Shifting Incomes for American Jobs

With some occupations, people make more annual income than others. Obvious. But we typically see figures in terms of means and medians when in reality, the difference between the person who makes the most and the one who makes the least can be significant.

The chart below shows the spread for major occupation groups, for several decades. Imagine you randomly select 50 people from each group, and this is what their annual income probably looks like.

The data for 2000 and earlier comes from the decennial census, and the data for 2010 and 2014 come from the American Community Survey.


As you progress through time, you’ll notice the distributions of income spread out more. This is especially obvious when you switch between 1960 and 2014. With the exception of lower paying jobs in areas such as food preparation and cleaning, it looks like there’s more opportunity to earn a higher salary (among those who have jobs at least).

That said, even if a job typically pays well, there are still people at the lower end of the bracket.

Make a Moving Bubbles Chart to Show Clustering and Distributions

Here’s how to make a chart similar to this one.

Nerd Notes

  • This is total personal income for individuals, as opposed to salary from an employer. I didn’t want to minus out the self-employed, but consequently the dollar values include things like welfare and retirement income.
  • The occupation groups are broad. See here for detailed listings.
  • I adjusted for inflation and binned by $5,000 increments, but it’s probably worth noting that some of the binning you see is from rounding.
  • I downloaded the data from IPUMS, which makes Census microdata much easier to grab.
  • I’m not fully sold on using a force-directed graph instead of histograms to show distributions, but I do like that it gets you closer to the individuals that the data represents.
  • I analyzed and prepared the data in R and made the final visualization with d3.js.

Chart Type Used

Beeswarm

It emphasizes individual points in a distribution instead of binning them like a histogram.

Become a member. Learn to visualize data. From beginner to advanced.

Join Today

Membership

This is for people interested in the process of creating, designing, and exploring data graphics. Your support goes directly to FlowingData, an independently run site.

What You Get

  • Instant access to tutorials on how to make and design data graphics
  • Source code and files to use with your own data
  • In-depth courses on visualization in R
  • Hand-picked links and resources from around the web

Favorites

Life expectancy changes

The data goes back to 1960 and up to the most current estimates for 2009. Each line represents a country.

Divorce and Occupation

Some jobs tend towards higher divorce rates. Some towards lower. Salary also probably plays a role.

Reviving the Statistical Atlas of the United States with New Data

Due to budget cuts, there is no plan for an updated atlas. So I recreated the original 1870 Atlas using today’s publicly available data.

Where Bars Outnumber Grocery Stores

A closer look at the age old question of where there are more bars than grocery stores, and vice versa.