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
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.
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.
You can install the package from CRAN:
install.packages("czso")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")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()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")
#> # A tibble: 900 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 890 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 stringand 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)
#> # 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.
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.
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.
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.Thanks to @jakubklimek and @martinnecasky for helping me figure out the SPARQL endpoint on the Czech National Open Data Catalogue.
An homage to the CZSO’s work in releasing its data in an open format, something that is not necessarily in its DNA.
It alludes to the shades of the country reflected in the tabular data provided, By interspersing the comma symbol into the name of the package, it refers to both integration between statistics and open data and the slight disruption that the world of statistics undergoes when that integration happens.
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 and the {hlidacr} package.
For access to some of Prague’s open geospatial data in R, see pragr.
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.