Multi-dimensional view of Cryptocurrencies

Shyam BV

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Published in

Coinmonks

4 min readNov 2, 2021

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Introduction

Crypto is universal, and it is here to stay. If so, we also needed a multi-dimensional view of Crypto from different exchanges. This article will show how to retrieve data from multiple data sources and use it for trading.

Background

Recently, I have written about an article on US stocks. Some of them have requested me to write a similar piece on Crypto. Hence this article is about Crypto.

Multi dimension view of stocks | Non-technical view

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Many also requested to add info about data retrieval. So in this post, I will also show how to retrieve the data from different APIs.

Get trending lists

One trusted place to see all the trending coins are CoinGecko. It looks at the recent trends and shows the trending coins. They also have a python client to access the data.

The short explanation is fetching the trending coins, using a pipe package to process each element further. Below is what it performs

Select coins from the returned dictionary.
Fetching items of the repeated list
Selecting symbol, name, price compared to BTC, and market cap
Finally, renaming the columns

We can also write traditional python code here. However, this is another way to code quickly. Give yourself a try!

Get Reddit list

Below is one of my quotes (Yes, I came up with that)!

What goes up is already discussed on reddit

Yes, Reddit is a top place to discuss meme stocks and Crypto. How can we miss it? SatoshiStreetBets is one of the top places to discuss cryptocurrencies. It is the sibling of Wallstreetbets.

In the below code, we will fetch the comments and parse those comments for the ticker.

Top Cryptocurrencies

Now let's get the top 15 cryptocurrencies. We have to go and search for the ultimate 15 cryptocurrencies according to the market cap. We can also sort it according to different fields.

Coinbase Penny listings

Coinbase is one of the trusted exchanges. Rather than spending hours finding the listed Crypto in different exchanges, let's get the top penny ones in two categories. One is less than $1 and another less than $5.

Once we fetch the data, we can filter the data according to the price and in respective buckets.

Conclusion

We have used APIs from different exchanges and created a report of multiple information. We can add more to it and extend the analysis. I will write my next article about combining various sources.