English | 日本語
dashboardapi is an unofficial R package for accessing the Statistics
Dashboard Web API provided by the Statistics Bureau of Japan. The API requires
no registration or API key.
The main workflow follows the same idea as bojapi and WDI: search metadata
for an indicator code, find any needed region codes, and retrieve observations
as a tidy data frame.
dashboard_search()/dashboard_indicators(): find indicator codes and inspect cycle, region, seasonal-adjustment, unit, source, and coveragedashboard_regions(): find Japanese municipality or ISO country codesdashboard_data(): retrieve normalized long or wide observationsdashboard_terms(),dashboard_events(), anddashboard_surveys(): access the API's auxiliary metadatadashboard_codes(): inspect common API enumerations offline- Automatic batching beyond the API limits of five indicators and 50 regions
- English and Japanese API responses, retries, timeouts, and rate-conscious pauses between automatically batched requests
- Typed API, HTTP, parsing, and no-data conditions
Install the development version from GitHub:
install.packages("remotes")
remotes::install_github("kenjimyzk/dashboardapi")To install from a local clone of the repository:
remotes::install_local(".")library(dashboardapi)
# 1. Find an indicator
population_meta <- dashboard_search(
"Total population (Both sexes)",
lang = "en"
)
population_meta[, c(
"indicator_code", "name", "cycle_name",
"regional_rank_name", "unit"
)]
# 2. Inspect region codes
prefectures <- dashboard_regions(
parent_region_code = "00000",
lang = "en"
)
# 3. Retrieve annual Japanese population
population <- dashboard_data(
indicator_code = c(population = "0201010000000010000"),
region_code = "00000",
time_from = "2020CY00",
time_to = "2024CY00",
cycle = "year",
regional_rank = "japan",
seasonal = "original",
lang = "en"
)The time column preserves the API's exact period code. The date column
contains the first day of the represented period for analysis:
20240100 becomes 2024-01-01, 20242Q00 becomes 2024-04-01,
2024CY00 becomes 2024-01-01, and 2024FY00 becomes 2024-04-01.
prefecture_population <- dashboard_data(
indicator_code = c(population = "0201010000000010000"),
region_code = c("13000", "27000"),
time_from = "2020CY00",
time_to = "2024CY00",
cycle = "year",
regional_rank = "prefecture",
seasonal = "original",
wide = TRUE
)The official API page asks users not to generate a large access volume in a
short period. A request with more than five indicators or 50 regions is split
automatically, and dashboardapi waits at least one second between those
requests.
options(
dashboardapi.wait = 2,
dashboardapi.timeout = 60,
dashboardapi.retries = 3
)API errors have class dashboard_api_response_error, communication errors
have class dashboard_http_error, and unexpected structures have class
dashboard_parse_error. A successful no-data response issues a
dashboard_no_data_warning and returns a typed empty tibble.
The official Copyright Policy distinguishes three requirements when content from the Statistics Dashboard is published:
- Cite the source.
- If content or data are edited, say so and identify the editing entity.
- If a service uses the API, display the specified API credit.
dashboard_api_credit() returns the corresponding source citation,
edited-content template, and API credit. Replace <entity> before publishing
edited content:
attribution <- dashboard_api_credit("en")
attribution$source
attribution$processed
attribution$creditdashboardapi is independently developed and is not affiliated with or
endorsed by the Statistics Bureau of Japan. Its MIT license does not relicense
government or third-party data, metadata, code systems, or official texts.
Check any individual rights statement before reusing third-party content.