17 datasets found
  1. d

    U.S. Voting by Census Block Groups

    • search.dataone.org
    Updated Oct 29, 2025
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    Bryan, Michael (2025). U.S. Voting by Census Block Groups [Dataset]. http://doi.org/10.7910/DVN/NKNWBX
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    Dataset updated
    Oct 29, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Bryan, Michael
    Area covered
    United States
    Description

    PROBLEM AND OPPORTUNITY In the United States, voting is largely a private matter. A registered voter is given a randomized ballot form or machine to prevent linkage between their voting choices and their identity. This disconnect supports confidence in the election process, but it provides obstacles to an election's analysis. A common solution is to field exit polls, interviewing voters immediately after leaving their polling location. This method is rife with bias, however, and functionally limited in direct demographics data collected. For the 2020 general election, though, most states published their election results for each voting location. These publications were additionally supported by the geographical areas assigned to each location, the voting precincts. As a result, geographic processing can now be applied to project precinct election results onto Census block groups. While precinct have few demographic traits directly, their geographies have characteristics that make them projectable onto U.S. Census geographies. Both state voting precincts and U.S. Census block groups: are exclusive, and do not overlap are adjacent, fully covering their corresponding state and potentially county have roughly the same size in area, population and voter presence Analytically, a projection of local demographics does not allow conclusions about voters themselves. However, the dataset does allow statements related to the geographies that yield voting behavior. One could say, for example, that an area dominated by a particular voting pattern would have mean traits of age, race, income or household structure. The dataset that results from this programming provides voting results allocated by Census block groups. The block group identifier can be joined to Census Decennial and American Community Survey demographic estimates. DATA SOURCES The state election results and geographies have been compiled by Voting and Election Science team on Harvard's dataverse. State voting precincts lie within state and county boundaries. The Census Bureau, on the other hand, publishes its estimates across a variety of geographic definitions including a hierarchy of states, counties, census tracts and block groups. Their definitions can be found here. The geometric shapefiles for each block group are available here. The lowest level of this geography changes often and can obsolesce before the next census survey (Decennial or American Community Survey programs). The second to lowest census level, block groups, have the benefit of both granularity and stability however. The 2020 Decennial survey details US demographics into 217,740 block groups with between a few hundred and a few thousand people. Dataset Structure The dataset's columns include: Column Definition BLOCKGROUP_GEOID 12 digit primary key. Census GEOID of the block group row. This code concatenates: 2 digit state 3 digit county within state 6 digit Census Tract identifier 1 digit Census Block Group identifier within tract STATE State abbreviation, redundent with 2 digit state FIPS code above REP Votes for Republican party candidate for president DEM Votes for Democratic party candidate for president LIB Votes for Libertarian party candidate for president OTH Votes for presidential candidates other than Republican, Democratic or Libertarian AREA square kilometers of area associated with this block group GAP total area of the block group, net of area attributed to voting precincts PRECINCTS Number of voting precincts that intersect this block group ASSUMPTIONS, NOTES AND CONCERNS: Votes are attributed based upon the proportion of the precinct's area that intersects the corresponding block group. Alternative methods are left to the analyst's initiative. 50 states and the District of Columbia are in scope as those U.S. possessions voting in the general election for the U.S. Presidency. Three states did not report their results at the precinct level: South Dakota, Kentucky and West Virginia. A dummy block group is added for each of these states to maintain national totals. These states represent 2.1% of all votes cast. Counties are commonly coded using FIPS codes. However, each election result file may have the county field named differently. Also, three states do not share county definitions - Delaware, Massachusetts, Alaska and the District of Columbia. Block groups may be used to capture geographies that do not have population like bodies of water. As a result, block groups without intersection voting precincts are not uncommon. In the U.S., elections are administered at a state level with the Federal Elections Commission compiling state totals against the Electoral College weights. The states have liberty, though, to define and change their own voting precincts https://en.wikipedia.org/wiki/Electoral_precinct. The Census Bureau... Visit https://dataone.org/datasets/sha256%3A05707c1dc04a814129f751937a6ea56b08413546b18b351a85bc96da16a7f8b5 for complete metadata about this dataset.

  2. Change in House of Representatives seats due to Census U.S. 2021, by state

    • statista.com
    Updated Apr 26, 2021
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    Statista (2021). Change in House of Representatives seats due to Census U.S. 2021, by state [Dataset]. https://www.statista.com/statistics/1231748/change-house-representatives-seats-census-state-us/
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    Dataset updated
    Apr 26, 2021
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    United States
    Description

    Every 10 years, the number of seats a state has in the U.S. House of Representatives, and therefore the Electoral College, changes based on population. While many states experienced no change in representation due to the 2020 Census, a few states gained or lost seats. Texas notably gained *** seats due to an increase in population, while New York, Michigan, California, West Virginia, Pennsylvania, Ohio, and Illinois all lost *** seat.

    This change will stay in place until 2030, when the next Census is conducted in the United States.

