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:
You can install the latest in-development release from github with:
or the latest version with:
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 × 3
#> dataset_id title description
#> <chr> <chr> <chr>
#> 1 110080 Průměrná hrubá měsíční mzda a medián mezd v krajích Datová sad…
#> 2 110079 Zaměstnanci a průměrné hrubé měsíční mzdy podle odvětví Datová sad…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: 1,080 × 14
#> idhod hodnota stapro_kod SPKVANTIL_cis SPKVANTIL_kod POHLAVI_cis POHLAVI_kod
#> <chr> <dbl> <chr> <chr> <chr> <chr> <chr>
#> 1 73662… 21782 5958 7636 Q5 <NA> <NA>
#> 2 73662… 25625 5958 <NA> <NA> <NA> <NA>
#> 3 73662… 28431 5958 <NA> <NA> 102 1
#> 4 73662… 22133 5958 <NA> <NA> 102 2
#> 5 73662… 23533 5958 7636 Q5 102 1
#> 6 73662… 19731 5958 7636 Q5 102 2
#> 7 74595… 26033 5958 <NA> <NA> <NA> <NA>
#> 8 74595… 28873 5958 <NA> <NA> 102 1
#> 9 74595… 22496 5958 <NA> <NA> 102 2
#> 10 74595… 21997 5958 7636 Q5 <NA> <NA>
#> # ℹ 1,070 more rows
#> # ℹ 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 × 5
#> name titles `dc:description` required datatype
#> <chr> <chr> <chr> <lgl> <chr>
#> 1 idhod idhod "unikátní identifikátor údaje … TRUE string
#> 2 hodnota hodnota "zjištěná hodnota" TRUE number
#> 3 stapro_kod stapro_kod "kód statistické proměnné ze s… TRUE string
#> 4 spkvantil_cis spkvantil_cis "kód číselníku pro kvantil" TRUE string
#> 5 spkvantil_kod spkvantil_kod "kód položky z číselníku pro k… TRUE string
#> 6 pohlavi_cis pohlavi_cis "kód číselníku pro pohlaví" TRUE string
#> 7 pohlavi_kod pohlavi_kod "kód položky číselníku pro poh… TRUE string
#> 8 rok rok "rok referenčního období ve fo… TRUE number
#> 9 uzemi_cis uzemi_cis "kód číselníku pro referenční … TRUE string
#> 10 uzemi_kod uzemi_kod "kód položky číselníku pro ref… TRUE string
#> 11 uzemi_txt uzemi_txt "text položky z číselníku pro … TRUE string
#> 12 stapro_txt stapro_txt "text statistické proměnné" TRUE string
#> 13 spkvantil_txt spkvantil_txt "text položky číselníku pro kv… TRUE string
#> 14 pohlavi_txt pohlavi_txt "text položky číselníku pro po… TRUE stringand download the documentation in PDF:
czso_get_dataset_doc("110080", action = "download", format = "pdf")
#> ✔ Downloaded <https://www.czso.cz/documents/62353418/171419376/110080-22dds.pdf> to '110080-22dds.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 × 11
#> kodjaz akrcis kodcis chodnota zkrtext text admplod admnepo cznuts kod_ruian
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 CS KRAJ_N… 100 3000 Extra-… Extr… 2004-0… 9999-0… CZZZZ <NA>
#> 2 CS KRAJ_N… 100 3018 Hl. m.… Hlav… 2001-0… 9999-0… CZ010 19
#> 3 CS KRAJ_N… 100 3026 Středo… Stře… 2001-0… 9999-0… CZ020 27
#> 4 CS KRAJ_N… 100 3034 Jihoče… Jiho… 2001-0… 9999-0… CZ031 35
#> 5 CS KRAJ_N… 100 3042 Plzeňs… Plze… 2001-0… 9999-0… CZ032 43
#> 6 CS KRAJ_N… 100 3051 Karlov… Karl… 2001-0… 9999-0… CZ041 51
#> 7 CS KRAJ_N… 100 3069 Ústeck… Úste… 2001-0… 9999-0… CZ042 60
#> 8 CS KRAJ_N… 100 3077 Libere… Libe… 2001-0… 9999-0… CZ051 78
#> 9 CS KRAJ_N… 100 3085 Králov… Král… 2001-0… 9999-0… CZ052 86
#> 10 CS KRAJ_N… 100 3093 Pardub… Pard… 2001-0… 9999-0… CZ053 94
#> 11 CS KRAJ_N… 100 3107 Kraj V… Kraj… 2001-0… 9999-0… CZ063 108
#> 12 CS KRAJ_N… 100 3115 Jihomo… Jiho… 2001-0… 9999-0… CZ064 116
#> 13 CS KRAJ_N… 100 3123 Olomou… Olom… 2001-0… 9999-0… CZ071 124
#> 14 CS KRAJ_N… 100 3131 Zlínsk… Zlín… 2001-0… 9999-0… CZ072 141
#> 15 CS KRAJ_N… 100 3140 Moravs… Mora… 2001-0… 9999-0… CZ080 132
#> # ℹ 1 more variable: 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.