Scrapes https://api.census.gov/data.json and returns a dataframe that includes columns for dataset title, description, name, vintage, url, dataset type, and other useful fields.
Arguments
- name
Optional complete or partial API dataset programmatic name. For example, "acs", "acs/acs5", "acs/acs5/subject". If using a partial name, this needs to be the left-most part of the dataset name before
/, e.g. "timeseries/eits" or "dec" or "acs/acs5".- vintage
Optional vintage (year) of dataset.
Value
A data frame with the following columns:
title: Short written description of the dataset.
name: Programmatic name of the dataset.
vintage: Year of the survey, for use with microdata and aggregate datasets.
type: Dataset type, which is either "Aggregate", "Microdata", or "Timeseries".
temporal: Time period of the dataset. Warning: not always documented.
spatial: Spatial region of the dataset. Warning: not always documented.
url: Base URL of the dataset endpoint.
modified: Date last modified. Warning: sometimes out of date.
description: Long written description of the dataset.
contact: Email address for specific questions about the Census Bureau survey.
See also
Other metadata:
listCensusMetadata(),
makeVarlist()
Examples
# Get information about every dataset available in the APIs
apis <- listCensusApis()
head(apis)
#> title name
#> 1 Current Population Survey: Basic Monthly cps/basic/feb
#> 2 Current Population Survey: Basic Monthly cps/basic/jan
#> 3 Current Population Survey Annual Social and Economic Supplement cps/asec/mar
#> 4 Current Population Survey: Basic Monthly cps/basic/apr
#> 5 Current Population Survey: Basic Monthly cps/basic/aug
#> 6 Current Population Survey: Basic Monthly cps/basic/dec
#> vintage type temporal spatial
#> 1 2024 Microdata 2024-02/2024-02 United States
#> 2 2024 Microdata 2024-01/2024-01 United States
#> 3 2023 Microdata 2023-03/2023-03 United States
#> 4 2023 Microdata 2023-04/2023-04 United States
#> 5 2023 Microdata 2023-08/2023-08 United States
#> 6 2023 Microdata 2023-12/2023-12 United States
#> url modified
#> 1 http://api.census.gov/data/2024/cps/basic/feb 2024-01-11 15:35:41.0
#> 2 http://api.census.gov/data/2024/cps/basic/jan 2024-01-11 15:35:41.0
#> 3 http://api.census.gov/data/2023/cps/asec/mar 2023-08-14 09:09:01.0
#> 4 http://api.census.gov/data/2023/cps/basic/apr 2023-01-10 15:11:40.0
#> 5 http://api.census.gov/data/2023/cps/basic/aug 2023-01-10 15:11:40.0
#> 6 http://api.census.gov/data/2023/cps/basic/dec 2023-01-10 15:11:40.0
#> description
#> 1 To provide estimates of employment, unemployment, and other characteristics of the general labor force, of the population as a whole, and of various subgroups of the population. Monthly labor force data for the country are used by the Bureau of Labor Statistics (BLS) to determine the distribution of funds under the Job Training Partnership Act. These data are collected through combined computer-assisted personal interviewing (CAPI) and computer-assisted telephone interviewing (CATI). In addition to the labor force data, the CPS basic funding provides annual data on work experience, income, health insurance, and migration data from the Annual Social and Economic Supplement (ASEC), and on school enrollment of the population from the October Supplement. Other supplements, some of which are sponsored by other agencies, are conducted biennially or intermittently.
#> 2 To provide estimates of employment, unemployment, and other characteristics of the general labor force, of the population as a whole, and of various subgroups of the population. Monthly labor force data for the country are used by the Bureau of Labor Statistics (BLS) to determine the distribution of funds under the Job Training Partnership Act. These data are collected through combined computer-assisted personal interviewing (CAPI) and computer-assisted telephone interviewing (CATI). In addition to the labor force data, the CPS basic funding provides annual data on work experience, income, health insurance, and migration data from the Annual Social and Economic Supplement (ASEC), and on school enrollment of the population from the October Supplement. Other supplements, some of which are sponsored by other agencies, are conducted biennially or intermittently.
#> 3 The Annual Social and Economic Supplement or March CPS supplement is the primary source of detailed information on income and work experience in the United States. Numerous publications based on this survey are issued each year by the Bureaus of Labor Statistics and Census. A public-use microdata file is available for private researchers, who also produce many academic and policy-related documents based on these data. The Annual Social and Economic Supplement is used to generate the annual Population Profile of the United States, reports on geographical mobility and educational attainment, and detailed analysis of money income and poverty status. The labor force and work experience data from this survey are used to profile the U.S. labor market and to make employment projections. To allow for the same type of in-depth analysis of hispanics, additional hispanic sample units are added to the basic CPS sample in March each year. Additional weighting is also performed so that estimates can be made for households and families, in addition to persons.
