R packagesĪ number of other R packages contain time series data. These were transferred to DataMarket in June 2012 and are now available here. TSDLįor many years, I maintained the Time Series Data Library consisting of about 800 time series including many from well-known textbooks. The data come in zoo format, but can easily be converted to a ts object using as.ts. The short URL is provided on the “Export” tab of the page for the data set on Datamarket. The dmseries function from the rdatamarket package is simpler to use. Unauthenticated users are limited to 50 downloads per day. The Quandl function will also generate a warning that no authentication token has been used. For some bizarre reason, the Quandl data comes in reverse time order so rev needs to be used, and then the time series attributes applied. These data can be downloaded to R using the rdatamarket and Quandl packages respectively: library(rdatamarket)Īusgdp2 <- ts(rev(Quandl('FRED/AUSRGDPC', type='ts')), end=2011) The version from the Federal Reserve Bank in 2010 US dollars was available on both sites ( Datamarket and Quandl). A search for “Australian Real GDP per capita” on both sites returned many variants. DataMarket and Quandlīoth DataMarket and Quandl contain many thousands of time series that can be downloaded directly into R. The 1001 series from the M-competition and the 3003 series from the M3-competition are available as part of the Mcomp package in R. It is now relatively easy to access these data sets directly in R. There is no shortage of time series data available on the web for use in student projects, or self-learning, or to test out new forecasting algorithms.

Text file time series in r