My contribution to MakeOverMonday and my first published MakeOver

Since End of 2017 I take part in the MakeOverMonday Challenge. The essential concept is, to create a makeover of improvable visualizations which have been published on diverse internet mediums. The author of the homepage http://www.makeovermonday.co.uk, Andy Kriebel, provides a new makeover datavisualization beginning of each with week, along with the corresponding dataset.

It is a great opportunity to put various design concept into practice and discover what works for the respective dataset and what does not.My datavisualization tool is tableau. I discovered this program while taking the cousera Data Visualization with Tableau specialization.

From now on I will share my weekly makeovers on my Homepage together with my thoughts on:

  • what I dislike about the original viz
  • the key message I want to convey with my viz
  • the design choices I made to convey this information

I will begin with my makeover of CW2 2018. The original viz is the following:

British both gender rankings-01 (1).png

What I dislike about the viz:

  • There are too many colors. Looking at the viz, no color in particular stands out to me. Red, for example, as a key signal color, is not used at all in the color palette.
  • Size as well, does little to guide the reader to the most important part of the viz. The biggest bar charts are purple and stand for the question: “They have/make a decent amount of money“. On first sight, the size of the balk chart could signal that this attribute is the most important. Only on second sight, do we see that it is ranked sixth. Meaning that in the lowest ranking option it has the highest value.
  • It is tough to compare the values of women and men next to each other. If I want to compare the values of men and women for the respective questions,I always have to move up and down between the 2 separate bar charts and find the corresponding color.
  • The key finding, called out in the title, is not highlighted in the viz. The title mentiones as the most important finding of the data – “Personality is the most important characteristic in a romantic partner, say half of the Brits.” However, the viz does not support this claim visually. Both bars, for men and for women, are just another color in the viz.

My Makeover:

ValueInPartner

The key message I want to convey:

  • I focused on the difference by gender for each question. Since the dataset also provided survey data for multiple countries therefore it was also feasible to focus on the visualization of cultural differences. However, in my experience it can be overwhelming for the audience when the viz tries to answer too many questions at once. I settled for a comprise with the filter option which makes it hard to compare between countries, but allows to switch between them.

The design choices I made:

  • I chose a butterfly chart to facilitate the comparison by gender. For each question, the percentage value by gender are shown along the y-axis.
  • There are only two colors now in the viz. This results in a reduction of the cognitive overload caused by the original viz.

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