#> 4 To provide estimates of employment, unemployment, and other characteristics of the general labor force, of the population as a whole, and of various subgroups of the population. Monthly labor force data for the country are used by the Bureau of Labor Statistics (BLS to determine the distribution of funds under the Job Training Partnership Act. These data are collected through combined computer-assisted personal interviewing (CAPI) and computer-assisted telephone interviewing (CATI). In addition to the labor force data, the CPS basic funding provides annual data on work experience, income, health insurance, and migration data from the Annual Social and Economic Supplement (ASEC), and on school enrollment of the population from the October Supplement. Other supplements, some of which are sponsored by other agencies, are conducted biennially or intermittently.
#> 5 To provide estimates of employment, unemployment, and other characteristics of the general labor force, of the population as a whole, and of various subgroups of the population. Monthly labor force data for the country are used by the Bureau of Labor Statistics (BLS to determine the distribution of funds under the Job Training Partnership Act. These data are collected through combined computer-assisted personal interviewing (CAPI) and computer-assisted telephone interviewing (CATI). In addition to the labor force data, the CPS basic funding provides annual data on work experience, income, health insurance, and migration data from the Annual Social and Economic Supplement (ASEC), and on school enrollment of the population from the October Supplement. Other supplements, some of which are sponsored by other agencies, are conducted biennially or intermittently.
#> 6 To provide estimates of employment, unemployment, and other characteristics of the general labor force, of the population as a whole, and of various subgroups of the population. Monthly labor force data for the country are used by the Bureau of Labor Statistics (BLS) to determine the distribution of funds under the Job Training Partnership Act. These data are collected through combined computer-assisted personal interviewing (CAPI) and computer-assisted telephone interviewing (CATI). In addition to the labor force data, the CPS basic funding provides annual data on work experience, income, health insurance, and migration data from the Annual Social and Economic Supplement (ASEC), and on school enrollment of the population from the October Supplement. Other supplements, some of which are sponsored by other agencies, are conducted biennially or intermittently.
#> contact
#> 1 dsd.cps@census.gov
#> 2 dsd.cps@census.gov
#> 3 dsd.cps@census.gov
#> 4 dsd.cps@census.gov
#> 5 dsd.cps@census.gov
#> 6 dsd.cps@census.gov
# Get information about all vintage 2022 datasets
apis_2022 <- listCensusApis(vintage = 2022)
head(apis_2022)
#> title
#> 1 American Community Survey: 1-Year Estimates: Detailed Tables 1-Year
#> 2 American Community Survey: 1-Year Estimates: Comparison Profiles 1-Year
#> 3 American Community Survey: 1-Year Estimates: Data Profiles 1-Year
#> 4 2022 American Community Survey: 1-Year Estimates - Public Use Microdata Sample
#> 5 2022 American Community Survey: 1-Year Estimates - Public Use Microdata Sample Puerto Rico
#> 6 American Community Survey: 1-Year Estimates: Selected Population Profiles 1-Year
#> name vintage type temporal spatial
#> 1 acs/acs1 2022 Aggregate 2022/2022 US
#> 2 acs/acs1/cprofile 2022 Aggregate 2022/2022 US
#> 3 acs/acs1/profile 2022 Aggregate 2022/2022 US
#> 4 acs/acs1/pums 2022 Microdata 2022/2022 US
#> 5 acs/acs1/pumspr 2022 Microdata 2022/2022 Puerto Rico
#> 6 acs/acs1/spp 2022 Aggregate 2022/2022 US
#> url modified
#> 1 http://api.census.gov/data/2022/acs/acs1 2023-04-24 14:51:53.0
#> 2 http://api.census.gov/data/2022/acs/acs1/cprofile 2023-04-24 14:49:08.0
#> 3 http://api.census.gov/data/2022/acs/acs1/profile 2023-04-24 14:49:41.0
#> 4 http://api.census.gov/data/2022/acs/acs1/pums 2023-06-08 10:03:42.0
#> 5 http://api.census.gov/data/2022/acs/acs1/pumspr 2023-06-08 10:03:09.0
#> 6 http://api.census.gov/data/2022/acs/acs1/spp 2023-04-24 14:51:20.0
#> description
#> 1 The American Community Survey (ACS) is an ongoing survey that provides data every year -- giving communities the current information they need to plan investments and services. The ACS covers a broad range of topics about social, economic, demographic, and housing characteristics of the U.S. population. Much of the ACS data provided on the Census Bureau's Web site are available separately by age group, race, Hispanic origin, and sex. Summary files, Subject tables, Data profiles, and Comparison profiles are available for the nation, all 50 states, the District of Columbia, Puerto Rico, every congressional district, every metropolitan area, and all counties and places with populations of 65,000 or more. Detailed Tables contain the most detailed cross-tabulations published for areas 65k and more. The data are population counts. There are over 31,000 variables in this dataset.
