{"id":20733416,"url":"https://github.com/codewithmayank-py/covid19-data-analysis-using-python","last_synced_at":"2026-04-11T13:34:33.792Z","repository":{"id":234178600,"uuid":"788391312","full_name":"CodeWithMayank-Py/Covid19-Data-Analysis-Using-Python","owner":"CodeWithMayank-Py","description":"COVID-19 and Happiness Analysis","archived":false,"fork":false,"pushed_at":"2024-04-18T11:48:55.000Z","size":303,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-18T00:44:58.150Z","etag":null,"topics":["data-analysis","data-analysis-python","data-visualization","dataset","jupyter-notebooks","numpy","pandas","python3","seaborn"],"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/CodeWithMayank-Py.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":"2024-04-18T10:22:52.000Z","updated_at":"2024-04-18T11:37:21.000Z","dependencies_parsed_at":null,"dependency_job_id":"e28f443b-b058-42b1-b0d9-8679c1b39060","html_url":"https://github.com/CodeWithMayank-Py/Covid19-Data-Analysis-Using-Python","commit_stats":null,"previous_names":["codewithmayank-py/covid19-data-analysis-using-python"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CodeWithMayank-Py%2FCovid19-Data-Analysis-Using-Python","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CodeWithMayank-Py%2FCovid19-Data-Analysis-Using-Python/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CodeWithMayank-Py%2FCovid19-Data-Analysis-Using-Python/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CodeWithMayank-Py%2FCovid19-Data-Analysis-Using-Python/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/CodeWithMayank-Py","download_url":"https://codeload.github.com/CodeWithMayank-Py/Covid19-Data-Analysis-Using-Python/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243018140,"owners_count":20222585,"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-analysis-python","data-visualization","dataset","jupyter-notebooks","numpy","pandas","python3","seaborn"],"created_at":"2024-11-17T05:25:19.810Z","updated_at":"2025-12-16T12:04:30.467Z","avatar_url":"https://github.com/CodeWithMayank-Py.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# COVID-19 and Happiness Analysis\n\n## Overview\nThis repository contains the Jupyter Notebook file for analyzing the COVID-19 dataset in conjunction with the happiness dataset. The analysis aims to explore the relationship between the COVID-19 pandemic and happiness levels across different regions.\n\n## Dataset\n- **COVID-19 Dataset**: The COVID-19 dataset contains information about the number of confirmed cases, deaths, and recoveries across various countries and regions.\n- **Happiness Dataset**: The happiness dataset includes metrics related to happiness levels, such as GDP per capita, social support, life expectancy, freedom to make life choices, generosity, and perceptions of corruption.\n\n## Analysis\nThe Jupyter Notebook file (`COVID19_Happiness_Analysis.ipynb`) provides detailed analysis and visualization of the datasets. Some of the key aspects covered in the analysis include:\n- Exploratory Data Analysis (EDA) of COVID-19 and happiness datasets.\n- Correlation analysis between COVID-19 statistics and happiness metrics.\n- Visualization of trends and patterns using matplotlib and seaborn libraries.\n\n## How to Use\nTo replicate or explore the analysis:\n1. Clone this repository to your local machine.\n2. Ensure you have Jupyter Notebook installed.\n3. Open `COVID19_Happiness_Analysis.ipynb` using Jupyter Notebook.\n4. Follow the step-by-step instructions in the notebook to run the analysis.\n\n## Dependencies\n- Python 3.9\n- Jupyter Notebook\n- Pandas\n- NumPy\n- Matplotlib\n- Seaborn\n\n## Contributors\n- [Mayank Paliwal](https://github.com/CodeWithMayank-Py)\n\n## Acknowledgements\n- COVID-19 [Dataset](https://github.com/CodeWithMayank-Py/Covid19-Data-Analysis-Using-Python/blob/main/datasets/covid19_Confirmed_dataset.csv).\n- Happiness [Dataset](https://github.com/CodeWithMayank-Py/Covid19-Data-Analysis-Using-Python/blob/main/datasets/worldwide_happiness_report.csv).\n\nFeel free to contribute to this project by opening issues or pull requests.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcodewithmayank-py%2Fcovid19-data-analysis-using-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcodewithmayank-py%2Fcovid19-data-analysis-using-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcodewithmayank-py%2Fcovid19-data-analysis-using-python/lists"}