Abstract

The Integrated Public Use Microdata Series (IPUMS) Complete Count Data include more than 650 million individual-level and 7.5 million household-level records. The microdata are the result of collaboration between IPUMS and the nation’s two largest genealogical organizations—Ancestry.com and FamilySearch—and provides the largest and richest source of individual level and household data.

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Documentation

Historic data are scarce and often only exists in aggregate tables. The key advantage of historic US census data is the availability of individual and household level characteristics that researchers can tabulate in ways that benefits their specific research questions. The data contain demographic variables, economic variables, migration variables and family variables. Within households, it is possible to create relational data as all relations between household members are known. For example, having data on the mother and her children in a household enables researchers to calculate the mother’s age at birth. Another advantage of the Complete Count data is the possibility to follow individuals over time using a historical identifier.

In sum: the historic US census data are a unique source for research on social and economic change and can provide population health researchers with information about social and economic determinants.

The historic US 1920 census data was collected in January 1920. Enumerators collected data traveling to households and counting the residents who regularly slept at the household. Individuals lacking permanent housing were counted as residents of the place where they were when the data was collected. Household members absent on the day of data collected were either listed to the household with the help of other household members or were scheduled for the last census subdivision.

Notes

• We provide household and person data separately so that it is convenient to explore the descriptive statistics on each level. In order to obtain a full dataset, merge the household and person on the variables SERIAL and SERIALP. In order to create a longitudinal dataset, merge datasets on the variable HISTID.

• Households with more than 60 people in the original data were broken up for processing purposes. Every person in the large households are considered to be in their own household. The original large households can be identified using the variable SPLIT, reconstructed using the variable SPLITHID, and the original count is found in the variable SPLITNUM.

• Coded variables derived from string variables are still in progress. These variables include: occupation and industry.

• Missing observations have been allocated and some inconsistencies have been edited for the following variables: SPEAKENG, YRIMMIG, CITIZEN, AGE, BPL, MBPL, FBPL, LIT, SCHOOL, OWNERSHP, MORTGAGE, FARM, CLASSWKR, OCC1950, IND1950, MARST, RACE, SEX, RELATE, MTONGUE. The flag variables indicating an allocated observation for the associated variables can be included in your extract by clicking the ‘Select data quality flags’ box on the extract summary page.

• Most inconsistent information was not edited for this release, thus there are observations outside of the universe for some variables. In particular, the variables GQ, and GQTYPE have known inconsistencies and will be improved with the next release.

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Section 2

This dataset was created on 2020-01-10 18:46:34.647 by merging multiple datasets together. The source datasets for this version were:

IPUMS 1920 households: This dataset includes all households from the 1920 US census.

IPUMS 1920 persons: This dataset includes all individuals from the 1920 US census.

IPUMS 1920 Lookup: This dataset includes variable names, variable labels, variable values, and corresponding variable value labels for the IPUMS 1920 datasets.

The data comprising the Puerto Rico Census Project, 1920 contain individual and household records drawn from the 1920 Puerto Rican Population Census. The data include variables containing basic demographic information such as age, sex, race, marital status, number of children born and surviving, family size, place of birth, immigration status, county and neighborhood of residence, urban/rural status, and citizenship. The data also describe language proficiency, literacy, school attendance, and disabilities (blind or deaf) of the individuals. Other variables provide data on occupation, industry, ownership of residence, status of mortgage, and farm ownership. There are four classifications of variables belonging to this dataset: original input variables, coded variables, constructed variables, and quality flag variables. The original input variables contain the raw data collected by the enumerators. The coded variables are variables that were recoded by the University of Wisconsin Survey Center (UWSC) as part of the Puerto Rico Census Project. Constructed variables were produced by UWSC to capture additional relevant information. For example, one constructed variable measures literacy by combining separate variables containing data on whether the individual could read and if they could write. Finally, quality flag variables were created by UWSC to indicate whether it could be logically deduced that individual records had been hand edited by the Census Office.

1920 United States Federal Census contains records from Philadelphia, Pennsylvania, USA by Fourteenth Census of the United States, 1920. (NARA microfilm publication T625, 2076 rolls). Records of the Bureau of the Census, Record Group 29. National Archives, Washington, D.C. Year: 1920; Census Place: Philadelphia Ward 42, Philadelphia, Pennsylvania; Roll: T625_1643; Page: 13A; Enumeration District: 1564 - .

