The goal of statnipokladna is to provide programmatic access to open data from the Státní pokladna system. Státní pokladna is a comprehensive budgeting, reporting and accounting system for Czech public organisations. This package provides user-friendly ways to access the open data from that system available at https://monitor.statnipokladna.cz. The vignettes in the package also provide an introduction to the underlying data.
You can install the released version from CRAN:
You can install the current development release of statnipokladna from GitHub with:
remotes::install_github("petrbouchal/statnipokladna",
build_vignettes = TRUE,
ref = github_release())
or the latest in-development version with
I also keep binaries in a drat
repo, which you can access by
Please report bugs at https://github.com/petrbouchal/statnipokladna/issues.
See the Get started vignette for background on the underlying data.
See also Background information below.
the official system has been partially overhauled in February 2020 and I am trying to find out about which parts of its new API will remain stable and can be used externally. Depending on the result, some functionality in this package can be streamlined and some can be added - e.g.
Get data from a particular part (file) of a dataset (“výkaz”):
local_budgets <- sp_get_table(table_id = "budget-local", # table ID, see `sp_tables`
year = 2019,
month = 9)
#> ℹ Building URL for dataset 'finm': FIN 2-12 M - Plnění rozpočtu MŘO, '2019-09'
#> ℹ Get the dataset documentation at 'http:/monitor.statnipokladna.cz/data/struktura/finm.xlsx'
#> ✓ Storing downloaded archive in and extracting to '/var/folders/c8/pj33jytj233g8vr0tw4b2h7m0000gn/T/Rtmp52TEmf/statnipokladna/finm/2019/09/'
#> ℹ Set dest_dir for more control over downloaded files.
#> ℹ Reading data...
#> ℹ Transforming data...
The data is automatically downloaded to a temp directory, so it will be reused by future calls to sp_get_table()
made in the same session, unless you set force_redownload = TRUE
. You set the dest_dir
parameter e.g. to "."
, a directory will be created in your current working directory and the data will be downloaded into it so that it can persist across sessions.
It is a rather raw-looking data frame…
head(local_budgets)
#> # A tibble: 6 x 15
#> vykaz vtab per_yr per_m ucjed ico kraj nuts `0CI_TYPE` paragraf polozka
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 051 0002… 2019 09 1000… 7508… CZ03 CZ03 3 6409 5364
#> 2 051 0002… 2019 09 1000… 7508… CZ03 CZ03 3 6409 5909
#> 3 051 0001… 2019 09 1000… 0006… CZ010 CZ01… 2 0000 1111
#> 4 051 0001… 2019 09 1000… 0006… CZ010 CZ01… 2 0000 1112
#> 5 051 0001… 2019 09 1000… 0006… CZ010 CZ01… 2 0000 1113
#> 6 051 0001… 2019 09 1000… 0006… CZ010 CZ01… 2 0000 1121
#> # … with 4 more variables: budget_adopted <dbl>, budget_amended <dbl>,
#> # budget_spending <dbl>, period_vykaz <date>
but it has been cleaned up, and can be enriched with any of the metadata codelists:
functional_categories <- sp_get_codelist("paragraf")
#> ℹ Building URL for codelist 'paragraf' - Paragraf
#> ✓ Storing codelist in '/var/folders/c8/pj33jytj233g8vr0tw4b2h7m0000gn/T/Rtmp52TEmf/statnipokladna/'
#> ℹ Set dest_dir for more control over downloaded files.
#> ℹ Processing codelist data
#> Warning: The `x` argument of `as_tibble.matrix()` must have column names if `.name_repair` is omitted as of tibble 2.0.0.
#> Using compatibility `.name_repair`.
#> This warning is displayed once every 8 hours.
#> Call `lifecycle::last_warnings()` to see where this warning was generated.
functional_categories
#> # A tibble: 550 x 9
#> paragraf skupina oddil pododdil nazev kr_nazev str_nazev start_date
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <date>
#> 1 0000 Příjmy Příj… Příjmy Pro … "Pro př… "Pro pří… 1900-01-01
#> 2 1011 Zemědě… Země… Zeměděl… Udrž… "" "" 1900-01-01
#> 3 1012 Zemědě… Země… Zeměděl… Podn… "Podn.,… "Podniká… 1900-01-01
#> 4 1013 Zemědě… Země… Zeměděl… Gene… "Genet.… "Genetic… 1900-01-01
#> 5 1014 Zemědě… Země… Zeměděl… Ozdr… "Ozdrav… "Ozdrav.… 1900-01-01
#> 6 1019 Zemědě… Země… Zeměděl… Osta… "Ost.ze… "Ostatní… 1900-01-01
#> 7 1021 Zemědě… Země… Regulac… Orga… "Regul.… "Regulac… 1900-01-01
#> 8 1022 Zemědě… Země… Regulac… Orga… "Regul.… "Reg.trh… 1900-01-01
#> 9 1023 Zemědě… Země… Regulac… Orga… "Regul.… "Organiz… 1900-01-01
#> 10 1024 Zemědě… Země… Regulac… Orga… "Regul.… "Reg.trh… 1900-01-01
#> # … with 540 more rows, and 1 more variable: end_date <date>
This contains all codes for this codelist, some of which are not valid for the time period of our core data. The function add_codelist()
resolves this automatically.
As you can see below, you can
Codelists are also cached, but you have one in your namespace, you can pass it as an object, provided that it has the right columns.
local_budgets %>%
sp_add_codelist(functional_categories) %>%
sp_add_codelist("polozka")
#> Joining, by = "paragraf"
#> Joining, by = "paragraf"
#> ℹ Building URL for codelist 'polozka' - Rozpočtová položka
#> ✓ Storing codelist in '/var/folders/c8/pj33jytj233g8vr0tw4b2h7m0000gn/T/Rtmp52TEmf/statnipokladna/'
#> ℹ Set dest_dir for more control over downloaded files.
