check for duplicate for unique ID

[shoaibali]

I have a data frame like below, I want to check if for same id we have duplicate name.
and then mutate a new column.

df10 <- data.frame(id=c(9143,2357,4339,8927,9143,4285,2683,8217,3702,7857,3255,4262,8501,7111,2681,6970),            name=c("xly,mnn","xab,Lan","mhy,mun","vgtu,mmc","ftu,sdh","kull,nnhu","hula,njam","mund,jiha","htfy,ntha","sghu,njui","sgyu,hytb","vdti,kula","mftyu,huta","mhuk,ghul","cday,bhsue","ajtu,nudj"))

the output should be like

id	name	duplicate_name
9143	xly,mnn	1
2357	xab,Lan	0
4339	mhy,mun	0
8927	vgtu,mmc	0
9143	ftu,sdh	1
4285	kull,nnhu	0
2683	hula,njam	0
8217	mund,jiha	0
3702	htfy,ntha	0
7857	sghu,njui	0
3255	sgyu,hytb	0
4262	vdti,kula	0
8501	mftyu,huta	0
7111	mhuk,ghul	0
2681	cday,bhsue	0
6970	ajtu,nudj	0

[b.ocarrigan]

Hi,

group_by(id), then apply a counting function, then ungroup.

This code will count how many duplicates (counts > 1) are in the df.

df10 %>% 
  group_by(id) %>% 
  mutate(duplicate_name = n()-1) %>% 
  ungroup()

If you just need a binary yes/no 0/1 variable, then follow the count with an if_else to convert to 0/1

df10 %>% 
  group_by(id) %>% 
  add_count() %>% 
  mutate(duplicate_name = if_else(n > 1, 1, 0)) %>% 
  select(-n) %>% 
  ungroup()