This work is a demonstration of EDA and BI in Python Jupyter Notebook on the Los Angeles Metro Bike Share system's bicycle trip data. The project involved data cleaning, visualization, and statistical analysis to identify key trends, patterns, and actionable insights that could help improve bike share utilization and operational efficiency.
This work is a demonstration of EDA and BI in Python Jupyter Notebook on the Los Angeles Metro Bike Share system's bicycle trip data. The project involved data cleaning, visualization, and statistical analysis to identify key trends, patterns, and actionable insights that could help improve bike share utilization and operational efficiency.