As of July 2024, national general election polling in the United States showed Donald Trump leading Joe Biden by an average of 0.8 percentage points across several polls, which was lower than the months prior. Although Trump has maintained a lead over the last few months, the race between the two presidential front-runners has tightened.

The Politbarometer has been conducted since 1977 on an almost monthly basis by the Research Group for Elections (Forschungsgruppe Wahlen) for the Second German Television (ZDF). Since 1990, this database has also been available for the new German states. The survey focuses on the opinions and attitudes of the voting population in the Federal Republic on current political topics, parties, politicians, and voting behavior. From 1990 to 1995 and from 1999 onward, the Politbarometer surveys were conducted separately in the eastern and western federal states (Politbarometer East and Politbarometer West). The separate monthly surveys of a year are integrated into a cumulative data set that includes all surveys of a year and all variables of the respective year. The Politbarometer short surveys, collected with varying frequency throughout the year, are integrated into the annual cumulation starting from 2003.

United States The Economist YouGov Polls: 2024 Presidential Election: Donald Trump data was reported at 46.000 % in 29 Oct 2024. This stayed constant from the previous number of 46.000 % for 22 Oct 2024. United States The Economist YouGov Polls: 2024 Presidential Election: Donald Trump data is updated weekly, averaging 43.000 % from May 2023 (Median) to 29 Oct 2024, with 61 observations. The data reached an all-time high of 46.000 % in 29 Oct 2024 and a record low of 38.000 % in 31 Oct 2023. United States The Economist YouGov Polls: 2024 Presidential Election: Donald Trump data remains active status in CEIC and is reported by YouGov PLC. The data is categorized under Global Database’s United States – Table US.PR004: The Economist YouGov Polls: 2024 Presidential Election (Discontinued). If an election for president were going to be held now and the Democratic nominee was Joe Biden and the Republican nominee was Donald Trump, would you vote for...

This dataset provides detailed information for the 2024 US Presidential Election, offering a valuable resource for political analysis and research. It includes a variety of data types, such as profiles of candidates, primary/caucus results, poll data, and debate transcripts. Key updates have been integrated throughout the election season, including the latest poll figures, transcripts from the Vice-Presidential debate between Walz and Vance, and the debate between Trump and Harris.

Significant events covered within the dataset include an annotated image and transcripts related to an assassination attempt on former President Trump. The political landscape evolved with the Democratic Party replacing President Biden with Kamala Harris in late August, setting up a contest between Trump and Harris, alongside nominees from smaller factions. The dataset also features approval ratings for sitting presidents, including Biden and Trump, and details on candidates like Robert F Kennedy Jr, who is running as an independent. This collection is regularly updated to reflect developments as the election cycle progresses, making it a current and dynamic source for understanding the 2024 US Presidential Election.

Columns

The dataset contains information on candidates with formal bids for the presidency, including the following columns:

• party: The political party affiliation of the candidate (e.g., republican, democrat, other).
• name: The full name of the candidate.
• date_announced: The date on which the candidate formally announced their intention to run for president. This column contains 21 unique values, ranging from 16 November 2022 to 1 July 2024.
• date_withdrawn: The date on which the candidate withdrew their bid for the presidency.

The data indicates that 62% of the candidate entries are Republican, 19% are Democrat, and 19% represent other parties.

Distribution

The data file is typically provided in a CSV format. A sample file will be made available separately on the platform. The dataset is listed as Version 1.0 and has a quality rating of 5 out of 5. While specific row or record counts are not currently available, the dataset is structured to facilitate analysis of various aspects of the 2024 US Presidential Election. It is available globally and offered as a free dataset. The data types included are tabular and text.

Usage

This dataset is an ideal resource for a multitude of applications and use cases, including:

• Political analysis and research into election trends.
• Government and civic record analysis.
• Natural Language Processing (NLP) tasks, utilising the debate transcripts for sentiment analysis, topic modelling, or text generation.
• Artificial Intelligence (AI) and Machine Learning (ML) model development for election outcome prediction, voter behaviour analysis, or candidate performance assessment.
• Studying the historical context and evolution of presidential campaigns.
• Developing visualisations and dashboards for public understanding of the election.

Coverage

The dataset focuses on the 2024 US Presidential Election and its related events, primarily covering the United States. The time range for data updates spans from March through to the final election night update, with candidate announcement dates beginning as early as November 2022 and extending into July 2024. This includes critical periods such as primary elections, nominating conventions, and general election campaigning. While primarily focused on the 2024 cycle, Version 3 of this dataset previously included coverage of the 2022 Congressional Mid-term Elections. The dataset provides insights into various demographic aspects through its focus on candidates from different political parties (Republican, Democrat, and other factions) and covers key figures like Joe Biden, Donald Trump, Kamala Harris, Robert F Kennedy Jr, Walz, and Vance.

