The robonomistClient package is a robust R client for effortless access to statistical data. It empowers researchers, analysts, and developers to easily discover, retrieve, and analyze up-to-date data from numerous national and international sources — all in tidy, analysis-ready formats.
Key Features
The main features of robonomistClient include:
Comprehensive Data Coverage
Access data from national statistical agencies, international organizations, and regional sources — all in one place. Spend less time searching for data and more time analyzing it.
- Eurostat, OECD, World Bank, European Central Bank, and more.
High Data Fidelity and Trust
All data is reliable and accurately reflects the information from official statistical agencies. Datasets include comprehensive metadata, ensuring your analysis is based on credible and transparent information.
- Full transparency on data sources.
- Detailed metadata included.
Flexibility in Data Retrieval
Customize the way data is retrieved to fit your specific needs:
- Multilingual support
- Choose between variable labels or codes.
- Interpret time variables as dates or raw values.
Seamless Integration for Dynamic Workflows
Designed for robust integration with R, robonomistClient makes it easy to build dynamic documents and automatically updating applications:
- Provides a stable API, reducing disruptions from changes in official statistics APIs.
- Focus on insights, not data wrangling.
Datasources
The robonomistClient package provides seamless and efficient access to a wide range of datasources via the Robonomist Data Server. With support for 101 636 up-to-date data tables across 60 distinct datasources and 13 languages, the package is designed to streamline your data analysis workflow.
International Datasources
- Global Institutions: OECD, International Monetary Fund (IMF), World Bank, United Nations Economic Commission for Europe Statistical Database (UNECE), United Nations Conference on Trade and Development (UNCTAD), FAO (Food and Agriculture Organization), Bank for International Settlements (BIS).
- European Union: Eurostat, European Commission, European Central Bank (ECB).
- Nordic Countries: Statistics Sweden, Swedish National Institute of Economic Research, Swedish Agricultural Agency, Statistics Norway, Statistics Denmark, Statistics Iceland, Statistics Estonia, Nordic Statistics Database.
Finnish Datasources
- Statistics Finland: StatFin, StatFin archive databases, Municipal figures & financial data, Paavo postal code area statistics, experimental statistics, immigrants and integration database.
- Regional Data: Helsingin seudun aluesarjat -tilastotietokanta, Helsingin ympäristötilasto.
- National Agencies: Finnish Tax Administration, Finnish Centre for Pensions, Natural Resources Institute Finland (LUKE), Traficom (Finnish Transport and Communications Agency), Customs Finland, THL Sotkanet, Vipunen (Education Statistics Finland), Fingrid, TutkiHallintoa.fi (Valtiokonttori).
Thematic & Specialized Datasources
- Energy & Environment: Entso-E Transparency Platform, U.S. Energy Information Administration database, Fingrid.
- Financial: Deutsche Bundesbank time series database, FRED (Federal Reserve Economic Data**.
- Health & Pandemic Data: THL Epirapo, ECDC.
This list highlights just some of the many datasources available through the robonomistClient package.
Getting started
To set up a Robonomist Data Server for your organization, contact team@robonomist.com.
