Back Bay Water Quality Analysis
Data Analysis Project
Complete
Python
Data Analysis
Type
Data analysis project
Status
Complete
Dataset
2,400 row longitudinal dataset
Timeline
May to June 2025
Overview
Over May and June 2025, I analyzed a 2,400 row longitudinal dataset for Back Bay using Python, working through data cleaning, trend analysis, and visualization to quantify long term trends in water temperature, air temperature, and water depth.
My contribution
- Cleaned and organized the 2,400 row longitudinal dataset using pandas
- Performed trend and statistical analysis using NumPy to quantify long term patterns in water temperature, air temperature, and water depth
- Built visualizations in Matplotlib to communicate those trends clearly
Tools and technologies
Approach
- Data cleaning. Handling missing or inconsistent readings before running any analysis.
- Trend analysis. Using NumPy and pandas to organize and evaluate the data for meaningful patterns.
- Visualization. Building Matplotlib charts that make the trends easy to interpret at a glance.
Challenges
Real world environmental data is noisy and often incomplete, so a meaningful part of this project was deciding how to handle missing or questionable readings without distorting the overall trends.
What I learned
- Practical data cleaning with pandas before any analysis is meaningful
- How to turn a raw dataset into a clear visual narrative
- Communicating quantitative results in a way a non specialist can follow