Tipsy Dataset

As the dashboard week continues, it was apt that we were provided with the whisky auctions and distilleries data on the day of the Melbourne Cup. We were asked to use the Whisky Hunter API  This detailed the whisky auction, volumes, mean bid price for different auction houses. The data starts from 2007 till 2021. We were asked to get the story in a viz, get the data from the API using Alteryx and publish the blog.

Choosing the right data blend

I chose the route of multiple workflows, one each for an API. The datasets were different and I chose the one for auction data API. There were 2 sets of data. The APIs were for getting data for auctions altogether,  getting one auction at a time and their information. The other set was distilleries information. The workflow used the download tool to use the API followed by JSON parse and transposing it. You can see the workflow below.



Cocktail of insights

I built the dashboard to view mostly the trading volume, any outliers and relationship with winning bids. You can view this by selecting timelines, selecting a particular auction house or looking at the Top 10  winning bid prices. The objective is to see the mean prices of whiskies sold at the auctions, the overall behaviour of mean bid price vs trading volumes. You can see it online here.



There were a few interesting observations:

  1. The trading volumes and mean price follow the typical price asymptotic relationship price vs volumes. The high prices go with low volumes and low prices go with high volumes.
  2. One of the outliers was the bonham auction that has a very high mean price for bidding. Also, it has high variations. It seems that it is a auction house focused on very highly-priced whiskies and thus the observations are in line with this information.