Question

I have a dataframe (data) which includes a lot of dates. I want to lop off everything from before 1970. I can create a list of indices that are before 1970:

tmp <- which(data$data < '1970-01-01')
[1]  13446 102876 141199

and I want to create a new table that drops out those three rows. Something like:

data.after.1970 <- data[!tmp, ]

I know I could create a vector of all the incidents after 1970 and match against it with:

tmp <- which(data$data > '1970-01-01')
data.after.1970 <- data[tmp, ]

But I am wondering what syntax I would use to exclude items.

UPDATE

I finally just did this:

tmp <- which(data$data > as.Date('1970-01-01'))
data.after.1970 <- data[tmp, ]

and took a closer look at it. which(data$data < as.Date('1970-01-01')) gets three results, but nrow(data) - nrow(data.after.1970) shows that I dropped 45 rows. summary(datae$date) cleared that up:

summary(data$date)
        Min.      1st Qu.       Median         Mean      3rd Qu.         Max.         NA's 
"1933-07-01" "1989-01-25" "1992-07-09" "1992-05-03" "1996-06-10" "2006-09-14"         "42" 

Since my goal was to get a second dataset so I could compare my results if I exclude those with bad dates, I actually do want to drop those with NA values as well.

I still want to know what syntax I would use to exclude some numeric vector rather than include it.

Answer 1

Turns out it was actually pretty simple.

data.after.1970 <- data[-tmp, ]

will create a new frame, data.after.1970 that includes all the rows from data except those which match the indexes in tmp.