col_3...2 col_4...3 range_2122 col_2...5 col_3...6 col_4...7 range_2526 col_2...9 col_3...10 col_4...11 range_2930
#   <chr> <chr>         <int>     <int>      <int> <chr>         <int>     <int>      <int> <chr>          <int>      <int>      <int>
# 1 A     TT               12        21         21 PP               14        25         25 LL                16         29         29
# 2 C     JJ               15        22         22 EE               19        25         25 UU                10         29         29
# 3 D     II               14        21         21 LL               17        25         25 JJ                13         30         30