Use R to find duplicates in multiple columns at once

Question

I have a table with three columns: Surname, First Name and Address. I'm looking to match up families by searching for people with the same surname AND the same address. I figured out how to use Duplicated to filter down to only people with the same name OR the same address. Here's my sample table:

Surname First Name  Address
A1        Bobby       X1
B5         Joe        X2
B5        Mary        X3
F2        Lou         X4
F3        Sarah       X5
G4        Bobby       X6
G4        Fred        X6
G4        Anna        X6
H5        Eric        X7
K6        Peter       X8 

And the code I used to filter it is:

duplicates = duplicated(sample$Surname)
sample_surnames= sample %>% filter(duplicates)

Here's the output of that code:

Surname First Name  Address         
B5        Mary        X3
G4        Fred        X6
G4        Anna        X6

The problem is two fold:

1. This code drops the first instance of any duplicate. i.e. Bobby, Fred and Anna should all be included but Bobby is dropped.
2. Is there a way to filter for duplicates in both the Surname and Address columns at once or do I need to perform the operation twice? To be clear: I'm looking for instances where there's a duplicate in BOTH columns.

Update: Here is the table I'd like to get in the end: Please note, I'm not trying to remove the duplicates but, rather, keep the duplicates. In this case, Bobby, Fred and Anna are the only ones who have both the same Surname and Address.

Surname First Name  Address
G4       Bobby       X6
G4        Fred       X6
G4       Anna        X6

Answer 1

We can use unique with by option from data.table

library(data.table)
unique(setDT(df), by = c("Surname", "Address"))
#    Surname First Name Address
#1:      A1      Bobby      X1
#2:      B5        Joe      X2
#3:      B5       Mary      X3
#4:      F2        Lou      X4
#5:      F3      Sarah      X5
#6:      G4      Bobby      X6
#7:      H5       Eric      X7
#8:      K6      Peter      X8

---

Or with tidyverse

library(dplyr)
df %>% 
  distinct(Surname, Address, .keep_all = TRUE)
# Surname First Name Address
#1      A1      Bobby      X1
#2      B5        Joe      X2
#3      B5       Mary      X3
#4      F2        Lou      X4
#5      F3      Sarah      X5
#6      G4      Bobby      X6
#7      H5       Eric      X7
#8      K6      Peter      X8

Update

Based on the updated post, perhaps this helps

setDT(df)[, if((uniqueN(FirstName))>1) .SD,.(Surname, Address)]
#   Surname Address FirstName
#1:      G4      X6     Bobby
#2:      G4      X6      Fred
#3:      G4      X6      Anna