This dataset includes all individuals from the 1920 US census.

1920 United States Federal Census contains records from Caribou, Aroostook, Maine, USA by Year: 1920; Census Place: Caribou, Aroostook, Maine; Roll: T625_638; Page: 4B; Enumeration District: 11 - .

The Census Tree is the largest-ever database of record links among the historical U.S. censuses, with over 700 million links for people living in the United States between 1850 and 1940. These links allow researchers to construct a longitudinal dataset that is highly representative of the population, and that includes women, Black Americans, and other under-represented populations at unprecedented rates. Each .csv file consists of a crosswalk between the two years indicated in the filename, using the IPUMS histids. For more information, consult the included Read Me file, and visit https://censustree.org.

This dataset includes all households from the 1920 US census.

This map depicts US Census data from the 1920 decennial census for total population and race

This dataset includes variable names, variable labels, variable values, and corresponding variable value labels for the IPUMS 1920 datasets.

1920 United States Federal Census contains records from Philadelphia, Pennsylvania, USA by Year: 1920; Census Place: Philadelphia Ward 42, Philadelphia, Pennsylvania; Roll: T625_1643; Page: 1A; Enumeration District: 1586 - .

An appreciation of historical landuse and its effects is crucial when interpreting the structure, composition, and spatial characteristics of modern forests. The Harvard Forest has compiled many different historical data sources in an ongoing effort to understand how anthropogenic disturbances have shaped our modern landscapes. Estimates of town land use and land cover were gathered from a variety of sources, including tax valuations (1801-1860) and state agricultural census records (1865-1905). Data prior to 1801 rarely cover the entire state and are excluded from these datasets. Data on forest structure are available for several time periods, including 1885 and 1895 (Agricultural Censuses) and 1916-1920s (State Forester’s reports).

Block-level census coverage of early Central Phoenix for 1920, 1930, and 1940, including population, race/ethnicity, household ownership and rentership, and temporary residency. This dataset was designed for use in combination with parcel-level land-use data derived from Sanborn Fire Insurance Maps to assess environmental justice issues in Phoenix’s early 20th Century development.

This data collection contains electoral and demographic data at several levels of aggregation (kreis, land/regierungsberzirk, and wahlkreis) for Germany in the Weimar Republic period of 1919-1933. Two datasets are available. Part 1, 1919 Data, presents raw and percentagized election returns at the wahlkreis level for the 1919 election to the Nationalversammlung. Information is provided on the number and percentage of eligible voters and the total votes cast for parties such as the German National People's Party, German People's Party, Christian People's Party, German Democratic Party, Social Democratic Party, and Independent Social Democratic Party. Part 2, 1920-1933 Data, consists of returns for elections to the Reichstag, 1920-1933, and for the Reichsprasident elections of 1925 and 1932 (including runoff elections in each year), returns for two national referenda, held in 1926 and 1929, and data pertaining to urban population, religion, and occupations, taken from the German Census of 1925. This second dataset contains data at several levels of aggregation and is a merged file. Crosstemporal discrepancies, such as changes in the names of the geographical units and the disappearance of units, have been adjusted for whenever possible. Variables in this file provide information for the total number and percentage of eligible voters and votes cast for parties, including the German Nationalist People's Party, German People's Party, German Center Party, German Democratic Party, German Social Democratic Party, German Communist Party, Bavarian People's Party, Nationalist-Socialist German Workers' Party (Hitler's movement), German Middle Class Party, German Business and Labor Party, Conservative People's Party, and other parties. Data are also provided for the total number and percentage of votes cast in the Reichsprasident elections of 1925 and 1932 for candidates Jarres, Held, Ludendorff, Braun, Marx, Hellpach, Thalman, Hitler, Duesterburg, Von Hindenburg, Winter, and others. Additional variables provide information on occupations in the country, including the number of wage earners employed in agriculture, industry and manufacturing, trade and transportation, civil service, army and navy, clergy, public health, welfare, domestic and personal services, and unknown occupations. Other census data cover the total number of wage earners in the labor force and the number of female wage earners employed in all occupations. Also provided is the percentage of the total population living in towns with 5,000 inhabitants or more, and the number and percentage of the population who were Protestants, Catholics, and Jews.

