How can I subset the following example data frame to only return one observation for the earliest occurance [i.e. min(year)] of each id?
id <- c("A", "A", "C", "D", "E", "F")
year <- c(2000, 2001, 2001, 2002, 2003, 2004)
qty <- c(100, 300, 100, 200, 100, 500)
df=data.frame(year, qty, id)
In the example above there are two observations for the "A" id at years 2000 and 2001. In the case of duplicate id's, I would like the subset data frame to only include the the first occurance (i.e. at 2000) of the observations for the duplicate id.
df2 = subset(df, ???)
This is what I am trying to return:
df2
year qty id
2000 100 A
2001 100 C
2002 200 D
2003 100 E
2004 500 F
Any assistance would be greatly appreciated.
You can aggregate on minimum year + id, then merge with the original data frame to get qty:
df2 <- merge(aggregate(year ~ id, df1, min), df1)
# > df2
# id year qty
# 1 A 2000 100
# 2 C 2001 100
# 3 D 2002 200
# 4 E 2003 100
# 5 F 2004 500
Is this what you're looking for? Your second row looks wrong to me (it's the duplicated year, not the first).
> duplicated(df$year)
[1] FALSE FALSE TRUE FALSE FALSE FALSE
> df[!duplicated(df$year), ]
year qty id
1 2000 100 A
2 2001 300 A
4 2002 200 D
5 2003 100 E
6 2004 500 F
Edit 1: Er, I completely misunderstood what you were asking for. I'll keep this here for completeness though.
Edit 2:
Ok, here's a solution: Sort by year (so the first entry per ID has the earliest year) and then use duplicated
. I think this is the simplest solution:
> df.sort.year <- df[order(df$year), ]
> df.sort.year[!duplicated(df$id), ]
year qty id
1 2000 100 A
3 2001 100 C
4 2002 200 D
5 2003 100 E
6 2004 500 F
Using plyr
library(plyr)
## make sure first row will be min (year)
df <- arrange(df, id, year)
df2 <- ddply(df, .(id), head, n = 1)
df2
## year qty id
## 1 2000 100 A
## 2 2001 100 C
## 3 2002 200 D
## 4 2003 100 E
## 5 2004 500 F
or using data.table. Setting the key as id, year will ensure the first row is the minimum of year.
library(data.table)
DF <- data.table(df, key = c('id','year'))
DF[,.SD[1], by = 'id']
## id year qty
## [1,] A 2000 100
## [2,] C 2001 100
## [3,] D 2002 200
## [4,] E 2003 100
## [5,] F 2004 500
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