Weekly Viz – STD Infection Rates (1996 – 2014)

#MakeoverMonday Week 31 2019

This weeks dataset is from CDC and be found here.

The original visualization is as follows:

What’s good?

  • Provides an insight into all the information that the dataset packs within
  • Legible labels

What can be improved?

  • I view this as an information overload. Although very insightful – it is too much to process
  • Multiple graphs can be combined into one

I happened to stumble upon multiple articles that outlined data visualization best practices. I realized that although exhaustive – many of the visualizations i had been creating violated many important points highlighted in these best practices.

As someone who creates visualizations, we often become well versed with the dataset; this often translates into non intuitive representations for the end users.

So, for this weeks visualization I embarked on the path of data minimalism – trying to convey as much as possible with as little as possible. Here’s the rendition I made –

Click on the image to view the interactive viz

This visualization shows the progression of the no. of cases over the years. Since the dashboard is quite big – below are two gifs that show the dashboard in action:

I would love suggestion on best practices and on this visualization in general.

Follow me on twitter @viraj155

Weekly Viz – The Great American Sex Drought

#MakeoverMonday Week 29 2019

This week data-set was from GSS Data Explorer and can be found on data.world.

Here’s the original visualization:

What’s good?

  • Perfectly scaled axis
  • Legible labels
  • Provides a good comparison between the three parameters at hand across the years

Here’s my perspective –

View the interactive visualization on my Tableau Public Profile

My main motive was to first attract the viewer my giving the essence of the dashboard at first glance. Next, I tried to summarize the change from 1989 to 2018 via a dumb-bell graph which clearly conveys the trend supported by the annotated relevant values.

I welcome suggestions – connect with me on twitter (@viraj155) to share your visualizations!