License

CC By 4.0

Who Can Use It

This dataset is suitable for a wide range of users, including:

• Data analysts and scientists seeking to model election outcomes or understand political dynamics.
• Researchers and academics in political science, sociology, and media studies.
• Journalists and media organisations for reporting, investigative journalism, and creating data-driven stories about the election.
• Students undertaking projects or coursework related to American politics and elections.
• Developers and engineers creating applications or tools for political engagement or data visualisation.
• Government agencies or civic organisations interested in public opinion and electoral processes.

Dataset Name Suggestions

• 2024 US Presidential Election Data
• US Presidential Campaign 2024 Analytics
• American Election Data: 2024 Cycle
• US Presidential Candidate & Poll Data

Attributes

Original Data Source: [

The data set contains 2500 manually-stance-labeled tweets, 1250 for each candidate (Joe Biden and Donald Trump). These tweets were sampled from the unlabeled set that our research team collected English tweets related to the 2020 US Presidential election. Through the Twitter Streaming API, the authors collected data using election-related hashtags and keywords. Between January 2020 and September 2020, over 5 million tweets were collected, not including quotes and retweets.

Paper: Knowledge Enhanced Masked Language Model for Stance Detection

Context

United States 45th President Donald Trump has used Twitter as no one else. He primarily ran his government from a twitter firehose. Twitter has officially banned his account on January 8th 2021 after a deadly riot at Capitol on January 6th 2021. Twitter cites its World Leaders on Twitter: Principles and Approach as a guide to adhere to for public leaders.

Trump tweets and policies have far reaching effects that one can realize or he would accept to realize himself. Since, twitter is suspended there is no public way to read his past tweets and analyze it for public policy outcome or link it with global issues.

Here we are presenting the complete treasure trove of President Trump's tweet, all 56,572 for the public, data scientists and researchers.

Content

The dataset contains 56,572 tweets, tweet IDs, Tweet Date, How many liked and retweeted it.

Acknowledgements

I like to acknowledge Twitter and Trump's Tweet Archives on the Internet that have helped me create this dataset

Inspiration

I’d like to call the attention of my fellow Kagglers and Data Scientists to use Machine Learning and Data Sciences to help me explore these ideas:

• How many times Trump discussed a particular country in his tweets and if we can label the sentiments? (North Korea, India, Pakistan, Mexico?) • How many times Trump talks about immigrants and border wall? • How many times and ways he has insulted? • Can you find a link between his tweets and stock market prices? • How many times he has downplayed Corona/Covid? • How many times he has called the election fraud? • How many tweets about Hillary Clinton, Obama or Joe Biden? • Anything else you can find that surprises us?

The United States recorded a Government Debt to GDP of 124.30 percent of the country's Gross Domestic Product in 2024. This dataset provides - United States Government Debt To GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

CodeThis figshare repository hosts a collection of tools and scripts for Twitter data analysis, focusing on Election Prediction using sentiment analysis and tweet processing. The repository includes four key files:twitter_data_collection.py: This Python script is designed for collecting tweets from Twitter in JSON format. It provides a robust method for gathering data from the Twitter platform.EP.ipynb: EP.ipynb" is designed for sentiment analysis and tweet processing. It features three sentiment analysis methods: VADER, BERT, and BERTweet. It includes a US states dictionary for geolocating and categorizing tweets by state, providing sentiment analysis results in both volumetric and percentage formats. Furthermore, it offers time-series analysis options, particularly on a monthly basis. It also includes a feature for filtering COVID-19-related tweets. Additionally, it conducts election analysis at both state and country levels, giving insights into public sentiment and engagement regarding political elections.Datasetbiden and trump.csv Files:The "biden.csv" and "trump.csv" files together constitute an extensive dataset of tweets related to two prominent U.S. political figures, Joe Biden and Donald Trump. These files contain detailed information about each tweet, including the following key attributes:create_date: The date the tweet was created.id: A unique identifier for each tweet.tweet_text: The actual text content of the tweet.user_id: The unique identifier for the Twitter user who posted the tweet.user_name: The name of the Twitter user.user_screen_name: The Twitter handle of the user.user_location: The location provided by the user in their Twitter profile.state (location): The U.S. state associated with the user's provided location.text_clean: The tweet text after preprocessing, making it suitable for analysis.Additionally, sentiment analysis has been applied to these tweets using two different methods:VADER Sentiment Analysis: Each tweet has been assigned a sentiment score and a sentiment category (positive, negative, or neutral) using VADER sentiment analysis. The sentiment scores are provided in the "Vader_score" column, and the sentiment categories are in the "Vader_sentiment" column.BERTweet Sentiment Analysis: The files also feature sentiment labels assigned using the BERTweet sentiment analysis method, along with associated sentiment scores. The sentiment labels can be found in the "Sentiment" column, and the cleaned sentiment labels are available in the "Sentiment_clean" column.This combined dataset offers a valuable resource for exploring sentiment trends, conducting research on public sentiment, and analyzing Twitter users' opinions related to Joe Biden and Donald Trump. Researchers, data analysts, and sentiment analysis practitioners can utilize this data for a wide range of studies and projects.This repository serves as a resource for collecting, processing, and analyzing Twitter data with a focus on sentiment analysis. It offers a range of tools and datasets to support research and experimentation in this area.

