{"id":28907634,"url":"https://github.com/rezowanrahat/netflix_analysis","last_synced_at":"2026-05-07T17:39:09.266Z","repository":{"id":299966980,"uuid":"1004760834","full_name":"rezowanrahat/netflix_analysis","owner":"rezowanrahat","description":"Data analysis of Netflix content using Python, Pandas, and Seaborn","archived":false,"fork":false,"pushed_at":"2025-06-19T06:44:29.000Z","size":1755,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-19T07:32:03.586Z","etag":null,"topics":["data-analysis","data-visualization","netflix","pandas","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/rezowanrahat.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2025-06-19T06:23:20.000Z","updated_at":"2025-06-19T06:44:32.000Z","dependencies_parsed_at":"2025-06-19T07:33:03.958Z","dependency_job_id":"0c7dad43-e0dd-43f8-b8ca-b40f1bab6528","html_url":"https://github.com/rezowanrahat/netflix_analysis","commit_stats":null,"previous_names":["rezowanrahat/netflix_analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/rezowanrahat/netflix_analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rezowanrahat%2Fnetflix_analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rezowanrahat%2Fnetflix_analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rezowanrahat%2Fnetflix_analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rezowanrahat%2Fnetflix_analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rezowanrahat","download_url":"https://codeload.github.com/rezowanrahat/netflix_analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rezowanrahat%2Fnetflix_analysis/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":261153584,"owners_count":23116915,"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":["data-analysis","data-visualization","netflix","pandas","python"],"created_at":"2025-06-21T16:04:35.505Z","updated_at":"2026-05-07T17:39:09.261Z","avatar_url":"https://github.com/rezowanrahat.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🎬 Netflix Movies and TV Shows Analysis\n\nA data analytics project exploring trends, genres, and global reach of Netflix content using Python, Pandas, and Seaborn.\n\n---\n\n## 📊 Project Overview\n\nThis project analyzes a publicly available Netflix dataset from Kaggle, with the goal of identifying content trends such as:\n\n- Distribution of Movies vs TV Shows\n- Trends in content releases by year\n- Most popular content ratings (PG, R, etc.)\n- Top countries producing Netflix content\n- Most common genres\n\n---\n\n## 🧰 Technologies Used\n\n- Python\n- Pandas \u0026 NumPy\n- Matplotlib \u0026 Seaborn\n- Jupyter Notebook / Google Colab\n\n---\n\n## 📁 Dataset\n\n**Source**: [Netflix Movies and TV Shows | Kaggle](https://www.kaggle.com/datasets/shivamb/netflix-shows)  \n**File**: `netflix_titles.csv`\n\n---\n\n## 📌 Key Findings\n\n- 🧮 Netflix has more Movies than TV Shows (~70%).\n- 🌍 The United States is the leading producer of Netflix content.\n- 🕰️ Content release peaked around 2018-2019.\n- 📺 Most shows are rated TV-MA or TV-14.\n- 🎭 Dramas are the most common genre.\n\n\u003e Visuals are included in the notebook for deeper insights.\n\n---\n\n## 📸 Sample Visualizations\n\n![Movies vs TV Shows](Content_Type.png)\n![Most Content Producing Country](Most_Content_Producing_Country.png)\n\n*Add your plots as images using the Jupyter “Save As PNG” function and upload to a `images/` folder.*\n\n---\n\n## 🚀 How to Run\n\n1. Clone this repository\n2. Install the requirements (optional)\n3. Open the notebook `netflix_analysis.ipynb`\n4. Run all cells to view the analysis\n\n---\n\n## 🧠 Future Work\n\n- Perform sentiment analysis on Netflix descriptions\n- Integrate IMDb ratings for deeper insights\n- Create an interactive dashboard (e.g., with Plotly or Dash)\n\n---\n\n## 📄 License\n\nThis project is under the MIT License. Dataset is publicly available via Kaggle.\n\n---\n\n## 🙋‍♂️ Author\n\n**Rezowan Khan**  \n- GitHub: [@rezowanrahat](https://github.com/rezowanrahat )\n- LinkedIn: [Rezowan Khan](https://www.linkedin.com/in/rezowan-khan/)\n\n---\n\n## 🏷️ Tags\n\n`Python` • `Pandas` • `Netflix` • `Beginner Project` • `Data Analysis` • `Seaborn` • `EDA`\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frezowanrahat%2Fnetflix_analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frezowanrahat%2Fnetflix_analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frezowanrahat%2Fnetflix_analysis/lists"}