- Extracted and explored detailed salary data for MLB players.- Identified top earners, salary trends, and average salaries by year and position.- Analyzed total and average team salaries, revealing highest and lowest spenders.- Tracked salary growth and consistency for individual players.- Compared salaries across teams and identified top-paid positions.

Performed Analysis on Weather Live data Set using Python Libraries_ On July 2024 Using Tools and Technologies- Pandas, NumPy, Matplotlib libraries on Jupyter Notebook- Analyzed a time-series dataset with per-hour weather conditions, including temperature, humidity, wind speed, visibility, pressure, and conditions.- Performed data cleaning by handling null values and renaming columns.- Identified unique wind speeds and counted specific weather conditions (e.g., clear weather, wind speed at 4 km/h).- Calculated statistical measures like mean visibility, standard deviation of pressure, and variance of humidity.- Filtered data to find instances of snow, high wind speed with specific visibility, and various weather conditions.- Provided insights into weather patterns and anomalies.