This dataset comprises tweets collected on 20th January 2021, the day Joe Biden was sworn in as the 46th President of the United States. The data was scraped using the Tweepy Library in conjunction with the Twitter Developer API. It aims to facilitate the study of general and global opinions towards the new administration, including what people are most anticipating and their primary concerns. The collection of tweets focused on specific hashtags such as Biden, Trump, KamalaHarris, JoeBiden, DonaldTrump, USinauguration, USElections, POTUS, FLOTUS, BidenHarrisInauguration, BidenHarris, USInaugurationDay, USpresidentWhiteHouse, and USinauguration2021.

Columns

• index: An identifier for each record.
• created_at: The date and time when the tweet was sent.
• text: The raw text content of the tweet.
• user_location: The location specified by the user in their profile or detected by Twitter. There are 43,900 unique user locations, with 2% from the United States and 73% categorised as 'Other'.
• user_name: The user's public display name on Twitter. There are 34,273 unique user names.
• user_verified: A boolean indicator showing if the user is verified on Twitter. Approximately 1,537 users (3%) are verified, while 42,762 users (97%) are not verified.
• user_description: The user's public profile description or bio. There are 35,294 unique descriptions.
• user_created_at: The date when the user joined Twitter.

Distribution

The dataset consists of approximately 44,300 records, typically formatted as a CSV file. It was generated by scraping Twitter data via the Twitter API. A sample file will be made available separately on the platform.

Usage

This dataset is ideal for: * Studying general opinions and global perspectives on new administrations. * Conducting sentiment analysis regarding political events and figures. * Identifying key public expectations and major concerns related to political transitions. * Analysing social media discourse and trends during significant civic events.

Coverage

The dataset covers tweets posted specifically on 20th January 2021. Geographically, it is categorised as global, reflecting opinions from around the world, though a small percentage of user locations are specifically attributed to the United States.

License

CC0

Who Can Use It

This dataset is intended for: * Researchers interested in political science, social media analysis, and public opinion studies. * Data scientists and analysts performing natural language processing (NLP) tasks such as sentiment analysis or topic modelling. * Students and academics exploring civic engagement and discourse on major political events. * Anyone looking to understand the immediate public reaction to the 2021 US Presidential Inauguration.

Dataset Name Suggestions

• 2021 US Presidential Inauguration Tweets
• Joe Biden Inauguration Day Twitter Data
• US Inauguration 2021 Social Media Discourse
• January 2021 US Political Tweets

Attributes

Original Data Source: 2021 US Presidential Inauguration Tweets

This dataset contains the full acceptance speech of Joseph R. Biden Jr. at the Democratic National Convention (DNC) in 2020. The speech, delivered on a Thursday night in 2020, marked the beginning of his general-election challenge to then-President Trump. Democrats framed this challenge as a crucial mission to rescue a nation beleaguered by a severe pandemic and a White House characterised by perceived incompetence, racism, and abuse of power. In his address, Mr. Biden urged Americans to have faith in their ability to overcome a "season of darkness" and pledged to bridge the country's political divisions, contrasting with the approach of Mr. Trump. The data allows for analysis of emphasised words and phrases, offering insights into the direction of his campaign and whether he sought support from the left-wing or aimed to win over voters who had previously supported Trump.

Columns

• Phrase_ID: A unique identifier for each distinct phrase or segment of the speech.
• Speech_Text: The verbatim text of Joe Biden's acceptance speech.

Distribution

The dataset is typically provided in a CSV (Comma Separated Values) format. It includes the entire text of Joe Biden's DNC 2020 acceptance speech. Specific numbers for rows or records are not available in the provided information. The dataset is considered global in region.

Usage

This dataset is ideal for various applications, including: * Natural Language Processing (NLP): Analysing text patterns, identifying frequently repeated words, and performing sentiment analysis to determine the overall tone of the speech (e.g., positive or negative). * Political Analysis: Understanding the rhetoric and emphasis points of a major political figure. * Election Studies: Gaining insights into a presidential candidate's strategic messaging and how they attempt to appeal to different voter demographics. * Academic Research: Supporting studies on political communication, public discourse, and speech analytics.