#> 2 The American Community Survey (ACS) is an ongoing survey that provides data every year -- giving communities the current information they need to plan investments and services. The ACS covers a broad range of topics about social, economic, demographic, and housing characteristics of the U.S. population. Much of the ACS data provided on the Census Bureau's Web site are available separately by age group, race, Hispanic origin, and sex. Summary files, Subject tables, Data profiles, and Comparison profiles are available for the nation, all 50 states, the District of Columbia, Puerto Rico, every congressional district, every metropolitan area, and all counties and places with populations of 65,000 or more. Comparison profiles are similar to Data profiles but also include comparisons with past-year data. The current year data are compared with each of the last four years of data and include statistical significance testing. There are over 1,000 variables in this dataset.
#> 3 The American Community Survey (ACS) is a US-wide survey designed to provide communities a fresh look at how they are changing. The ACS replaced the decennial census long form in 2010 and thereafter by collecting long form type information throughout the decade rather than only once every 10 years. Questionnaires are mailed to a sample of addresses to obtain information about households -- that is, about each person and the housing unit itself. The American Community Survey produces demographic, social, housing and economic estimates in the form of 1 and 5-year estimates based on population thresholds. The strength of the ACS is in estimating population and housing characteristics. The data profiles provide key estimates for each of the topic areas covered by the ACS for the us, all 50 states, the District of Columbia, Puerto Rico, every congressional district, every metropolitan area, and all counties and places with populations of 65,000 or more. Although the ACS produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the US, states, counties, cities and towns, and estimates of housing units for states and counties. For 2010 and other decennial census years, the Decennial Census provides the official counts of population and housing units.
#> 4 The American Community Survey (ACS) Public Use Microdata Sample (PUMS) contains a sample of responses to the ACS. The ACS PUMS dataset includes variables for nearly every question on the survey, as well as many new variables that were derived after the fact from multiple survey responses (such as poverty status). Each record in the file represents a single person, or, in the household-level dataset, a single housing unit. In the person-level file, individuals are organized into households, making possible the study of people within the contexts of their families and other household members. Individuals living in Group Quarters, such as nursing facilities or college facilities, are also included on the person file. ACS PUMS data are available at the nation, state, and Public Use Microdata Area (PUMA) levels. PUMAs are special non-overlapping areas that partition each state into contiguous geographic units containing roughly 100,000 people each. ACS PUMS files for an individual year, such as 2022, contain data on approximately one percent of the United States population.
#> 5 The Public Use Microdata Sample (PUMS) for Puerto Rico (PR) contains a sample of responses to the Puerto Rico Community Survey (PRCS). The PRCS is similar to, but separate from, the American Community Survey (ACS). The PRCS collects data about the population and housing units in Puerto Rico. Puerto Rico data is not included in the national PUMS files. It is published as a state equivalent file and has a State FIPS code of "72". The file includes variables for nearly every question on the survey, as well as many new variables that were derived after the fact from multiple survey responses (such as poverty status). Each record in the file represents a single person, or, in the household-level dataset, a single housing unit. In the person-level file, individuals are organized into households, making possible the study of people within the contexts of their families and other household members. Individuals living in Group Quarters, such as nursing facilities or college facilities, are also included on the person file. Data are available at the state and Public Use Microdata Area (PUMA) levels. PUMAs are special non-overlapping areas that partition Puerto Rico into contiguous geographic units containing roughly 100,000 people each. The Puerto Rico PUMS file for an individual year, such as 2022, contain data on approximately one percent of the Puerto Rico population.
#> 6 Selected Population Profiles provide broad social, economic, and housing profiles for a large number of race, ethnic, ancestry, and country/region of birth groups. The data are presented as population counts for the total population and various subgroups and percentages.