1. Install the Package
Install the package from GitHub:
# Install devtools if needed
# install.packages("devtools")
# Install robonomistClient from GitHub
devtools::install_github("robonomist/robonomistClient")2. Set Up Your Connection
Set the hostname and access token for your Robonomist Data Server using set_robonomist_server():
library(robonomistClient)
set_robonomist_server(hostname = "hostname.com", access_token = "abc")3. Explore Available Datasources
See available datasources with the datasources() function:
#> # Robonomist Server Datasources
#> dataset title languages datasource available
#> <r_dataset> <chr> <iso2> <chr> <lgl>
#> 1 StatFin Statistics Finland, StatFin database fi,sv,en StatFin TRUE
#> 2 StatFin_Passiivi Statistics Finland, StatFin archive database fi,sv,en StatFin_P… TRUE
#> 3 Vero Finnish Tax Administration statistical database fi,sv,en Vero TRUE
#> 4 ec European Commission's Business and Consumer Surveys en EC TRUE
#> 5 kunnat Key statistics of municipalities, Statistics Finland fi,sv,en KuntienAv… TRUE
#> 6 kunnat Financial data reported by municipalities and joint municipal… fi,sv,en KuntienTa… TRUE
#> 7 paavo Statistics Finland's Paavo database fi,sv,en Paavo TRUE
#> 8 tulli Finnish Customs, Uljas Statistical Database fi,sv,en Tulli TRUE
#> 9 luke Statistics database of Natural Resources Institute Finland (L… fi,sv,en Luke TRUE
#> 10 etk Finnish Centre for Pensions' statistical database fi,sv,en ETK TRUE
#> # ℹ 50 more rows4. Search and Retrieve Data Tables
Use the data() function to search and list data tables:
data()#> # Robonomist Database search results
#> id title lang
#> <r_id> <chr> <chr>
#> 1 StatFin/adopt/statfin_adopt_pxt_11lv.px 11lv -- Adoptiot lapsen syntymämaan, ikäryhmän ja sukupuolen se… fi
#> 2 StatFin/adopt/statfin_adopt_pxt_13qh.px 13qh -- Adoptiot adoptoitavan vanhempien mukaan, 1999-2024 fi
#> 3 StatFin/aku/statfin_aku_pxt_12dz.px 12dz -- Aikuiskoulutukseen osallistuminen (ml. työhön tai ammat… fi
#> 4 StatFin/aku/statfin_aku_pxt_12ea.px 12ea -- Aikuiskoulutukseen osallistuminen (ml. työhön tai ammat… fi
#> 5 StatFin/aku/statfin_aku_pxt_14bu.px 14bu -- Aikuiskoulutukseen osallistuminen (ml. työhön tai ammat… fi
#> 6 StatFin/aku/statfin_aku_pxt_14bv.px 14bv -- Aikuiskoulutukseen osallistuminen (ml. työhön tai ammat… fi
#> 7 StatFin/ava/statfin_ava_pxt_12a9.px 12a9 -- Perusopetuksen vuosiluokkien 1-9 ja lisäopetuksen suori… fi
#> 8 StatFin/ava/statfin_ava_pxt_12aa.px 12aa -- Aikuisten perusopetuksen oppimäärän suorittaneiden kiel… fi
#> 9 StatFin/ava/statfin_ava_pxt_12ad.px 12ad -- Toisen asteen opiskelijoiden valitsemat vieraat kielet,… fi
#> 10 StatFin/ava/statfin_ava_pxt_139d.px 139d -- Toisen asteen opiskelijoiden valitsemien vieraiden kiel… fi
#> # ℹ 179,294 more rowsSearch for tables related to employment:
data("employment eurostat")#> # Robonomist Database search results
#> id title lang
#> <r_id> <chr> <chr>
#> 1 eurostat/bd_9pm_r2 High growth enterprises (growth by 10% or more) and related employment by … en
#> 2 eurostat/bd_9pm_r2$dv_2421 High growth enterprises (growth by 10% or more) and related employment by … en
#> 3 eurostat/bd_hg High growth enterprises and related employment by NACE Rev. 2 activity en
#> 4 eurostat/bd_hg$dv_2307 High growth enterprises and related employment by NACE Rev. 2 activity en
#> 5 eurostat/bd_hg_micro High growth micro enterprises and related employment by NACE Rev. 2 activi… en
#> 6 eurostat/bd_hg_micro$dv_2422 High growth micro enterprises and related employment by NACE Rev. 2 activi… en
#> 7 eurostat/bs_bs10_00 Turnover by client specialisation and employment size class (2000) en
#> 8 eurostat/bs_bs1_01 SBS variables by product specialisation and by employment size class for d… en
#> 9 eurostat/bs_bs1_03 SBS variables by employment size class for div 72 and 74 (2003) en
#> 10 eurostat/bs_bs1_04 Main economic variables by employment size class (2004) en
#> # ℹ 511 more rowsSearch for a specific dataset in another language:
data("eurostat/ lfs", lang = "de")You can search with keywords, partial names, or dataset IDs.
