Weather Data Analysis System - Ontario Weather Analysis Service

GITHUB LINK - https://github.com/DevS0ni/Weather-Data-Analysis-System

Overview: Developed a robust Ontario Weather Analysis Service, a command-line application written in C, to analyze and visualize weather data for the year 2023. The application provides comprehensive insights into precipitation patterns, allowing users to view records, sort by region, month, and location, and extract meaningful statistics.

TechStack Used:

• C, Data Structures and Algorithms, Modular Programming Approach

Key Features:

1. Data Visualization: Implemented functions to view all weather records, sorted by region, month, and location, facilitating quick and efficient data analysis.
2. Sorting Algorithms: Employed sorting algorithms to arrange records based on precipitation, both in descending order by region and ascending order by month.
3. User-Friendly Interface: Created an intuitive main menu for easy navigation, allowing users to choose specific analyses and explore weather data effortlessly.
4. File Input: Integrated a file import feature to read weather data from external files, enhancing the flexibility and scalability of the application.
5. Total and Average Calculations: Implemented functions to calculate the total precipitation and average precipitation for regions and months, providing valuable statistical summaries.

Achievements:

• Successfully handled diverse data sets, ensuring accurate analysis and reliable performance.
• Incorporated user input validation and error handling, enhancing the robustness and user experience of the application.

Technologies Used:

• Language: C
• File Handling: Standard I/O operations for reading and processing data from external files.
• Algorithms: Implemented sorting algorithms for efficient data organization.

Impact: The Ontario Weather Analysis Service provides a powerful tool for meteorologists, researchers, and weather enthusiasts to gain deep insights into precipitation trends. The application's robust functionality and user-friendly design contribute to a seamless and efficient weather data analysis experience.

Future Enhancements: Plans include incorporating additional features such as graphical visualization, extended data support, and real-time data integration to further enhance the application's capabilities.