{"id":27629375,"url":"https://github.com/bhavnanahar/coral_project","last_synced_at":"2026-04-14T03:32:49.254Z","repository":{"id":289263052,"uuid":"970664944","full_name":"Bhavnanahar/CORAL_PROJECT","owner":"Bhavnanahar","description":"ChatGPT said: This project analyzes and predicts the health of coral reefs in the Florida Keys by examining coral cover and species richness trends over time.","archived":false,"fork":false,"pushed_at":"2025-04-22T11:02:55.000Z","size":1081,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-23T15:16:47.091Z","etag":null,"topics":["colab-notebook","matplotlib","numpy","pandas","plotly","python","random-forest","scikit-learn","seabo"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Bhavnanahar.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-04-22T10:58:24.000Z","updated_at":"2025-04-22T11:06:33.000Z","dependencies_parsed_at":"2025-04-23T15:16:46.995Z","dependency_job_id":null,"html_url":"https://github.com/Bhavnanahar/CORAL_PROJECT","commit_stats":null,"previous_names":["bhavnanahar/coral_project"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Bhavnanahar/CORAL_PROJECT","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Bhavnanahar%2FCORAL_PROJECT","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Bhavnanahar%2FCORAL_PROJECT/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Bhavnanahar%2FCORAL_PROJECT/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Bhavnanahar%2FCORAL_PROJECT/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Bhavnanahar","download_url":"https://codeload.github.com/Bhavnanahar/CORAL_PROJECT/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Bhavnanahar%2FCORAL_PROJECT/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":260438614,"owners_count":23009261,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["colab-notebook","matplotlib","numpy","pandas","plotly","python","random-forest","scikit-learn","seabo"],"created_at":"2025-04-23T15:16:43.779Z","updated_at":"2026-04-14T03:32:49.249Z","avatar_url":"https://github.com/Bhavnanahar.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":":\n\n🌊 Florida Keys Coral Reef Health Analysis \u0026 Prediction 🐠\nThis project aims to analyze and predict the health of the coral reefs in the Florida Keys. Using a dataset that includes information about coral cover, species richness, and environmental conditions, we apply data analysis, machine learning, and time series forecasting to understand trends and predict future reef conditions.\n\n📊 Project Overview\nThe health of coral reefs is a critical indicator of marine ecosystem stability. This project focuses on analyzing coral cover and species richness over time, exploring factors influencing coral health (such as environmental data), and creating predictive models to forecast future coral reef conditions.\n\nThe main objectives of this project are:\n\n📈 Analyze historical trends in coral cover and species richness.\n\n🌍 Visualize data using heatmaps, plots, and other charts.\n\n🔍 Identify factors influencing coral health.\n\n🤖 Predict future coral reef health using time series and machine learning models.\n\n📂 Dataset\nThe dataset used in this project includes various columns such as coral species data, site information, environmental conditions, and survey results. Key columns include:\n\nYear: Year of the survey.\n\nSubregion: Specific area within the Florida Keys.\n\nCoral Species: Data on various coral species (e.g., Acropora_cervicornis, Porites_porites).\n\nEnvironmental Factors: Temperature, nutrients, pollution, etc.\n\nCoral Cover: Percentage of coral cover at the surveyed site.\n\nSpecies Richness: Count of coral species present.\n\n🛠️ Technologies Used\nPython 🐍: For data manipulation, visualization, and modeling.\n\nLibraries:\n\nPandas: Data manipulation and analysis.\n\nMatplotlib \u0026 Seaborn: Data visualization.\n\nScikit-learn: Machine learning models and evaluation.\n\n📝 Steps in the Project\n1. Data Preprocessing 🧹\nClean and preprocess the data, handling missing values and converting data types.\n\nFocus on essential columns like Year, Subregion, and total_coral_cover.\n\n2. Data Exploration \u0026 Visualization 📉\nAnalyze trends in coral cover and species richness over time.\n\nCreate heatmaps to visualize coral cover and species richness by region.\n\nExplore correlations between environmental factors (temperature, nutrients) and coral health.\n\n3. Predictive Modeling 🤖\nModel Selection: Use Random Forest, XGBoost, and Linear Regression for coral cover prediction.\n\nTime Series Forecasting: Use Prophet for predicting future coral cover trends.\n\nModel Evaluation: Evaluate models using metrics like RMSE.\n\n4. Model Interpretation \u0026 Insights 🧐\nPlot actual vs predicted coral cover values to visually assess model accuracy.\n\nUse feature importance from Random Forest and XGBoost to identify key predictors of coral health.\n\nData Visualizations: Trend lines, heatmaps, and scatter plots to understand coral health over time.\n\nPredictive Models: Forecasts for future coral cover, model accuracy metrics, and insights on coral health.\n\n📧 Contact\nFor any questions or feedback, feel free to open an issue in the repository or contact me at:\n\nEmail: bhavnanahar245@gmail.com 📧\n👏 Acknowledgments\nThanks to the creators of the dataset and any libraries used in this project.\n\nSpecial thanks to the open-source community for providing tools and frameworks that made this analysis possible.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbhavnanahar%2Fcoral_project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbhavnanahar%2Fcoral_project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbhavnanahar%2Fcoral_project/lists"}