The goal of czso is to provide direct, programmatic, hassle-free access from R to open data provided by the Czech Statistical Office (CZSO).

This is done by

  1. providing direct access from R to the catalogue of open CZSO datasets, eliminating the hassle from data discovery. Normally this is done done through the CZSO’s product catalogue which is unfortunately a bit clunky, or data.gov.cz, which is not a natural starting point for many.

  2. providing a function to load a specific dataset to R directly from the CZSO’s datastore, eliminating the friction of copying a URL, downloading, unzipping etc.

Additionally, the package provides access to metadata on datasets and to codelists (číselníky) as a special case of datasets listed in the catalogue.

Installation

You can install the package from CRAN:

You can install the latest in-development release from github with:

remotes::install_github("petrbouchal/czso", ref = github_release())

or the latest version with:

remotes::install_github("petrbouchal/czso")

I also keep binaries in a drat repo, which you can access by

install.packages("czso", repos = "https://petrbouchal.xyz/drat")

Example

Say you are looking for a dataset whose title refers to wages (mzda/mzdy):

First, retrieve the list of available CZSO datasets:

library(czso)
suppressPackageStartupMessages(library(dplyr))
suppressPackageStartupMessages(library(stringr))

catalogue <- czso_get_catalogue()
#> ℹ Reading data from data.gov.cz
#> ✓ Done downloading and reading data
#> ℹ Transforming data

Now search for your terms of interest in the dataset titles:

catalogue %>% 
  filter(str_detect(title, "[Mm]zd[ay]")) %>% 
  select(dataset_id, title, description)
#> # A tibble: 2 x 3
#>   dataset_id title                       description                            
#>   <chr>      <chr>                       <chr>                                  
#> 1 110080     Průměrná hrubá měsíční mzd… Datová sada obsahuje časovou řadu prům…
#> 2 110079     Zaměstnanci a průměrné hru… Datová sada obsahuje časovou řadu počt…

You could also search in descriptions or keywords which are also retrieved into the catalogue.

We can see the dataset_id for the required dataset - now use it to get the dataset:

czso_get_table("110080")
#> ℹ File already in '/Users/petr/czso_data/110080/', not downloading.
#>   Set `force_redownload = TRUE` if needed.
#> # A tibble: 810 x 14
#>    idhod hodnota stapro_kod SPKVANTIL_cis SPKVANTIL_kod POHLAVI_cis POHLAVI_kod
#>    <chr>   <dbl> <chr>      <chr>         <chr>         <chr>       <chr>      
#>  1 7459…   26211 5958       <NA>          <NA>          <NA>        <NA>       
#>  2 7459…   29026 5958       <NA>          <NA>          102         1          
#>  3 7459…   22729 5958       <NA>          <NA>          102         2          
#>  4 7459…   22266 5958       7636          Q5            <NA>        <NA>       
#>  5 7459…   23955 5958       7636          Q5            102         1          
#>  6 7459…   20271 5958       7636          Q5            102         2          
#>  7 7459…   26033 5958       <NA>          <NA>          <NA>        <NA>       
#>  8 7459…   28873 5958       <NA>          <NA>          102         1          
#>  9 7459…   22496 5958       <NA>          <NA>          102         2          
#> 10 7459…   21997 5958       7636          Q5            <NA>        <NA>       
#> # … with 800 more rows, and 7 more variables: rok <int>, uzemi_cis <chr>,
#> #   uzemi_kod <chr>, STAPRO_TXT <chr>, uzemi_txt <chr>, SPKVANTIL_txt <chr>,
#> #   POHLAVI_txt <chr>

You can retrieve the schema for the dataset:

czso_get_table_schema("110080")
#> # A tibble: 14 x 5
#>    name       titles     `dc:description`                      required datatype
#>    <chr>      <chr>      <chr>                                 <lgl>    <chr>   
#>  1 idhod      idhod      "unikátní identifikátor údaje Veřejn… TRUE     string  
#>  2 hodnota    hodnota    "zjištěná hodnota"                    TRUE     number  
#>  3 stapro_kod stapro_kod "kód statistické proměnné ze systému… TRUE     string  
#>  4 spkvantil… spkvantil… "kód číselníku pro kvantil"           TRUE     string  
#>  5 spkvantil… spkvantil… "kód položky z číselníku pro kvantil" TRUE     string  
#>  6 pohlavi_c… pohlavi_c… "kód číselníku pro pohlaví"           TRUE     string  
#>  7 pohlavi_k… pohlavi_k… "kód položky číselníku pro pohlaví"   TRUE     string  
#>  8 rok        rok        "rok referenčního období ve formátu … TRUE     number  
#>  9 uzemi_cis  uzemi_cis  "kód číselníku pro referenční území " TRUE     string  
#> 10 uzemi_kod  uzemi_kod  "kód položky číselníku pro referenčn… TRUE     string  
#> 11 uzemi_txt  uzemi_txt  "text položky z číselníku pro refere… TRUE     string  
#> 12 stapro_txt stapro_txt "text statistické proměnné"           TRUE     string  
#> 13 spkvantil… spkvantil… "text položky číselníku pro kvantil"  TRUE     string  
#> 14 pohlavi_t… pohlavi_t… "text položky číselníku pro pohlaví"  TRUE     string

and download the documentation in PDF:

czso_get_dataset_doc("110080", action = "download", format = "pdf")
#> ✓ Downloaded 'https:/www.czso.cz/documents/62353418/109720808/110080-19dds.pdf' to '110080-19dds.pdf'

