Summary of ObjectivePerformed exploratory data analysis on the USFS Bat Conservation Strategy (BCS) data to explore collection efforts, distribution, and species populations. The data included capture, roost, and hibernacula locations for four core bat species: Tricolored bat, Northern Long-eared bat, Little Brown bat, and Indiana bat.

Process and Methodology-Retrieved, quality-checked, and prepared capture, roost, and hibernacula data submitted in both geospatial and Excel formats. Used the matplotlib module to create visualizations showing collection efforts and species distribution at regional and unit levels.Data were loaded into pandas data frames and cleaned to retain only essential fields. A unit code field was created to standardize unit naming. Data types were confirmed and adjusted for compatibility with visualization tools. Histograms and summaries were generated to assess activity across regions and units.

Outcome-The analysis revealed regional and unit-level differences in data collection activity. Region 9 showed more capture data efforts than Region 8. Hibernacula collection efforts were similar across both regions, though specific units varied in activity. Region 8 led in roost data collection.This analysis provides a foundation for identifying data gaps and exploring population trends. It highlighted differences in maternity and species population evidence, which can support further investigations into species health.

Lessons Learned-This project emphasized that there are many ways to write code, but efficiency comes with experience. I learned that persistence is key—debugging code was a humbling process. While I don’t expect to become a master coder, I now have practical skills that will benefit my unit by streamlining large data tasks. Like golf, coding brings frustrations, but those small wins keep me motivated.

Project Impact-Organizing large datasets manually requires time and staff. Python enabled efficient processing, improved data quality, and reduced errors at scale. The tools and techniques I learned allowed for both quality control and high-level analysis. This project provided a data-driven snapshot of endangered bat species trends across two USFS regions.