Switzerland's Data Series in One Place.

dataseries: Switzerland's Data Series in One Place

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.

Installation

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 model

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.

Usage

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.

Beyond R

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_100