{"id":23024525,"url":"https://github.com/derrickbaruga7/python-data-analysis","last_synced_at":"2025-07-31T00:40:19.410Z","repository":{"id":250028744,"uuid":"833273874","full_name":"derrickbaruga7/Python-Data-Analysis","owner":"derrickbaruga7","description":"This project analyzes ORU’s off-season sewer usage using Python, with `pandas` for data handling, histograms and line plots for exploration, and a `scipy`-based model for prediction. 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Pearson’s correlation and visualizations help reveal key trends and relationships.\n\nExecutive Summary\n\nThe project aims to understand and reduce sewer usage during the off-season (November to April) at ORU. It explores factors influencing sewer usage, including cooling degrees and water usage, and builds a predictive model to minimize off-season usage.\n\nGoals of the Project\n\nUnderstand Off-Season Sewer Usage: Analyze factors affecting sewer usage during off-season months and hypothesize methods to reduce it.\nAnalyze Relationships: Examine how cooling degrees, water usage, and sewer charges relate to sewer usage.\nPredictive Modeling: Develop a model to predict and reduce off-season sewer usage.\nWhat We Did\n\nExploratory Data Analysis: Generated histograms and line plots to capture usage patterns and seasonality.\nUsage Comparison: Compared off-season and on-season sewer usage to identify high-contributing meters.\nPredictive Modeling: Created a model with a low Mean Squared Error to estimate future sewer usage.\nResults\n\nUsage Patterns: Histograms revealed significant variations in water and sewer usage, highlighting seasonal trends and anomalies.\nSeasonal Trends: The summary line graph showed a decrease in sewer usage from 2012 to present, with a spike in off-season usage from 2014 to 2017.\nTrouble Meters: Identified meters with higher off-season usage, such as Quad.Maintenance and Hamill_Timko_Dorms, which are key targets for intervention.\nUsage Comparisons: Significant decreases in water usage during the off-season were noted, with the NEC, Welcome.Center, and Chapel being less impactful compared to the major users.\nYearly Trends: Off-season sewer usage generally exceeds on-season usage from 2013 onwards, with notable peaks and fluctuations.\nDiscussion\n\nThe analysis provides valuable insights into sewer and water usage patterns, identifying key meters contributing to off-season usage. The predictive model shows promise, but further validation is needed.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fderrickbaruga7%2Fpython-data-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fderrickbaruga7%2Fpython-data-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fderrickbaruga7%2Fpython-data-analysis/lists"}