Trump's Campaign Funding

Goal:

The Mission of the FEC is, "to protect the integrity of the federal campaign finance process by providing transparency and fairly enforcing and administering federal campaign finance laws." It is evident that President Trump favors those who support him financially, so I wanted to see who exactly that was. In this project I explore the top contributors to Donald Trump's presidential campaign from 11/15/22 - the date he announced officially that he was running for president - to 11/05/24 - the day he was elected to his second presidential term. This tableau dashboard answers the questions: what states gave the most money, who in each state gave the most money, what were the jobs of the people who contributed to his campaign, and more.

Methods:

In order to complete this project I collected data from FEC.gov, processed the data using Python (Pandas library) and created the visualization in Tableau. This project, "Search Through Donald Trump Contributors," can be found on my Tableau Public profile. I used Python to apply the following filters to isolate the individual contributor data: used Candidate master (2021-2022, 2023-2024) from the FEC to obtain Trump's candidate identification number; with Trump's candidate identification number, I filtered the Candidate-committee linkage (2021-2022, 2023-2024) data file to only committees linked to Trump and recorded their committee identification numbers; with Trump's candidate identification number I also filtered the Contributions from committees to candidates (2021-2022, 2023-2024) data file to only committees that were linked to Trump's candidate id number and had a transaction type that indicated they were supporting his campaign (24C and 24E). With the committee ids from two data sets and the date range, I filtered the Contributions by individuals (2021-2022, 2023-2024) dataset. I then imported the filtered Contributions by individuals dataset into Tableau for visualization.

Challenges:

The greatest challenge working on this project was the sheer size of the dataset. To overcome this, I filtered the data further once it was in Tableau: removed contributions from outside the 50 U.S. states (excluded territories), combined the data I could (names misspelled, married couples I could verify, individuals that I could verify listed different occupations different times they donated, etc.), removed negative contributions (refunds), and removed individuals that contributed less than $1,000 overall.

Tools:

• Languages: Python (Pandas)
• IDEs: PyCharm
• Git repository: GitHub
• Visualization Software: Tableau Desktop and Tableau Online

Sources:

FEC.gov

Improvements:

If I were to do this project over again I would filter it heavily while still working in Pycharm rather than waiting until I was working in Tableau. I am continuing this project by researching those who contributed over $1M during this time period to better understand who they are, how they are contributing to and benefiting from the current administration now that Trump is in office, and to see how the net worth of some of the highest contributors (Elon Musk, Gavin DeBecker, Timothy Mellon, etc.) has changed. You can see this in-progress continuation on the Trump Contributions Continued project page. As of 4/19/25, some of the original data has disappeared from my personal database (Elon Musk is missing for example) and this is in the process of being fixed.

Github:

See this project on GitHub