{"id":19328880,"url":"https://github.com/bishopce16/cryptocurrencies","last_synced_at":"2026-05-02T18:38:55.760Z","repository":{"id":104182258,"uuid":"547775660","full_name":"bishopce16/cryptocurrencies","owner":"bishopce16","description":"An analysis on cryptocurrencies dataset using unsupervised machine learning, PCA algorithm, and K-means clustering.","archived":false,"fork":false,"pushed_at":"2022-10-10T21:07:39.000Z","size":4855,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-06T07:47:54.373Z","etag":null,"topics":["hvplot","jupyter-notebook","pandas","plotly","python","scikit-learn","unsupervised-machine-learning","visual-studio-code"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/bishopce16.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-10-08T09:11:47.000Z","updated_at":"2022-10-10T21:20:48.000Z","dependencies_parsed_at":null,"dependency_job_id":"47daad89-602b-4f10-8afb-1aeca91b9ed2","html_url":"https://github.com/bishopce16/cryptocurrencies","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bishopce16%2Fcryptocurrencies","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bishopce16%2Fcryptocurrencies/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bishopce16%2Fcryptocurrencies/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bishopce16%2Fcryptocurrencies/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/bishopce16","download_url":"https://codeload.github.com/bishopce16/cryptocurrencies/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240434193,"owners_count":19800548,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["hvplot","jupyter-notebook","pandas","plotly","python","scikit-learn","unsupervised-machine-learning","visual-studio-code"],"created_at":"2024-11-10T02:25:22.765Z","updated_at":"2026-05-02T18:38:55.705Z","avatar_url":"https://github.com/bishopce16.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# cryptocurrencies\n\nAn analysis on cryptocurrencies dataset using unsupervised machine learning, PCA algorithm, and K-means clustering.\n\n## Overview of Project\n\nThe purpose of this project was to analyze a cryptocurrencies dataset using unsupervised machine learning, PCA algorithm, and K-means clustering. To create a report and visualization of currently traded cryptocurrencies categorized by grouping them by their features, for a new investment portfolio on cryptocurrencies.\n\n---\n\n## Resource:\n\nData Sources: crypto_data.csv\n\nTools: Visual Studio Code, Jupyter Notebook, Python, Unsupervised Machine Learning, pandas, Scikit-learn, Ploty, hvPlot\n \n---\n\n## Results and Summary:\n\nThe dataset crypto_data.csv was retrieved from [CryptoCompare ](https://min-api.cryptocompare.com/data/all/coinlist), containing 1,252 entries. Only 1,144 of the cryptocurrencies were currently trading, once the null values were removed. Just cryptocurrencies that had a total number of mined coins greater than zero remained, leaving 532 tradable cryptocurrencies.\n\n![ crypto_df_drop_coinname.png](images/crypto_df_drop_coinname.png)\n\n Tradable cryptocurrencies table\n\n![ clustered_df_hvplot_table.png](images/clustered_df_hvplot_table.png)\n\nUsing the K-means algorithm, an elbow curve found the best k-value seems to be k=4. Settling the cryptocurrencies would have an output of 4 clusters to be categorized.\n\n![ elbow_curve_hvplot.png](images/elbow_curve_hvplot.png)\n\nThe 3-D scatter plot below made by reducing the cryptocurrencies to three principal components using the PCA algorithm.\n\n![3d_scatter_wclusters.png](images/3d_scatter_wclusters.png)\n\nThe 2-D scatter plot shows (TotalCoinsMined on the x-axis and TotalCoinSupply on the y-axis)  the cryptocurrencies distribution of the 4 clusters. \n\n![ plot_df_hvplot_scatter.png](images/plot_df_hvplot_scatter.png)\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbishopce16%2Fcryptocurrencies","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbishopce16%2Fcryptocurrencies","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbishopce16%2Fcryptocurrencies/lists"}