  3. Data from: US Election Dataset

    • kaggle.com
    Updated Nov 6, 2024
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    essarabi (2024). US Election Dataset [Dataset]. https://www.kaggle.com/datasets/essarabi/ultimate-us-election-dataset
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 6, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    essarabi
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    United States
    Description

    Description

    This dataset contains the county-wise vote share of the United States presidential election of 2020, and in the future 2024, the main advantage of the dataset is that it contains various important county statistics such as the counties racial composition, median and mean income, income inequality, population density, education level, population and the counties occupational distribution.

    _Imp: this dataset will be updated as the 2024 results come in, I will also be adding more county demographic data, if you have any queries or suggestions please feel free to comment _

    Motivation

    The reasons for constructing this dataset are many, however the prime reason was to aggregate all the data on counties along with the election result data for easy analysis in one place. I noticed that Kaggle contains no datasets with detailed county information, and that using the US census bureau site is pretty difficult and time consuming to extract data so it would be better to have a pre-prepared table of data

    Columns

    • The first columns contain information on the county and state
    • The next columns contain the 2020 vote both raw and %
    • The next columns contain the education level of the county population
    • Following that we have information about the income and income inequality in the county
    • Then we have the county racial composition
    • The counties population and population density
    • The final columns contain information about the distribution of occupations in the county
  4. d

    AP VoteCast 2020 - General Election

    • data.world
    csv, zip
    Updated Mar 29, 2024
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    The Associated Press (2024). AP VoteCast 2020 - General Election [Dataset]. https://data.world/associatedpress/ap-votecast
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    csv, zipAvailable download formats
    Dataset updated
    Mar 29, 2024
    Authors
    The Associated Press
    Description

    AP VoteCast is a survey of the American electorate conducted by NORC at the University of Chicago for Fox News, NPR, PBS NewsHour, Univision News, USA Today Network, The Wall Street Journal and The Associated Press.

    AP VoteCast combines interviews with a random sample of registered voters drawn from state voter files with self-identified registered voters selected using nonprobability approaches. In general elections, it also includes interviews with self-identified registered voters conducted using NORC’s probability-based AmeriSpeak® panel, which is designed to be representative of the U.S. population.

    Interviews are conducted in English and Spanish. Respondents may receive a small monetary incentive for completing the survey. Participants selected as part of the random sample can be contacted by phone and mail and can take the survey by phone or online. Participants selected as part of the nonprobability sample complete the survey online.

    In the 2020 general election, the survey of 133,103 interviews with registered voters was conducted between Oct. 26 and Nov. 3, concluding as polls closed on Election Day. AP VoteCast delivered data about the presidential election in all 50 states as well as all Senate and governors’ races in 2020.

    Using this Data - IMPORTANT

    This is survey data and must be properly weighted during analysis: DO NOT REPORT THIS DATA AS RAW OR AGGREGATE NUMBERS!!

    Instead, use statistical software such as R or SPSS to weight the data.

    National Survey

    The national AP VoteCast survey of voters and nonvoters in 2020 is based on the results of the 50 state-based surveys and a nationally representative survey of 4,141 registered voters conducted between Nov. 1 and Nov. 3 on the probability-based AmeriSpeak panel. It included 41,776 probability interviews completed online and via telephone, and 87,186 nonprobability interviews completed online. The margin of sampling error is plus or minus 0.4 percentage points for voters and 0.9 percentage points for nonvoters.

    State Surveys

    In 20 states in 2020, AP VoteCast is based on roughly 1,000 probability-based interviews conducted online and by phone, and roughly 3,000 nonprobability interviews conducted online. In these states, the margin of sampling error is about plus or minus 2.3 percentage points for voters and 5.5 percentage points for nonvoters.

    In an additional 20 states, AP VoteCast is based on roughly 500 probability-based interviews conducted online and by phone, and roughly 2,000 nonprobability interviews conducted online. In these states, the margin of sampling error is about plus or minus 2.9 percentage points for voters and 6.9 percentage points for nonvoters.

    In the remaining 10 states, AP VoteCast is based on about 1,000 nonprobability interviews conducted online. In these states, the margin of sampling error is about plus or minus 4.5 percentage points for voters and 11.0 percentage points for nonvoters.

    Although there is no statistically agreed upon approach for calculating margins of error for nonprobability samples, these margins of error were estimated using a measure of uncertainty that incorporates the variability associated with the poll estimates, as well as the variability associated with the survey weights as a result of calibration. After calibration, the nonprobability sample yields approximately unbiased estimates.

    As with all surveys, AP VoteCast is subject to multiple sources of error, including from sampling, question wording and order, and nonresponse.

    Sampling Details

    Probability-based Registered Voter Sample

    In each of the 40 states in which AP VoteCast included a probability-based sample, NORC obtained a sample of registered voters from Catalist LLC’s registered voter database. This database includes demographic information, as well as addresses and phone numbers for registered voters, allowing potential respondents to be contacted via mail and telephone. The sample is stratified by state, partisanship, and a modeled likelihood to respond to the postcard based on factors such as age, race, gender, voting history, and census block group education. In addition, NORC attempted to match sampled records to a registered voter database maintained by L2, which provided additional phone numbers and demographic information.

