• Megan Johanson

Data Makeover: Gender Bias in Housework Persists

Academic research papers have certain requirements for tables and visualizations that do not align with current best practices in data visualization. Here I take a hard-to-parse research table and turn it into a bar chart that is much easier to interpret.


The Data Summary

I recently came across an article comparing the amount of housework men and women did in 1993 and 2006. The data were interesting and showed many changes in behaviors across the years, but were buried in a paragraph summarizing the findings (see excerpt below).



There was no chart or even table to help readers see which categories of housework changed over time. You really have to be concentrating to make sense of the summary and retain the main findings after reading.


The Original Source

Fortunately, the paragraph had a link to the original research paper, which presented the same data in tables, but not in charts. This paper, published in Socius: Sociological Research for a Dynamic World, does not contain a single chart.


The data mentioned in the summary article can be found in the bottom section of Table 2.



Be honest. How long did you look at the table before your eyes glazed over?


This table has a ton of information, but it is still really hard to see where the big changes have occurred so I took the data from the bottom part of the table and turned it into an overlapping bar chart.


Transforming the Boring Table to a Beautiful Chart

The key strategies to turn this dated academic table into an easy-to-understand chart were:


1. Grouping the data into categories to represent what percentage of couples say the men or women did more of each chore, or if they were shared equally.

2. Overlapping the bars depicting two years of data. You can find a tutorial on how to accomplish this here.

3. Making the bars representing the older data gray in color so they do not visually compete with the more recent data bars, which I made a brighter color.

4. Adding data labels to the 2006 bars only. With overlapping bars you can’t label both the bars, but since they are both on the same scale it is pretty easy to estimate the background bar’s length based on the front bar.

5. Using a title that summarizes the main finding I want people to remember and a subtitle that provides data details.




There are many interesting take-aways from this chart beyond what I called out in the title. A few that I find the most interesting are:


1. The percentage of couples with women doing most of the bill paying has actually increased since 1992.

2. The chores most likely to be equally shared in 2006 are shopping and doing the dishes.

3. The chores with the biggest increase in men doing most of the work are doing dishes, doing laundry, and cleaning the house.


Conclusion

I really like using overlapping bar charts when the purpose of the visualization is to compare two points in time or goals versus actual performance. For this data set, overlapping bars allow us to fit more information into a condensed space and still understand the big ideas.


What do you think of the makeover? Any suggestions for improving the clarity of the chart?

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© 2019 by Megan Johanson.