{"id":31556914,"url":"https://github.com/lisashei/analytics_pet-projects","last_synced_at":"2025-10-04T23:19:44.919Z","repository":{"id":316441155,"uuid":"1063381413","full_name":"lisashei/analytics_pet-projects","owner":"lisashei","description":"Data analysis and visualization projects","archived":false,"fork":false,"pushed_at":"2025-09-24T17:00:14.000Z","size":4929,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-09-24T17:23:28.637Z","etag":null,"topics":["analytics","business-analytics","data-analysis","data-visualization","powerbi","product-analytics","python","r","sql","tableau"],"latest_commit_sha":null,"homepage":"","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/lisashei.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,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-09-24T14:47:28.000Z","updated_at":"2025-09-24T17:05:57.000Z","dependencies_parsed_at":"2025-09-24T17:35:58.638Z","dependency_job_id":null,"html_url":"https://github.com/lisashei/analytics_pet-projects","commit_stats":null,"previous_names":["lisashei/analytics_pet-projects"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/lisashei/analytics_pet-projects","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lisashei%2Fanalytics_pet-projects","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lisashei%2Fanalytics_pet-projects/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lisashei%2Fanalytics_pet-projects/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lisashei%2Fanalytics_pet-projects/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lisashei","download_url":"https://codeload.github.com/lisashei/analytics_pet-projects/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lisashei%2Fanalytics_pet-projects/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278386497,"owners_count":25978184,"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","status":"online","status_checked_at":"2025-10-04T02:00:05.491Z","response_time":63,"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":["analytics","business-analytics","data-analysis","data-visualization","powerbi","product-analytics","python","r","sql","tableau"],"created_at":"2025-10-04T23:19:40.734Z","updated_at":"2025-10-04T23:19:44.902Z","avatar_url":"https://github.com/lisashei.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Analytics Pet-projects\nThis repository contains data analysis and visualization projects using Python, R, SQL, Tableau, and Power BI.\n\n## Projects\n### [Power BI Company Performance](https://github.com/lisashei/analytics_pet-projects/tree/main/Power%20BI%20Company%20Performance)\n\nThis dashboard provides an overview of company performance by tracking key metrics like gross profit, sales, and quantity. It enables detailed analysis of trends, identifies underperforming regions and products, and offers client segmentation to guide strategic decisions for improving profitability.\n\n**Tools**: Power BI\n\n### [Power BI Sales and Customer](https://github.com/lisashei/analytics_pet-projects/tree/main/Power%20BI%20Sales%20and%20Customer)\n\nThis project consists of two complementary dashboards that analyze sales performance and customer behavior to drive business strategy. The Sales Report tracks regional and product performance, while the Customer Report provides insights into demographics and purchasing patterns to enable targeted marketing.\n\n**Tools**: Power BI\n\n### [Tableau HBO Movies and Shows](https://github.com/lisashei/analytics_pet-projects/tree/main/Tableau%20HBO%20Movies%20and%20Shows)\n\nThis dashboard analyzes HBO's content library by providing insights into release trends, genre popularity, and production patterns across movies and shows.\n\n**Tools**: Tableau\n\n### [Tableau Product Sales](https://github.com/lisashei/analytics_pet-projects/tree/main/Tableau%20Product%20Sales)\n\nThis dashboard provides an analysis of product sales performance by tracking key metrics, profit trends, and product categorization to identify profit drivers and optimize product strategy.\n\n**Tools**: Tableau\n\n### [Python Customer Analysis](https://github.com/lisashei/analytics_pet-projects/tree/main/Python%20Customer%20Analysis)\n\nThis customer analysis project employs statistical testing to uncover key behavioral patterns, spending patterns, and payment preferences across different customer segments. It provides data-driven recommendations for optimizing customer retention strategies, discount campaigns, and payment system improvements to enhance business performance.\n\n**Tools**: Python (numpy, pandas, matplotlib, seaborn, scipy)\n\n### [Python HBO Analysis](https://github.com/lisashei/analytics_pet-projects/tree/main/Python%20HBO%20Analysis)\n\nThis statistical analysis uses regression modeling to identify key factors influencing IMDB ratings for HBO's movies and shows, providing insights for content strategy and rating prediction.\n\n**Tools**: Python (numpy, pandas, matplotlib, seaborn, scipy, statsmodels, sklearn)\n\n### [SQL Customer Report](https://github.com/lisashei/analytics_pet-projects/tree/main/SQL%20Customer%20Report)\n\nThis customer report analyzes purchasing behavior, segments customers into categories, and calculates performance metrics. It serves as a foundation for predictive modeling to improve customer retention and engagement.\n\n**Tools**: SQL Server Management Studio\n\n### [SQL Window Functions](https://github.com/lisashei/analytics_pet-projects/tree/main/SQL%20Window%20Functions)\n\nThis project utilizes advanced window functions to analyze sales trends and product performance through cumulative totals, moving averages, yearly sales comparisons, and product rankings. \n\n**Tools**: SQL Server Management Studio\n\n### [R City Recommendation App](https://github.com/lisashei/analytics_pet-projects/tree/main/R%20City%20Recommendation%20App)\n\nThis application provides personalized European city recommendations by clustering destinations based on similarity features and matching them to users' budget constraints and travel preferences. It helps travelers discover optimal destinations through intelligent filtering, while suggesting alternative cities from the same cluster to expand their options.\n\n**Tools**: R (dplyr, shiny, caret) \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flisashei%2Fanalytics_pet-projects","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flisashei%2Fanalytics_pet-projects","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flisashei%2Fanalytics_pet-projects/lists"}