ALovettII/10-challenge

Jupyter notebook that clusters cryptocurrencies by their performance in different time periods & visulizes these clusters

Jupyter Notebook

10-challenge

Jupyter notebook that clusters cryptocurrencies by their performance in different time periods & visulizes these clusters

Technologies

import pandas as pd
import hvplot.pandas
from path import Path
from sklearn.cluster import KMeans
from sklearn.decomposition import PCA
from sklearn.preprocessing import StandardScaler

Installation Guide

Using the Conda package manager: My GitHub Project

You will also the following libraries:

# Activate your Conda dev environment
conda activate dev

# Install scikit-learn
pip install -U scikit-learn

# Install hvPlot
conda install -c pyviz hvplot

Usage

Running this program will allow the following:

Import the Data (provided in the starter code)
Prepare the Data (provided in the starter code)
Find the Best Value for k Using the Original Data
Cluster Cryptocurrencies with K-means Using the Original Data
Optimize Clusters with Principal Component Analysis
Find the Best Value for k Using the PCA Data
Cluster the Cryptocurrencies with K-means Using the PCA Data
Visualize and Compare the Results

The program should yield such results as:

By changing the imported CSV you will be able to run this analysis on other data sets.

Contributors

Created by Arthur Lovett