Add a new column if multiple columns have negative value

user_4299569 0
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I am trying to add a new column "result" in my dataframe df1, if the condition is

  1. select only specific columns (from count1:count3 columns) have negative value, then result = "negative"
  2. if any one of the columns (count1, count2, count3) have a positive value the result = "positive"

input

df1<- data.frame(ID= c("ID1","ID2","ID3","ID4"), count1 = c(1,-1,0,-1), count2 = c(1,-1,-1,1), count3 = c(1,-1,1,-1))

expected output

df2 <- data.frame(ID= c("ID1","ID2","ID3","ID4"),count1 = c(1,-1,1,-1), count2 = c(1,-1,-1,1), count3 = c(1,-1,1,-1), result = c("positive","negative","positive","positive"))

  ID count1 count2 count3   result
 ID1      1      1      1 positive
 ID2     -1     -1     -1 negative
 ID3      1     -1      1 positive
 ID4     -1      1     -1 positive
tidyverse dataframe r
4 Answers

Does this work:

apply(df1,1,function(x) if(all(x > 0)) 'positive' else 'negative')
[1] "positive" "negative" "negative" "negative"

library(dplyr)
df1 %>% rowwise() %>% mutate(result = if_else(all(c_across(cols = everything()) > 0),'positive','negative'))
# A tibble: 4 x 4
# Rowwise: 
  count1 count2 count3 result  
   <dbl>  <dbl>  <dbl> <chr>   
1      1      1      1 positive
2     -1     -1     -1 negative
3      0     -1      1 negative
4     -1      1     -1 negative
user_107227520

This should do it:

df2 <- df1 %>%
  mutate(results = if_else(apply(df1, 1, min) < 0, "negative", "positive"))
user_94228710

Using rowSums:

df1$results <- ifelse(rowSums(df1[ grepl("^count", colnames(df1)) ] > 0) > 0,
                      "positive", "negative")


df1
#    ID count1 count2 count3  results
# 1 ID1      1      1      1 positive
# 2 ID2     -1     -1     -1 negative
# 3 ID3      0     -1      1 positive
# 4 ID4     -1      1     -1 positive
user_6800680

A data.table option

setDT(df1)[, result := c("negative", "positive")[1 + (rowSums(.SD == 1) > 0)], .SDcols = patterns("count")][]

gives

    ID count1 count2 count3   result
1: ID1      1      1      1 positive
2: ID2     -1     -1     -1 negative
3: ID3      0     -1      1 positive
4: ID4     -1      1     -1 positive
user_121587570
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