Best Of

This is a very simple line chart I did in R; it is holiday counts by month and region. I have not completely figured out ggplot so the x axis is not labelled (although I did hide the nonsense that wanted to be there). Its Jan-Dec left to right.

I put together a visual on the number of unique holidays across the world. Helpful techniques used were calculated field to count the number of distinct holidays for each country and copy as crosstab, to get a subsection of the data. In the interactive Tableau dashboard you can filter to view the unique holidays for each country.

How many pina coladas do you get?

Here is a very nice TED presentation done by Hans Rosling:

I am hoping that I can create some of them in Tableau.

For this month challenge, I worked with @Sybil_D on a heat map.
Attached is the PDF for the heat map. It shows the 5 year survival trends over the years of different types of cancer by race and gender.

I just wanted to try out this challenge myself.

I thought a bump chart would be informative in terms of ranking the states by obesity rates over the 5 years to see how states compared against each other. It was already evident in the original visual that all states were seeing an increase in obesity over the years. Also I limited my chart to look at only the 50 US states, not the US protectorates or the US capital that was in the data. One limitation with bump charts that I saw was in assessing how to rank states with equal percentages or competing rank.

I like to attempt using different tools, so I tried this method using Tableau and R. Spoilers - Using this chart, one can see the majority of the top states for highest obesity rates were mostly southern U.S. states. Maybe a label of some sort to highlight this finding in the vizzes might have been useful if the viewer is not aware of the regions of U.S. states.

Feel free to comment or come by and assist me or view and think what I could have done instead.

R output

• For the R visual, I try to highlight the top 10 states for obesity rankings in 2015 by keeping them in color across years, while keeping other states in grey as they are not my focus; however, I was unable to replicate the same effect in Tableau with my dual axis setup.

Tableau output

All 50 states in the bump chart is informative but too many colors...

You can tell Colorado had the lowest obesity rates amongst the 50 states for 5 years.

Decided to limit my rankings and analysis to the top 10 states for 2015.

Can see from the viz below, that Mississippi had the highest obesity rate in 2011 at the #1 spot of the 10 selected states and Louisiana had the highest obesity rate in 2015.

Update 11/8/2018: Although a 'unique ranking' was useful for setting up the viz, it wouldn't be right to prioritize one state over another as #1 when the rate for both states were the same, therefore I labeled the Tableau ranks for the select states using a 'dense ranking' label. Also I adjusted the color for Kansas (KS) as it was too close in color to Oklahoma (OK).

• My Cross Tab for the Tableau Viz for reference
  

Some sites that I am working with in my Healthcare Data Analytics class to find data sets:

• Institute for Health Metrics and Evaluation - healthdata.org/
• World Health Organization - who.int/topics/en/
• Big Cities Health Coalition - https://bchi.bigcitieshealth.org/indicators/1892/15164
• Data Science Central - https://datasciencecentral.com/profiles/blogs/10-great-healthcare-data-sets
• National Cancer Institute - https://seer.cancer.gov/
• Expert Health Data Programming - https://ehdp.com/vitalnet/datasets.htm
• Medicare - https://data.medicare.gov/data

There is also a brand new data set search engine from Google:
https://toolbox.google.com/datasetsearch

Now able to upload the packaged workbook. Try the slider.