Analyzing the 2024 Stablecoin Ranking Changes with Python

스테이블 코인 순위 시각화 그림
(Visualize the ranking of stablecoins over the past year)

Today we're going to analyze the stablecoin market using Python, specifically the Visualize changes in the top 5 stablecoin rankingsI'll give it a try, and I think it will help me better understand the market dynamics of different stablecoin types.

What are stablecoins?

A stablecoin is a special type of cryptocurrency designed to maintain a stable value. They are usually Value tied to a fiat currency like the US dollar or a real asset like goldIt is used as a stable store of value in the volatile cryptocurrency market.

Stablecoin types and features

( Illustration of stablecoin types )

Below, we've listed the main types of stablecoins and their characteristics.

1. Tether (USDT)

Tetheris a type of stablecoin designed to ensure that the value of 1 USDT is always equal to 1 US dollar (USD). USDT provides stability for transactions on the blockchain and is widely used to transfer assets between exchanges and users.

Features:

  • Initially claimed to be 100% backed by the US dollar, it is now backed by a variety of reserve assets (cash, bonds, etc.).
  • It is the most widely used stablecoin, with the largest market liquidity and use cases.
  • They are issued on a variety of blockchain networks, including Ethereum (ERC-20), Tron (TRC-20), and Solana.

2. USD Coin (USDC)

USD Coinis a stablecoin developed by the Center consortium, co-founded by Circle and Coinbase. It emphasizes transparency and regulatory compliance, and 1 USDC is backed 1:1 by US dollars.

Features:

  • Periodically validate reserve assets with independent accounting audit reports.
  • Our regulatory-friendly approach has earned us the trust of enterprises and institutions.
  • Available on a variety of networks, including Ethereum, Solana, Polygon, and more.

3.Binance USD (BUSD)

BUSDis a stablecoin issued by Binance in partnership with Paxos Trust Company and authorized by the New York Department of Financial Services (NYDFS).

Features:

  • It is backed 1:1 by the US dollar, emphasizing its reliability.
  • It is used as a major trading pair on the Binance platform and has high liquidity.
  • Paxos audits your reserves monthly to ensure transparency.

4. Dai (DAI)

Daiis a stablecoin issued by a decentralized finance (DeFi) project called MakerDAO that maintains the value of one U.S. dollar through an algorithm.

Features:

  • They are issued as collateral for cryptocurrencies (ETH, USDC, etc.) rather than reserve assets.
  • It operates through smart contracts with no centralized authority, emphasizing decentralization.
  • It is widely used in the DeFi ecosystem, and its circulation is adjusted based on the collateralization ratio.

5. TrueUSD (TUSD)

TrueUSDis a stablecoin issued by the TrustToken platform, backed 1:1 by dollar deposits. We value user trust and transparency.

Features:

  • Regularly verify reserves with an independent third-party accounting audit.
  • It is legally compliant and used in business-to-business (B2B) transactions and crypto exchanges.
  • Designed for stability and reliability.

These coins are utilized in a variety of uses and ecosystems, depending on their characteristics and design philosophies.

Analyzing ranking changes with Python

We will now explain how to use Python to analyze the change in stablecoin rankings over the course of a year.

The code below leverages Python libraries such as yfinance, pandas, and matplotlib to fetch price data for stablecoins and visualize stablecoin rankings based on it. I will explain the main code step by step.

1. import the required libraries

import yfinance as yf
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime, timedelta

Interpreting code:

  • yfinance: A library for downloading financial data from the Yahoo Finance API.
  • PANDAS: A dataframe library for efficiently managing and analyzing data.
  • matplotlib: A library for visualizing data.
  • datetime and timedelta: Python standard libraries for calculating dates.

2. define a stablecoin list

stablecoins = ['USDT-USD', 'USDC-USD', 'BUSD-USD', 'DAI-USD', 'TUSD-USD']
  • Set Tether (USDT), USD Coin (USDC), Binance USD (BUSD), Dai (DAI), and TrueUSD (TUSD) as the coins to analyze.
  • Search Yahoo Finance for data by the symbol of that coin.

3. set the duration

end_date = datetime.now()
start_date = end_date - timedelta(days=365)

Code interpretation:

  • Set the analysis period from the current date (datetime.now()) to one year ago (365 days).

