The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Download and import open Swiss economic time series from dataseries.org, a comprehensive and
up-to-date collection of public data from Switzerland. The package talks
to the public dataseries.org API
and imports series as a data.frame or ts
object.
The current version, which talks to the new dataseries.org API, lives on GitHub:
# install.packages("remotes")
remotes::install_github("cynkra/dataseries")(The version on CRAN is the older 0.2.0 release and predates the API.)
Data on dataseries.org is organized into datasets. A
dataset is a family of related series and, in most cases, a
multi-dimensional cube — a single time series is one cell of
that cube, addressed by the dataset plus one code per dimension. For
example the GDP dataset (ch_seco_gdp) splits along three
dimensions: type (nominal/real/…), structure
(GDP, value added, …) and seas_adj (seasonally adjusted or
not).
ds_catalog() lists every dataset.ds_search(pattern) is a flat, searchable list of the
individual series.ds_meta(id) describes a dataset’s dimensions and the
codes within them.ds(id, ...) downloads series.library(dataseries)
# Browse what's available
ds_catalog()
# Find a specific series across all datasets
ds_search("unemployment")
# A dataset's dimensions and codes
ds_meta("ch_seco_gdp")
# Whole dataset (long data.frame)
ds("ch_fso_cpi")
# One series: pass dimension codes as named arguments
ds("ch_fso_cpi", item = "100_100")
# Several series, restricted to a date range
ds("ch_fso_cpi", item = c("100_100", "100_1"), from = "2020-01-01")
# One cell of a multi-dimensional cube, as a ts object
ds("ch_seco_gdp", type = "real", structure = "gdp", seas_adj = "csa",
class = "ts")All series on dataseries.org are regular (annual, quarterly or
monthly), so ts covers them. If you prefer
xts, convert the ts in one line:
xts::as.xts(ds("ch_fso_cpi", item = "100_100", class = "ts")).
Dimension arguments are optional: omit them and you get the whole
dataset. Filtering happens on the server, so selecting one series does
not download the whole cube. Downloads are cached in memory for the
session; cache_rm() forces a fresh download.
Every series is also available as a plain CSV from any tool that can read a URL:
https://api.dataseries.org/series.csv?dataset=ch_fso_cpi&dims=item=100_100These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.