Purpose
In the age of uncertainty of employment, we wanted to create a visualization that helps explore how individual jobs and categories as a whole have changed over the past 60 years. We took inspiration from Job Voyager's concept, and expanded upon it by exploring income trends and distributions of age and salary ranges. A noteable difference between this visualization and JobVoyager is that we focused on the change in job categories, taking in to account income total as a secondary factor.
Data Source
We took the census data from 1950 to 2010 from IPUMS USA. We selected the income total, age, and jobs variables with samples from the listed years. We wrangled the data using pandas, a Python data-wrangling library. Initially, the original data set contained over 300 million data points. However, we wrangled it down and aggregated the data to only around 2000 lines, adjusting for inflation, and binning the age and salary data along the way.
Quickstart and Overview
Each circles represent individual job category, with the number of people that fall into a given category plotted along the y-axis and the average income of the category along the x-axis. You can click and drag the year to move forward and backwards through the decades 1950 to 2010 and see how each jobs and categories income and age distribution changes.
Acknowledgements and Inspirations
Our idea originates from Job Voyager. Our initial protoype was essentially a port of Job Voyager from flare to D3 which can be found here. Despite successfully porting Job Voyager to D3, we decided that we want to go in a slightly different direction and hopefully reveal more about job trends. For the final, we decided to ditch the stacked graph visualization that Job Voyager used and applied a more intuitive way to display all the data we added. With the stacked graph visualization, some jobs were squished into unclickably thin lines. We solved this problem by encoding each job category/title as a circle and applied Voronoi layout for better interaction.
To display the age and salary distributions, we used animation to intuitively display the changes across decades. We decided to go with bubble pack for the average income salary as differing categories can significantly vary in the number of job titles they have. While some jobs may only contain two or three titles, others may contain as many as 20 or more.
The multivariate display with the year slider was made with help from Mike Bostock's source code. The entire visualization was done in D3 while the website was a template from Bootstrap.