Historical population as enumerated and corrected from 1790 through 2020. North Carolina was one of the 13 original States and by the time of the 1790 census had essentially its current boundaries. The Census is mandated by the United States Constitution and was first completed for 1790. The population has been counted every ten years hence, with some limitations. In 1790 census coverage included most of the State, except for areas in the west, parts of which were not enumerated until 1840. The population for 1810 includes Walton County, enumerated as part of Georgia although actually within North Carolina. Historical populations shown here reflect the population of the respective named county and not necessarily the population of the area of the county as it was defined for a particular census. County boundaries shown in maps reflect boundaries as defined in 2020. Historic boundaries for some counties may include additional geographic areas or may be smaller than the current geographic boundaries. Notes below list the county or counties with which the population of a currently defined county were enumerated historically (Current County: Population counted in). The current 100 counties have been in place since the 1920 Census, although some modifications to the county boundaries have occurred since that time. For historical county boundaries see: Atlas of Historical County Boundaries Project (newberry.org)County Notes: Note 1: Total for 1810 includes population (1,026) of Walton County, reported as a Georgia county but later determined to be situated in western North Carolina. Total for 1890 includes 2 Indians in prison, not reported by county. Note 2: Alexander: *Iredell, Burke, Wilkes. Note 3: Avery: *Caldwell, Mitchell, Watauga. Note 4: Buncombe: *Burke, Rutherford; see also note 22. Note 5: Caldwell: *Burke, Wilkes, Yancey. Note 6: Cleveland: *Rutherford, Lincoln. Note 7: Columbus: *Bladen, Brunswick. Note 8: Dare: *Tyrrell, Currituck, Hyde. Note 9: Hoke: *Cumberland, Robeson. Note 10: Jackson: *Macon, Haywood. Note 11: Lee: *Moore, Chatham. Note 12: Lenoir: *Dobbs (Greene); Craven. Note 13: McDowell: *Burke, Rutherford. Note 14: Madison: *Buncombe, Yancey. Note 15: Mitchell: *Yancey, Watauga. Note 16: Pamlico: *Craven, Beaufort. Note 17: Polk: *Rutherford, Henderson. Note 18: Swain: *Jackson, Macon. Note 19: Transylvania: *Henderson, Jackson. Note 20: Union: *Mecklenburg, Anson. Note 21: Vance: *Granville, Warren, Franklin. Note 22: Walton: Created in 1803 as a Georgia county and reported in 1810 as part of Georgia; abolished after a review of the State boundary determined that its area was located in North Carolina. By 1820 it was part of Buncombe County. Note 23: Watauga: *Ashe, Yancey, Wilkes; Burke. Note 24: Wilson: *Edgecombe, Nash, Wayne, Johnston. Note 25: Yancey: *Burke, Buncombe. Note 26: Alleghany: *Ashe. Note 27: Haywood: *Buncombe. Note 28: Henderson: *Buncombe. Note 29: Person: Caswell. Note 30: Clay: Cherokee. Note 31: Graham: Cherokee. Note 32: Harnett: Cumberland. Note 33: Macon: Haywood.

Note 34: Catawba: Lincoln. Note 35: Gaston: Lincoln. Note 36: Cabarrus: Mecklenburg.
Note 37: Stanly: Montgomery. Note 38: Pender: New Hanover. Note 39: Alamance: Orange.
Note 40: Durham: Orange, Wake. Note 41: Scotland: Richmond. Note 42: Davidson: Rowan. Note 43: Davie: Rowan.Note 44: Forsyth: Stokes. Note 45: Yadkin: Surry.
Note 46: Washington: Tyrrell.Note 47: Ashe: Wilkes. Part III. Population of Counties, Earliest Census to 1990The 1840 population of Person County, NC should be 9,790. The 1840 population of Perquimans County, NC should be 7,346.

