Fill new column with different numbers depending on how often values appear in other column, R-CodePudding

I have a dataframe with different company IDs appearing from once to over 30 times in different rows. I want to add a new column "di_Flex" and fill it with specific values depending on how often the same company ID appears in a column:

If it appears twice in the column, add the value 6 to the new column "di_Flex", if it appears 3x, add "8", if it appears 4x add "10", if it appears 5x add "12.8", if it appears 6x add "14.67", if it appears 7 or more times add "16".

Here is the dataframe:

c(0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 
6, 6, 6, 6, 7, 7, 8, 9, 9, 9, 10, 10, 11, 11, 12, 12, 13, 14, 
15, 16, 17, 17, 18, 18, 19, 20, 21, 22, 23, 23, 23, 24, 24, 24, 
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 25, 25, 
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 
25, 25, 26, 26, 26, 26, 26, 26, 26, 26, 26, 27, 27, 27, 27, 27, 
28, 29, 30, 31, 31, 32, 32, 32, 33, 33, 33, 34, 34, 34, 35, 36, 
36, 37, 38, 38, 38, 38, 38, 38, 39, 40, 41, 41, 41, 42, 42, 42, 
43, 43, 43, 44, 45, 45, 46, 46, 46, 47, 48, 49, 50, 50, 51, 53, 
54, 54, 54, 54, 55, 57, 57, 57, 59, 59, 59, 59, 60, 60, 60, 60, 
61, 61, 62, 62, 62, 63, 63, 64, 64, 64, 64, 65, 65, 66, 66, 66, 
66, 66, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA)

Thank you for your help!

CodePudding user response：

Assuming your data is called df with a column value:

library(tidyverse)

left_join(df, df %>% 
  group_by(value) %>% 
  tally()) %>% 
  mutate(di_Flex = case_when(n == 2 ~  6,
                             n == 3 ~  8,
                             n == 4 ~  10,
                             n == 5 ~  12.8,
                             n == 6 ~  14.67,
                             n >= 7 ~  16)) %>% 
  select(-n)

This gives us:

1      0    12.8
2      0    12.8
3      0    12.8
4      0    12.8
5      0    12.8
6      1      NA
7      2      NA
8      3      NA
9      4      NA
10     5     8.0
11     5     8.0
12     5     8.0
13     6    16.0
14     6    16.0
15     6    16.0
16     6    16.0
17     6    16.0
18     6    16.0
19     6    16.0
20     6    16.0

Data:

df <- data.frame(value = c(0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 
        6, 6, 6, 6, 7, 7, 8, 9, 9, 9, 10, 10, 11, 11, 12, 12, 13, 14, 
        15, 16, 17, 17, 18, 18, 19, 20, 21, 22, 23, 23, 23, 24, 24, 24, 
        24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 
        24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 25, 25, 
        25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 
        25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 
        25, 25, 26, 26, 26, 26, 26, 26, 26, 26, 26, 27, 27, 27, 27, 27, 
        28, 29, 30, 31, 31, 32, 32, 32, 33, 33, 33, 34, 34, 34, 35, 36, 
        36, 37, 38, 38, 38, 38, 38, 38, 39, 40, 41, 41, 41, 42, 42, 42, 
        43, 43, 43, 44, 45, 45, 46, 46, 46, 47, 48, 49, 50, 50, 51, 53, 
        54, 54, 54, 54, 55, 57, 57, 57, 59, 59, 59, 59, 60, 60, 60, 60, 
        61, 61, 62, 62, 62, 63, 63, 64, 64, 64, 64, 65, 65, 66, 66, 66, 
        66, 66, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
        NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
        NA, NA, NA, NA, NA))