CrimeDataAnalyzer

Developed a comprehensive crime data management system for Pittsburgh crime records from the 1990s, enabling efficient spatial queries, data analysis, and visualization Implemented a 2D Tree data structure to store 27,218 crime records, providing a foundation for efficient data traversal and various tree traversal algorithms, including inorder, preorder, levelorder, postorder, and reverseLevelOrder Utilized the State Plane Coordinate System (X, Y) pairs to calculate distances between crime locations, facilitating the application of Prim's Minimum Spanning Tree algorithm for solving the approximate Traveling Salesman Problem (TSP) tour based on user-specified dates Integrated LZW compression and decompression algorithms to optimize storage and data transfer for the crime data CSV file, ensuring efficient encoding and decoding processes Leveraged latitude and longitude coordinates for crime data visualization in GIS tools such as Google Earth, providing spatial analysis and enhanced geographical context for users