Sources: U.S. Census Bureau, Census 2020; generated by CCRPC staff; using 2020 Census Demographic Data Map Viewer; https://www.census.gov/library/visualizations/2021/geo/demographicmapviewer.html; (18 August 2021); U.S. Census Bureau; Census 2000, Summary File 1, Table DP-1; generated by CCRPC staff; using American FactFinder; http://factfinder2.census.gov; (30 December 2015). U.S. Census Bureau; Census 2010, Summary File 1, Table P1; generated by CCRPC staff; using American FactFinder; http://factfinder2.census.gov; (30 December 2015). U.S. Census Bureau; 1980 Census of Population, Volume 1: Characteristics of the Population, Chapter A: Number of Inhabitants, Part 15: Illinois, PC80-1-A15, Table 2, Land Area and Population: 1930-1980. U.S. Census Bureau; Fourteenth Census of the United States; State Compendium Illinois, Table 1. - Area and Population of Counties: 1850 to 1920; https://www.census.gov/library/publications/1924/dec/state-compendium.html; (23 August 2018).

The dataset is based on two separate censuses of the Netherlands of 1920, population census (7 vols) and occupational census (3 vols).
Content: images of the publication, pdf files of the text sections and excel files with data entered from the published tables.

1920 Census Counties of State of Missouri Geo-dataset delineating 1920 Census Counties

This data collection contains information about total population, total number of professionally employed, income and property within the principal occupational groups agriculture and subsidiary industry, industry and craft, commerce, transport, storage and communication, public service, domestic work, and former professionally employed, and also within subgroups of these principal groups.

Japan Population Census: Age 30 to 34 Years data was reported at 7,290,878.000 Person in 2015. This records a decrease from the previous number of 8,341,497.000 Person for 2010. Japan Population Census: Age 30 to 34 Years data is updated yearly, averaging 7,681,689.000 Person from Dec 1920 (Median) to 2015, with 20 observations. The data reached an all-time high of 10,771,731.000 Person in 1980 and a record low of 3,609,450.000 Person in 1920. Japan Population Census: Age 30 to 34 Years data remains active status in CEIC and is reported by Statistical Bureau. The data is categorized under Global Database’s Japan – Table JP.G002: Population: Annual.

Abstract

For more than 150 years, the U.S. Department of Commerce, Bureau of the Census, conducted the census of agriculture. However, the 2002 Appropriations Act transferred the responsibility from the Bureau of the Census to the U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS). The 2007 Census of Agriculture for the U.S. Virgin Islands is the second census in the U.S. Virgin Islands conducted by NASS. The census of agriculture is taken to obtain agricultural statistics for each county, State (including territories and protectorates), and the Nation. The first U.S. agricultural census data were collected in 1840 as a part of the sixth decennial census. From 1840 to 1920, an agricultural census was taken as a part of each decennial census. Since 1920, a separate national agricultural census has been taken every 5 years. The 2007 census is the 14th census of agriculture of the U.S. Virgin Islands. The first, taken in 1920, was a special census authorized by the Secretary of Commerce. The next agriculture census was taken in 1930 in conjunction with the decennial census, a practice that continued every 10 years through 1960. The 1964 Census of Agriculture was the first quinquennial (5-year) census to be taken in the U.S. Virgin Islands. In 1976, Congress authorized the census of agriculture to be taken for 1978 and 1982 to adjust the data-reference year to coincide with the 1982 Economic Censuses covering manufacturing, mining, construction, retail trade, wholesale trade, service industries, and selected transportation activities. After 1982, the agriculture census reverted to a 5-year cycle. Data in this publication are for the calendar year 2007, and inventory data reflect what was on hand on December 31, 2007. This is the same reference period used in the 2002 census. Prior to the 2002 census, data was collected in the summer for the previous 12 months, with inventory items counted as what was on hand as of July 1 of the year the data collection was done.

Objectives: The census of agriculture is the leading source of statistics about the U.S. Virgin Islands’s agricultural production and the only source of consistent, comparable data at the island level. Census statistics are used to measure agricultural production and to identify trends in an ever changing agricultural sector. Many local programs use census data as a benchmark for designing and evaluating surveys. Private industry uses census statistics to provide a more effective production and distribution system for the agricultural community.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was a farm, defined as "any place from which USD 500 or more of agricultural products were produced and sold, or normally would had been sold, during the calendar year 2007". According to the census definition, a farm is essentially an operating unit, not an ownership tract. All land operated or managed by one person or partnership represents one farm. In the case of tenants, the land assigned to each tenant is considered a separate farm, even though the landlord may consider the entire landholding to be one unit rather than several separate units.