    Prior to dialing, all probability sample records were mailed a postcard inviting them to complete the survey either online using a unique PIN or via telephone by calling a toll-free number. Postcards were addressed by name to the sampled registered voter if that individual was under age 35; postcards were addressed to “registered voter” in all other cases. Telephone interviews were conducted with the adult that answered the phone following confirmation of registered voter status in the state.

    Nonprobability Sample

    Nonprobability participants include panelists from Dynata or Lucid, including members of its third-party panels. In addition, some registered voters were selected from the voter file, matched to email addresses by V12, and recruited via an email invitation to the survey. Digital fingerprint software and panel-level ID validation is used to prevent respondents from completing the AP VoteCast survey multiple times.

    AmeriSpeak Sample

    During the initial recruitment phase of the AmeriSpeak panel, randomly selected U.S. households were sampled with a known, non-zero probability of selection from the NORC National Sample Frame and then contacted by mail, email, telephone and field interviewers (face-to-face). The panel provides sample coverage of approximately 97% of the U.S. household population. Those excluded from the sample include people with P.O. Box-only addresses, some addresses not listed in the U.S. Postal Service Delivery Sequence File and some newly constructed dwellings. Registered voter status was confirmed in field for all sampled panelists.

    Weighting Details

    AP VoteCast employs a four-step weighting approach that combines the probability sample with the nonprobability sample and refines estimates at a subregional level within each state. In a general election, the 50 state surveys and the AmeriSpeak survey are weighted separately and then combined into a survey representative of voters in all 50 states.

    State Surveys

    First, weights are constructed separately for the probability sample (when available) and the nonprobability sample for each state survey. These weights are adjusted to population totals to correct for demographic imbalances in age, gender, education and race/ethnicity of the responding sample compared to the population of registered voters in each state. In 2020, the adjustment targets are derived from a combination of data from the U.S. Census Bureau’s November 2018 Current Population Survey Voting and Registration Supplement, Catalist’s voter file and the Census Bureau’s 2018 American Community Survey. Prior to adjusting to population totals, the probability-based registered voter list sample weights are adjusted for differential non-response related to factors such as availability of phone numbers, age, race and partisanship.

    Second, all respondents receive a calibration weight. The calibration weight is designed to ensure the nonprobability sample is similar to the probability sample in regard to variables that are predictive of vote choice, such as partisanship or direction of the country, which cannot be fully captured through the prior demographic adjustments. The calibration benchmarks are based on regional level estimates from regression models that incorporate all probability and nonprobability cases nationwide.

    Third, all respondents in each state are weighted to improve estimates for substate geographic regions. This weight combines the weighted probability (if available) and nonprobability samples, and then uses a small area model to improve the estimate within subregions of a state.

    Fourth, the survey results are weighted to the actual vote count following the completion of the election. This weighting is done in 10–30 subregions within each state.

    National Survey

    In a general election, the national survey is weighted to combine the 50 state surveys with the nationwide AmeriSpeak survey. Each of the state surveys is weighted as described. The AmeriSpeak survey receives a nonresponse-adjusted weight that is then adjusted to national totals for registered voters that in 2020 were derived from the U.S. Census Bureau’s November 2018 Current Population Survey Voting and Registration Supplement, the Catalist voter file and the Census Bureau’s 2018 American Community Survey. The state surveys are further adjusted to represent their appropriate proportion of the registered voter population for the country and combined with the AmeriSpeak survey. After all votes are counted, the national data file is adjusted to match the national popular vote for president.

  5. d

    Voter Registration by Census Tract

    • catalog.data.gov
    • data.kingcounty.gov
    • +1more
    Updated Jun 29, 2025
    + more versions
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    data.kingcounty.gov (2025). Voter Registration by Census Tract [Dataset]. https://catalog.data.gov/dataset/voter-registration-by-census-tract
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    Dataset updated
    Jun 29, 2025
    Dataset provided by
    data.kingcounty.gov
    Description

