Index of /web/packages/restatapi/readme

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restatapi

An R package to search and retrieve data from Eurostat database using SDMX

installation

Now ‘restatapi’ is on CRAN so it can be installed by

> install.packages("restatapi")

or use the development version from GitHub

> devtools::install_github("eurostat/restatapi")

background

This package is similar to other packages like the eurostat, rdbnomics, RJSDMX or TSsdmx which can be used to download data from Eurostat database. The difference is that restatapi is based on SDMX (Statistical Data and Metadata eXchange) and XML to search and retrieve filtered datasets and use the TSV (tab separeted values) bulk download facility to get whole data tables. The code was written in a way that the number of dependencies on other packages should be very small. The restatapi package provides flexible filtering options, data caching, and uses the parallel and data.table package to handle large dataset in an efficient way.

content

The package contains 8 main functions and several other sub functions in 3 areas.

1. downloading and filtering the list of avaialble datasets:
   • the get_eurostat_toc function downloads the Table of Contents (TOC) of all Eurostat datasets.
   • the search_eurostat_toc function provides the facility to search for phrase, pattern and regular expressions in the TOC and returns the rows of the TOC where the search string(s) found.
2. downloading and searching in the metadata:
   • the get_eurostat_dsd function returns the Data Structure Definition (DSD) of a given dataset containing the possible dimensions and values with their labels.
   • the search_eurostat_dsd function provides the facility to search for phrase, pattern and regular expressions in the DSD and returns the rows of the DSD where the search string(s) found.
   • the create_filter_table function creates a filter table based on the DSD and the search expresssions which can be applied on the local computer to filter out data from whole data tables.
3. retrieving full or partial datasets:
   • the get_eurostat_raw function downloads the full data table as it is either using the TSV format (default) or the SDMX format keeping all the column names and rows as it is in the original files.
   • the get_eurostat_bulk function downloads the full data set keeping only a unique frequency with standardized column names and removing those columns which do not contain additional information, like frequency and time format.
     
   • the get_eurostat_data function retrieves a data table which can be labeled using the labels from the DSD. The table can contain the whole datasets or only part of it if filters are applied. If after the filtering the number of observations is to large, then the whole dataset is downloaded and the filter applied on the local computer. If no filter used, it is equivalent with the get_eurostat_bulk function, but in this case labels can be applied.

Below there are examples demonstrating the main features, the detailed documentation of the functions is in the package.

Next to the functions the package contains a list of country codes for different groups of European countries based on the Eurostat standard code list, e.g.: European Union (EU28, …, EU6), Euro Area (EA19, …, EA11) or New Member States (NMS13, …, NMS2).

examples

Example 1: Setting the number of cores/threads to 3 and download the txt version of the English TOC and search not case sensitive for the word energie in the German version of the TOC.

> options(restatapi_cores=3)
> get_eurostat_toc()
> get_get_eurostat_toc(mode="txt",verbose=TRUE)
> search_eurostat_toc("energie",lang="de",ignore.case=TRUE)

Other examples:

> dsd<-get_eurostat_dsd("ei_bsfs_q")
> search_eurostat_dsd("EU",dsd)
> search_eurostat_dsd("EU",dsd,name=FALSE)
> 
> get_eurostat_data("NAMA_10_GDP")
> get_eurostat_data("nama_10_gdp",update_cache=TRUE,check_toc=TRUE)
> get_eurostat_data("nama_10_gdp",cache_dir="/tmp",stringAsFactors=FALSE,cflags=TRUE)
>
> options(restatapi_update=TRUE)
> options(restatapi_cache_dir=file.path(tempdir(),"restatapi"))
>
> dt<-get_eurostat_data("avia_par_me",select_freq="A",cache=FALSE)
> dt<-get_eurostat_data("agr_r_milkpr",date_filter=2008,keep_flags=TRUE)
> dt<-get_eurostat_data("avia_par_ee",
>                        filters="BE$",
>                        date_filter=c("2017-03",2016,"2017-07-01",2012:2014),
>                        select_freq="Q",
>                        label=TRUE,
>                        verbose=TRUE,
>                        name=FALSE)
> dt<-get_eurostat_data("bop_its6_det",
>                        filters=list(bop_item="SC",
>                                     currency="MIO_EUR",
>                                     partner="EXT_EU28",
>                                     geo=c("EU28","HU"),
>                                     stk_flow="BAL"),
>                        date_filter="2010:2012",
>                        select_freq="A",
>                        label=TRUE,
>                        name=FALSE,
>                        ignore.case=TRUE)     
> options(restatapi_cache_dir=tempdir())
> dt<-get_eurostat_data("agr_r_milkpr",
>                       filters=c("BE$","Hungary"),
>                       date_filter="2007-06<",
>                       keep_flags=TRUE)
> dt<-get_eurostat_data("agr_r_milkpr",
>                       filters="BE",
>                       exact_match=FALSE,
>                       date_filter="2006-02:2008-06-05",
>                       keep_flags=TRUE,
>                       stringsAsFactors=FALSE,
>                       label=TRUE,
>                       ignore.case=TRUE)
>
> eu<-get("cc",envir=.restatapi_env)
> dt<-get_eurostat_data("agr_r_milkpr",
>                       filters=eu$NMS10,
>                       date_filter="2009-03-01:2011-06-05",
>                       keep_flags=TRUE,
>                       stringsAsFactors=FALSE,
>                       label=TRUE)
>
> dt<-get_eurostat_data("nama_10_a10_e",
>                       filters=c("Annual","EU28","Belgium","AT","Total","EMP_DC","person"),
>                       date_filter=c("2008",2002,"2005-01",2013:2018))
> dt<-get_eurostat_data("avia_par_me",
>                       filters="Q...ME_LYPG_HU_LHBP+ME_LYTV_UA_UKKK",
>                       date_filter=c("2016-08","2017-07-01"),
>                       select_freq="M") 
> dt<-get_eurostat_data("avia_par_me",
>                       filters=c("HU","Quarterly","Monthly"),
>                       date_filter=c("2016-08","2014-03-01"),
>                       label=TRUE)
>
> clean_restatapi_cache(tempdir(),verbose=TRUE)