Project Title: Weather Forecast

Problem and Motivation: The problem at hand involves predicting and analyzing weather patterns in a specific region based on historical data. This initiative aims to provide valuable insights for stakeholders, including businesses and the general public, assisting them in making informed decisions related to activities sensitive to weather conditions such as agriculture or personal travel preferences.

Features Implemented: The project implemented features allowing users to analyze the dataset based on key weather parameters. Users can sort the data in ascending or descending order by amount of precipitation, average temperature, maximum temperature, minimum temperature, and wind speed for a specific month or the entire year of 2016. Additionally, the runtime of each sorting algorithm was measured.

Description of Data: The dataset used for the project consists of reports from 122 different Weather Forecast Offices, covering the daily weather in their respective regions in 2016 (https://think.cs.vt.edu/corgis/csv/weather/). The dataset provides a record of various weather parameters including dates, locations, precipitation, temperatures, and wind speeds.

Tools/Languages/APIs/Libraries Used: The project utilized C++ for implementation. Various components of the C++ standard library, such as iostream, fstream, sstream, vector, iomanip, and chrono, were employed.

Algorithms Implemented: The project incorporated mergesort and quicksort algorithms for sorting the weather data.

Additional Data Structures/Algorithms Used: We stored the relevant data into a vector of unordered maps. The project also incorporated rudimentary maps using arrays to convert keys into values.