{"id":37717599,"url":"https://github.com/datamole-ai/edvart","last_synced_at":"2026-02-11T11:04:03.537Z","repository":{"id":182771236,"uuid":"669059308","full_name":"datamole-ai/edvart","owner":"datamole-ai","description":"An open-source Python library for Data Scientists \u0026 Data Analysts designed to simplify the exploratory data analysis process. 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Downloads\" src=\"https://img.shields.io/pypi/dm/edvart.svg?label=PyPI%20downloads\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://github.com/astral-sh/ruff\"\u003e\n        \u003cimg alt=\"Ruff\", src=\"https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json\"\u003e\n    \u003c/a\u003e\n\u003c/p\u003e\n\nEdvart is an open-source Python library designed to simplify and streamline\nyour exploratory data analysis (EDA) process.\n\n## Key Features\n* **One-line Reports**: Generate a comprehensive set of pandas DataFrame\nvisualizations using a single Python statement.\nEdvart supports:\n    - Data overview,\n    - Univariate analysis,\n    - Bivariate analysis,\n    - Multivariate analysis,\n    - Grouped analysis,\n    - Time series analysis.\n* **Customizable Reports**: Produce, iterate, and style detailed reports\n    in Jupyter notebooks and HTML formats.\n* **Flexible API**: From high-level simplicity in a single line of code\n    to detailed control, choose the API level that fits your needs.\n* **Interactive Visualizations**: Many of the visualizations are interactive\n    and can be used to explore the data in detail.\n\n## One-line Report\n\n![Edvart report demo](images/edvart-demo.gif)\n\n## Installation\n\nEdvart is available on PyPI and can be installed using pip:\n\n```bash\npip install edvart\n```\n\n## Usage\n\n\nSee the notebook\n[examples/report-example.ipynb](https://nbviewer.org/github/datamole-ai/edvart/blob/main/examples/report-example.ipynb)\nfor an example report on a tabular dataset or\n[examples/time-series-report-example.ipynb](https://nbviewer.org/github/datamole-ai/edvart/blob/main/examples/time-series-report-example.ipynb)\nfor an example report on a time-series dataset.\n\nSee the [Usage section](https://datamole-ai.github.io/edvart/usage.html) of the documentation\nfor more information.\n\n### Creating a Default Report\n\n```python\nimport edvart\n\n# Load a dataset to a pandas DataFrame\ndataset = edvart.example_datasets.dataset_titanic()\n# Create a default report\nreport = edvart.DefaultReport(dataset)\n# Show the report in the current Jupyter notebook\nreport.show()\n# Export the report to an HTML file\nreport.export_html(\"report.html\")\n# Export the code generating the report to a Jupyter notebook\nreport.export_notebook(\"report.ipynb\")\n```\n\n## User Documentation\n\nThe user documentation is available at https://datamole-ai.github.io/edvart/.\n\n## License\n\nEdvart is licensed under the [MIT\nlicense](https://opensource.org/license/mit/). See the LICENSE file for more\ndetails.\n\n## Contact\nEdvart has a [Gitter room](https://app.gitter.im/#/room/#edvart:gitter.im)\nfor development-related and general discussions.\n\n## How to Contribute\n\nSee [CONTRIBUTING.md](CONTRIBUTING.md).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatamole-ai%2Fedvart","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdatamole-ai%2Fedvart","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatamole-ai%2Fedvart/lists"}