5. Retrieve a Specific Data Table
If you know the ID of a data table, retrieve it directly:
#> # Robonomist id: eurostat/bd_hg
#> # Title: High growth enterprises and related employment by NACE Rev. 2 activity
#> # Vintage: 2025-10-24 23:00:00
#> # A tibble: 6 × 6
#> freq indic_sbs nace_r2 geo time value
#> <chr> <chr> <chr> <chr> <date> <dbl>
#> 1 Annual Employees in young high-growth enterprises measured in employment - numb… Other … Port… 2023-01-01 NA
#> 2 Annual Employees in young high-growth enterprises measured in employment - numb… Other … Roma… 2023-01-01 112
#> 3 Annual Employees in young high-growth enterprises measured in employment - numb… Other … Swed… 2023-01-01 36
#> 4 Annual Employees in young high-growth enterprises measured in employment - numb… Other … Slov… 2023-01-01 0
#> 5 Annual Employees in young high-growth enterprises measured in employment - numb… Other … Slov… 2023-01-01 0
#> 6 Annual Employees in young high-growth enterprises measured in employment - numb… Other … Türk… 2023-01-01 NA6. Fetch Data Using Web Links
Copy a dataset link from your browser and pass it to data(). For example, if you find a dataset on the OECD website, you can retrieve it like this:
data("https://data-explorer.oecd.org/vis?tm=sna&pg=0&fs[0]=Measure%2C0%7CAquaculture%20production%23AQUA_PD%23&fc=Measure&snb=1&vw=tb&df[ds]=dsDisseminateFinalDMZ&df[id]=DSD_FISH_PROD%40DF_FISH_AQUA&df[ag]=OECD.TAD.ARP&df[vs]=1.0&pd=2010%2C&dq=.A.._T.T&ly[rw]=REF_AREA&ly[cl]=TIME_PERIOD&to[TIME_PERIOD]=false")#> ℹ The URL points to a data table in dataset "oecd".
#> ℹ For direct data retrieval, use:
#> > data_get("oecd/DSD_FISH_PROD@DF_FISH_AQUA..A.._T.T")
#> # Robonomist id: oecd/DSD_FISH_PROD@DF_FISH_AQUA
#> # Title: Aquaculture production
#> # Vintage: 2025-03-10 14:23:35
#> # A tibble: 1,456 × 10
#> REF_AREA FREQ MEASURE SPECIES UNIT_MEASURE time value UNIT_MULT DECIMALS CONVENTION
#> * <chr> <chr> <chr> <chr> <chr> <date> <dbl> <chr> <chr> <chr>
#> 1 Argentina Annual Aquaculture production Total Tonnes 1995-01-01 1474 0 0 LW
#> 2 Argentina Annual Aquaculture production Total Tonnes 1996-01-01 1322 0 0 LW
#> 3 Argentina Annual Aquaculture production Total Tonnes 1997-01-01 1314 0 0 LW
#> 4 Argentina Annual Aquaculture production Total Tonnes 1998-01-01 1040 0 0 LW
#> 5 Argentina Annual Aquaculture production Total Tonnes 1999-01-01 1218 0 0 LW
#> 6 Argentina Annual Aquaculture production Total Tonnes 2000-01-01 1784 0 0 LW
#> 7 Argentina Annual Aquaculture production Total Tonnes 2001-01-01 1340 0 0 LW
#> 8 Argentina Annual Aquaculture production Total Tonnes 2002-01-01 1457 0 0 LW
#> 9 Argentina Annual Aquaculture production Total Tonnes 2003-01-01 1647 0 0 LW
#> 10 Argentina Annual Aquaculture production Total Tonnes 2004-01-01 1848 0 0 LW
#> # ℹ 1,446 more rows7. Retrieve Data for Production Use
robonomistClient is a stable platform for building dynamic documents and real-time data applications. For production use, use the data_get() function with a data table ID for consistent results.
# Fetch a specific dataset using its ID for production use
production_data <- data_get("StatFin/synt/statfin_synt_pxt_12dx.px")