Retrieves National Income and Product Accounts data from the
Bureau of Economic Analysis API.
Requires a BEA API key saved in the BEA_API_KEY environment variable.
Usage
get_bea_nipa(
tables,
years,
frequency = c("year", "quarter", "month"),
underlying = FALSE,
metadata = FALSE,
bea_api_key = Sys.getenv("BEA_API_KEY")
)Arguments
- tables
Character vector of NIPA table names (e.g., "T10101", "T20305"). Can be a named vector to add custom names.
- years
Numeric vector of years or "ALL" for all available years
- frequency
Character string: "year" (annual), "quarter" (quarterly), or "month" (monthly). Can specify multiple as comma-separated string.
- underlying
Logical flag to use NIUnderlyingDetail dataset instead of NIPA (default: FALSE)
- metadata
Logical flag to return additional metadata columns (default: FALSE)
- bea_api_key
BEA API key (defaults to BEA_API_KEY environment variable)
Value
A tibble with columns: table_name, table_description, line_number, line_description, date_frequency, date, value, and date variables (year, quarter, month) appropriate to the frequency of data returned. Annual data includes only year; quarterly data includes year and quarter; monthly data includes year, quarter, and month. If metadata = TRUE, also includes unit_mult, metric_name, cl_unit, series_code, and note_text (list column). If tables is a named vector, includes a "name" column as the first column.
Examples
get_bea_nipa("T10101", years = 2020:2024, frequency = "quarter")
#> # A tibble: 500 × 9
#> table_name table_description line_number line_description date_frequency
#> <chr> <chr> <int> <chr> <chr>
#> 1 T10101 Table 1.1.1. Percent … 1 Gross domestic … quarter
#> 2 T10101 Table 1.1.1. Percent … 1 Gross domestic … quarter
#> 3 T10101 Table 1.1.1. Percent … 1 Gross domestic … quarter
#> 4 T10101 Table 1.1.1. Percent … 1 Gross domestic … quarter
#> 5 T10101 Table 1.1.1. Percent … 1 Gross domestic … quarter
#> 6 T10101 Table 1.1.1. Percent … 1 Gross domestic … quarter
#> 7 T10101 Table 1.1.1. Percent … 1 Gross domestic … quarter
#> 8 T10101 Table 1.1.1. Percent … 1 Gross domestic … quarter
#> 9 T10101 Table 1.1.1. Percent … 1 Gross domestic … quarter
#> 10 T10101 Table 1.1.1. Percent … 1 Gross domestic … quarter
#> # ℹ 490 more rows
#> # ℹ 4 more variables: date <date>, year <int>, quarter <int>, value <dbl>
get_bea_nipa(
c("gdp" = "T10101", "personal_income" = "T20305"),
years = 2023:2024,
frequency = "year"
)
#> # A tibble: 112 × 9
#> name table_name table_description line_number line_description
#> <chr> <chr> <chr> <int> <chr>
#> 1 gdp T10101 Table 1.1.1. Percent Change Fr… 1 Gross domestic …
#> 2 gdp T10101 Table 1.1.1. Percent Change Fr… 1 Gross domestic …
#> 3 gdp T10101 Table 1.1.1. Percent Change Fr… 2 Personal consum…
#> 4 gdp T10101 Table 1.1.1. Percent Change Fr… 2 Personal consum…
#> 5 gdp T10101 Table 1.1.1. Percent Change Fr… 3 Goods
#> 6 gdp T10101 Table 1.1.1. Percent Change Fr… 3 Goods
#> 7 gdp T10101 Table 1.1.1. Percent Change Fr… 4 Durable goods
#> 8 gdp T10101 Table 1.1.1. Percent Change Fr… 4 Durable goods
#> 9 gdp T10101 Table 1.1.1. Percent Change Fr… 5 Nondurable goods
#> 10 gdp T10101 Table 1.1.1. Percent Change Fr… 5 Nondurable goods
#> # ℹ 102 more rows
#> # ℹ 4 more variables: date_frequency <chr>, date <date>, year <int>,
#> # value <dbl>
get_bea_nipa("T10101", years = 2023, frequency = "year", metadata = TRUE)
#> # A tibble: 25 × 15
#> table_name table_description line_number line_description date_frequency
#> <chr> <chr> <int> <chr> <chr>
#> 1 T10101 Table 1.1.1. Percent … 1 Gross domestic … year
#> 2 T10101 Table 1.1.1. Percent … 2 Personal consum… year
#> 3 T10101 Table 1.1.1. Percent … 3 Goods year
#> 4 T10101 Table 1.1.1. Percent … 4 Durable goods year
#> 5 T10101 Table 1.1.1. Percent … 5 Nondurable goods year
#> 6 T10101 Table 1.1.1. Percent … 6 Services year
#> 7 T10101 Table 1.1.1. Percent … 7 Gross private d… year
#> 8 T10101 Table 1.1.1. Percent … 8 Fixed investment year
#> 9 T10101 Table 1.1.1. Percent … 9 Nonresidential year
#> 10 T10101 Table 1.1.1. Percent … 10 Structures year
#> # ℹ 15 more rows
#> # ℹ 10 more variables: date <date>, year <int>, quarter <int>, month <int>,
#> # value <dbl>, unit_mult <int>, metric_name <chr>, cl_unit <chr>,
#> # series_code <chr>, note_text <list>