I put together this repository to encourage data analysis for anyone who is interested and wants to learn about it. The technologies used are Python, SQL, data analysis tools (numpy), and data visualization tools (matplotlib).
As an example, I've done a peak price analysis of cryptocurrencies on Coinbase Pro.
- Tools and Scripts
- Relevant Links and Resources
We're looking at only one cryptocurrency exchange, but it's probably the most beginner friendly and widely used of all: Coinbase (aka Coinbase Pro, previously known as GDAX). We're looking at all the prices in history and specifying that we want the highest price ever reached by using the following query:
SELECT *, datetime(time, 'unixepoch', 'localtime') as date FROM candles WHERE (market, time) IN (SELECT market, MIN(time) FROM candles WHERE (market, CAST(high as FLOAT)) IN (SELECT market, MAX(CAST(high as FLOAT)) FROM candles GROUP BY market) GROUP BY market)
On December 12th, 2017, Litecoin, the least popular of the group, was the first to reach its all-time-high.
Bitcoin followed shortly after on December 17th, 2017, however it took Ethereum about a month, January 13th, 2018.
Bitcoin's and Litecoin's peaks occurred in the early morning (relative to the PST timezone), 4:36 AM and 6:11 AM, respectively. For Ethereum, this was in the afternoon, 1:03 PM.
Litecoin's peak price is an integer, precisely $420.
Cryptocurrency investors were highly optimistic about cryptocurrency until the 2017 holiday season, but then quickly shifted to a pessimistic attitude in the beginning of 2018. Litecoin was probably the first to reach its all-time-high due to being the cheapest coin, thus its price could be manipulated more easily. We'll need to see another incredible rally upward if those peak prices are ever to be surpassed.
Tools and Scripts
All the scripts used are available in the main repository. Each analysis is under the "analysis" folder and the way to create your own database is under the "data" folder. Here is the link to the README for generating your own database https://github.com/milan102/Cryptocurrency-Data-Analysis/tree/master/data
Here is the python script used for analysis https://github.com/milan102/Cryptocurrency-Data-Analysis/blob/master/analysis/peaks/peaks.py
Relevant Links and Resources
This resource was helpful for turning a python SQL query into something that can be analyzed and visualized https://github.com/SuruchiFialoke/DataQuest/blob/master/GuidedProject-WorkingWithSQLiteDatabase/basic.ipynb
Proof of Authorship
I'm the owner of the repository, in the "Notes" section of my main README I put my Medium and Steemit username https://github.com/milan102/Cryptocurrency-Data-Analysis#notes
I'm excited to do more analysis and ease into doing more advanced data manipulation. My findings will be posted in the repository, Medium, and Steemit. As always, everything will be open source so that everyone can learn and benefit.