Worked on the Multi-Energy-Systems-Optimization/mesido repository to enhance the efficiency of daily profile generation from hourly data. Focused on optimizing the adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day function, achieving a sixfold speed increase by refactoring the underlying data processing logic. Leveraged Python and performance optimization techniques to streamline the conversion of hourly profiles into daily averages while preserving hourly peak information. Updated project documentation, including the changelog, to ensure traceability of these improvements. The work emphasized robust data processing workflows and scalability, addressing the need for faster, more efficient handling of large datasets in energy systems modeling applications.