Package {dataseries}

dataseries: Switzerland's Data Series in One Place

Description

Download and import open Swiss economic time series from dataseries.org.

Details

The data are organized as datasets, each of which is a family of related series. Most datasets are multi-dimensional cubes: a single time series is one cell, addressed by the dataset plus one code per dimension (e.g. the GDP cube splits along type, structure and seas_adj). A handful of datasets are a single series and need no dimensions at all.

• ds_catalog() lists every available dataset.

• ds_search() is a flat, searchable list of the individual series.

• ds_meta() describes one dataset's dimensions and their codes.

• ds() downloads series, as a data.frame or ts object.

Author(s)

Maintainer: Christoph Sax christoph.sax@gmail.com

Other contributors:

• Jannes Muenchow malnamalja@gmx.de [contributor]

See Also

Useful links:

• https://dataseries.org

• https://github.com/cynkra/dataseries

• Report bugs at https://github.com/cynkra/dataseries/issues

List or clear the in-memory cache

Description

Everything downloaded from dataseries.org is cached in memory for the lifetime of the R session. cache_ls() lists the cached objects (keyed by request URL); cache_rm() empties the cache, which forces the next call to download fresh data.

Usage

cache_ls()

cache_rm()

Value

cache_ls() returns a character vector of cache keys; cache_rm() is called for its side effect and returns NULL invisibly.

Examples

## Not run: 
ds_catalog()
cache_ls()
cache_rm()

## End(Not run)

Download time series from dataseries.org

Description

ds() downloads open Swiss economic time series from dataseries.org.

Usage

ds(dataset, ..., from = NULL, to = NULL, class = c("data.frame", "ts"))

Arguments

Details

Data on dataseries.org is organized into datasets. A dataset is a family of related series and is, in most cases, a multi-dimensional cube: a single time series is one cell of the cube, addressed by the dataset plus one code per dimension. Pass those codes as named arguments (the names are the dimension names, see ds_meta()):

ds("ch_seco_gdp", type = "real", structure = "gdp", seas_adj = "csa")

Dimension arguments are optional. Omit them and you get the whole dataset (all series, in long format). A few datasets are a single series and take no dimensions at all (e.g. ds("ch_kof_barometer")). Filtering happens on the server, so selecting one series does not download the whole cube.

Downloads are cached in memory for the session. Run cache_rm() to force a fresh download.

Value

A data.frame or ts/mts object, or NULL if the selection is empty.

See Also

ds_catalog() for the list of datasets and ds_meta() for a dataset's dimensions.

Examples

## Not run: 
# whole dataset (long data.frame)
ds("ch_fso_cpi")

# one series, by dimension code
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")

# as a ts object
ds("ch_seco_gdp", type = "real", structure = "gdp", seas_adj = "csa",
   class = "ts")

## End(Not run)

Catalog of available datasets

Description

Lists every dataset available on dataseries.org, one row per dataset. Use the id column with ds() to download data and with ds_meta() to inspect a dataset's dimensions.

Usage

ds_catalog()

Value

A data.frame with one row per dataset and the columns id, title, concept, topic, source, license, frequency, start, end and n_series.

Examples

## Not run: 
cat <- ds_catalog()
head(cat)

# search the catalog
cat[grepl("price", cat$title, ignore.case = TRUE), c("id", "title")]

## End(Not run)

Metadata for one dataset

Description

Returns the full metadata for a single dataset: its dimensions, the codes (levels) available within each dimension, labels, source, license and date range. Use this to discover which dimension codes to pass to ds().

Usage

ds_meta(dataset)

Arguments

Value

A named list (the parsed metadata). Notable elements are dim_order (the dataset's dimensions) and dimensions (each dimension's levels, keyed by code, with a label).

Examples

## Not run: 
m <- ds_meta("ch_seco_gdp")
m$dim_order                       # "type", "structure", "seas_adj"
names(m$dimensions$type$levels)   # the codes you can pass as type = ...

## End(Not run)

Search for series across all datasets

Description

Returns a flat, searchable table of the individual series available across every dataset on dataseries.org — one row per series. This is the finest-grained way to discover what exists: grep it, or pass a pattern to filter. The dataset, dim and code columns are exactly what you feed back to ds().

Usage

ds_search(pattern = NULL)

Arguments

Value

A data.frame with the columns dataset, dataset_title, frequency, dim, code, label and path.

See Also

ds_catalog() for the dataset-level list and ds_meta() for one dataset's dimensions.

Examples

## Not run: 
# everything
ds_search()

# find unemployment series, then download one
hits <- ds_search("unemployment")
head(hits)
ds(hits$dataset[1], setNames(list(hits$code[1]), hits$dim[1]))

## End(Not run)

Inventory of available series (deprecated)

Description

Deprecated. Use ds_catalog() for the dataset-level list or ds_search() for individual series. Retained as a thin wrapper so code written against earlier versions keeps working.

Usage

inventory()

Value

The value of ds_catalog().