在 R 中使用 mutate_at() 创建一个新列

Question

i'm trying to do some modifications to the next data frame:

df <- data.frame(
    zgen = c("100003446", "100001749","100002644","100001755"),
    Name_mat = c("EVEROLIMUS 10 MG CM", "GALSULFASA 5MG/5ML FAM", "IDURSULFASE 2MG/ML SOL. P/INFUSION FAM","IMIGLUCERASA 400U POL. LIOF. FAM"),
    details= c("CM", "FAM", "SOL. P/INFUSION FAM","NA")
)

And i'm using mutate_at( ) from dplyr package to create a new column calling "type". That column can change depending of a list of characters that can appear in the columns of my data frame ("name_mat" and "details"). The code is:

df <- df %>% mutate_at(vars(one_of("Name_mat ","details")),
                       funs(case_when( "FAM|FRA" == TRUE ~ "FA",
                                       "CM|COMPRIMIDO" == TRUE~ "COM",
                                       "SOL"== TRUE~"SOL",
                                       "CP|CAPSULA"== TRUE~"CAP",
                                       TRUE ~ "bad_mat")))

My first time using mutate_at and i don't know how to create a new column calling "type" in my data frame "df". Finally i need something like:

       ZGEN                                 Name_mat               details   Type
1 100003446                      EVEROLIMUS 10 MG CM                    CM    COM
2 100001749                   GALSULFASA 5MG/5ML FAM                   FAM     FA
3 100002644   IDURSULFASE 2MG/ML SOL. P/INFUSION FAM   SOL. P/INFUSION FAM     FA
4 100001755         IMIGLUCERASA 400U POL. LIOF. FAM                    NA     FA

I appreciate any help or any other point of view about how to do this.

Thanks!

Answer 1

try to do it this way

  library(tidyverse)
  library(stringr)

  df %>% mutate(TYPE = case_when(
  str_detect(Name_mat, pattern = "FAM") | str_detect(details, "FRA") ~ "FA",
  str_detect(Name_mat, pattern = "CM") | str_detect(details, "COMPRIMODO") ~ "CM",
  str_detect(Name_mat, pattern = "SOL") ~ "SOL",
  str_detect(Name_mat, pattern = "CP") | str_detect(details, "CAPSULA") ~ "CAP",
  TRUE ~ "bad_mat"))

Answer 2

We can also use

library(dplyr)
library(purrr)
library(stringr)
pat <- "\\b(FAM|FRA|CM|COMPRIMIDO|SOL|CP|CAPSULA)\\b"

nm1 <- setNames(c("FA", "FA", "COM", "COM", "SOL", "CAP", "CAP"),
       c("FAM", "FRA", "CM", "COMPRIMIDO", "SOL", "CP", "CAPSULA"))
df %>% 
     select(Name_mat, details) %>%
     map(str_extract_all, pattern = pat) %>% 
           transpose %>% 
     map_chr( ~ nm1[flatten_chr(.x)][1] ) %>%
     bind_cols(df, Type = .)