{"id":18418833,"url":"https://github.com/yash-kavaiya/ai-analytics","last_synced_at":"2025-07-20T15:33:40.701Z","repository":{"id":204156401,"uuid":"706165224","full_name":"Yash-Kavaiya/ai-analytics","owner":"Yash-Kavaiya","description":"This is a Streamlit app that uses Pandas and AI to perform data analytics on uploaded CSV files.","archived":false,"fork":false,"pushed_at":"2023-11-12T14:02:26.000Z","size":1143,"stargazers_count":1,"open_issues_count":0,"forks_count":4,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-19T07:20:53.704Z","etag":null,"topics":["data-analysis","generative-ai","pandas","streamlit"],"latest_commit_sha":null,"homepage":"https://pandas-ai-website.streamlit.app/","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/Yash-Kavaiya.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":"2023-10-17T12:32:20.000Z","updated_at":"2024-01-03T11:41:32.000Z","dependencies_parsed_at":"2023-11-02T17:39:18.200Z","dependency_job_id":"d96ee163-b075-46e2-9a76-9c7a7b3d4d1d","html_url":"https://github.com/Yash-Kavaiya/ai-analytics","commit_stats":null,"previous_names":["yash-kavaiya/pandas-ai","yash-kavaiya/ai-analytics"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Yash-Kavaiya/ai-analytics","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Yash-Kavaiya%2Fai-analytics","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Yash-Kavaiya%2Fai-analytics/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Yash-Kavaiya%2Fai-analytics/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Yash-Kavaiya%2Fai-analytics/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Yash-Kavaiya","download_url":"https://codeload.github.com/Yash-Kavaiya/ai-analytics/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Yash-Kavaiya%2Fai-analytics/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266151525,"owners_count":23884436,"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","generative-ai","pandas","streamlit"],"created_at":"2024-11-06T04:14:46.481Z","updated_at":"2025-07-20T15:33:40.677Z","avatar_url":"https://github.com/Yash-Kavaiya.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# **AI Analytics App with Streamlit and PandasAI**\n\nYoutube Video :- https://youtube.com/live/dtB78cuY08U\n\nStreamlit  website :- https://pandas-ai-website.streamlit.app/\n\nThis is a Streamlit app that uses Pandas and AI to perform data analytics on uploaded CSV files.\n\n## Features\n\n* Upload and analyze CSV files\n* Perform a variety of statistical analyses, including mean, mode, median, standard deviation, and variance\n* Generate interactive charts and visualizations\n* Use AI to extract insights from your data\n\n## Usage\n\n1. Upload a CSV file by clicking the \"Choose a CSV file\" button.\n2. Write analytics prompt .\n3. Click the \"Analyze\" button to generate results.\n4. The results will be displayed in a table and in a variety of charts and visualizations.\n5. You can also use the AI tab to generate insights from your data.\n\n## Getting Started\n\nTo run this app, you will need to have the following Python packages installed:\n\n* Streamlit\n* PandasAI\n```\n!pip install pandasai\n!pip install google.generativeai\n```\n\nOnce you have the required packages installed, clone this repository to your local machine and run the following command:\n\n```\nstreamlit run app.py\n```\n\nThe app will open in your web browser at http://localhost:8501.\n\n## Dependencies\n\n* Streamlit\n* Pandas\n* AI library of your choice (e.g., NumPy, scikit-learn, TensorFlow, PyTorch)\n\n## License\n\nThis project is licensed under the MIT License.\n\n```\nWhat is mean in glucose and standard deviation\n```\n\nThe AI will generate a response such as:\n\n121.365\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyash-kavaiya%2Fai-analytics","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fyash-kavaiya%2Fai-analytics","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyash-kavaiya%2Fai-analytics/lists"}