4. download pricing data

data = yf.download(stablecoins, start=start_date, end=end_date)['Close']

Code interpretation:

  • Use yfinance's download function to get the close data for the specified stablecoin.
  • Specify a time period via start and end.
  • The data consists of each coin's closing price by date.

5. Calculate the ranking

rankings = data.rank(axis=1, ascending=False, method='min')

Code interpretation:

  • Use the rank method of the dataframe to calculate the rank of the coins on each day.
  • ascending=False means a higher value means a higher ranking.
  • method='min' gives the minimum ranking when values are equal.

6. visualize

plt.figure(figsize=(14, 8))

for coin in stablecoins:
    plt.plot(rankings.index, rankings[coin], label=coin, linewidth=1)

Code interpretation:

  • Visualize the change in ranking using matplotlib.
  • Different lines represent the change in rank for each stablecoin.

7. Set up and display the graph

plt.title('Stablecoin Ranking Changes (1 Year)')
plt.xlabel('Date')
plt.ylabel('Rank')
plt.legend()
plt.gca().invert_yaxis()
plt.grid(True, alpha=0.3)
plt.show()

Code interpretation:

  • Add graph titles and axis labels to convey information intuitively.
  • The invert_yaxis sets the lower-ranked values to move up (#1 is at the top).
  • Add grid lines to the graph with grid(True, alpha=0.3) to make it more readable.

Stablecoin ranking visualization full code

This code visualizes the ranking of stablecoins over the course of a year, by date. This allows you to see which stablecoins have gained more dominance in the market over time. The graph clearly shows the change in ranking for each coin and helps you easily identify trends in the market.

import yfinance as yf
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime, timedelta

List # stablecoins
stablecoins = ['USDT-USD', 'USDC-USD', 'BUSD-USD', 'DAI-USD', 'TUSD-USD']

Get # data
end_date = datetime.now()
start_date = end_date - timedelta(days=365)

Download # data
data = yf.download(stablecoins, start=start_date, end=end_date)['Close']

Calculate # rankings
rankings = data.rank(axis=1, ascending=False, method='min')

Apply the # 7-day moving average
smoothed_rankings = rankings.rolling(window=7).mean()

Set up the # graph
plt.figure(figsize=(14, 8))
for coin in stablecoins:
    plt.plot(smoothed_rankings.index, smoothed_rankings[coin],
             label=coin, linewidth=2)

plt.title('Stablecoin Ranking Changes (7-Day Moving Average)')
plt.xlabel('Date')
plt.ylabel('Rank')
plt.legend()
plt.gca().invert_yaxis()
plt.grid(True, alpha=0.3)
plt.show()

Output the latest ranking for #
latest_ranking = rankings.iloc[-1].sort_values()
print("Latest Stablecoin Rankings:")
for rank, (coin, value) in enumerate(latest_ranking.items(), 1):
    print(f"Rank {rank}: {coin}")

Rank change analysis results

You can see some interesting patterns in the graph.

  1. BUSD's Dominance: Binance USD (BUSD) remains in first place for most of the period.
  2. Competitive landscape: USDC, DAI, and USDT compete for the top 2-3 spots.
  3. Bottom of the RankingsYou can see that TUSD fluctuates frequently in the top 4-5 positions.

And here are the latest rankings that resulted from the above analysis.

Rank 1: BUSD-USD

Rank 2: USDT-USD

Rank 3: TUSD-USD

Rank 4: USDC-USD

Rank 5: DAI-USD

Implications

Here's what you can learn from analyzing these ranking changes.

  1. The stablecoin market has a clear divide between the top and the bottom.
  2. Market power can fluctuate significantly, even over short periods of time.
  3. The emergence of a new competitor or the downfall of an existing coin can happen in an instant.

To conclude the stablecoin ranking visualization

There are many types of stablecoins and their markets are constantly changing. Analyzing this data can help you better understand market movements and guide your investment or trading decisions. We'll continue to monitor the market as it evolves and discover new insights.

There are many types of stablecoins, and their rankings are up and down, but Bitcoin is the one you are most interested in, right? Bitcoin's market price fluctuation is Analyzing a 30-day Bitcoin Dollar chart with Python and the CryptoCompare API Check out the post and see for yourself on your own computer!

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