Merging two data frames without duplicating metric values - r

Question

I have two data frames and I want to merge them by leader values, so that I can see the total runs and walks for each groups. Each leader can have multiple members in their team, but the problem that I'm having is that when I merge them, the metrics also gets duplicated over to the newly added rows.
Here is an example of the two data sets that I have:
Data set 1:
+-------------+-----------+------------+-------------+
| leader name | leader id | total runs | total walks |
+-------------+-----------+------------+-------------+
| ab | 11 | 4 | 9 |
| tg | 47 | 8 | 3 |
+-------------+-----------+------------+-------------+
Data set 2:
+-------------+-----------+--------------+-----------+
| leader name | leader id | member name | member id |
+-------------+-----------+--------------+-----------+
| ab | 11 | gfh | 589 |
| ab | 11 | tyu | 739 |
| tg | 47 | rtf | 745 |
| tg | 47 | jke | 996 |
+-------------+-----------+--------------+-----------+
I want to merge the two datasets so that they become like this:
+-------------+-----------+--------------+------------+------------+-------------+
| leader name | leader id | member name | member id | total runs | total walks |
+-------------+-----------+--------------+------------+------------+-------------+
| ab | 11 | gfh | 589 | 4 | 9 |
| ab | 11 | tyu | 739 | | |
| tg | 47 | rtf | 745 | 8 | 3 |
| tg | 47 | jke | 996 | | |
+-------------+-----------+--------------+------------+------------+-------------+
But right now I keep getting:
+-------------+-----------+--------------+------------+------------+-------------+
| leader name | leader id | member name | member id | total runs | total walks |
+-------------+-----------+--------------+------------+------------+-------------+
| ab | 11 | gfh | 589 | 4 | 9 |
| ab | 11 | tyu | 739 | 4 | 9 |
| tg | 47 | rtf | 745 | 8 | 3 |
| tg | 47 | jke | 996 | 8 | 3 |
+-------------+-----------+--------------+------------+------------+-------------+
It doesn't matter if they're blank, NA's or 0's, as long as the values aren't duplicating. Is there a way to achieve this?

Answer 1

We can do a replace on those 'total' columns after a 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
Or without using the group_by
left_join(df2, df1 ) %>%
mutate_at(vars(starts_with('total')), ~
replace(., duplicated(leadername), NA))
Or a base R option is
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))