# R: Calculating Percentiles For Multiple Groups

I am working with the R programming language.

I have the following dataset:

``````set.seed(123)

library(dplyr)
var1 = rnorm(10000, 100,100)
var2 = rnorm(10000, 100,100)
var3 = rnorm(10000, 100,100)
var4 = rnorm(10000, 100,100)
id = 1:10000

final = data.frame(id, var1, var2, var3, var4)

final = final %>%
mutate(class1 = case_when(var1 < mean(var1) ~ "A",
TRUE ~ "B")) %>%
mutate(class2 = case_when(var2 < mean(var2) ~ "C",
TRUE ~ "D"))
``````

I want to calculate deciles for var3 and var4 based on every unique combination of class1 and class2.

As I understand, this means:

• For all rows WHERE class1 = A AND class2 = C, calculate/assign deciles for var3 and var4
• For all rows WHERE class1 = A AND class2 = D, calculate/assign deciles for var3 and var4
• For all rows WHERE class1 = B AND class2 = C, calculate/assign deciles for var3 and var4
• For all rows WHERE class1 = B AND class2 = D, calculate/assign deciles for var3 and var4

Here is the R code I wrote for this:

``````final = final %>%
group_by(class1, class2) %>%
mutate(class3 = case_when(ntile(var3, 10) == 1 ~ "one",
ntile(var3, 10) == 2 ~ "two",
ntile(var3, 10) == 3 ~ "three",
ntile(var3, 10) == 4 ~ "four",
ntile(var3, 10) == 5 ~ "five",
ntile(var3, 10) == 6 ~ "six",
ntile(var3, 10) == 7 ~ "seven",
ntile(var3, 10) == 8 ~ "eight",
ntile(var3, 10) == 9 ~ "nine",
ntile(var3, 10) == 10 ~ "ten")) %>%
mutate(class4 = case_when(ntile(var4, 10) == 1 ~ "one",
ntile(var4, 10) == 2 ~ "two",
ntile(var4, 10) == 3 ~ "three",
ntile(var4, 10) == 4 ~ "four",
ntile(var4, 10) == 5 ~ "five",
ntile(var4, 10) == 6 ~ "six",
ntile(var4, 10) == 7 ~ "seven",
ntile(var4, 10) == 8 ~ "eight",
ntile(var4, 10) == 9 ~ "nine",
ntile(var4, 10) == 10 ~ "ten"))
``````

Can someone please tell me if I have done this correctly?

Thanks!

### >Solution :

Instead of doing the `case_when` it can be done easily with `english`

``````library(dplyr)
library(stringr)
final %>%
group_by(class1, class2) %>%
mutate(across(var3:var4,
~ as.character(english::english(ntile(.x, 10))),
.names = "{str_replace(.col, 'var', 'class')}")) %>%
ungroup
``````

-output

``````# A tibble: 10,000 × 9
id  var1  var2    var3  var4 class1 class2 class3 class4
<int> <dbl> <dbl>   <dbl> <dbl> <chr>  <chr>  <chr>  <chr>
1     1  44.0 337.    16.4   80.6 A      D      three  five
2     2  77.0  83.3   77.9  126.  A      C      five   six
3     3 256.  193.  -110.    46.2 B      D      one    four
4     4 107.   43.2  -66.8  -17.9 B      C      one    two
5     5 113.  123.    -9.80 190.  B      D      two    nine
6     6 272.  213.   -66.6   98.4 B      D      one    six
7     7 146.  238.    95.0  118.  B      D      five   six
8     8 -26.5  76.7  256.   160.  A      C      ten    eight
9     9  31.3 -60.1   59.5  126.  A      C      four   six
10    10  55.4  70.2  179.   130.  A      C      eight  seven
# … with 9,990 more rows
# ℹ Use `print(n = ...)` to see more rows
``````