Мы можем сделать replace
для этих «итоговых» столбцов после left_join
library(dplyr)
left_join(df2, df1 ) %>%
group_by(leadername) %>%
mutate_at(vars(starts_with('total')), ~ replace(., row_number() > 1, NA))
# A tibble: 4 x 6
# Groups: leadername [2]
# leadername leaderid membername memberid totalruns totalwalks
# <chr> <dbl> <chr> <dbl> <dbl> <dbl>
#1 ab 11 gfh 589 4 9
#2 ab 11 tyu 739 NA NA
#3 tg 47 rtf 745 8 3
#4 tg 47 jke 996 NA NA
Или без использования group_by
left_join(df2, df1 ) %>%
mutate_at(vars(starts_with('total')), ~
replace(., duplicated(leadername), NA))
Или base R
опция
out <- merge(df2, df1, all.x = TRUE)
i1 <- duplicated(out$leadername)
out[i1, c("totalruns", "totalwalks")] <- NA
out
# leadername leaderid membername memberid totalruns totalwalks
#1 ab 11 gfh 589 4 9
#2 ab 11 tyu 739 NA NA
#3 tg 47 rtf 745 8 3
#4 tg 47 jke 996 NA NA
data
df1 <- structure(list(leadername = c("ab", "tg"), leaderid = c(11, 47
), totalruns = c(4, 8), totalwalks = c(9, 3)), class = "data.frame", row.names = c(NA,
-2L))
df2 <- structure(list(leadername = c("ab", "ab", "tg", "tg"), leaderid = c(11,
11, 47, 47), membername = c("gfh", "tyu", "rtf", "jke"), memberid = c(589,
739, 745, 996)), class = "data.frame", row.names = c(NA, -4L))