In the second and third weeks of September 2024, the presidential campaign of U.S. vice president Kamala Harris spent 41.3 million U.S. dollars on broadcast TV advertising, while her main sponsor, the FF PAC in coordination with LCV Victory Fund, spent almost 17 million. The campaign of Harris' competitor, former president Donald Trump, spent 1.9 million, while his main sponsor, Make America Great Again Inc., allotted 10.3 million.

Leading theories of race and participation posit that minority voters are mobilized by co-ethnic candidates. However, past studies are unable to disentangle candidate effects from factors associated with the places from which candidates emerge. I reevaluate the links between candidate race, district composition, and turnout by leveraging a nationwide database of over 185 million individual registration records, including estimates for the race of every voter. Combining these records with detailed information about 3,000 recent congressional primary and general election candidates, I find that minority turnout is not higher in districts with minority candidates, after accounting for the relative size of the ethnic group within a district. Instead, Black and Latino citizens are more likely to vote in both primary and general elections as their share of the population increases, regardless of candidate race.

About this dataset

Context

The dataset tabulates the population of Lead by race. It includes the population of Lead across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Lead across relevant racial categories.

Key observations

The percent distribution of Lead population by race (across all racial categories recognized by the U.S. Census Bureau): 95.60% are white, 0.87% are American Indian and Alaska Native, 0.53% are some other race and 3% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Lead
• Population: The population of the racial category (excluding ethnicity) in the Lead is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Lead total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Lead Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Lead by race. It includes the distribution of the Non-Hispanic population of Lead across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Lead across relevant racial categories.

Key observations

Of the Non-Hispanic population in Lead, the largest racial group is White alone with a population of 2,854 (96.91% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Lead
• Population: The population of the racial category (for Non-Hispanic) in the Lead is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Lead total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Lead Population by Race & Ethnicity. You can refer the same here

As of January 1, 2009, Connecticut law mandates that medical providers must conduct annual lead screening (i.e., blood lead testing) for each child 9 to 35 months of age. Furthermore, the law requires that any child between 36-72 months of age who has not been previously tested must also be tested by the child’s medical provider, regardless of risk.

This dataset shows the relative risk of childhood lead poisoning by race/ethnicity.

Outside spending in U.S. political races for 2024 shows the presidential contest dominating with over two billion U.S. dollars invested, dwarfing Senate and House races. This massive influx of funds highlights the outsized influence of external groups on American elections. Senate battlegrounds attract major outside money Key Senate races are drawing substantial outside spending, with Ohio leading at nearly 309 million U.S. dollars. This investment proved impactful, as Republican Bernie Moreno secured a victory, flipping the previously Democratic-held seat. Similarly, Montana's Senate race, which saw 165.5 million U.S. dollars in outside spending, resulted in Republican Tim Sheehy winning and flipping another Democratic seat. Presidential race funding reaches new heights The 2024 presidential race continues the trend of escalating campaign costs, with outside spending topping 2 billion U.S. dollars. This follows the pattern set in 2020 when Democratic candidates alone spent approximately 3.16 billion U.S. dollars. By December 2024, Vice President Kamala Harris's campaign had amassed about 1.2 billion U.S. dollars in committee funding, surpassing former President Donald Trump's committee. These figures reflect the intensifying financial arms race in presidential campaigns, highlighting the growing role of money in American politics.

As of January 1, 2009, Connecticut law mandates that medical providers must conduct annual lead screening (i.e., blood lead testing) for each child 9 to 35 months of age. Furthermore, the law requires that any child between 36-72 months of age who has not been previously tested must also be tested by the child’s medical provider, regardless of risk. This dataset shows the incidence of childhood lead poisoning by race/ethnicity. Incidence = Number of new cases Incidence % = Number of new cases / Population screened with no history of elevated level

The Impact Evaluation of Race to the Top and School Improvement Grants (RTT-SIG Impact Evaluation) is a study that is part of the Impact Evaluation of Race to the Top and School Improvement Grants (RTT-SIG Impact Evaluation) program. RTT-SIG Impact Evaluation (https://ies.ed.gov/ncee/projects/evaluation/other_racetotop.asp) is a cross-sectional survey that assesses the implementation of the Race to the Top (RTT) and School Improvement Grant (SIG) programs at the State, local education agency (LEA), and school levels, as well as whether the receipt of RTT and/or SIG funding to implement a school turnaround model has had an impact on outcomes for the lowest-achieving schools. Additionally, the study investigates whether RTT reforms were related to improvements in student outcomes and whether implementation of the four school turnaround models, and the strategies within those models, was related to improvement in outcomes for the lowest-achieving schools. The study was conducted using a combination of telephone interviews and web-based surveys targeted to school administrators at the state, LEA, and school levels. Key statistics produced from RTT-SIG Impact Evaluation include State, LEA, and school adoption levels of policies and practices promoted by RTT and SIG, as well as impacts on student outcomes of RTT and SIG funding.

