For this project, I use classification to group various cryptocurrencies.
This project accomplishes the following main tasks:
Data Preprocessing:
- Data is prepared for dimension reduction with PCA and clustering using K-Means.
Reducing Data Dimensions Using PCA:
- Completion of this task results in the following dataframe:
Clustering Cryptocurrencies Using K-Means:
- An Elbow Curve is created to find the best value for k.
- Once the best value for k is defined, the Kmeans algorithm is used to predict the k clusters for the cryptocurrencies data.
- Completion of this task results in the following dataframe:
Visualizing Results:
- A 3D-Scatter plot is created using Plotly Express to plot the clusters.
hvplot.table
is used to create a data table with all the current tradable cryptocurrencies.- A scatter plot is created using
hvplot.scatter
, to present the clustered data about cryptocurrencies havingx="TotalCoinsMined"
andy="TotalCoinSupply"
to contrast the number of available coins versus the total number of mined coins.