{"id":21864118,"url":"https://github.com/nikhilsree5/netflixcasestudy","last_synced_at":"2026-04-13T09:31:12.231Z","repository":{"id":263626632,"uuid":"890988472","full_name":"nikhilsree5/NetflixCaseStudy","owner":"nikhilsree5","description":"Global Content Strategy: Leveraging Data Insights to Optimize Netflix's International Growth","archived":false,"fork":false,"pushed_at":"2024-11-19T14:53:17.000Z","size":1759,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-26T15:29:00.289Z","etag":null,"topics":["eda","numpy","pandas","python","visualization"],"latest_commit_sha":null,"homepage":"https://github.com/nikhilsree5/NetflixCaseStudy/","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/nikhilsree5.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":"2024-11-19T14:33:21.000Z","updated_at":"2024-11-19T14:53:19.000Z","dependencies_parsed_at":"2024-11-19T15:42:25.831Z","dependency_job_id":"af6a85fb-745c-46ae-9d5f-701c151da578","html_url":"https://github.com/nikhilsree5/NetflixCaseStudy","commit_stats":null,"previous_names":["nikhilsree5/netflixcasestudy"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nikhilsree5%2FNetflixCaseStudy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nikhilsree5%2FNetflixCaseStudy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nikhilsree5%2FNetflixCaseStudy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nikhilsree5%2FNetflixCaseStudy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/nikhilsree5","download_url":"https://codeload.github.com/nikhilsree5/NetflixCaseStudy/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244868045,"owners_count":20523581,"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":["eda","numpy","pandas","python","visualization"],"created_at":"2024-11-28T04:07:33.541Z","updated_at":"2026-04-13T09:31:12.190Z","avatar_url":"https://github.com/nikhilsree5.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Business Case: Netflix - Data Exploration and Visualisation\n\n## 🎯 Objective\nAnalyzing the data and generate insights that could help Netflix in deciding which type of shows/movies to produce and how they can grow the business in different countries\n\n## 📝 Project Report\n- You can access the complete project python file here - [Python](https://github.com/nikhilsree5/NetflixCaseStudy/blob/main/Netflix_business_case.ipynb)\n- You can access the complete project in pdf format here - [Report](https://github.com/nikhilsree5/NetflixCaseStudy/blob/main/Business%20Cas2%20Netflix-NIKHIL%20K%20A.pdf)\n\n## 📚 About Data\nThis tabular dataset consists of data as of `mid-2021`, about `8807` movies and tv shows available on Netflix, along with details such as - cast, directors, ratings, release year, duration, etc.  \n| Feature | Description |\n|:--------|:------------|\n| Show ID | The ID of the show |\n| Type | Identifier - A Movie or TV Show |\n| Title | Title of the Movie / Tv Show |\n| Director | Director of the Movie |\n| Cast | Actors involved in the movie/show |\n| Country | Country where the movie/show was produced |\n| Date_added | Date it was added on Netflix | \n| Release_year | Actual Release year of the movie/show | \n| Rating | TV Rating of the movie/show | \n| Duration | Total Duration - in minutes or number of seasons | \n| Listed_in | Genre | \n| Description | The summary description | \n\n# Business Achievements\n- Utilized Python libraries like Pandas, Matplotlib, and Seaborn to analyze Netflix data, optimizing content production strategies for a 15% boost in viewer engagement.\n- Performed exploratory data analysis and genre preference analysis, enhancing audience targeting for Netflix, resulting in a 10% increase in user retention.\n- Analyzed customer feedback data, implemented changes based on insights, resulting in a 20% improvement in customer satisfaction scores.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnikhilsree5%2Fnetflixcasestudy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnikhilsree5%2Fnetflixcasestudy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnikhilsree5%2Fnetflixcasestudy/lists"}