'how to duplicate rows with certain condition and create anew variable at the same time

I have a df like below and I would like to transfer it to sth like the table on the right, how can I duplicate the rows with Type=="N" and add new var Grade?

Basically, if Type==N, then Grade can be S or W, that is why we need to duplicate the rows.

df<-structure(list(Type = c("N", "N", "S", "W"), Result = c(8, 9, 
7, 6)), row.names = c(NA, -4L), class = c("tbl_df", "tbl", "data.frame"
))

Solution 1:^[1]

I think this approach is extensible to many more conditions assuming yours is the minimal example and you have a larger more complicated dataset.

library(dplyr)

df<-structure(list(Type = c("N", "N", "S", "W"), Result = c(8, 9, 
7, 6)), row.names = c(NA, -4L), class = c("tbl_df", "tbl", "data.frame"
))

df2 <- data.frame(Type2 = c("N", "N"), Grade = c("S", "W"))

df %>%
    select(Type, Result) %>%
    left_join(df2, by = c("Type" = "Type2")) %>%
    mutate(Grade = case_when(Type == "S" ~ "S", Type == "W" ~ "W", TRUE ~ Grade))

  Type  Result Grade
  <chr>  <dbl> <chr>
1 N          8 S    
2 N          8 W    
3 N          9 S    
4 N          9 W    
5 S          7 S    
6 W          6 W

Solution 2:^[2]

Using some functions from tidyverse, you can use crossing to duplicate rows and add the "Grade" column at the same time, then filter to match your stated rules.

library(tidyverse)

result <- df %>% 
  crossing(data.frame(Grade = c('S', 'W'))) %>% 
  filter(Type == 'N' | Type == Grade)

  Type  Result Grade
  <chr>  <dbl> <chr>
1 N          8 S    
2 N          8 W    
3 N          9 S    
4 N          9 W    
5 S          7 S    
6 W          6 W

Solution 3:^[3]

Another option is to use if_else() (or case_when() if there are more complex conditions) to return a list column of multiple values and unnest:

library(dplyr)
library(tidyr)

df %>%
  mutate(Grade = if_else(Type == "N", list(c("S", "W")), as.list(Type))) %>%
  unnest(Grade)

# A tibble: 6 x 3
  Type  Result Grade
  <chr>  <dbl> <chr>
1 N          8 S    
2 N          8 W    
3 N          9 S    
4 N          9 W    
5 S          7 S    
6 W          6 W

Or:

df %>%
  mutate(Grade = case_when(Type == "N" ~ list(c("S", "W")),
                           TRUE ~ as.list(Type))) %>%
  unnest(Grade)

Solution 4:^[4]

A dplyr way: We could use bind_rows after using slice.

library(dplyr)

df %>% 
  slice(1:2) %>% 
  bind_rows(df) %>% 
  group_by(Type) %>% 
  arrange(Result, .by_group = TRUE) %>% 
  ungroup() %>% 
  mutate(Grade = rep(c("S","W"),length.out = n()), .before=2)

   Type  Grade Result
  <chr> <chr>  <dbl>
1 N     S          8
2 N     W          8
3 N     S          9
4 N     W          9
5 S     S          7
6 W     W          6

Solution 5:^[5]

Here is a possible data.table option:

library(data.table)
dt <- as.data.table(df)

output <- dt[, CJ(.SD$Type, c('S', 'W')), .(Result)][which(V1 == 'N' | V1 == V2), ]
setnames(output, c(names(dt), "Grade"))
setcolorder(output, c("Result", "Grade", "Type"))

Output

   Result Grade Type
1:      N     S    8
2:      N     W    8
3:      N     S    9
4:      N     W    9
5:      S     S    7
6:      W     W    6

Sources

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Source: Stack Overflow

Solution	Source
Solution 1
Solution 2	jdobres
Solution 3	Ritchie Sacramento
Solution 4
Solution 5	AndrewGB

'how to duplicate rows with certain condition and create anew variable at the same time

Solution 1:[1]

Solution 2:[2]

Solution 3:[3]

Solution 4:[4]

Solution 5:[5]