从多个列R创建名义变量

Question

My intention involves creating a variable based on the values of two numeric ones. I have not written any user-defined functions in R and need help getting started.

Dataset:

My dataset has over 3k stores, but created a reproducible example of the first 10 rows. Deliveries per day of week show total volume for that day through the year. Store_num represents store number and Total shows the total deliveries for a store throughout year.

I want predominant delivery days created in a variable called Del_Sch with the following inequalities. If first condition TRUE (50-100%), then create the variable with the column name. If FALSE, test second condition and create variable with all column names between 32-50%, ect. If there are no days over 20%, no predominant delivery days are counted.

-Volume in a day between 50-100% of the total.

-Volume in a day between 32-50% of total

-Volume in a day between 25-32% of total.

-Volume in a day between 20-25% of total.

-Volume in a day less than 20% of total.

Reproducible Example:

Store_Num <- c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
#Total deliveries made per week
Sun_Del <- c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA)
Mon_Del <- c(10, 50, 51, 7, 80, 97, 21, 49, 30, 3)
Tue_Del <- c(7, NA, 2, 50, 5, 56, 1, 4, 35, 52)
Wed_Del <- c(49, 51, 1, 4, 51, 16, 2, 2, 1, 1)
Thu_Del <- c(3, 2, 47, 7, 40, 2, 6, 5, 1, 7)
Fri_Del <- c(50, 49, 3, 51, 53, 86, 9, 52, 25, 52)
Sat_Del <- c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA)
Total <- c(119, 152, 104, 119, 229, 257, 39, 112, 92, 115)
#Single dataset
Schedule <- data.frame(Store_Num, Sun_Del, Mon_Del, Tue_Del,
                       Wed_Del, Thu_Del, Fri_Del, Sat_Del, Total)

Schedule
   Store_Num Sun_Del Mon_Del Tue_Del Wed_Del Thu_Del Fri_Del Sat_Del Total
1          1      NA      10       7      49       3      50      NA   119
2          2      NA      50      NA      51       2      49      NA   152
3          3      NA      51       2       1      47       3      NA   104
4          4      NA       7      50       4       7      51      NA   119
5          5      NA      80       5      51      40      53      NA   229
6          6      NA      97      56      16       2      86      NA   257
7          7      NA      21       1       2       6       9      NA    39
8          8      NA      49       4       2       5      52      NA   112
9          9      NA      30      35       1       1      25      NA    92
10        10      NA       3      52       1       7      52      NA   115

Desired Output:

   Store_Num Sun_Del Mon_Del Tue_Del Wed_Del Thu_Del Fri_Del Sat_Del Total Del_Sch
1          1      NA      10       7      49       3      50      NA   119     WF
2          2      NA      50      NA      51       2      49      NA   152     MWF
3          3      NA      51       2       1      47       3      NA   104     MTh
4          4      NA       7      50       4       7      51      NA   119     TF
5          5      NA      80       5      51      40      53      NA   229     MWF
6          6      NA      97      56      16       2      86      NA   257     MTF
7          7      NA      21       1       2       6       9      NA    39     M
8          8      NA      49       4       2       5      52      NA   112     MF
9          9      NA      30      35       1       1      25      NA    92     MTF
10        10      NA       3      52       1       7      52      NA   115     TF

Answer 1

Using tidyr and dplyr . I made the names be the first two letter pasted to fix the Tuesday/Thursday confusion:

library(dplyr)
library(tidyr)
Schedule %>% gather(Day, del, -Store_Num, -Total) %>%
             mutate(proportion = ifelse(del/Total >= 0.5, 1,
                                 ifelse(del/Total >= 0.32, 2,
                                 ifelse(del/Total >= 0.25, 3,
                                 ifelse(del/Total >= 0.20, 4,
                                 NA))))) %>%
             group_by(Store_Num) %>%
             summarise(days = paste0(substr(Day[which(
                                         proportion == min(proportion, na.rm = TRUE))],
                                           1, 2), collapse = "")) %>%
             merge(Schedule, ., by = "Store_Num")

   Store_Num Sun_Del Mon_Del Tue_Del Wed_Del Thu_Del Fri_Del Sat_Del Total   days
1          1      NA      10       7      49       3      50      NA   119   WeFr
2          2      NA      50      NA      51       2      49      NA   152 MoWeFr
3          3      NA      51       2       1      47       3      NA   104   MoTh
4          4      NA       7      50       4       7      51      NA   119   TuFr
5          5      NA      80       5      51      40      53      NA   229     Mo
6          6      NA      97      56      16       2      86      NA   257   MoFr
7          7      NA      21       1       2       6       9      NA    39     Mo
8          8      NA      49       4       2       5      52      NA   112   MoFr
9          9      NA      30      35       1       1      25      NA    92   MoTu
10        10      NA       3      52       1       7      52      NA   115   TuFr

Edit: there are a couple of mismatches between my results and your data (line 5,6 and 9), according to your rules, you have mistakes there.