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Polygon NFT Market Wearable Sales Analysis
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About
Market data focused on Aavegotchi non-fungible tokens (NFTs) and their associated wearable items, detailing transactional activity on the Polygon blockchain from 2020 through 2022. This product provides rich insight into the evolving dynamics of the NFT Polygon ecosystem by analysing the Aavegotchi protocol. The data is divided into three files covering sales of Gotchis, sales of wearable items, and the daily closing price of the associated $GHST cryptocurrency.
Columns
The primary Aavegotchi sales data file includes 16 columns detailing individual Gotchi transactions:
- $GHST_price: The sale price denominated in $GHST cryptocurrency.
- ID: The unique identifier for the Gotchi.
- BRS: The Base Rarity Score, calculated directly from the Gotchi's innate traits.
- HAUNT: Indicates the edition the Gotchi belongs to, specifically Haunt 1 or Haunt 2.
- Wearables: A list detailing the wearable items equipped on the Gotchi at the moment of sale, indexed by body slot (e.g., Body, Face, Eyes, Head, Pet, Background).
- Seller/Buyer: Wallet addresses for the transacting parties.
- MBRS: The Modified Basic Rarity Score, which incorporates the rarity effects derived from equipped wearables.
- Traits: Includes specific intrinsic traits such as nrgTrait (Energy), aggTrait (Aggression), spkTrait (Spookyness), brnTrait (Brain), eysTrait (Eyeshape), and eyecTrait (Eyecolour).
- Date: The day the sale occurred.
- $USD_price: The mean daily US dollar price of the $GHST cryptocurrency on the sale date.
The wearable sales file includes details such as WearID, Rarity (ranging from Common to Godlike), Quantity sold, and transactional information.
Distribution
This product is provided in a tabular format (CSV files). The core Aavegotchi sales table consists of 16 columns and approximately 13,600 valid records. The data covers Gotchis from Haunt 1 (Edition 1, 10,000 entities) and Haunt 2 (15,000 entities). The data is expected to be updated on an annual basis.
Usage
The data is ideal for several applications, including exploratory data analysis and statistical analysis. Users can apply regression techniques to model the relationship between Gotchi traits (such as rarity score, modified score, energy, and aggression) and market price. It is also suitable for analysing marketplace trends and transaction volumes within the specific NFT segment.
Coverage
The sales activity documented spans from 2020 to 2022, with specific transaction dates recorded between March 2021 and December 2022. The scope is centred entirely on the Aavegotchi protocol operating on the Polygon network, encompassing two distinct editions of the NFTs (Haunt 1 and Haunt 2).
License
CC0: Public Domain
Who Can Use It
- Data Scientists: For training models that predict NFT valuation based on rarity metrics and equipped item bonuses.
- Blockchain Analysts: To study market liquidity, seller/buyer behavior, and the efficiency of the Aavegotchi marketplace.
- Researchers: Investigating the impact of in-game customisation (wearables) on digital asset value.
- Beginner Analysts: Due to the data's structured, tabular nature, it is suitable for introductory market analysis projects.
Dataset Name Suggestions
- Aavegotchi Protocol NFT Market Data 2020-2022
- Polygon NFT Market Wearable Sales Analysis
- GHST Cryptocurrency and Aavegotchi Transaction History
- NFT Rarity and Trait Valuation Data
Attributes
Original Data Source: Polygon NFT Market Wearable Sales Analysis
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