$3.8 trillion is the estimated amount the US government spent in 2022, according to the Congressional Budget Office. That’s a staggering number, and it got me thinking: what if we could visualize this data to better understand where our tax dollars are going? As a developer, I decided to build an interactive dashboard using D3.js to track government spending and policy initiatives. The results were eye-opening, and I’m excited to share my findings with you.

But what does this data really tell us? Is it just a bunch of numbers, or can we glean some insights from it? I wrote about a similar project in our data journalism piece where we used Python and Pandas to analyze election results. This time, I wanted to focus on government spending, and how we can use data visualization to make sense of it. Turns out, it’s not just about the numbers - it’s about the stories they tell.

Why D3.js?

D3.js is a powerful library for creating interactive, web-based data visualizations. I chose it for this project because of its flexibility and customization options. With D3.js, I could create a dashboard that would allow users to explore the data in a non-linear fashion, drilling down into specific categories and time periods. And, as it turns out, NASA uses D3.js to visualize some of their own data - so I’m in good company.

Pulling the Numbers Myself

To get started, I needed to fetch the data from the government’s website. I used a combination of Python and the requests library to scrape the data, and then parsed it using json. Here’s a snippet of the code:

// fetch data from government website
fetch('https://www.usa.gov/data')
 .then(response => response.json())
 .then(data => {
 // parse data and create visualization
 const margin = { top: 20, right: 20, bottom: 30, left: 40 };
 const width = 500 - margin.left - margin.right;
 const height = 300 - margin.top - margin.bottom;
 const svg = d3.select('body')
 .append('svg')
 .attr('width', width + margin.left + margin.right)
 .attr('height', height + margin.top + margin.bottom);
 // .. rest of the code ..

This code fetches the data, parses it, and creates a basic SVG element for the visualization. From there, I could start building the interactive dashboard.

A Data Reality Check

So, what do the numbers actually show? According to the Bureau of Labor Statistics, 64% of the government’s spending goes towards mandatory programs like Social Security and Medicare. That’s a significant chunk of the budget, and it’s not something you often hear about in the news. But, as I dug deeper, I found that the popular narrative around government spending is often misleading. For example, McKinsey’s 2025 report estimates that $1.3 trillion of the budget could be improved through better management and technology. That’s a staggering amount, and it highlights the need for data-driven decision making in government.

And this is where it gets interesting. When you look at the data, you start to see patterns that casual observers miss. For example, the government spends $150 billion on defense contracting every year, according to the Defense Contract Management Agency. But, when you break it down by category, you see that $50 billion of that goes towards IT and cybersecurity. That’s a significant investment, and it highlights the importance of technology in modern defense.

The Short List

So, what can you do with this data? Here are a few actionable recommendations:

  1. Use D3.js to create your own visualizations: it’s a powerful library, and it’s free.
  2. Explore the government’s data portal: there’s a wealth of information available, and it’s all free.
  3. Build a dashboard to track government spending: it’s a great way to stay informed, and it can be a valuable tool for citizens and policymakers alike.
  4. Use Python and Pandas to analyze the data: it’s a great combination for data analysis, and it’s easy to learn.
  5. Check out the Gartner report on government tech trends: it’s a great resource for staying up-to-date on the latest developments.

But, as I looked at the data, I started to wonder: what other stories are hidden in these numbers? What other insights can we glean from this data? And, more importantly, how can we use this data to make a positive impact on our communities?

Frequently Asked Questions

What tools did you use to build the dashboard?

I used D3.js, Python, and Pandas to build the dashboard. I also used the requests library to fetch the data from the government’s website.

How did you handle errors and inconsistencies in the data?

I used a combination of data cleaning and error handling techniques to deal with inconsistencies in the data. I also used data validation to ensure that the data was accurate and complete.

What other libraries or tools would you recommend for data visualization?

I would recommend using Next.js for building interactive web applications, and Flask for building APIs. I would also recommend using Puppeteer for automating web scraping tasks.

Can I use this data for my own projects?

Yes, the data is publicly available, and you can use it for your own projects. However, be sure to check the terms of use and any applicable licenses before using the data.

Sources & Further Reading