    This web map displays data from the voter registration database as the percent of registered voters by census tract in King County, Washington. The data for this web map is compiled from King County Elections voter registration data for the years 2013-2019. The total number of registered voters is based on the geo-location of the voter's registered address at the time of the general election for each year. The eligible voting population, age 18 and over, is based on the estimated population increase from the US Census Bureau and the Washington Office of Financial Management and was calculated as a projected 6 percent population increase for the years 2010-2013, 7 percent population increase for the years 2010-2014, 9 percent population increase for the years 2010-2015, 11 percent population increase for the years 2010-2016 & 2017, 14 percent population increase for the years 2010-2018 and 17 percent population increase for the years 2010-2019. The total population 18 and over in 2010 was 1,517,747 in King County, Washington. The percentage of registered voters represents the number of people who are registered to vote as compared to the eligible voting population, age 18 and over. The voter registration data by census tract was grouped into six percentage range estimates: 50% or below, 51-60%, 61-70%, 71-80%, 81-90% and 91% or above with an overall 84 percent registration rate. In the map the lighter colors represent a relatively low percentage range of voter registration and the darker colors represent a relatively high percentage range of voter registration. PDF maps of these data can be viewed at King County Elections downloadable voter registration maps. The 2019 General Election Voter Turnout layer is voter turnout data by historical precinct boundaries for the corresponding year. The data is grouped into six percentage ranges: 0-30%, 31-40%, 41-50% 51-60%, 61-70%, and 71-100%. The lighter colors represent lower turnout and the darker colors represent higher turnout. The King County Demographics Layer is census data for language, income, poverty, race and ethnicity at the census tract level and is based on the 2010-2014 American Community Survey 5 year Average provided by the United States Census Bureau. Since the data is based on a survey, they are considered to be estimates and should be used with that understanding. The demographic data sets were developed and are maintained by King County Staff to support the King County Equity and Social Justice program. Other data for this map is located in the King County GIS Spatial Data Catalog, where data is managed by the King County GIS Center, a multi-department enterprise GIS in King County, Washington. King County has nearly 1.3 million registered voters and is the largest jurisdiction in the United States to conduct all elections by mail. In the map you can view the percent of registered voters by census tract, compare registration within political districts, compare registration and demographic data, verify your voter registration or register to vote through a link to the VoteWA, Washington State Online Voter Registration web page.

  6. Voter turnout in U.S. presidential elections by age 1964-2020

    • statista.com
    Updated Oct 18, 2022
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    Statista (2022). Voter turnout in U.S. presidential elections by age 1964-2020 [Dataset]. https://www.statista.com/statistics/1096299/voter-turnout-presidential-elections-by-age-historical/
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    Dataset updated
    Oct 18, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Since 1964, voter turnout rates in U.S. presidential elections have generally fluctuated across all age groups, falling to a national low in 1996, before rising again in the past two decades. Since 1988, there has been a direct correlation with voter participation and age, as people become more likely to vote as they get older. Participation among eligible voters under the age of 25 is the lowest of all age groups, and in the 1996 and 2000 elections, fewer than one third of eligible voters under the age of 25 participated, compared with more than two thirds of voters over 65 years.

  7. a

    Ventura County Community College Board of Trustee

    • hub.arcgis.com
    • venturacountydatadownloads-vcitsgis.hub.arcgis.com
    Updated Apr 24, 2024
    + more versions
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    County of Ventura (2024). Ventura County Community College Board of Trustee [Dataset]. https://hub.arcgis.com/datasets/ee8e8ce0f8e14048ad9534c93aa10b6b
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    Dataset updated
    Apr 24, 2024
    Dataset authored and provided by
    County of Ventura
    Area covered
    Description

    The boundary of the individual Trustee Districts was provided by the School District to the Ventura County Clerk/Recorder Elections Division. These boundaries are based on Census data from the 2020 census. The census data does not follow current GIS data for the County of Ventura. The data was used to modify the Election Precincts as maintained by the Ventura County Clerk/Recorder Elections Division. The boundary was then provided to Information Technology Services Department/GIS division to be matched up to the boundary of the School District. The interior lines were redrawn to match Election Precinct polygons. The next scheduled changes should be for the 2030 census data in 2032. The Political boundaries extends 3 miles offshore but the polygons only reflect the land area.

  8. Non Voters[U.S.]

    • kaggle.com
    zip
    Updated Dec 6, 2020
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    Rishabh Dhyani (2020). Non Voters[U.S.] [Dataset]. https://www.kaggle.com/datasets/rishabhdhyani4/non-votersus/discussion
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    zip(289343 bytes)Available download formats
    Dataset updated
    Dec 6, 2020
    Authors
    Rishabh Dhyani
    License

    https://www.usa.gov/government-works/https://www.usa.gov/government-works/

    Area covered
    United States
    Description

    Context

    Why Millions Of Americans Don’t Vote
    

    Content

    Data presented here comes from polling done by Ipsos for FiveThirtyEight, using Ipsos’s KnowledgePanel, a probability-based online panel that is recruited to be representative of the U.S. population. The poll was conducted from Sept. 15 to Sept. 25 among a sample of U.S. citizens that oversampled young, Black and Hispanic respondents, with 8,327 respondents, and was weighted according to general population benchmarks for U.S. citizens from the U.S. Census Bureau’s Current Population Survey March 2019 Supplement. The voter file company Aristotle then matched respondents to a voter file to more accurately understand their voting history using the panelist’s first name, last name, zip code, and eight characters of their address, using the National Change of Address program if applicable. Sixty-four percent of the sample (5,355 respondents) matched, although we also included respondents who did not match the voter file but described themselves as voting “rarely” or “never” in our survey, so as to avoid underrepresenting nonvoters, who are less likely to be included in the voter file to begin with. We dropped respondents who were only eligible to vote in three elections or fewer. We defined those who almost always vote as those who voted in all (or all but one) of the national elections (presidential and midterm) they were eligible to vote in since 2000; those who vote sometimes as those who voted in at least two elections, but fewer than all the elections they were eligible to vote in (or all but one); and those who rarely or never vote as those who voted in no elections, or just one.

