Download a table of data from Kolada. Data is selected based on three metadata dimensions: KPI (ID), municipality (ID) and period (years). You must supply arguments for at least two of these three dimensions. If a dimension is omitted, all available data for that dimension will be downloaded.
get_values(
kpi = NULL,
municipality = NULL,
period = NULL,
ou = NULL,
unit_type = "municipality",
max_results = NULL,
simplify = TRUE,
verbose = FALSE
)
What kpis should be fetched? Can be a single name or a vector of names.
For which municipalities should data be fetched? Can be a single name or a vector of names.
For what years should data be fetched? Can be one or more four-digit integers or character strings.
(Optional) for what Operating Units should data be fetched? Only available for certain KPIs.
One of "municipality"
or "ou"
. Whether to
fetch data for Municipalities or Organizational Units.
(Optional) Specify the maximum number of results returned by the query.
Whether to make results more human readable.
Whether to print the call to the Kolada API as a message to the R console.
A tibble containing Kolada values and metadata.
# Download data for KPIs for Gross Regional Product ("BRP" in Swedish)
# for three municipalities
brp_kpi <- get_kpi(
id = c("N03068", "N03069", "N03070", "N03700", "N03701")
) %>%
kpi_search("BRP") %>%
kpi_extract_ids()
munic_sample <- get_municipality() %>%
municipality_name_to_id(c("Stockholm", "Arboga", "Lund"))
grp_data <- get_values(
kpi = brp_kpi,
municipality = munic_sample
)
# If you already know the ID numbers you are looking for,
# you can use these directly as argments.
grp_data <- get_values(
kpi = c("N03700", "N03701"),
municipality = c("0180", "1480", "1280")
)
# To download OU data instead of Municipality data, set the parameter
# "unit_type" to "ou".
ou_data <- get_values(
kpi = "N15033",
ou = "V15E144001101",
unit_type = "ou"
)