Use merge with one data frame in R [duplicate] - r

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I have one data frame in R with duplicate indexes stored in the first column.
df <- data.frame("Index" = c(1,2,1), "Age" = c("Jane Doe","John Doe","Jane
Doe"), "Address" = c("123 Fake Street","780 York Street","456 Elm
Street"),"Telephone" = c("xxx-xxx-xxxx","zzz-zzz-zzzz","yyy-yyy-yyyy"))
Index Name Address Telephone
1 Jane Doe 123 Fake Street xxx-xxx-xxxx
2 John Doe 780 York Street zzz-zzz-zzzz
1 Jane Doe 456 Elm Street yyy-yyy-yyyy
I would like to combine the above data frame to look like:
Index Name Address Telephone Address 2 Telephone 2
1 Jane, Doe 123 Fake Street xxx-xxx-xxxx 456 Elm Street yyy-yyy-yyyy
2 John Doe 780 York Street zzz-zzz-zzzz NA NA
Can I use "merge" on the same data frame or is their another command in R that would accomplish this task? Thank you.

Answer 1

with tidyverse
df %>%
group_by(Age) %>%
summarize_at(vars(Telephone,Address),paste, collapse="|") %>%
separate(Address,into=c("Address1","Address2"),sep="\\|") %>%
separate(Telephone,into=c("Telephone1","Telephone2"),sep="\\|")
# # A tibble: 2 x 5
# Age Telephone1 Telephone2 Address1 Address2
# <fct> <chr> <chr> <chr> <chr>
# 1 Jane Doe xxx-xxx-xxxx yyy-yyy-yyyy 123 Fake Street 456 Elm Street
# 2 John Doe zzz-zzz-zzzz <NA> 780 York Street <NA>
To be more general, we can nest the values using summarize and list, and reformat the content to unnestit with the right format:
df %>%
group_by(Age) %>%
summarize_at(vars(Telephone,Address),
~lst(setNames(invoke(tibble,.),seq_along(.)))) %>%
unnest(.sep = "")
# # A tibble: 2 x 5
# Age Telephone1 Telephone2 Address1 Address2
# <fct> <fct> <fct> <fct> <fct>
# 1 Jane Doe xxx-xxx-xxxx yyy-yyy-yyyy 123 Fake Street 456 Elm Street
# 2 John Doe zzz-zzz-zzzz <NA> 780 York Street <NA>
The function inside of summarize is a bit scary but you can wrap it into a friendlier name if you want to use it again (I added a names parameter just in case):
nest2row <- function(x,names = seq_along(x))
lst(setNames(invoke(tibble,x),names[seq_along(x)]))
df %>%
group_by(Age) %>%
summarize_at(vars(Telephone,Address), nest2row) %>%
unnest(.sep = "")
And this would be the recommended tidy way I suppose :
df %>%
group_by(Age) %>%
mutate(id=row_number()) %>%
gather(key,value,Address,Telephone) %>%
unite(key,key,id,sep="") %>%
spread(key,value)
# # A tibble: 2 x 6
# # Groups: Age [2]
# Index Age Address1 Address2 Telephone1 Telephone2
# <dbl> <fct> <chr> <chr> <chr> <chr>
# 1 1 Jane Doe 123 Fake Street 456 Elm Street xxx-xxx-xxxx yyy-yyy-yyyy
# 2 2 John Doe 780 York Street <NA> zzz-zzz-zzzz <NA>
With my second solution you keep your factors and there's not this awkward forcing different types of variables in the same column that the idiomatic way has.

Answer 2

Try something like this:
df <- data.frame("Index" = c(1,2,1), "Age" = c("Jane Doe","John Doe","Jane Doe"),
"Address" = c("123 Fake Street","780 York Street","456 Elm Street"),
"Telephone" = c("xxx-xxx-xxxx","zzz-zzz-zzzz","yyy-yyy-yyyy"),
stringsAsFactors = F)
df$unindex=paste(df$Index,df$Age)
sapply(unique(df$unindex),function(li){ # li="1 Jane Doe"
dft=df[li==df$unindex,3:4]
if(nrow(dft)==1)dft else c(t(dft))
})