how to read a csv with a timestamp field?

Question

I'm trying to import a csv file that has a field Ts containing ISO8601 time stamp values (E.g. 2014-12-01T18:54:22.973+0000).

I have seen that you can specify the class of columns:

kd <- read.csv( "my.csv", colClasses=c( "Ts"="?"  ))

However, I can't find how to declare a timestamp field.

Question: How can I specify that this field is a time stamp?

Answer 1

If you want to read the .csv file directly into a time series object, you can use the function read.zoo() from the zoo package. This internally calls read.table() (rather than read.csv) and then converts the specified time index column(s). See ?read.zoo and vignette("zoo-read", package = "zoo").

An example with time stamps like yours is:

csv <-
"x,y,timestamp
0,1,2014-12-01T18:54:22.973+0000
1,2,2014-12-01T19:43:11.862+0000"
read.zoo(text = csv, sep = ",", header = TRUE, index = "timestamp",
  format = "%Y-%m-%dT%H:%M:%OS%z", tz = "GMT")

And this yields a zoo series with POSIXct time stamps:

                    x y
2014-12-01 18:54:22 0 1
2014-12-01 19:43:11 1 2

(Of course, the text = csv would have to be replaced by something like file = "my.csv" if you are reading a .csv file from the disk rather than a text string from within R.)