selecting rows with specific conditions in R - r

Question

I currently have a data that looks like this for multiple ids (that range until around 1600)
id year name status
1 1980 James 3
1 1981 James 3
1 1982 James 3
1 1983 James 4
1 1984 James 4
1 1985 James 1
1 1986 James 1
1 1987 James 1
2 1982 John 2
2 1983 John 2
2 1984 John 1
2 1985 John 1
I want to subset this data so that it only has the information for status=1 and the status right before that. I also want to eliminate multiple 1s and only save the first 1s. In conclusion I would want:
id year name status
1 1984 James 4
1 1985 James 1
2 1983 John 2
2 1984 John 1
I'm doing this because I'm in the process of figuring out in what year how many people from certain status changed to status 1. I only know the subset command and I don't think I can get this data from doing subset(data, subset=(status==1)). How could I save the information right before that
I want to add to this question one more time - I did not get same results when I applied the first reply to this question (which uses plr packages) and the third reply which uses duplicated command. I found out that the first reply preserved information accurately while the third one did not.

Answer 1

This does what you want.
library(plyr)
ddply(d, .(name), function(x) {
i <- match(1, x$status)
if (is.na(i))
NULL
else
x[c(i-1, i), ]
})
id year name status
1 1 1984 James 4
2 1 1985 James 1
3 2 1983 John 2
4 2 1984 John 1

Answer 2

Here's a solution - for each grouping of numbers (the cumsum bit), it looks at the first one and takes that and the previous row if status is 1:
library(data.table)
dt = data.table(your_df)
dt[dt[, if(status[1] == 1) c(.I[1]-1, .I[1]),
by = cumsum(c(0,diff(status)!=0))]$V1]
# id year name status
#1: 1 1984 James 4
#2: 1 1985 James 1
#3: 2 1983 John 2
#4: 2 1984 John 1

Answer 3

Using base R, here is a way to do this:
# this first line is how I imported your data after highlighting and copying (i.e. ctrl+c)
d<-read.table("clipboard",header=T)
# find entries where the subsequent row's "status" is equal to 1
# really what's going on is finding rows where "status" = 1, then subtracting 1
# to find the index of the previous row
e<-d[which(d$status==1)-1 ,]
# be careful if your first "status" entry = 1...
# What you want
# Here R will look for entries where "name" and "status" are both repeats of a
# previous row and where "status" = 1, and it will get rid of those entries
e[!(duplicated(e[,c("name","status")]) & e$status==1),]
id year name status
5 1 1984 James 4
6 1 1985 James 1
10 2 1983 John 2
11 2 1984 John 1

Answer 4

I like the data.table solution myself, but there actually is a way to do it with subset.
# import data from clipboard
x = read.table(pipe("pbpaste"),header=TRUE)
# Get the result table that you want
x1 = subset(x, status==1 |
c(status[-1],0)==1 )
result = subset(x1, !duplicated(cbind(name,status)) )