If you are interested in linking this data to different data, you might need the NUTS codes for regions. Seeing that the lines with regional breakdown list uzemi_cis as "100", you can get that codelist (číselník):

czso_get_codelist(100)
#> ℹ File already in '/Users/petr/czso_data/cis100/', not downloading.
#>   Set `force_redownload = TRUE` if needed.
#> # A tibble: 15 x 11
#>    KODJAZ AKRCIS KODCIS CHODNOTA ZKRTEXT TEXT  ADMPLOD    ADMNEPO    CZNUTS
#>    <chr>  <chr>  <chr>  <chr>    <chr>   <chr> <date>     <date>     <chr> 
#>  1 CS     KRAJ_… 100    3000     Extra-… Extr… 2004-05-01 9999-09-09 CZZZZ 
#>  2 CS     KRAJ_… 100    3018     Hl. m.… Hlav… 2001-03-01 9999-09-09 CZ010 
#>  3 CS     KRAJ_… 100    3026     Středo… Stře… 2001-03-01 9999-09-09 CZ020 
#>  4 CS     KRAJ_… 100    3034     Jihoče… Jiho… 2001-03-01 9999-09-09 CZ031 
#>  5 CS     KRAJ_… 100    3042     Plzeňs… Plze… 2001-03-01 9999-09-09 CZ032 
#>  6 CS     KRAJ_… 100    3051     Karlov… Karl… 2001-03-01 9999-09-09 CZ041 
#>  7 CS     KRAJ_… 100    3069     Ústeck… Úste… 2001-03-01 9999-09-09 CZ042 
#>  8 CS     KRAJ_… 100    3077     Libere… Libe… 2001-03-01 9999-09-09 CZ051 
#>  9 CS     KRAJ_… 100    3085     Králov… Král… 2001-03-01 9999-09-09 CZ052 
#> 10 CS     KRAJ_… 100    3093     Pardub… Pard… 2001-03-01 9999-09-09 CZ053 
#> 11 CS     KRAJ_… 100    3107     Kraj V… Kraj… 2001-03-01 9999-09-09 CZ063 
#> 12 CS     KRAJ_… 100    3115     Jihomo… Jiho… 2001-03-01 9999-09-09 CZ064 
#> 13 CS     KRAJ_… 100    3123     Olomou… Olom… 2001-03-01 9999-09-09 CZ071 
#> 14 CS     KRAJ_… 100    3131     Zlínsk… Zlín… 2001-03-01 9999-09-09 CZ072 
#> 15 CS     KRAJ_… 100    3140     Moravs… Mora… 2001-03-01 9999-09-09 CZ080 
#> # … with 2 more variables: KOD_RUIAN <chr>, ZKRKRAJ <chr>

You would then need to do a bit of manual work to join this codelist onto the data.

A note about “tables” and “datasets”

In the parlance of the official open data catalogue, a dataset can have multiple distributions (typically multiple formats of the same data). These are called resources in the internals, and manifest as tables in this package. Some metainformation is the property of a dataset (the documentation), while other - the schema - is the property of a table. Hence the function names in this package. This is to keep things organised even if the CZSO almost always provides only one table per dataset and appends new data to it over time.

Data sources

The catalogue is drawn from https://data.gov.cz through the SPARQL endpoint.

The data and specific metadata is then accessed via the package_show endpoint of the CZSO API at (example) https://vdb.czso.cz/pll/eweb/package_show?id=290038r19.

Credit and notes

  • not created or endorsed by the Czech Statistical Office, though they, as well as the open data team at the Ministry of Interior deserve credit for getting the data out there.
  • the package relies on the data.gov.cz catalogue of open data and on the CZSO’s local catalogue
  • NB: The robots.txt at the domain hosting the CZSO’s catalogue prohibits robots from accessing it; while this may be an inappropriate/erroneous setting for what is in essence a data API, this package tries to honor the spirit of that setting by only accessing the API once per czso_get_table() call, relying on a different system for czso_get_catalogue(). Hence, do not use this package for harvesting large numbers of datasets from the CZSO.

Acknowledgments

Thanks to @jakubklimek and @martinnecasky for helping me figure out the SPARQL endpoint on the Czech National Open Data Catalogue.

See also

This package takes inspiration from the packages

which are very useful in their own right - much recommended.

For Czech geospatial data, see CzechData by JanCaha.

For Czech fiscal data, see statnipokladna.

For various transparency disclosures, see Hlídač státu.

For access to some of Prague’s open geospatial data in R, see pragr.

Contributing / code of conduct

Please note that the ‘czso’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.