    The data included here is the final sample we used: 5,239 respondents who matched to the voter file and whose verified vote history we have, and 597 respondents who did not match to the voter file and described themselves as voting "rarely" or "never," all of whom have been eligible for at least 4 elections.

    Acknowledgements

    We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.

    Inspiration

    Your data will be in front of the world's largest data science community. What questions do you want to see answered?

  9. c

    Legislative Districts of Idaho for 1992 - 2002 [Historical]

    • s.cnmilf.com
    • catalog.data.gov
    • +2more
    Updated Nov 30, 2020
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    Idaho Legislative Services Office (2020). Legislative Districts of Idaho for 1992 - 2002 [Historical] [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/legislative-districts-of-idaho-for-1992-2002-historical
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    Dataset updated
    Nov 30, 2020
    Dataset provided by
    Idaho Legislative Services Office
    Area covered
    Idaho
    Description

    The downloadable ZIP file contains Esri shapefiles and PDF maps. Contains the information used to determine the _location of the new legislative and congressional district boundaries for the state of Idaho as adopted by Idaho's first Commission on Redistricting on March 9, 2002. Contains viewable and printable legislative and congressional district maps, viewable and printable reports, and importable geographic data files.These data were contributed to INSIDE Idaho at the University of Idaho Library in 2001. CD/DVD -ROM availability: https://alliance-primo.hosted.exlibrisgroup.com/permalink/f/m1uotc/CP71156191150001451These files were created by a six-person, by-partisan commission, consisting of six commission members, three democrats and three republicans. This commission was given 90 days to redraw congressional and legislative district boundaries for the state of Idaho. Due to lawsuits, the process was extended. This legislative plan was approved by the commission on March 9th, 2002 and was previously called L97. All digital data originates from TIGER/Line files and 2000 U.S. Census data.Frequently asked questions:How often are Idaho's legislative and congressional districts redrawn? Once every ten years after each census, as required by law, or when directed by the Idaho Supreme Court. The most recent redistricting followed the 2000 census. Redistricting is not expected to occur again in Idaho until after the 2010 census. Who redrew Idaho's legislative and congressional districts? In 2001, for the first time, Idaho used a citizens' commission to redraw its legislative and congressional district boundaries. Before Idaho voters amended the state Constitution in 1994 to create a Redistricting Commission, redistricting was done by a committee of the Idaho Legislature. The committee's new district plans then had to pass the Legislature before becoming law. Who was on the Redistricting Commission? Idaho's first Commission on Redistricting was composed of Co-Chairmen Kristi Sellers of Chubbuck and Tom Stuart of Boise and Stanley. The other four members were Raymond Givens of Coeur d'Alene, Dean Haagenson of Hayden Lake, Karl Shurtliff of Boise, John Hepworth of Buhl (who resigned effective December 4, 2001), and Derlin Taylor of Burley (who was appointed to replace Mr. Hepworth). What are the requirements for being a Redistricting Commissioner? According to Idaho Law, no person may serve on the commission who: 1. Is not a registered voter of the state at the time of selection; or 2. Is or has been within one (1) year a registered lobbyist; or 3. Is or has been within two (2) years prior to selection an elected official or elected legislative district, county or state party officer. (This requirement does not apply to precinct committeepersons.) The individual appointing authorities may consider additional criteria beyond these statutory requirements. Idaho law also prohibits a person who has served on the Redistricting Commission from serving in either house of the legislature for five years following their service on the commission. When did Idaho's first Commission on Redistricting meet? Idaho law allows the Commission only 90 days to conduct its business. The Redistricting Commission was formed on June 5, 2001. Its 90-day time period would expire on September 3, 2001. After holding hearings around the state in June and July, a majority of the Commission voted to adopt new legislative and congressional districts on August 22, 2001. On November 29th, the Idaho Supreme Court ruled the Commission's legislative redistricting plan unconstitutional and directed them to reconvene and adopt an alternative plan. The Commission did so, adopting a new plan on January 8, 2000. The Idaho Supreme Court found the Commission's second legislative map unconstitutional on March 1, 2002 and ordered the Commission to try again. The Commission adopted a third plan on March 9, 2002. The Supreme Court denied numerous challenges to this third map. It then became the basis for the 2002 primary and General elections and is expected to be used until the 2012 elections. What is the basic timetable for Idaho to redraw its legislative and congressional districts?Typically, and according to Idaho law, the Redistricting Commission cannot be formally convened until after Idaho has received the official census counts and not before June 1 of a year ending in one. Idaho's first Commission on redistricting was officially created on June 5, 2001. By law, a Commission then has 90 days (or until September 3, 2001 in the case of Idaho's first Commission) to approve new legislative and congressional district boundaries based on the most recent census figures. If at least four of the six commissioners fail to approve new legislative and congressional district plans before that 90-day time period expires, the Commission will cease