{"id":21669893,"url":"https://github.com/gabrielmazzotta/time-series-analysis-and-forecasting_case-study","last_synced_at":"2026-04-19T02:09:03.642Z","repository":{"id":224628792,"uuid":"763727182","full_name":"GabrielMazzotta/Time-Series-Analysis-and-Forecasting_Case-Study","owner":"GabrielMazzotta","description":" This project focuses on Time Series Analysis techniques, uncovering patterns and leveraging forecasting models to predict future sales trends.","archived":false,"fork":false,"pushed_at":"2024-09-09T18:03:39.000Z","size":1208,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-20T00:21:13.224Z","etag":null,"topics":["arima-model","exponential-smoothing","holt-winters-forecasting","sarima","statsmodels","time-series-analysis","time-series-decomposition"],"latest_commit_sha":null,"homepage":"https://www.linkedin.com/in/gabrielmazzotta/","language":"Jupyter Notebook","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/GabrielMazzotta.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}},"created_at":"2024-02-26T20:12:33.000Z","updated_at":"2025-03-14T02:04:55.000Z","dependencies_parsed_at":null,"dependency_job_id":"b6842c2a-c6f4-4098-96dd-1ec4ad40f1b5","html_url":"https://github.com/GabrielMazzotta/Time-Series-Analysis-and-Forecasting_Case-Study","commit_stats":null,"previous_names":["gabrielmazzotta/time-series-analysis-and-forecasting"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/GabrielMazzotta/Time-Series-Analysis-and-Forecasting_Case-Study","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GabrielMazzotta%2FTime-Series-Analysis-and-Forecasting_Case-Study","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GabrielMazzotta%2FTime-Series-Analysis-and-Forecasting_Case-Study/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GabrielMazzotta%2FTime-Series-Analysis-and-Forecasting_Case-Study/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GabrielMazzotta%2FTime-Series-Analysis-and-Forecasting_Case-Study/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/GabrielMazzotta","download_url":"https://codeload.github.com/GabrielMazzotta/Time-Series-Analysis-and-Forecasting_Case-Study/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GabrielMazzotta%2FTime-Series-Analysis-and-Forecasting_Case-Study/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31991721,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-18T20:23:30.271Z","status":"online","status_checked_at":"2026-04-19T02:00:07.110Z","response_time":55,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["arima-model","exponential-smoothing","holt-winters-forecasting","sarima","statsmodels","time-series-analysis","time-series-decomposition"],"created_at":"2024-11-25T12:26:12.253Z","updated_at":"2026-04-19T02:09:03.620Z","avatar_url":"https://github.com/GabrielMazzotta.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"![image](image.png)\n\n# Time Series Analysis and Forecasting\n\n## Introduction\n\nIn the ever-evolving landscape of data science, the ability to understand and predict trends over time is a crucial skill. Time series analysis plays a pivotal role in unraveling patterns, identifying anomalies, and making informed predictions based on historical data. This Jupyter Notebook project delves into the realm of time series data, exploring various techniques for analysis and forecasting.\n\n## Case Study\n\n\nIn this project, I analyze the monthly sales data of a medium-sized rental store business located in England.\n\nBecause rental activity varies from season to season due to proms, reunions, and other activities, business is expected to be seasonal. Financial manager would like to measure this seasonal effect, both to assist him in managing his\nbusiness and to use in negotiating a loan repayment\nwith his banker.\n\nEven greater interest is finding a way of forecasting monthly sales. As business continues to grow, it requires more capital and long-term debt. \n\n\n## Models and Concepts\n- Seasonal Decomposition\n- Exponential Smoothing Holt-Winters\n- Augmented Dickey–Fuller test\n- SARIMA\n- Metrics and measure: RMSE (Root Mean Squared Error), AIC. \n \n## Language/Libraries\n* Python / Jupyter notebooks\n* Statsmodels\n* Scipy\n* Sklearn.metrics\n* Pandas\n* Numpy\n* Matplotlib\n* Seaborn\n\n## Dataset\n\nThis dataset spans 8 years and captures monthly sales records of a medium-sized rental store business.\n\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgabrielmazzotta%2Ftime-series-analysis-and-forecasting_case-study","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgabrielmazzotta%2Ftime-series-analysis-and-forecasting_case-study","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgabrielmazzotta%2Ftime-series-analysis-and-forecasting_case-study/lists"}