Our group has met multiple times thus far.
Our first two meetings together were focused on getting the data from the website and into Excel. The data set that we chose was the National Physician 2014 information table. Excel was not strong enough to handle all 2 million entries from this table, so we set parameters to only give us doctors that filled the following criteria:
- Graduated between 2010 and 2015
- Were practicing in North Carolina
- Had a chiropractic focus
There were roughly 2 million entries in this data set, and the above criteria narrowed the entries down to a total of 115 from this data set. We then cut the data down to 95 when we removed 20 entries that were duplicates.
In our most recent meeting, we were able to take this data and put it into Tableau to get a couple of visualizations of the data. We are looking to find out the following:
- Doctor current locations
- School attended
- Medicare acceptance
- Number of members in practice
Our first visualization of our data is a tile-based tree map. Going from left to right, it displays the number of chiropractors and in each city and address. The information is also color coded. For example, Raleigh is dark green and in the upper left hand corner of the graphic because it has the most chiropractors in the area from our data set. In contrast, the bottom right hand corner is Winston Salem, which is the lightest shade of yellow and there is only one chiropractor in this data set.
The next visualization that we produced was a male to female chiropractor comparison. We wanted to see what gender ratio the data set represented. It is clear that there are more male chiropractors in our data set than there are females. Moving forward, our group would like to research national data and see how our data compares to what the averages are.
Our group is progressing with our data set and we are beginning to build more valuable visualizations. Moving forward, we would like to compare the information that we have gained from analyzing our data and compare it to national data. This will allow us to tell more of a complete story about our data.