Datasets:

OptimalSolution
/

databank-bea-io

year int16 2.01k 2.02k	commodity stringclasses 403 values	commodity_kind stringclasses 2 values	commodity_is_derived bool 2 classes	industry stringclasses 414 values	industry_kind stringclasses 5 values	industry_is_derived bool 2 classes	value float64 -339,295 37.1M	unit stringclasses 1 value
2,007	1111A0	commodity	false	1111A0	industry	false	24,160	MIO_USD
2,007	115000	commodity	false	1111A0	industry	false	222	MIO_USD
2,007	713900	commodity	false	1111A0	industry	false	160	MIO_USD
2,007	T017	total	true	1111A0	industry	false	24,543	MIO_USD
2,007	1111B0	commodity	false	1111B0	industry	false	60,998	MIO_USD
2,007	115000	commodity	false	1111B0	industry	false	470	MIO_USD
2,007	713900	commodity	false	1111B0	industry	false	338	MIO_USD
2,007	T017	total	true	1111B0	industry	false	61,806	MIO_USD
2,007	111200	commodity	false	111200	industry	false	18,453	MIO_USD
2,007	115000	commodity	false	111200	industry	false	169	MIO_USD
2,007	713900	commodity	false	111200	industry	false	122	MIO_USD
2,007	T017	total	true	111200	industry	false	18,744	MIO_USD
2,007	111300	commodity	false	111300	industry	false	18,684	MIO_USD
2,007	115000	commodity	false	111300	industry	false	172	MIO_USD
2,007	713900	commodity	false	111300	industry	false	123	MIO_USD
2,007	T017	total	true	111300	industry	false	18,979	MIO_USD
2,007	111400	commodity	false	111400	industry	false	18,309	MIO_USD
2,007	115000	commodity	false	111400	industry	false	169	MIO_USD
2,007	713900	commodity	false	111400	industry	false	122	MIO_USD
2,007	T017	total	true	111400	industry	false	18,600	MIO_USD
2,007	111900	commodity	false	111900	industry	false	20,776	MIO_USD
2,007	113000	commodity	false	111900	industry	false	721	MIO_USD
2,007	114000	commodity	false	111900	industry	false	1	MIO_USD
2,007	115000	commodity	false	111900	industry	false	196	MIO_USD
2,007	3219A0	commodity	false	111900	industry	false	12	MIO_USD
2,007	713900	commodity	false	111900	industry	false	139	MIO_USD
2,007	T017	total	true	111900	industry	false	21,843	MIO_USD
2,007	112120	commodity	false	112120	industry	false	35,639	MIO_USD
2,007	115000	commodity	false	112120	industry	false	326	MIO_USD
2,007	713900	commodity	false	112120	industry	false	235	MIO_USD
2,007	T017	total	true	112120	industry	false	36,200	MIO_USD
2,007	1121A0	commodity	false	1121A0	industry	false	56,569	MIO_USD
2,007	115000	commodity	false	1121A0	industry	false	459	MIO_USD
2,007	713900	commodity	false	1121A0	industry	false	330	MIO_USD
2,007	T017	total	true	1121A0	industry	false	57,358	MIO_USD
2,007	112300	commodity	false	112300	industry	false	32,995	MIO_USD
2,007	115000	commodity	false	112300	industry	false	305	MIO_USD
2,007	713900	commodity	false	112300	industry	false	219	MIO_USD
2,007	T017	total	true	112300	industry	false	33,519	MIO_USD
2,007	112A00	commodity	false	112A00	industry	false	23,393	MIO_USD
2,007	113000	commodity	false	112A00	industry	false	107	MIO_USD
2,007	115000	commodity	false	112A00	industry	false	187	MIO_USD
2,007	713900	commodity	false	112A00	industry	false	134	MIO_USD
2,007	T017	total	true	112A00	industry	false	23,821	MIO_USD
2,007	111400	commodity	false	113000	industry	false	39	MIO_USD
2,007	113000	commodity	false	113000	industry	false	18,999	MIO_USD
2,007	2332D0	commodity	false	113000	industry	false	30	MIO_USD
2,007	T017	total	true	113000	industry	false	19,068	MIO_USD
2,007	114000	commodity	false	114000	industry	false	6,426	MIO_USD
2,007	2332D0	commodity	false	114000	industry	false	11	MIO_USD
2,007	T017	total	true	114000	industry	false	6,437	MIO_USD
2,007	115000	commodity	false	115000	industry	false	18,528	MIO_USD
2,007	2332D0	commodity	false	115000	industry	false	17	MIO_USD
2,007	541511	commodity	false	115000	industry	false	0	MIO_USD
2,007	T017	total	true	115000	industry	false	18,545	MIO_USD
2,007	211000	commodity	false	211000	industry	false	224,168	MIO_USD
2,007	2123A0	commodity	false	211000	industry	false	153	MIO_USD
2,007	213111	commodity	false	211000	industry	false	13,979	MIO_USD
2,007	21311A	commodity	false	211000	industry	false	4,637	MIO_USD
2,007	233240	commodity	false	211000	industry	false	76	MIO_USD
2,007	332710	commodity	false	211000	industry	false	0	MIO_USD
2,007	333130	commodity	false	211000	industry	false	0	MIO_USD
2,007	324110	commodity	false	211000	industry	false	21,596	MIO_USD
2,007	325120	commodity	false	211000	industry	false	115	MIO_USD
2,007	325190	commodity	false	211000	industry	false	69	MIO_USD
2,007	325310	commodity	false	211000	industry	false	290	MIO_USD
2,007	424700	commodity	false	211000	industry	false	97	MIO_USD
2,007	541511	commodity	false	211000	industry	false	90	MIO_USD
2,007	541700	commodity	false	211000	industry	false	729	MIO_USD
2,007	T017	total	true	211000	industry	false	266,000	MIO_USD
2,007	211000	commodity	false	212100	industry	false	0	MIO_USD
2,007	212100	commodity	false	212100	industry	false	33,769	MIO_USD
2,007	2123A0	commodity	false	212100	industry	false	0	MIO_USD
2,007	21311A	commodity	false	212100	industry	false	2,209	MIO_USD
2,007	233240	commodity	false	212100	industry	false	5,052	MIO_USD
2,007	324110	commodity	false	212100	industry	false	0	MIO_USD
2,007	423A00	commodity	false	212100	industry	false	56	MIO_USD
2,007	541511	commodity	false	212100	industry	false	0	MIO_USD
2,007	541700	commodity	false	212100	industry	false	8	MIO_USD
2,007	T017	total	true	212100	industry	false	41,094	MIO_USD
2,007	212230	commodity	false	212230	industry	false	10,516	MIO_USD
2,007	2122A0	commodity	false	212230	industry	false	902	MIO_USD
2,007	21311A	commodity	false	212230	industry	false	545	MIO_USD
2,007	233240	commodity	false	212230	industry	false	797	MIO_USD
2,007	541511	commodity	false	212230	industry	false	1	MIO_USD
2,007	541700	commodity	false	212230	industry	false	14	MIO_USD
2,007	T017	total	true	212230	industry	false	12,775	MIO_USD
2,007	212230	commodity	false	2122A0	industry	false	580	MIO_USD
2,007	2122A0	commodity	false	2122A0	industry	false	11,570	MIO_USD
2,007	21311A	commodity	false	2122A0	industry	false	1,139	MIO_USD
2,007	233240	commodity	false	2122A0	industry	false	856	MIO_USD
2,007	423A00	commodity	false	2122A0	industry	false	0	MIO_USD
2,007	541511	commodity	false	2122A0	industry	false	2	MIO_USD
2,007	541700	commodity	false	2122A0	industry	false	21	MIO_USD
2,007	T017	total	true	2122A0	industry	false	14,167	MIO_USD
2,007	212310	commodity	false	212310	industry	false	14,312	MIO_USD
2,007	2123A0	commodity	false	212310	industry	false	203	MIO_USD
2,007	21311A	commodity	false	212310	industry	false	2,303	MIO_USD
2,007	233240	commodity	false	212310	industry	false	1,783	MIO_USD
2,007	327320	commodity	false	212310	industry	false	27	MIO_USD