About this dataset

Context

The dataset tabulates the population of Lead Hill by race. It includes the population of Lead Hill across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Lead Hill across relevant racial categories.

Key observations

The percent distribution of Lead Hill population by race (across all racial categories recognized by the U.S. Census Bureau): 91.87% are white, 0.71% are Black or African American, 1.77% are some other race and 5.65% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Lead Hill
• Population: The population of the racial category (excluding ethnicity) in the Lead Hill is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Lead Hill total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Lead Hill Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Round Top by race. It includes the distribution of the Non-Hispanic population of Round Top across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Round Top across relevant racial categories.

Key observations

Of the Non-Hispanic population in Round Top, the largest racial group is White alone with a population of 99 (97.06% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Round Top
• Population: The population of the racial category (for Non-Hispanic) in the Round Top is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Round Top total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Round Top Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Lead Hill by race. It includes the distribution of the Non-Hispanic population of Lead Hill across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Lead Hill across relevant racial categories.

Key observations

Of the Non-Hispanic population in Lead Hill, the largest racial group is White alone with a population of 258 (91.81% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Lead Hill
• Population: The population of the racial category (for Non-Hispanic) in the Lead Hill is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Lead Hill total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Lead Hill Population by Race & Ethnicity. You can refer the same here

This repository includes data and code needed to recreate Figure 1 in the main text and all tables and figures in the Online Appendix of "One Run Leads to Another: Minority Incumbents and the Emergence of Lower Ticket Minority Candidates."

On November 5, 2024, Senate elections will be held in the state of Texas. As of November polling, Republican incumbent Ted Cruz was leading Democratic U.S. Representative Colin Alfred by over four percentage points. This race is one of the nine Republican-held U.S. Senate seats up for election in 2024.

This page contains links to publications, research, reports, related sites, technical assistance, events notices, or presentations for the Race to the Top Fund program.

The 1948 US presidential election was the first in sixteen years that did not have Franklin D. Roosevelt leading the ticket. The race was contested by incumbent President Harry S. Truman of the Democratic Party, who had ascended to the presidency following FDR's death in 1945, and Thomas E. Dewey of the Republican Party, who had also appeared on the 1944 ballot. Storm Thurmond and Henry A. Wallace made the largest impact out of any third party candidates. Thurmond represented the newly-formed States' Rights Party, which was made up of former Democrats who wanted to protect racial segregation in the South, and were disturbed by Truman's support of civil rights for ethnic minorities. Wallace had recently formed a new Progressive Party (not to be confused with Theodore Roosevelt's Progressive Party in the 1912 election) which facilitated the former Vice President's election campaign after his dismissal as Secretary of Commerce by President Truman in 1945. The race for Eisenhower Many Republican voters had put forward Dwight D. Eisenhower (the most popular General of the Second World War) as their candidate, and he was the favorite in the early stages of the race, despite the fact that Eisenhower had never shown interest in running for office. When he refused to accept the nomination, a close, three-way race ensued, with Dewey eventually emerging as the Republican candidate. In contrast to the Republicans, it was the Democratic Party's leadership who wished to put Eisenhower forward as their candidate, with President Truman secretly agreeing to run as Eisenhower's vice president. When Eisenhower refused to run, the Democratic leadership failed to find a suitable opponent, and reluctantly supported Truman for a second term. Results Dewey was the firm favorite to win the presidency, due to Truman's low approval ratings, however Truman was re-elected as President of the United States with just under fifty percent of the popular vote, and more than 57 percent of the electoral vote. Dewey receive 45 percent of the popular vote and 36 percent of the electoral votes, while the two most popular third party candidates received 2.4 percent of the popular vote. The difference between these two candidates, however, was that Strom Thurmond carried four states and took 7.3 percent of the the popular vote, and this was also the first time that Mississippi or Alabama did not vote for the Democratic Candidate since 1872, marking the end of the Democratic Party's grip on the southern states.

2024 Florida Senate - Scott vs. Mucarsel-Powell | RealClearPolling

Dataset Description: F1 Races 2000-2024

Overview

This dataset consolidates data from Formula 1 races between 2000 and 2024, designed to facilitate predictive modeling and analytical tasks related to race outcomes. The dataset integrates information from multiple reliable sources, including the Ergast API, VisualCrossing API, and Wikipedia, enriched through feature engineering techniques to enhance its predictive power.

Data Sources

• Ergast API: Provides historical race data including driver and constructor statistics, race results, qualifying times, and more.
• VisualCrossing API: Offers detailed weather data, including precipitation information during race events.
• Wikipedia: Supplies circuit-specific details like the number of turns and track length through automated web scraping.

Dataset Structure

The dataset includes comprehensive race-related attributes categorized as follows: - Race Information: Year, round, circuit ID, and weather conditions. - Driver & Constructor Details: IDs, performance metrics, historical standings, and nationality. - Race Metrics: Grid position, lap times, pit stops, status, and final positions. - Engineered Features: Derived variables such as driver and constructor podium finish percentages, average positions, weighted probabilities based on circuit characteristics, and recent performance trends.