to exist. The law is silent as to what happens next. Could you summarize the important dates for Idaho's first Commission on Redistricting one more time please? After January 1, 2001 but before April 1, 2001: As required by federal law, the Census Bureau must deliver to the states the small area population counts upon which redistricting is based. The Census Bureau determines the exact date within this window when Idaho will get its population figures. Idaho's were delivered on March 23, 2001. Why conduct a census anyway? The original and still primary reason for conducting a national census every ten years is to determine how the 435 seats in the United States House of Representatives are to be apportioned among the 50 states. Each state receives its share of the 435 seats in the U.S. House based on the proportion of its population to that of the total U.S. population. For example, the population shifts during the 1990's resulted in the Northeastern states losing population and therefore seats in Congress to the Southern and the Western states. What is reapportionment? Reapportionment is a federal issue that applies only to Congress. It is the process of dividing up the 435 seats in the U.S. House of Representatives among the 50 states based on each state's proportion of the total U.S. population as determined by the most recent census. Apportionment determines the each state's power, as expressed by the size of their congressional delegation, in Congress and, through the electoral college, directly affects the selection of the president (each state's number of votes in the electoral college equals the number of its representatives and senators in Congress). Like all states, Idaho has two U.S. senators. Based on our 1990 population of 1,006,000 people and our 2000 population of 1,293,953, and relative to the populations of the other 49 states, Idaho will have two seats in the U.S. House of Representatives. Even with the state's 28.5% population increase from 1990 to 2000, Idaho will not be getting a third seat in the U.S. House of Representatives. Assuming Idaho keeps growing at the same rate it did through the decade of the 1990's, it will likely be 30 or 40 years (after 3 or 4 more censuses) before Idaho gets a third congressional seat. What is redistricting? Redistricting is the process of redrawing the boundaries of legislative and congressional districts within each state to achieve population equality among all congressional districts and among all legislative districts. The U.S. Constitution requires this be done for all congressional districts after each decennial census. The Idaho Constitution also requires that this be done for all legislative districts after each census. The democratic principle behind redistricting is "one person, one vote." Requiring that districts be of equal population ensures that every elected state legislator or U.S. congressman represents very close to the same number of people in that state, therefore, each citizen's vote will carry the same weight. How are reapportionment and redistricting related to the census? The original and still primary reason for conducting a census every ten years is to apportion the (now) 435 seats in the U.S. House of Representatives among the several states. The census records population changes and is the legally recognized basis for redrawing electoral districts of equal population. Why is redistricting so important? In a democracy, it is important for all citizens to have equal representation. The political parties also see redistricting as an opportunity to draw districts that favor electing their members and, conversely, that are unfavorable for electing their political opposition. (It's for this reason that redistricting has been described as "the purest form of political bloodsport.") What is PL 94-171? Public Law (PL) 94-171 (Title 13, United States Code) was enacted by Congress in 1975. It was intended to provide state legislatures with small-area census population totals for use in redistricting. The law's origins lie with the "one person, one vote" court decisions in the 1960's. State legislatures needed to reconcile Census Bureau's small geographic area boundaries with voting tabulation districts (precincts) boundaries to create legislative districts with balanced populations. The Census Bureau worked with state legislatures and others to meet this need beginning with the 1980 census. The resulting Public Law 94-171 allows states to work voluntarily with the Census Bureau to match voting district boundaries with small-area census boundaries. With this done, the Bureau can report to those participating states the census population totals broken down by major race group and Hispanic origin for the total population and for persons aged 18 years and older for each census subdivision. Idaho participated in the Bureau's Census 2000 Redistricting Data Program and, where counties used visible features to delineate precinct boundaries, matched those boundaries with census reporting areas. In those instances where counties did not use visible features

  10. Presidential Election exit polls: share of votes by income U.S. 2020

    • statista.com
    Updated Nov 3, 2020
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    Statista (2020). Presidential Election exit polls: share of votes by income U.S. 2020 [Dataset]. https://www.statista.com/statistics/1184428/presidential-election-exit-polls-share-votes-income-us/
    Explore at:
    Dataset updated
    Nov 3, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 3, 2020
    Area covered
    United States
    Description

    According to exit polling in the 2020 Presidential Election in the United States, ** percent of surveyed voters making less than 50,000 U.S. dollars reported voting for former Vice President Joe Biden. In the race to become the next president of the United States, ** percent of voters with an income of 100,000 U.S. dollars or more reported voting for incumbent President Donald Trump.