#> ℹ Processing codelist data
#> Joining, by = "polozka"
#> Joining, by = "polozka"
#> # A tibble: 1,189,627 x 36
#> vykaz vtab per_yr per_m ucjed ico kraj nuts `0CI_TYPE` paragraf polozka
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 051 0002… 2019 09 1000… 7508… CZ03 CZ03 3 6409 5364
#> 2 051 0002… 2019 09 1000… 7508… CZ03 CZ03 3 6409 5909
#> 3 051 0001… 2019 09 1000… 0006… CZ010 CZ01… 2 0000 1111
#> 4 051 0001… 2019 09 1000… 0006… CZ010 CZ01… 2 0000 1112
#> 5 051 0001… 2019 09 1000… 0006… CZ010 CZ01… 2 0000 1113
#> 6 051 0001… 2019 09 1000… 0006… CZ010 CZ01… 2 0000 1121
#> 7 051 0001… 2019 09 1000… 0006… CZ010 CZ01… 2 0000 1122
#> 8 051 0001… 2019 09 1000… 0006… CZ010 CZ01… 2 0000 1211
#> 9 051 0001… 2019 09 1000… 0006… CZ010 CZ01… 2 0000 1332
#> 10 051 0001… 2019 09 1000… 0006… CZ010 CZ01… 2 0000 1333
#> # … with 1,189,617 more rows, and 25 more variables: budget_adopted <dbl>,
#> # budget_amended <dbl>, budget_spending <dbl>, period_vykaz <date>,
#> # skupina <chr>, oddil <chr>, pododdil <chr>,
#> # functional_categories_nazev <chr>, functional_categories_kr_nazev <chr>,
#> # functional_categories_str_nazev <chr>,
#> # functional_categories_start_date <date>,
#> # functional_categories_end_date <date>, polozka_start_date <date>,
#> # polozka_end_date <date>, druh <chr>, trida <chr>, seskupeni <chr>,
#> # podseskupeni <chr>, polozka_nazev <chr>, polozka_kr_nazev <chr>,
#> # polozka_str_nazev <chr>, kon_pol <lgl>, kon_okr <lgl>, kon_kraj <lgl>,
#> # kon_rep <lgl>
Download a whole “výkaz” (dataset/data dump):
sp_get_dataset("finm") # dataset ID, see `sp_datasets`
#> Warning: Either year or month not set.
#> Using defaults of 2018 and 12.
#> ● Set these values explicitly for reproducibility as the defaults may change in the future
#> to provide access to the latest data by default.
#> ℹ Building URL for dataset 'finm': FIN 2-12 M - Plnění rozpočtu MŘO, '2018-12'
#> ℹ Get the dataset documentation at 'http:/monitor.statnipokladna.cz/data/struktura/finm.xlsx'
#> ✓ Storing downloaded archive in and extracting to '/var/folders/c8/pj33jytj233g8vr0tw4b2h7m0000gn/T/Rtmp52TEmf/statnipokladna/finm/2018/12/'
#> ℹ Set dest_dir for more control over downloaded files.
#> [1] "/var/folders/c8/pj33jytj233g8vr0tw4b2h7m0000gn/T//Rtmp52TEmf/statnipokladna/finm/2018/12/FINM201_2018012.csv"
#> [2] "/var/folders/c8/pj33jytj233g8vr0tw4b2h7m0000gn/T//Rtmp52TEmf/statnipokladna/finm/2018/12/FINM202_2018012.csv"
#> [3] "/var/folders/c8/pj33jytj233g8vr0tw4b2h7m0000gn/T//Rtmp52TEmf/statnipokladna/finm/2018/12/FINM203_2018012.csv"
#> [4] "/var/folders/c8/pj33jytj233g8vr0tw4b2h7m0000gn/T//Rtmp52TEmf/statnipokladna/finm/2018/12/FINM204_2018012.csv"
#> [5] "/var/folders/c8/pj33jytj233g8vr0tw4b2h7m0000gn/T//Rtmp52TEmf/statnipokladna/finm/2018/12/FINM205_2018012.csv"
#> [6] "/var/folders/c8/pj33jytj233g8vr0tw4b2h7m0000gn/T//Rtmp52TEmf/statnipokladna/finm/2018/12/FINM207_2018012.csv"
This will put the files in a temp directory.
Then look at its documentation:
statnipokladna::sp_get_dataset_doc("finm")
#> Getting dataset documentation from http://monitor.statnipokladna.cz/data/struktura/finm.xlsx
#> File downloaded to ./finm.xlsx.
You can get details of all the available tables in the sp_tables
data frame; for datasets, see sp_datasets
.
Note that while the package provides a bridge from complicated data dumps to a clean data structure, you still need quite a bit of domain knowledge to be able analyse the data safely.
See the “How the data works” vignette (in Czech only, the terminology is impossible to translate) for an overview of the structure of the data on which this package draws. This also contains some notes useful for interpreting the data.
A subset of this information is in the Get started vignette.
There is also a log of various data gotchas I discovered, also in Czech only, stored in the data issues vignette.
A basic glossary of some of the terms used in the data sets is at http://monitor.statnipokladna.cz/metodika/.
Not created or endorsed by the Czech Ministry of Finance, who produce the data - but they definitely deserve credit for releasing the data and maintaining the application.
Thanks to @smallhillcz and the Státní pokladna/Monitor developers and maintainers for responding to queries and generally keeping the thing running.
See CONTRIBUTING.md for a guide on how to contribute to the project.
Please note that the ‘statnipokladna’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.