EarthquakeDataVisualization

The project is implemented using K-Means Clustering to find clusters of data in the given dataset based on the given features. K-Means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster.

The project exhibites the follwing:

1. Read data from csv file and implement K-Means algorithm.

2. Implement K-Means clustering algorithm by defining features such as latitude or longitude.

3. Number of clusters,lables,number of points in a cluster and distance between two clusters can be calculated.

4. The data can be visualized with help of a barchart and scatterplot as well.