R's equivaltent of Python's np.select(conditions, choices)-CodePudding

I'm trying to create a new column in an R dataframe based on a set of conditions that are mutually exclusive. There is a clever way to achieve this on python using np.select(conditions, choices), instead of np.where (See this solved question). I've been looking for an equivalent on R that allows me to avoid writing a gigantic nested ifelse (which is the equivalent of np.where) without any success.

The amount of conditions that I have can change and I'm implementing a function for this. Therefore, and equivalent could be really helpful. Is there any option to do this? I'm new in R and come from python.

Thank you!

CodePudding user response：

Yes, you can use case_when in R:

library(dplyr)
mtcars%>%
  mutate(cyl2=case_when(cyl>7~"High",
                        cyl==6~"Medium",
                        T~"Low"))

    mpg cyl  disp  hp drat    wt  qsec vs am gear carb   cyl2
1  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4 Medium
2  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4 Medium
3  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1    Low
4  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1 Medium
5  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2   High

CodePudding user response：

There's also cut(), Convert Numeric to Factor, with or without your own labels:

df <- data.frame(a = 1:10)

df$b <- cut(df$a, 
            breaks = c(-Inf,3,7,Inf), 
            labels = c("lo", "med", "hi"))

df$c <- cut(df$a, 
            breaks = c(-Inf,3,7,Inf))

df
#>     a   b        c
#> 1   1  lo (-Inf,3]
#> 2   2  lo (-Inf,3]
#> 3   3  lo (-Inf,3]
#> 4   4 med    (3,7]
#> 5   5 med    (3,7]
#> 6   6 med    (3,7]
#> 7   7 med    (3,7]
#> 8   8  hi (7, Inf]
#> 9   9  hi (7, Inf]
#> 10 10  hi (7, Inf]