We analyzed NASDAQ 100 executive salaries to see who makes the most money

Although it is a pretty obvious statement to say that public company executives take home large comp packages, we've always been curious exactly how much various CEOs make. Through the Key Executives dataset on databar.ai, we can get the compensation packages of public company executives and run a quick analysis!

Before we get into the data, I'd like to mention that compensation can vary by company. Some executives take home compensation in the form of stock, options, and carry + bonuses. This dataset primarily focuses on the pure cash payment that executives receive.

Getting the dataset

Getting the dataset is extremely simple with databar.ai:

1. First, we need to get a list of NASDAQ 100 tickers via the List of NASDAQ 100 Companies dataset. 
2. Download the NASDAQ 100 tickers and head over to the Key Executives dataset.
3. Click on the Enrich tab in the side-bar and upload the tickers csv file.
4. Click run and wait 30-60 seconds for Databar.ai to fill the table. With this operation, we're making 100 requests to FMP's API to get the salaries of executives at each of the tickers uploaded. Once the request is finished, let's download the data and get started with the analysis!

Analyzing the data

Before we visualize anything, we need to remove empty rows of data. Many executives don't have published salary data so those are the ones we remove (the simplest way to do that is to open the csv file in Excel, sort by the 'Pay' column, and delete rows that are empty).

Now that we have a complete dataset, lets upload it to Plotly Studio and visualize it! There are many ways to go about the visualization - we decided to create two traces of data, showing the salary distributions of male and female executives, sorted descending by pay size. And voila - here's the result!

Mark Zuckerberg makes a whole $25.3M, followed by Marcos Galberin with $21.5M and Theodore Sarandos with $21.0M! You can play around with the full dataset and plot here. 

Curious to learn how we built this with Databar.ai? Schedule a call with us here!