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version](https://img.shields.io/pypi/v/streamlit-advanced-dataframe)](https://pypi.org/project/streamlit-advanced-dataframe/)\n[![Python version](https://img.shields.io/pypi/pyversions/streamlit-advanced-dataframe)](https://pypi.org/project/streamlit-advanced-dataframe/)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n[![Downloads](https://img.shields.io/pypi/dm/streamlit-advanced-dataframe)](https://pypi.org/project/streamlit-advanced-dataframe/)\n\nStreamlit's `st.dataframe` with advanced features using TanStack Table.\n\n## Demo \u0026 Docs\n\n- [Live Demo](https://app-advanced-dataframe-ezjlvffyxpev3iima6ttwr.streamlit.app/)\n- [Documentation](https://j4rviscmd.github.io/streamlit-advanced-dataframe/)\n\n## Quick Start\n\n```bash\npip install streamlit-advanced-dataframe\n```\n\n```python\nimport pandas as pd\nfrom streamlit_advanced_dataframe import advanced_dataframe\n\ndf = pd.DataFrame({\n    \"name\": [\"Alice\", \"Bob\", \"Charlie\"],\n    \"age\": [25, 30, 35],\n    \"city\": [\"Tokyo\", \"Osaka\", \"Kyoto\"]\n})\n\nadvanced_dataframe(data=df, height=400)\n```\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fj4rviscmd%2Fstreamlit-advanced-dataframe","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fj4rviscmd%2Fstreamlit-advanced-dataframe","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fj4rviscmd%2Fstreamlit-advanced-dataframe/lists"}