{"id":22038967,"url":"https://github.com/ayushsiloiya619/brain-stroke-analysis","last_synced_at":"2026-05-05T00:36:31.307Z","repository":{"id":232139127,"uuid":"782316783","full_name":"ayushsiloiya619/Brain-Stroke-Analysis","owner":"ayushsiloiya619","description":"Data Analytics with Python","archived":false,"fork":false,"pushed_at":"2024-04-09T12:06:48.000Z","size":405,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-28T19:16:32.925Z","etag":null,"topics":["data-analysis","matplotlib-pyplot","python3","seaborn","seaborn-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":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ayushsiloiya619.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}},"created_at":"2024-04-05T04:02:39.000Z","updated_at":"2024-04-08T06:05:14.000Z","dependencies_parsed_at":"2024-04-08T07:26:03.954Z","dependency_job_id":"99fe8298-1c14-4a63-9962-5c1b39b844cc","html_url":"https://github.com/ayushsiloiya619/Brain-Stroke-Analysis","commit_stats":null,"previous_names":["ayushsiloiya619/brain-stroke-analysis"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ayushsiloiya619%2FBrain-Stroke-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ayushsiloiya619%2FBrain-Stroke-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ayushsiloiya619%2FBrain-Stroke-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ayushsiloiya619%2FBrain-Stroke-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ayushsiloiya619","download_url":"https://codeload.github.com/ayushsiloiya619/Brain-Stroke-Analysis/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245104460,"owners_count":20561377,"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","matplotlib-pyplot","python3","seaborn","seaborn-python"],"created_at":"2024-11-30T11:08:56.624Z","updated_at":"2026-05-05T00:36:26.281Z","avatar_url":"https://github.com/ayushsiloiya619.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Brain Stroke Analysis\n\n## Overview\nThis project focuses on analyzing brain stroke occurrences using Python and data analysis techniques. It involves thorough data preprocessing, exploratory analysis, statistical tests, and visualization to gain valuable insights into this critical healthcare domain.\n\n## Project Highlights\n- **Null Value Handling:** Identified and addressed null values meticulously, ensuring impeccable data integrity and accuracy for further analysis.\n- **In-depth Analysis:** Conducted thorough analysis to decipher patterns and trends related to brain stroke occurrences, providing valuable insights for healthcare professionals.\n- **Data Manipulation Expertise:** Employed advanced techniques to fill missing values and optimize data quality, enhancing the reliability and usefulness of the dataset.\n- **Python Libraries Mastery:** Leveraged powerful Python libraries including Pandas and NumPy for seamless data preprocessing, cleaning, and analysis, maximizing efficiency.\n- **Visualization Proficiency:** Utilized state-of-the-art visualization tools such as Matplotlib and Seaborn to craft visually engaging charts and graphs, effectively communicating complex insights to stakeholders.\n\n## Tools Used\n- Python\n- Pandas\n- NumPy\n- Matplotlib\n- Seaborn\n- Jupyter Notebooks\n\n## Workflow\n1. Data Collection and Preprocessing\n   - Gathered and cleaned data to ensure data integrity.\n2. Exploratory Data Analysis (EDA)\n   - Analyzed data to identify patterns and correlations.\n3. Statistical Analysis\n   - Performed statistical tests to validate findings.\n4. 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