I'm trying to create a time series plot using R where obtain the dates from a REST request and then I want to group and count the date occurrences on a one week interval. I followed the examples of ts() in R and tried plots, which worked great. But I couldn't find any examples that shows how to create date aggregation based on existing data. Can someone point me in the proper direction?
This is a sample of my parsed REST data:
REST Response excerpt ....
"2014-01-16T14:51:50.000-0800"
"2014-01-14T15:42:55.000-0800"
"2014-01-13T17:29:08.000-0800"
"2014-01-13T16:19:31.000-0800"
"2013-12-16T16:56:39.000-0800"
"2014-02-28T08:11:54.000-0800"
"2014-02-28T08:11:28.000-0800"
"2014-02-28T08:07:02.000-0800"
"2014-02-28T08:06:36.000-0800"
....
Sincerely, code B.
You can define the date with "as.Date" and then create a time series with "xts", as it allows merging by any period of time.
library(xts)
REST$date <- as.Date(REST$date, format="%Y-%m-%d")
REST$variable <- seq(0,2.4,by=.3)
ts <- xts(REST[,"variable"], order.by=REST[,"date"])
> to.monthly(ts)
ts.Open ts.High ts.Low ts.Close
Dec 2013 1.2 1.2 1.2 1.2
Xan 2014 0.6 0.9 0.0 0.0
Feb 2014 1.5 2.4 1.5 2.4
> to.weekly(ts)
ts.Open ts.High ts.Low ts.Close
2013-12-16 1.2 1.2 1.2 1.2
2014-01-16 0.6 0.9 0.0 0.0
2014-02-28 1.5 2.4 1.5 2.4
Not sure if this is what you needed. Is it?