This project focuses on data cleaning, preprocessing, and exploratory data analysis of a gym exercise tracking dataset using Python. The raw dataset was inspected for missing values, inconsistent data types, and data quality issues. After cleaning and preprocessing the data, YData Profiling was used to generate an automated exploratory data analysis report.
- Imported and explored raw gym exercise tracking data.
- Identified and handled missing values.
- Corrected and validated data types.
- Performed data quality checks and preprocessing.
- Generated an automated profiling report using YData Profiling.
- Analyzed feature distributions, correlations, outliers, and summary statistics.
Python, Pandas, NumPy, YData Profiling, Google Colab
Created a clean and analysis-ready dataset and generated a comprehensive profiling report that provides insights into data quality, statistical distributions, and relationships among exercise tracking variables.