如何在新列中基于条件语句添加文本

Question

In RStudio, I want to add two new columns to a dataframe. These two columns should be filled with text based on conditional statements from an already existing column in the dataframe.

Data.frame

Variable is: number c(1,2,3,4, etc.)

I need a code (statement) creating and filling out the two new columns "type_a" and "type_b" based on the number in the "number" column. I have to use the exact number, so "if 1 in "number" fill out "type_a" with "some_text1" and fill out "type_b" with "some_text2". Next line will be "if 2 or 3 in "number" fill out "type_a" with "some_text3" and "type_b" with "some_text4".

This should be fairly simple, however, I am new to R and currently following courses.

Thanks,

EDIT:

Thanks to the answers below, I have now managed to do what I want with this code. The question now is, can I somehow include the "type_b" statement in the first "case_when" so I dont have to write the list of numbers twice, or is it only possible to include one column per "case_when"? (in SAS I would create the two columns type_a and type_b first and then write "if number in (1,2,4,6) then do; type_a='some_text'; type_b ='some_text2; end;).

Thanks

ds <- tibble(number = 1:6)

ds %>% 
  mutate(
    type_a = case_when(
      number %in% c(1,2,4,6) ~ "some_text", TRUE ~ NA_character_
    ),
    type_b = case_when(
      number %in% c(1,2,4,6) ~ "some_text2", TRUE ~NA_character_
      )
    )

#The code below do not work, but hopefully you get the idea!

library(tidyverse)
ds <- tibble(number = 1:6)

 ds %>% 
  mutate(
    type_a, type_b = case_when(
      number %in% c(1,2,4,6) ~ "some_text", ~ "some_text2", 
TRUE ~ NA_character_))

Answer 1

You can create a data frame with your keys to replace and use the merge function :

n <- 4
df <- data.frame(number = sample(1:n, 10, replace = TRUE))
df
>   number
1       2
2       2
3       1
4       4
5       4
6       1
7       4
8       3
9       1
10      3


df_text <- data.frame(number = 1:n, text_a = paste0("text", 1:n), text_b = paste0("text", 1:n+n))
df_text
>  number text_a text_b
1      1  text1  text5
2      2  text2  text6
3      3  text3  text7
4      4  text4  text8

merge(df, df_text)
>   number text_a text_b
1       1  text1  text5
2       1  text1  text5
3       1  text1  text5
4       2  text2  text6
5       2  text2  text6
6       3  text3  text7
7       3  text3  text7
8       4  text4  text8
9       4  text4  text8
10      4  text4  text8

You can use sort = FALSE in merge if order matters

Answer 2

If you are just starting out with R, I would recommend looking into "R for data science" ( https://r4ds.had.co.nz/ ) by Hadley Wickham. Great resource.

Here's a solution to what I think you are trying to do:

library(tidyverse)
ds <- tibble(number = 1:5)

ds %>% 
mutate(
  type_a = case_when(
    number == 1 ~ "some_text1",
    number == 2 | number == 3 ~ "some_text3",
    TRUE ~ NA_character_
  ), 
  type_b = case_when(
    number == 1 ~ "some_text2",
    number == 2 | number == 3 ~ "some_text4",
    TRUE ~ NA_character_
  )
)