This week, the classroom was tasked with turning a large dataset about Uber usage in NYC into an effective Tableau dashboard. This assignment was coupled with our relevant readings in the textbook which discussed dashboards and various chart types. Additionally, we have been watching training videos in Tableau which have guided our creation of this in-class assignment.

Based off of requirements as prescriber by Professor Villafranca, this is the dashboard that I created in Tableau.

Since our assignment was primarily focused on being able to drill down into the pickup data by individual boroughs and specific dates, I decided to use a vertical bar chart on the lefthand side as a filter. I believe it was the clearest and easiest way to select the borough you wanted to drill down into. Also, I think a bar chart was the best way to summarize the total data and the best way to visualize the drill down on the righthand side. Once you select a borough (or bar) the righthand side of the dashboard will filter the holiday, monthly, and average daily pickup data for that particular group of data as seen above. If you were not to select a bar, you would be able to see the entirety of all the data in each different visual. I selected the text tables because I think that is the easiest and quickest way to interpret the data for the monthly and holiday data, and I selected the line charts because I believe it represented the average daily data in an interesting way. I think that you can learn more from this line chart because it shows how pickups fluctuate on a regular basis, and I think the text charts represents the unique circumstances like holidays or the total monthly data best because you can’t learn the most from outlier data or mass data from a line graph.

 

For instance, you can see that there is much more variability in the Manhattan data set. But, this chart has some flaws. If you were to filter into the Bronx, which seems consistent, you can see that this is not the case. That is why I provided the dashboard capability to filter by borough, and then the corresponding charts will adjust so you can more accurately visualize this data.

 

 

Clearly, there could be more ways to refine this data for presenting, but this is my best submission for the time I worked on it.

 

Additionally, I met with my team and narrowed our research/data sets and submitted them to the professor. I believe our team has a better-refined research question and data sets which will help us visualize it.

 

Signing Off,

Chandler