  11. U.S. presidential election exit polls: share of votes by education 2024

    • statista.com
    Updated Nov 9, 2024
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    Statista (2024). U.S. presidential election exit polls: share of votes by education 2024 [Dataset]. https://www.statista.com/statistics/1535279/presidential-election-exit-polls-share-votes-education-us/
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    Dataset updated
    Nov 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 9, 2024
    Area covered
    United States
    Description

    According to exit polling in *** key states of the 2024 presidential election in the United States, almost ********** of voters who had never attended college reported voting for Donald Trump. In comparison, a similar share of voters with ******** degrees reported voting for Kamala Harris.

  12. V

    Loudoun Election Districts 2022

    • data.virginia.gov
    • catalog.data.gov
    • +9more
    Updated Sep 12, 2023
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    Loudoun County (2023). Loudoun Election Districts 2022 [Dataset]. https://data.virginia.gov/dataset/loudoun-election-districts-2022
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    arcgis geoservices rest api, html, kml, geojson, zip, csvAvailable download formats
    Dataset updated
    Sep 12, 2023
    Dataset provided by
    Loudoun County GIS
    Authors
    Loudoun County
    Area covered
    Loudoun County
    Description

    More Metadata

    This file contains the boundaries of the Board of Supervisors election districts derived from 2020 US census. The layer also contains the voting precincts inside each district, which is location of polling places for each district. The Voting Precincts within each District undergo a yearly evaluation, which may lead to a yearly update to the layer itself. The Election District Boundaries will not change until 2030, but the individual Precincts may be split, combined, adjusted, etc.

    On June 7, 2022, the Loudoun County Board of Supervisors approved the proposed Amendments to the Codified Ordinances of Loudoun County, Chapter 207 – Election Districts (which implemented the LT-Revised 1 Redistricting Plan). Loudoun County submitted the Certificate of No Objection to the Office of the Attorney General on June 23, 2022.

  13. U.S. presidential election exit polls: share of votes by race and ethnicity...

    • statista.com
    Updated Nov 9, 2024
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    Statista (2024). U.S. presidential election exit polls: share of votes by race and ethnicity 2024 [Dataset]. https://www.statista.com/statistics/1535265/presidential-election-exit-polls-share-votes-race-and-ethnicity-us/
    Explore at:
    Dataset updated
    Nov 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 9, 2024
    Area covered
    United States
    Description

    According to exit polling in ten key states of the 2024 presidential election in the United States, ** percent of surveyed white voters reported voting for Donald Trump. In contrast, ** percent of Black voters reported voting for Kamala Harris.

  14. P

    Broward County Voter Precincts 2022

    • data.pompanobeachfl.gov
    Updated Jan 13, 2023
    + more versions
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    External Datasets (2023). Broward County Voter Precincts 2022 [Dataset]. https://data.pompanobeachfl.gov/dataset/broward-county-voter-precincts-2022
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    zip, kml, html, geojson, csv, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Jan 13, 2023
    Dataset provided by
    cjennings_BCGIS
    Authors
    External Datasets
    Area covered
    Broward County
    Description

    Voter Precincts for the County of Broward. There are 345 precincts along with areas designated as "998" non voter areas. The precincts encompass all Broward municipalities. Precincts were combined prior to the August 23rd, 2022. Then split prior to the national November 8th, 2022 election.

    Source: Broward County Supervisor of Elections, Florida International University, U.S. Census Data, ESRI

    Effective Date: 1/13/2023

    Update Cycle: TBD

  15. U.S. presidential election exit polls: share of votes by income 2024

    • statista.com
    Updated Dec 13, 2024
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    Abigail Tierney (2024). U.S. presidential election exit polls: share of votes by income 2024 [Dataset]. https://www.statista.com/topics/11901/2024-us-presidential-election/
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    Dataset updated
    Dec 13, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Abigail Tierney
    Area covered
    United States
    Description

    According to exit polling in ten key states of the 2024 presidential election in the United States, 46 percent of voters with a 2023 household income of 30,000 U.S. dollars or less reported voting for Donald Trump. In comparison, 51 percent of voters with a total family income of 100,000 to 199,999 U.S. dollars reported voting for Kamala Harris.

  16. Voter turnout in US presidential elections by ethnicity 1964-2020

    • statista.com
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    Statista, Voter turnout in US presidential elections by ethnicity 1964-2020 [Dataset]. https://www.statista.com/statistics/1096113/voter-turnout-presidential-elections-by-ethnicity-historical/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    United States presidential elections are quadrennial elections that decide who will be the President and Vice President of the United States for the next four years. Voter turnout has ranged between 54 and 70 percent since 1964, with white voters having the highest voter turnout rate (particularly when those of Hispanic descent are excluded). In recent decades, turnout among black voters has got much closer to the national average, and in 2008 and 2012, the turnout among black voters was higher than the national average, exceeded only by non-Hispanic white voters; this has been attributed to Barack Obama's nomination as the Democratic nominee in these years, where he was the first African American candidate to run as a major party's nominee. Turnout among Asian and Hispanic voters is much lower than the national average, and turnout has even been below half of the national average in some elections. This has been attributed to a variety of factors, such as the absence of voting tradition in some communities or families, the concentration of Asian and Hispanic communities in urban (non-swing) areas, and a disproportionate number of young people (who are less likely to vote).

