Calulate row sums with dplyr omitting a column by its name

Question

Using dplyr, I would like to calculate row sums across all columns exept one. I managed to do that by using the column index. However, I would like to use the column name instead of the column index. How can I do that?

Example data:

# Using dplyr 0.5.0
library(tidyverse)

# Create example data
`UrbanRural` <- c("rural", "urban")
type1 <- c(1582, 671)
type2 <- c(5247, 4123)
type3 <- c(87, 65)
df <- data.frame(`UrbanRural`, type1, type2, type3)
df <- tbl_df(df)

# A tibble: 2 x 5
  UrbanRural type1 type2 type3   tot
      <fctr> <dbl> <dbl> <dbl> <dbl>
  1    rural  1582  5247    87  6916
  2    urban   671  4123    65  4859

Example that works (using the column index):

df %>% mutate(tot = rowSums(.[-1]))

# A tibble: 2 x 5
  UrbanRural type1 type2 type3   tot
      <fctr> <dbl> <dbl> <dbl> <dbl>
1      rural  1582  5247    87  6916
2      urban   671  4123    65  4859

Example of what I would like to do:

df %>% mutate(tot = rowSums(select(., -UrbanRural)))

Answer 1

We can use setdiff to select columns except "UrbanRural"

df %>%
   mutate(tot = rowSums(.[setdiff(names(.), "UrbanRural")]))
#   UrbanRural type1 type2 type3   tot
#       <fctr> <dbl> <dbl> <dbl> <dbl>
#1      rural  1582  5247    87  6916
#2      urban   671  4123    65  4859

---

If we want to use select

df %>% 
   select(-one_of("UrbanRural")) %>% 
   rowSums() %>% 
   cbind(df, tot = .) 
#   UrbanRural type1 type2 type3   tot
# 1      rural  1582  5247    87  6916
# 2      urban   671  4123    65  4859