Get a list of available data sources

Usage

mi_sources(level, year = NULL, limit = 1000)

Arguments

level: a character string specifying the NUTS level ("0", "1", "2", or "3"). You can also always check valid NUTS levels using mi_nuts_levels.
year: an integer of length 1, specifying the year. Optional.
limit: An integer specifying the maximum number of results to return. Default is 2000.

Value

a tibble of sources with the following columns:

source_name: name of the data source
short_description: short description of the data source
description: description of the data source

Examples


# \donttest{
# get up to 10 sources for NUTS level 3
mi_sources("3", limit = 10)
#> # A tibble: 10 × 3
#>    source_name    short_description      description                            
#>    <chr>          <chr>                  <chr>                                  
#>  1 DEMO_R_D3AREA  "Area of regions"      Area by NUTS 3 region (ESTAT)          
#>  2 PROJ_19RAASFR3 "Fertility assumption" Assumptions for fertility rates by age…
#>  3 PROJ_19RAASMR3 "Death assumptions"    Assumptions for probability of dying b…
#>  4 BD_HGNACE2_R3  "Business demography " Business demography and high growth en…
#>  5 BD_SIZE_R3     "Business demography " Business demography by size class and …
#>  6 CENS_11DWOB_R3 "Dwellings by groups"  Conventional dwellings by occupancy st…
#>  7 CRIM_GEN_REG   "Crimes by region"     Crimes recorded by the police by NUTS …
#>  8 DEMO_R_MAGEC3  "Deaths by goups"      Deaths by age group, sex and NUTS 3 re…
#>  9 DEMO_R_DEATHS  "Deaths by region"     Deaths (total) by NUTS 3 region (ESTAT)
#> 10 CENS_01RDHH    "Dwellings by type"    Dwellings by type of housing, building…

# get all sources for NUTS level 3 and year 2020
mi_sources("3", year = 2020)
#> # A tibble: 18 × 3
#>    source_name    short_description      description                            
#>    <chr>          <chr>                  <chr>                                  
#>  1 PROJ_19RAASFR3 "Fertility assumption" Assumptions for fertility rates by age…
#>  2 PROJ_19RAASMR3 "Death assumptions"    Assumptions for probability of dying b…
#>  3 BD_HGNACE2_R3  "Business demography " Business demography and high growth en…
#>  4 BD_SIZE_R3     "Business demography " Business demography by size class and …
#>  5 DEMO_R_MAGEC3  "Deaths by goups"      Deaths by age group, sex and NUTS 3 re…
#>  6 DEMO_R_DEATHS  "Deaths by region"     Deaths (total) by NUTS 3 region (ESTAT)
#>  7 BD_ENACE2_R3   "Employer demography"  Employer business demography by NACE R…
#>  8 DEMO_R_FIND3   "Fertility indicators" Fertility indicators by NUTS 3 region …
#>  9 ookla          "Ookla internet speed" Fixed broadband and mobile (cellular) …
#> 10 DEMO_R_FAGEC3  "Live births by group" Live births by age group of the mother…
#> 11 DEMO_R_BIRTHS  "Live births, regions" Live births (total) by NUTS 3 region (…
#> 12 pm25           "Air particulates"     PM2.5 Satellite-derived particulate ma…
#> 13 DEMO_R_GIND3   "Population change"    Population change - Demographic balanc…
#> 14 DEMO_R_D3DENS  "Population density"   Population density by NUTS 3 region (E…
#> 15 PROJ_19RALEXP3 "Life expectancy"      Projected life expectancy by age (reac…
#> 16 REGION_SOCIAL  "Indicators Soc & Env" Regional Social and Environmental indi…
#> 17 ghs_smod       "Settlement type"      Satellite-based settlement types based…
#> 18 REGION_ST      "Short-term stats"     Short-term regional statistics (OECD)  

# }