Dashboard week continues.
Dashboard Week, The Data Schools’ challenge to consultants nearing the end of their intense fourth month training before starting placement. The challenge for each day this week – create a dashboard and tell a story using a newly provided dataset each day.
Day 2: Whiskey Hunter API
The challenge for our second day of Dashboard Week was to access data from the Whisky Hunter API to create a dashboard story. To access the data available from the API we needed to download the data and clean it. The data on offer was based on Auctions for buying and selling Whiskey of different from around the globe. Unfortunately the data was somewhat limited in that we only had part of the data for the entire auctioning process.
The Whiskey Hunter API has data on:
- distiller locations across the globe, and
- auction price/bidding information (limited details of items sold).
My idea for the story of my dashboard was to focus on distilleries in Japan and pitch the idea of travelling to Japan for whisky. My approach was to filter the data for just distilleries in japan and to find the geo-locations to plot on a map of Japan. In addition, I wanted the user to be able to create an itinerary based location, number of whiskeys on offer and rating of each distillery.
Accessing the Whisky Hunter API was straight-forward and required a basic URL. Thankfully there was no authentication or API keys required. Using the download tool with the API URL, I then needed to parse the data, cross-tab and add a few cleaning steps.
With my focus being on distilleries within Japan, I filtered the distilleries only in Japan. The data available for each distillery included: the name of the distillery, rating and number of whiskies.
With the dataset not including a longitude and latitude for each distillery, I decided to create my own dataset with this information. Searching goggle, I couldn’t find a dataset with this information, so I searched google for the addresses of each distillery. Thankfully there were on 38 distilleries, but this still took a bit of time.
Creating a list of distilleries by address, I used an online geo-coder to convert each address into longitude and latitude. The reason I didn’t use Alteryx is because of time and not fully understanding each part of a Japanese address. With this information I then combined it to the Whisky Hunter data to start working in Tableau.
The challenging part about my story idea was to make my dashboard engaging and allow the user to create a travel itinerary based on the rating, location and number of whiskies. Overall I believe I was able to accomplish this by allowing the user to add distilleries into a travel itinerary. However with more time more data can be added and the dashboard could be refined further.
Functionality included allows the user to add distilleries to a travel itinerary by selecting locations on the map of Japan. Users can analyse each distillery by location, rating and number of whiskies on offer. Decluttering the dashboard, I have also include a slider to reduce the number of distilleries show in the bar charts. I have also included help buttons to help with navigation and interactivity.