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US Input-Output Accounts (BEA)

The US supply and use tables -- which industries make which commodities, and who consumes them -- at three levels of industry detail. Annual 1997-2023 at the Sector and Summary levels, plus the 2017 Detail benchmark.

Terms

Licence: public domain (US federal government work) (https://www.bea.gov/help/faq/125)
Attribution: Source: U.S. Bureau of Economic Analysis
Cite as: U.S. Bureau of Economic Analysis, Input-Output Accounts Data, 2024-12 release.
Source: https://www.bea.gov/itable/input-output

Redistributed by OptimalSolution LLC -- see DISCLAIMER.md. Redistribution only: no responsibility for the content, no endorsement or position, no affiliation with the publisher, no warranty. What was changed from the published data is recorded per dataset under bank.modifications and bank.changes.

Datasets

dataset	rows	coverage
`bea_supply_sector`	7,142	1997-2023
`bea_supply_summary`	41,740	1997-2023
`bea_supply_detail`	30,294	2007, 2012, 2017
`bea_use_sector`	12,665	1997-2023
`bea_use_summary`	121,974	1997-2023
`bea_use_detail`	159,538	2007, 2012, 2017

Read this before you aggregate

Both axes carry their own totals. T007, T017, T001, T005, T013-T019, VABAS and VAPRO are sums of other cells in the same table. Summing an axis without filtering *_is_derived double-counts. The manifest's default_filter drops them.
Not every non-industry code is a total. Final uses (F*), value added (V001, V003, the tax and subsidy rows), margins (Trade, Trans), taxes (TOP, SUB, MDTY) and imports (MCIF, MADJ) are real content, not aggregates. Filter on *_kind, not on 'is it in the scale'.
The published Sector tables are coarser than BEA's own Sector column. They merge manufacturing (31ND+33DG into 31G), finance (52+53 into FIRE), professional services (54+55+56 into PROF), education and health (61+62 into 6) and arts and hospitality (71+72 into 7). The scale carries both as sector and naics_sector; the build checks the merge numerically against the data.
The Sector and Summary tables differ in their final-demand columns too. Sector uses F020 and F100; Summary carries their components. Both are flagged, but they are not interchangeable.
Suppressed cells are dropped, not zeroed. BEA writes ... where a cell is not published; those rows are absent.
The Detail benchmarks spell the account codes differently. They pad to six characters (F01000 for F010, V00100 for V001) and upper-case the margins (TRADE, TRANS). Codes are stored as published, so a join across levels on the literal code will miss them; commodity_kind and industry_kind are level-independent and are the safe thing to filter on.
Other and Used are commodities only. Noncomparable imports, the rest-of-the-world adjustment, scrap and secondhand goods appear on the commodity axis with no matching industry.

Using it

library(arrow); library(dplyr)
d <- read_parquet("datasets/bea_use_summary/data/part-0.parquet")

# The core use matrix for one year, totals excluded.
d |>
  filter(year == 2023, !commodity_is_derived, !industry_is_derived,
         commodity_kind == "commodity", industry_kind == "industry") |>
  select(commodity, industry, value)

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