Moonbirds is the official PFP NFT project of the Proof collective. It consists of 10,000 utility-enabled PFPs that unlock different benefits depending on the traits and the locking period of the Moonbird NFT. In this blog post, we will use Python and Alchemy to do a deep dive analysis of the collection in its first week of trading.
The Meebits NFT collection is the latest project from Larva Lab, the creator of Cryptopunks and Autoglyphs. In this tutorial, we will use Python and OpenSea API to download and analyze the transactions related to Meebits. We will cover how to download Meebits transactions using python and OpenSea API, and we will analyze the data with the goal of understanding sales trends and the behavior of some of the sellers and owners of Meebits.
Since its emergence in Asia late 2019, the coronavirus COVID-19 pandemic has been devastating. The virus spread to most countries causing severe respiratory infections and many human casualties. The virus also put half of the world population in lockdown which resulted in a slowdown of the world economy and a fall in stock prices. The goal of this tutorial is to introduce the steps for collecting and analyzing stock data in the context of the coronavirus pandemic.
In this tutorial, I will combine Coursera course catalogue together with social media data to assess the popularity of courses. To to this, I will use the Coursera API to retrieve the course catalogue, I will use the sharecount.com API to get social media metrics for each course, and I will use python's pandas library to query and order the courses by popularity. The technique introduced in this tutorial can be leveraged to other use cases that require a popularity ranking system for measuring the relevance of a list of links.
Sabermetrics is the apllication of statistical analysis to baseball data in order to measure in-game activity. In this post, I will use Lahman’s Baseball Database and Python programming language to explain some of the techniques used in Sabermetrics.