The data contains latitude and longitude variables which is known as geo position data, from which insights can be extracted and later analysed.
From the data containing longitude and latitude variables, location of where the shooting took place can be analysed.
Later on, Geodesic distance can be used to find the distance between the each longitude and latitude co-ordinates of one place to another.
I have used haversine formula to find the geodesic distance that is reasonably accurate estimate of the shortest distance between the two points.
Then created Geolist plot using matplotlib by including all the longitude and latitude co-ordinates.
After analysing the visualisation, performed a clustering algorithm, KNN to group points that are close to each other on the map.
Also created heatmap to identify the regions with low and high concentration of data points.
Since the geolist plot had time stamps, analysed the distribution of points over times.
Another clustering algorithm, DBSCAN (Density based spatial clustering of applications with noise) is used for grouping spatial data points based on their density.
It used for discovering clusters with irregular shapes and handling outliers. Geo histogram is used for this specific data.
Next, i will find the outliers in the data and perform the DBSCAN algorithm.
