Does any column match requirement? - r

Question

I have a count of stems by tree species for different plots.
structure(list(Plot = c(1, 2), Pine = c(0, 430), Spruce = c(708,
1241), Birch = c(119, 48), Aspen = c(0, 0), Salix = c(0, 0),
Rowan = c(0, 0), Alnus = c(0, 0), stem_sum = c(827, 1719)), row.names = c(NA,
-2L), groups = structure(list(.rows = structure(list(1L, 2L), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -2L), class = c("tbl_df",
"tbl", "data.frame")), class = c("rowwise_df", "tbl_df", "tbl",
"data.frame"))
What I want to do is use dplyr 1.0 convention to mutate a new column, "Main species", if any of the tree species columns exceed 80% of the stem_sum of that plot.
My thought process:
df %>% rowwise() %>% mutate(`Main species`= c_across(Pine:Alnus, if(.. / stem/sum >= 0.8, paste(...))
How can I modify this code such that if there are more than one column which fulfils the requirement, the output will be "Mixed"?

Answer 1

You can use :
library(dplyr)
df %>%
rowwise() %>%
mutate(Main_Species = if(any(c_across(Pine:Alnus) >= 0.8 * stem_sum))
'Mixed' else 'Not Mixed')
# Plot Pine Spruce Birch Aspen Salix Rowan Alnus stem_sum Main_Species
# <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
#1 1 0 708 119 0 0 0 0 827 Mixed
#2 2 430 1241 48 0 0 0 0 1719 Not Mixed
Or in base R :
df$Main_species <- ifelse(rowSums(df[2:8] >= df$stem_sum * 0.8) > 0,
'Mixed', 'Not Mixed')

Answer 2

library(tidyverse)
df %>%
pivot_longer(-c(Plot, stem_sum)) %>%
arrange(Plot, desc(value)) %>%
group_by(Plot) %>%
mutate(pct = value/stem_sum,
main_species = case_when(
pct > 0.8 & pct == max(pct) ~ name,
pct == max(pct) ~ "mixed"
)
) %>% ungroup() %>%
fill(main_species, .direction = "down") %>%
select(-pct) %>%
pivot_wider()