Today I have gone through the topics by which I can do my analysis for the Police shooting data. Moreover, I followed the pdf file in which the geolocations have been given to locate the killings in the United States with the help of latitude and longitude.

Geo-positions, also known as geographic coordinates, are a means to depict a particular spot on the surface of the Earth. Latitude and longitude values are often included. Many modules and tools are available in Python for working with geo-position data. The GeoPy and GeoPandas libraries are two of the most used ones for this.

A common clustering approach is K-Means, which divides data points into K clusters based on how similar they are. Numerous libraries for Python offer K-Means clustering capabilities. Scikit-learn is one of the most frequently used libraries for K-Means clustering.

A machine learning method called Clustering is used to put comparable data points together based on specific attributes or qualities. In data analysis, clustering is a technique used to group together comparable data points based on specific traits or qualities. Finding underlying patterns or structures in data is the aim of clustering, which enables you to comprehend the logical groupings within a dataset. It is a type of unsupervised machine learning since it makes use of the inherent similarities and differences in the data rather than labeled data or predefined categories to identify groupings.

In the next blog, I will implement these techniques in my analysis and find out the hidden key points in the dataset.