Key Features

• Top 3 Finish: Binary target variable indicating if a driver finished in the top 3.
• Weather Conditions: Binary indicator for rainy conditions during the race.
• Performance Metrics: Historical and seasonal averages for both drivers and constructors.
• Track Characteristics: Number of turns and track length for each circuit.

Potential Use Cases

• Predictive Modeling: Classify and predict podium finishes using machine learning algorithms.
• Performance Analysis: Evaluate driver and constructor performance trends over multiple seasons.
• Feature Engineering Practice: Apply advanced techniques to create new predictive features.

Technical Details

• Data Format: CSV
• Total Records: Over 9,800 race results
• Missing Values: Managed through strategic imputation methods, especially for rookie drivers and new race entries.
• Class Imbalance: Addressed using SMOTE during modeling to ensure balanced predictive outcomes.

Acknowledgments

Special thanks to the contributors of the Ergast API, VisualCrossing API, and the Wikipedia community for providing essential data points that made this dataset possible.

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in Race to the Top: The Case for the Financial Stability Board, PIIE Policy Brief 17-12. If you use the data, please cite as: Sheets, Nathan. (2017). Race to the Top: The Case for the Financial Stability Board. PIIE Policy Brief 17-12. Peterson Institute for International Economics.

According to exit polling in the 2020 Presidential Election in the United States, ** percent of surveyed voters whose leading issue was the coronavirus pandemic reported voting for former Vice President Joe Biden. In the race to become the next president of the United States, ** percent of voters whose leading issue was crime and safety reported voting for incumbent President Donald Trump.

General Overview

I created this dataset originally to preserve NASCAR stage results. NASCAR's official website preserves full stage results, but as of now, only 2023-2025 results are available there. The results from earlier years were removed and links to them redirect to Racing Reference, a site which stores all NASCAR (and many other racing series) results since the beginning of the sport. However, that site only records the top 10 stage finishers for each race (points earning positions). To see full stage 1 and stage 2 finishing orders from 2017 (the first year of stage racing) through 2022, you had to use the Wayback Machine on NASCAR.com...until now.

Originality

• Only publicly available dataset (I'm aware of) that contains NASCAR results and points-per-race data all in one file, so to be useful for analysis and predictive modeling
• Only NASCAR results source containing team names (as opposed to names of owners on Racing Reference)
• Only NASCAR results source with full stage finishing orders going back to 2017 (still looking for complete stage finishing orders, beyond just top 10s, from Race 23 of 2017 through Race 36 of 2019)

Attribute overview

1) year - year in which the observation took place

2) race_num - order of races each season, with 1 being the first and 36 being the last - to include the pre-season Daytona Duel races (which count as a stage), I gave Duel 1 the value '-1' and Duel 2 the value '-2'

3) track - shortened name of the track at which the observation took place - tracks with terrain changes / multiple layouts were considered separate tracks, ex: Bristol and Bristol Dirt, Daytona and Daytona Road Course

4) track_type - 6 different track types including: short tracks (less than 1 mile), short intermediates (more than 1 mile and less than 1.5 miles), intermediates (roughly 1.5 miles / "cookie cutters"), long intermediates (longer than 1.5 miles but not superspeedways or road courses), superspeedways (drafting / pack racing tracks), road course (tracks with both left and right turns) - notably, Atlanta was the only track to change its track type in the observed years, being reconfigured from intermediate to superspeedway in 2022

5) fin - final finishing order of each race

6) start - starting order of each race (no distinction between traditional qualifying and formula / owners-points-based starting lineups)

7) car_num - the number printed on the race car, distinct from all other competitors in each race

8) driver - full name of the driver

9) manu - manufacturer of the car

10) team_name - name of the team which fielded the driver and car in a particular observation

11) laps - number of laps the driver completed in the race

12) laps_led - number of laps the driver led in the race

13) status - 'running' for drivers who finished the race; otherwise, the reason they failed to finish - 'accident' is a synonym for 'crash' (used interchangeably on different sources)

14) points - total points earned in the race - Note 1: drivers who did not declare for Cup points earned 0 points regardless of finishing position - Note 2: disqualified drivers are given last place points, and if there is more than one disqualified driver, they will be ordered by their original finishing position behind everyone else

15) stage_1 - finishing position in stage 1

16) stage-2 - finishing position in stage 2

17) stage_3_or_duel - finishing position in stage 3 (Coca Cola 600 only) or Daytona Duel race (counts as a stage)

18) stage_points - total stage points earned in the race - Note 1: drivers who did not declare for Cup points earned 0 points regardless of stage finishing position, as did disqualified drivers, and Championship 4 drivers in the season finale - Note 2: if a disqualified driver would have earned stage points, their points were given to the next finisher, and so on, so that the original 11th place finisher earns 1 stage point