有没有一种方法可以根据条件向R添加新列

Question

Currently using R in Azure. I'm trying to create a new column within my dataframe whose values are dependent on an exisiting column("Sum of Pillar".

->WithSumIDAPillars <- maml.mapInputPort(1)

->WithSumIDAPillars["newcolumn"] <- NA

->WithSumIDAPillars$newcolumn <- if (WithSumIDAPillars$Sum of Pillar <5 ="Low";WithSumIDAPillars$Sum of Pillar <=6<=10 ="Medium";WithSumIDAPillars$Sum of Pillar <=11<=16 ="High"

I need to create a new column that would set the following requirements: If "Sum of PIllar" value is between 0-5=Low, 6-11=Medium and 11-16=High.

Answer 1

Have you used the dplyr package? Would something like this work?

library("dplyr")

WithSumIDAPillars$newcolumn <- 
  case_when(
    WithSumIDAPillars$`Sum of Pillar` <= 6 ~ "Low",
    WithSumIDAPillars$`Sum of Pillar` <= 11 ~ "Medium",
    WithSumIDAPillars$`Sum of Pillar` <= 16 ~ "High",
    TRUE ~ NA_character_
  )

The case_when() function goes through each case sequentially for until one of the expressions on the left side of the ~ evaluates to TRUE , so the last statement is used as a default value.

Depending on your application, it may make things easier to name your column sum_of_pillar , using underscores. That would make it easier to use the pipe ( %>% ) and the mutate() function to write things a little more concisely:

WithSumIDAPillars <- 
  WithSumIDAPillars %>%
  mutate(
    newcolumn = case_when(
      sum_of_pillar <=  5 ~ "Low",
      sum_of_pillar <= 11 ~ "Medium",
      sum_of_pillar <= 16 ~ "High",
      TRUE ~ NA_character_
    )
  )

To learn more about dplyr, you can visit the website: https://dplyr.tidyverse.org/ or the (free) R for Data Science Book: https://r4ds.had.co.nz/

Hope this helps!

Answer 2

An alternative, perhaps less elegant method to case_when is using nested if_else statements. Maybe the one advantage is you don't have to may too much attention to the order or the statements as you do with case_when .

library(tidyverse)

WithSumIDAPillars %>%
    mutate(new_col = if_else(`Sum of the Pillar` >= 0 & <= 5, "Low",
                             if_else(`Sum of the Pillar` >= 6 & <= 11, "Medium",
                                     if_else(`Sum of the Pillar` >= 12 & <= 18, "High",
                                             NA))))

NB - there's an overlap between your upper Medium and lower High thresholds so I upped the lower boundary for High to 12.