LeBron James Top Shot Transaction data Visualization
Background
NBA Top Shot is an NFT marketplace for fans to buy or sell basketball clips. In NBA Top Shot, it includes different kind of level, rarity and types of plays of NFT. Of course, if that's a rare NFT, the price will be higher. If the play was a crucial moment, the price will be high too. In this visualization, I utlized plotly and htmlwidgets to complete. The data we recevied was the data of LeBron James Top Shot transaction from 2020/07/30 to 2021/03/20.
Data
The data we got is a dataset of LeBron James Top Shot NFT transaction record, it has 32026 observations and 22 variation. The dataset includes the transaction of some of LeBron James NFT from 2020/07/30 to 2021/03/30. In the dataset, it has the information of transaction detail such as price, timestamp, seller, buyer, moment id, play category and so on.
In the dataset, I found out that if you combine play_external_id and ser_external_id with nbatopshot.com in the front, this link will lead you to that specific play's website. So I create another excel sheet with each play's link in there and then merge the links into the original dataset. I also included the date, detail and tier of that play in the dataset.
R
After having my dataset all prepared, I started the coding part. My thought process was to showcase the difference between an NFT's average price based on their tier and transactions. Since I got the link of each play, I want the user to be able to click on the value so it will link to that NFT's website, like an interaction plot.
I first group by the information I need in the plot which are Detail, play_category, tier, link, and date. Then I summarised the price and transactions. Next, I found the package called "htmlwidgets" which can accomplish the goal of the user clicking on the value and linking it to the NFT's website part.
Summary
From the final plot, we can easily tell that Legendary has the highest average price with the lowest transactions. On the other hand, common has the highest transactions with the lowest average price. The biggest gain I got was definitely the "htmlwidgets" which you can click on the value and links to the designated website. Not just that, if you click on the legend on the upper right, you can filter what tier you want to look at which make user easier to look into the plot.