  17. U.S. top presidential candidates for 2024 election October 2024, by age

    • statista.com
    Updated Oct 4, 2024
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    Statista (2024). U.S. top presidential candidates for 2024 election October 2024, by age [Dataset]. https://www.statista.com/statistics/1422251/top-2024-presidential-candidates-age-us/
    Explore at:
    Dataset updated
    Oct 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Sep 29, 2024 - Oct 1, 2024
    Area covered
    United States
    Description

    According to an October 2024 survey, young Americans were much more likely to vote for Kamala Harris in the November 2024 presidential elections. Of those between the ages of 18 and 29, 60 percent said they were planning on voting for Harris, compared to 33 percent who said they planned on voting for Trump. In contrast, Trump was much more popular among those between 45 and 64 years old.

  18. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Bryan, Michael (2025). U.S. Voting by Census Block Groups [Dataset]. http://doi.org/10.7910/DVN/NKNWBX

U.S. Voting by Census Block Groups

Explore at:
3 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Oct 29, 2025
Dataset provided by
Harvard Dataverse
Authors
Bryan, Michael
Area covered
United States
Description

PROBLEM AND OPPORTUNITY In the United States, voting is largely a private matter. A registered voter is given a randomized ballot form or machine to prevent linkage between their voting choices and their identity. This disconnect supports confidence in the election process, but it provides obstacles to an election's analysis. A common solution is to field exit polls, interviewing voters immediately after leaving their polling location. This method is rife with bias, however, and functionally limited in direct demographics data collected. For the 2020 general election, though, most states published their election results for each voting location. These publications were additionally supported by the geographical areas assigned to each location, the voting precincts. As a result, geographic processing can now be applied to project precinct election results onto Census block groups. While precinct have few demographic traits directly, their geographies have characteristics that make them projectable onto U.S. Census geographies. Both state voting precincts and U.S. Census block groups: are exclusive, and do not overlap are adjacent, fully covering their corresponding state and potentially county have roughly the same size in area, population and voter presence Analytically, a projection of local demographics does not allow conclusions about voters themselves. However, the dataset does allow statements related to the geographies that yield voting behavior. One could say, for example, that an area dominated by a particular voting pattern would have mean traits of age, race, income or household structure. The dataset that results from this programming provides voting results allocated by Census block groups. The block group identifier can be joined to Census Decennial and American Community Survey demographic estimates. DATA SOURCES The state election results and geographies have been compiled by Voting and Election Science team on Harvard's dataverse. State voting precincts lie within state and county boundaries. The Census Bureau, on the other hand, publishes its estimates across a variety of geographic definitions including a hierarchy of states, counties, census tracts and block groups. Their definitions can be found here. The geometric shapefiles for each block group are available here. The lowest level of this geography changes often and can obsolesce before the next census survey (Decennial or American Community Survey programs). The second to lowest census level, block groups, have the benefit of both granularity and stability however. The 2020 Decennial survey details US demographics into 217,740 block groups with between a few hundred and a few thousand people. Dataset Structure The dataset's columns include: Column Definition BLOCKGROUP_GEOID 12 digit primary key. Census GEOID of the block group row. This code concatenates: 2 digit state 3 digit county within state 6 digit Census Tract identifier 1 digit Census Block Group identifier within tract STATE State abbreviation, redundent with 2 digit state FIPS code above REP Votes for Republican party candidate for president DEM Votes for Democratic party candidate for president LIB Votes for Libertarian party candidate for president OTH Votes for presidential candidates other than Republican, Democratic or Libertarian AREA square kilometers of area associated with this block group GAP total area of the block group, net of area attributed to voting precincts PRECINCTS Number of voting precincts that intersect this block group ASSUMPTIONS, NOTES AND CONCERNS: Votes are attributed based upon the proportion of the precinct's area that intersects the corresponding block group. Alternative methods are left to the analyst's initiative. 50 states and the District of Columbia are in scope as those U.S. possessions voting in the general election for the U.S. Presidency. Three states did not report their results at the precinct level: South Dakota, Kentucky and West Virginia. A dummy block group is added for each of these states to maintain national totals. These states represent 2.1% of all votes cast. Counties are commonly coded using FIPS codes. However, each election result file may have the county field named differently. Also, three states do not share county definitions - Delaware, Massachusetts, Alaska and the District of Columbia. Block groups may be used to capture geographies that do not have population like bodies of water. As a result, block groups without intersection voting precincts are not uncommon. In the U.S., elections are administered at a state level with the Federal Elections Commission compiling state totals against the Electoral College weights. The states have liberty, though, to define and change their own voting precincts https://en.wikipedia.org/wiki/Electoral_precinct. The Census Bureau... Visit https://dataone.org/datasets/sha256%3A05707c1dc04a814129f751937a6ea56b08413546b18b351a85bc96da16a7f8b5 for complete metadata about this dataset.

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