Coverage

• Geographic Scope: Global, with a focus on the United States political context.
• Time Range: The data covers Joe Biden's acceptance speech delivered in 2020.
• Demographic Scope: Relates to Joseph R. Biden Jr., the Democratic Party, and the American electorate during the 2020 US presidential election.

License

CC0

Who Can Use It

This dataset is suitable for: * Data Scientists and Analysts: For NLP tasks, sentiment analysis, and extracting key themes. * Political Researchers and Strategists: To study political rhetoric, campaign messaging, and candidate positioning. * Students: For academic projects on political science, communication studies, or data analysis. * Journalists: To inform articles and reports on the 2020 US election and Biden's campaign.

Dataset Name Suggestions

• Joe Biden 2020 DNC Acceptance Speech
• Biden DNC 2020 Speech Transcript
• US Presidential Election 2020: Biden's DNC Address
• Joseph R. Biden Jr. Democratic Nomination Speech 2020

AttributesBiden

Original Data Source: Joe Biden 2020 DNC Speech

Money Supply M2 in the United States increased to 21942 USD Billion in May from 21862.40 USD Billion in April of 2025. This dataset provides - United States Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Context

I found this dataset on the US Office of Government Ethics website, but all the financial reports were in the PDF format. I wanted to make it more easily accessible for data analysis & data science; hence, I converted all the PDF files to the Excel format that is much easier to use.

Content

It contains the Annual & on-termination financial reports for the entire Execution branch & it's administration from 2013 to 2020 including those of the President & vice-president. So, it covers the Obama Administration & the Trump Administration between those dates. It includes financial Assets, transactions, Retirement Accounts, Employments, Liabilities, Gifts & Travel Reimbursements, etc. with their values, income amounts, dates, name/description, etc.

I have seen inaccuracies in the data when converting from the PDF to Excel for the President & Vice-president's (Obama, Biden, Trump, Pence) files. I have tried to fix the numerical errors as much as I can. Also, I am attaching the raw PDF files so you can compare it with the excel & fix your analysis. I haven't seen any inaccuracies between the PDF & Excel file for the rest of the administration files (which is easily the bulk of this dataset).

Acknowledgements

This dataset, ofcourse, would not be possible without the US Office of Government Ethics collecting this & making it available for downloads. So, thanks to them! You can find the original PDF files on their website at : https://www.oge.gov/web/oge.nsf

The data also comes with Terms of Use that I have uploaded as the LICENSE.txt file. I am pasting it here too for easy access. By using this dataset, you are acknowledging & accepting these terms.

Public Financial Disclosure Reports Title 1 of the Ethics in Government Act of 1978, as amended, 5 U.S.C. app. § 105(c), states that: It shall be unlawful for any person to obtain or use a report: (A) for any unlawful purpose; (B) for any commercial purpose, other than by news and communications media for dissemination to the general public; (C) for determining or establishing the credit rating of any individual; or (D) for use, directly or indirectly, in the solicitation of money for any political, charitable, or other purpose. The Attorney General may bring a civil action against any person who obtains or uses a report for any purpose prohibited in paragraph (1) of this subsection. The court in which such action is brought may assess against such person a penalty in any amount not to exceed $11,000. Such remedy shall be in addition to any other remedy available under statutory or common law.

Inspiration

I don't know exactly what questions to ask, but feel free to use your imagination or follow your inspiration. Some interesting things might be how people's finances have evolved over time, does anyone seemingly have any conflict of interest based on their investments & their role

Using the Data The Union of Concerned Scientists' (UCS) Center for Science and Democracy has tracked attacks on science across four presidential administrations (Bush, Obama, Trump, and Biden). This page was last updated in April 2023. This data is free and unrestricted for use. Further Information Each attack on science includes a link for more information. The Center for Science and Democracy at the Union of Concerned Scientists has documented these attacks in greater detail at www.ucsusa.org/center-science-and-democracy/attacks-on-science. Caveats The database is derived from publicly available information. Attacks related to policy decisions have firm dates; other attacks are best estimations. If the attack was only brought to light by an investigation by a news outlet, the date of the attack is the publication date by that outlet. Details of attacks on science sometimes emerged after the end of a presidential administration; all dates correspond to when the attack was brought to light by media, Congress, the GAO, or other organizations. Data Dictionary Month- Which month the attack on science happened Day- Which day the attack on science happened Year- Which year the attack on science happened Admin- Which presidential administration the attack took place during Short Description- A brief overview of what happened Issue- In this column we list if the attack on science is related to one of six issue areas: equity, environmental, climate change, public health, COVID-19 and/or endangered species. A dash ("-") indicates that the attack did not fall into one of these issue areas. Agency/ies Involved- Which government agencies were involved in the attack. When "Congress" or the "White House" is listed, it indicates that Congress or the White House carried out the action. Attack Category- In this column we list which tactic was used to carry out each type of attack on science. More information- A link to more detailed information about the attack