#> contact
#> 1 acso.users.support@census.gov
#> 2 acso.users.support@census.gov
#> 3 acso.users.support@census.gov
#> 4 acso.users.support@census.gov
#> 5 acso.users.support@census.gov
#> 6 acso.users.support@census.gov
# Get information about all timeseries datasets
apis_timeseries <- listCensusApis(name = "timeseries")
head(apis_timeseries)
#> title
#> 1 Annual Economic Surveys: Annual Survey of Manufactures Area
#> 2 Economic Surveys: Annual Survey of Manufactures: Annual Survey of Manufactures Area
#> 3 Annual Economic Surveys: Annual Survey of Manufactures Benchmark 2017
#> 4 Time Series Annual Survey of Manufactures: Statistics for Industry Groups and Industries
#> 5 Time Series Annual Survey of Manufactures: Value of Shipments for Product Classes
#> 6 Time Series Annual Survey of Manufactures: Statistics for All Manufacturing by State
#> name type temporal spatial
#> 1 timeseries/asm/area2012 Timeseries <NA> <NA>
#> 2 timeseries/asm/area2017 Timeseries 2018/2021 United States
#> 3 timeseries/asm/benchmark2017 Timeseries <NA> <NA>
#> 4 timeseries/asm/industry Timeseries <NA> United States
#> 5 timeseries/asm/product Timeseries <NA> United States
#> 6 timeseries/asm/state Timeseries <NA> United States
#> url modified
#> 1 http://api.census.gov/data/timeseries/asm/area2012 2018-12-13 00:00:00.0
#> 2 http://api.census.gov/data/timeseries/asm/area2017 2020-03-17 00:00:00.0
#> 3 http://api.census.gov/data/timeseries/asm/benchmark2017 2021-03-17 00:00:00.0
#> 4 http://api.census.gov/data/timeseries/asm/industry 2018-06-29
#> 5 http://api.census.gov/data/timeseries/asm/product 2017-12-15
#> 6 http://api.census.gov/data/timeseries/asm/state 2017-12-15
#> description
#> 1 The Annual Survey of Manufactures (ASM) provides key intercensal measures of manufacturing activity, products, and location for the public and private sectors. The ASM provides the best current measure of current U.S. manufacturing industry outputs, inputs, and operating status, and is the primary basis for updates of the Longitudinal Research Database (LRD). Census Bureau staff and academic researchers with sworn agent status use the LRD for micro data analysis.
#> 2 The Annual Survey of Manufactures (ASM) provides key intercensal measures of manufacturing activity, products, and location for the public and private sectors. The ASM provides the best current measure of current U.S. manufacturing industry outputs, inputs, and operating status, and is the primary basis for updates of the Longitudinal Research Database (LRD). Census Bureau staff and academic researchers with sworn agent status use the LRD for micro data analysis.
#> 3 The Annual Survey of Manufactures (ASM) Benchmark provides key intercensal measures of manufacturing activity and products for the public and private sectors for four years following the Economic Census of Manufacturing. These benchmark tables present manufacturing establishment statistics from the 2013-2016 Annual Survey of Manufactures (ASM). The ASM Benchmark provides statistics on employment, payroll, worker hours, cost of materials, value added by manufacturing, inventories, and estimates for value of shipments for product classes of products manufactured as defined by the North American Industry Classification System. The ASM provides the best current measure of current U.S. manufacturing industry outputs, inputs, and operating status, and is the primary basis for updates of the Longitudinal Research Database (LRD). Census Bureau staff and academic researchers with sworn agent status use the LRD for micro data analysis.
#> 4 The Annual Survey of Manufactures (ASM) provides key intercensal measures of manufacturing activity, products, and location for the public and private sectors. The ASM provides the best current measure of current U.S. manufacturing industry outputs, inputs, and operating status, and is the primary basis for updates of the Longitudinal Research Database (LRD). Census Bureau staff and academic researchers with sworn agent status use the LRD for micro data analysis.
#> 5 The Annual Survey of Manufactures (ASM) provides key intercensal measures of manufacturing activity, products, and location for the public and private sectors. The ASM provides the best current measure of current U.S. manufacturing industry outputs, inputs, and operating status, and is the primary basis for updates of the Longitudinal Research Database (LRD). Census Bureau staff and academic researchers with sworn agent status use the LRD for micro data analysis.
#> 6 The Annual Survey of Manufactures (ASM) provides key intercensal measures of manufacturing activity, products, and location for the public and private sectors. The ASM provides the best current measure of current U.S. manufacturing industry outputs, inputs, and operating status, and is the primary basis for updates of the Longitudinal Research Database (LRD). Census Bureau staff and academic researchers with sworn agent status use the LRD for micro data analysis.
