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Common Python Function for Exploratory Data Analysis and Cryptocurrency Volatility: A Simple Overview  


NB:This is not a financial advice– NFA

Volatility is one of the major factors that goes into accessing investment risks and when it comes to cryptocurrency, newcomers to this asset class need to be informed. This is because how much these assets move up or down can not be adequately explained or predicted. The implication of this is that you as a user can become a queen, living your dream or a pauper overnight when all your investments drain away in blood (Red Candle). 

In this article, I used a dataset which I web scraped from the CoinGecko website using ChromeWebScraper. The data was scraped just once and I didn't consider the event for a long period of time. However, the brief overview given in this post will give you some insights whenever you are ready to begin your cryptocurrency journey or buy a new coin.


1. The dataset is stored in a variable called df. Subsequently, I will be referring to this variable.

The dataset consisted of several columns and using the python function df.columns, I could see all the column names.





2. df.shape gave the total number of rows (number of coins) in the data



4a. df.isnull().sum() examined all the nulls in the dataset.



4b. As seen in the above fig, three different columns contain missing values; all the observations in the 24hoursVolume columns were null, so the column was dropped using df. drop('24hrsVol'). Note that there are several ways of dealing with null values, but we are not discussing that here.

5. Using the df.dtype, it revealed that all the columns were of data type objects and as such, arithmetic operations could not be performed on the column. That meant that the next task involved data cleaning. This was a tedious task for me as some of the columns contained special symbols such as the infinity symbol, thus making it difficult to convert from string to floats.

6. New columns were created and converted to float data to ensure that arithmetic operations were possible and columns which are not needed for the analysis were deleted using df. drop()







Visualizations and Insights

1. In terms of Market Capital, the illustration below shows the top 10 coins to look out for in the cryptocurrency market and it is obvious that Bitcoin is leading, followed closely by Ethereum.


2. Market Capital is one of the key factors to consider when deciding to buy a coin. 100 different coins were considered for this analysis out of the numerous coins/tokens available in the cryptocurrency market. The plot below shows that the majority of the coins/tokens belong to either the medium or low market capital groups while around 10 coins/tokens have a large market capital.


3. The prices of cryptocurrency coins move up and down. In fact, charts of the movement can show price changes within seconds, hours, days or over months or years. The figure below shows the all-time high of the top coins and their current prices as at 28th February 2022.



Insights from the figure above show that;

  • Coins like Bitcoin (BTC), Ethereum (ETH), and Avalanche are trading close to their all-time high.

  • Coins like Ripple (XRP), Cardano (ADA), and SOL (Solana) are yet to recover from the dip (a drastic downward movement of price). This can be seen from the difference between their all-time high price and the current price. 

  • There are different types of cryptocurrencies and there is a particular group called Stable coins. This is because their values are pegged to the US dollar, and such coins are not significantly affected by changes in the market. The illustration below shows such properties in the USD Coin and Tether (USDT) as their values did not change significantly.

4. Comparing the all-time lows with the current price of coins/tokens, we see;

  • All the coins show a major upward movements from their all-time-low compared to the current prices except USD Coin and Tether (USDT). For example, XRP had an all-time low of 0.002686 and a current price of 3.4, which implies a 1265% increase. This means that a user who invested $100 when it was at its all-time low will now have the investment increased to $126500– let's remember that the coin is still far below its all-time high, hmmm🤔.

  • Nill or non-significant movement in USD Coin and Tether also further confirms that both are examples of stable coins.

CONCLUSION:

  1. USD Coin and Tether (USDT) are examples of stable coins whose values are not significantly affected by changes in the market. Therefore, citizens of countries whose currency always face devaluations can confidently save their funds in this type of currency.

  2. Movement of coins/tokens cannot be adequately predicted– an investor can gain 100% today and lose 5000% tomorrow.

  3. The greatest rule in this asset class is to BUY low and SELL high, not the other way around.

  4. Investors should always perceive this asset class as a long-term investment and not view it as a get-rich-quick scheme.


Click here to see the notebook for the code.
THANK YOU. Kindly drop your comment below, also feel free to tell me if cryptocurrency has either made or ruined you. If you are currently holding a particular coin, drop the name below.

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