Kind of data

Census/enumeration data [cen]

Sampling procedure

(a) Method of Enumeration As in the previous censuses of the U.S. Virgin Islands, a direct enumeration procedure was used in the 2007 Census of Agriculture. Enumeration was based on a list of farm operators compiled by the U.S. Virgin Islands Department of Agriculture. This list was compiled with the help of the USDA Farm Services Agency located in St. Croix. The statistics in this report were collected from farm operators beginning in January of 2003. Each enumerator was assigned a list of individuals or farm operations from a master enumeration list. The enumerators contacted persons or operations on their list and completed a census report form for all farm operations. If the person on the list was not operating a farm, the enumerator recorded whether the land had been sold or rented to someone else and was still being used for agriculture. If land was sold or rented out, the enumerator got the name of the new operator and contacted that person to ensure that he or she was included in the census.

(b) Frame The census frame consisted of a list of farm operators compiled by the U.S. Virgin Islands DA. This list was compiled with the help of the USDA Farm Services Agency, located in St. Croix.

(c) Complete and/or sample enumeration methods The census was a complete enumeration of all farm operators registered in the list compiled by the United States of America in the CA 2007.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire (report form) for the CA 2007 was prepared by NASS, in cooperation with the DA of the U.S. Virgin Islands. Only one questionnaire was used for data collection covering topics on:

• Land owned
• Land use
• Irrigation
• Conservation programs and crop insurance
• Field crops
• Bananas, coffee, pineapples and plantain crops
• Hay and forage crops
• Nursery, Greenhouse, Floriculture, Sod and tree seedlings
• Vegetables and melons
• Hydroponic crops
• Fruit
• Root crops
• Cattle and calves
• Poultry
• Hogs and pigs
• Aquaculture
• Other animals and livestock products
• Value of sales
• Organic agriculture
• Federal and commonwealth agricultural program payments
• Income from farm-related sources
• Production expenses
• Farm labour
• Fertilizer and chemicals applied
• Market value of land and buildings
• Machinery, equipment and buildings
• Practices
• Type of organization
• Operator characteristics

The questionnaire of the 2007 CA covered 12 of the 16 core items' recommended for the WCA 2010 round.

Cleaning operations

DATA PROCESSING The processing of the 2007 Census of Agriculture for the U.S. Virgin Islands was done in St. Croix. Each report form was reviewed and coded prior to data keying. Report forms not meeting the census farm definition were voided. The remaining report forms were examined for clarity and completeness. Reporting errors in units of measures, illegible entries, and misplaced entries were corrected. After all the report forms had been reviewed and coded, the data were keyed and subjected to a thorough computer edit. The edit performed comprehensive checks for consistency and reasonableness, corrected erroneous or inconsistent data, supplied missing data based on similar farms, and assigned farm classification codes necessary for tabulating the data. All substantial changes to the data generated by the computer edits were reviewed and verified by analysts. Inconsistencies identified, but not corrected by the computer, were reviewed, corrected, and keyed to a correction file. The corrected data were then tabulated by the computer and reviewed by analysts. Prior to publication, tabulated totals were reviewed by analysts to identify inconsistencies and potential coverage problems. Comparisons were made with previous census data, as well as other available data. The computer system provided the capability to review up-to-date tallies of all selected data items for various sets of criteria which included, but were not limited to, geographic levels, farm types, and sales levels. Data were examined for each set of criteria and any inconsistencies or potential problems were then researched by examining individual data records contributing to the tabulated total. W hen necessary, data inconsistencies were resolved by making corrections to individual data records.

Sampling error estimates

The accuracy of these tabulated data is determined by the joint effects of the various nonsampling errors. No direct measures of these effects have been obtained; however, precautionary steps were taken in all phases of data collection, processing, and tabulation of the data in an effort to minimize the effects of nonsampling errors.