#> contact
#> 1 Ewd.outreach@census.gov
#> 2 ewd.outreach@census.gov
#> 3 Ewd.outreach@census.gov
#> 4 econ.dissemination@census.gov
#> 5 stephen.c.mangum@census.gov
#> 6 stephen.c.mangum@census.gov
# Get information about 2020 Decennial Census datasets
apis_decennial_2020 <- listCensusApis(name = "dec", vintage = 2020)
head(apis_decennial_2020)
#> title
#> 1 Decennial Census: 118th Congressional District Summary File
#> 2 Decennial Census of Island Areas: American Samoa Detailed Crosstabulations
#> 3 Decennial Census of Island Areas: Guam Detailed Crosstabulations
#> 4 Decennial Census of Island Areas: Commonwealth of the Northern Mariana Islands Detailed Crosstabulations
#> 5 Decennial Census of Island Areas: U.S. Virgin Islands Detailed Crosstabulations
#> 6 Decennial Census: Detailed Demographic and Housing Characteristics File A
#> name vintage type temporal spatial
#> 1 dec/cd118 2020 Aggregate 2020/2020 US
#> 2 dec/crosstabas 2020 Aggregate 2020/2020 American Samoa
#> 3 dec/crosstabgu 2020 Aggregate 2020/2020 Guam
#> 4 dec/crosstabmp 2020 Aggregate 2020/2020 Northern Mariana Islands
#> 5 dec/crosstabvi 2020 Aggregate 2020/2020 U.S. Virgin Islands
#> 6 dec/ddhca 2020 Aggregate 2020/2020 United States
#> url modified
#> 1 http://api.census.gov/data/2020/dec/cd118 2022-10-25 00:00:00.0
#> 2 http://api.census.gov/data/2020/dec/crosstabas 2023-05-09 10:44:24.0
#> 3 http://api.census.gov/data/2020/dec/crosstabgu 2023-05-09 10:46:02.0
#> 4 http://api.census.gov/data/2020/dec/crosstabmp 2023-05-09 10:45:29.0
#> 5 http://api.census.gov/data/2020/dec/crosstabvi 2023-05-09 10:44:57.0
#> 6 http://api.census.gov/data/2020/dec/ddhca 2022-09-09 00:00:00.0
#> description
#> 1 The Congressional District Summary File (118th Congress) (CD118) contains the data compiled from the questions asked of all people and about every housing unit in the 2020 Census. This product retabulates selected summary levels from the Demographic and Housing Characteristics File (DHC) for the 118th Congress and 2022 state legislative districts. Population items include age, sex, race, Hispanic or Latino origin, household type, family type, relationship to householder, group quarters population, housing occupancy and housing tenure (whether a housing unit is owner-occupied or renter-occupied).
#> 2 This product will include key socio-demographic and economic variables presented in cross-tabulations that present the complex data together.
#> 3 This product will include….
#> 4 This product will include key socio-demographic and economic variables presented in cross-tabulations that present the complex data together.
#> 5 This product will include key socio-demographic and economic variables presented in cross-tabulations that present the complex data together.
#> 6 This product provides the population counts and sex and age statistics for detailed racial and ethnic groups and American Indian and Alaska Native tribes and villages.
#> contact
#> 1 pio@census.gov
#> 2 pio@census.gov
#> 3 pio@census.gov
#> 4 pio@census.gov
#> 5 pio@census.gov
#> 6 pio@census.gov
# Get information about one particular dataset
api_sahie <- listCensusApis(name = "timeseries/healthins/sahie")
head(api_sahie)
#> title
#> 1 Small Area Health Insurance Estimates: Small Area Health Insurance Estimates
#> name type temporal spatial
#> 1 timeseries/healthins/sahie Timeseries 2006/2020 US
#> url modified
#> 1 http://api.census.gov/data/timeseries/healthins/sahie 2021-04-12 00:00:00.0
#> description
#> 1 The U.S. Census Bureau's Small Area Health Insurance Estimates program produces the only source of data for single-year estimates of health insurance coverage status for all counties in the U.S. by selected economic and demographic characteristics. This program is partially funded by the Centers for Disease Control and Prevention's (CDC) Division of Cancer Prevention and Control (DCPC). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the National Breast and Cervical Cancer Early Detection Program (NBCCEDP). For estimation, SAHIE uses statistical models that combine survey data from the American Community Survey (ACS) with administrative records data and Census 2010 data.
#> contact
#> 1 Sehsd.sahie@census.gov