Analyzing Cryptocurrency Markets Using Python

A Data-Driven Approach To Cryptocurrency Speculation

How do Bitcoin markets behave? What are the causes of the sudden spikes and dips in cryptocurrency values? Are the markets for different altcoins inseparably linked or largely independent? How can we predict what will happen next?

Articles on cryptocurrencies, such as Bitcoin and Ethereum, are rife with speculation these days, with hundreds of self-proclaimed experts advocating for the trends that they expect to emerge. What is lacking from many of these analyses is a strong foundation of data and statistics to backup the claims.

The goal of this article is to provide an easy introduction to cryptocurrency analysis using Python. We will walk through a simple Python script to retrieve, analyze, and visualize data on different cryptocurrencies. In the process, we will uncover an interesting trend in how these volatile markets behave, and how they are evolving.

This is not a post explaining what cryptocurrencies are (if you want one, I would recommend this great overview), nor is it an opinion piece on which specific currencies will rise and which will fall. Instead, all that we are concerned about in this tutorial is procuring the raw data and uncovering the stories hidden in the numbers.

To read more, visit - blog.patricktriest.com/analyzing-cryptocurrencies-python

An HTML version of the entire notebook, with results and visualizations, is available here - https://cdn.patricktriest.com/blog/images/posts/crypto-markets/Cryptocurrency-Pricing-Analysis.html

Included in this repository are the

• IPython Notebook
• Notebook Python File
• Notebook HTML Page
• Pre-rendered charts (PNG and HTML)

This Python notebook is 100% open-source, feel free to utilize the code however you would like.

The MIT License (MIT)

Copyright (c) 2017 Patrick Triest

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