How to delete duplicates but keep most recent data in R - r

Question

I have the following two data frames:
df1 = data.frame(names=c('a','b','c','c','d'),year=c(11,12,13,14,15), Times=c(1,1,3,5,6))
df2 = data.frame(names=c('a','e','e','c','c','d'),year=c(12,12,13,15,16,16), Times=c(2,2,4,6,7,7))
I would like to know how I could merge the above df but only keeping the most recent Times depending on the year. It should look like this:
Names Year Times
a 12 2
b 12 2
c 16 7
d 16 7
e 13 4

Answer 1

I'm guessing that you do not mean to merge these but rather combine by stacking. Your question is ambiguous since the "duplication" could occur at the dataframe level or at the vector level. You example does not display any duplication at the dataframe level but would at the vector level. The best way to describe the problem is that you want the last (or max) Times entry within each group if names values:
> df1
names year Times
1 a 11 1
2 b 12 1
3 c 13 3
4 c 14 5
5 d 15 6
> df2
names year Times
1 a 12 2
2 e 12 2
3 e 13 4
4 c 15 6
5 c 16 7
6 d 16 7
> dfr <- rbind(df1,df2)
> dfr <-dfr[order(dfr$Times),]
> dfr[!duplicated(dfr, fromLast=TRUE) , ]
names year Times
1 a 11 1
2 b 12 1
6 a 12 2
7 e 12 2
3 c 13 3
8 e 13 4
4 c 14 5
5 d 15 6
9 c 15 6
10 c 16 7
11 d 16 7
> dfr[!duplicated(dfr$names, fromLast=TRUE) , ]
names year Times
2 b 12 1
6 a 12 2
8 e 13 4
10 c 16 7
11 d 16 7

Answer 2

This uses base R functions; there are also newer packages (such as plyr) that many feel make the split-apply-combine process more intuitive.
df <- rbind(df1, df2)
do.call(rbind, lapply(split(df, df$names), function(x) x[which.max(x$year), ]))
## names year Times
## a a 12 2
## b b 12 1
## c c 16 7
## d d 16 7
## e e 13 4

Answer 3

We could also use aggregate:
df <- rbind(df1,df2)
aggregate(cbind(df$year,df$Times)~df$names,df,max)
# df$names V1 V2
# 1 a 12 2
# 2 b 12 1
# 3 c 16 7
# 4 d 16 7
# 5 e 13 4

Answer 4

In case you wanted to see a data.table solution,
# load library
library(data.table)
# bind by row and convert to data.table (by reference)
df <- setDT(rbind(df1, df2))
# get the result
df[order(names, year), .SD[.N], by=.(names)]
The output is as follows:
names year Times
1: a 12 2
2: b 12 1
3: c 16 7
4: d 16 7
5: e 13 4
The final line orders the row-binded data by names and year, and then chooses the last observation (.sd[.N]) for each name.