This project has been archived by its maintainers, and is no longer receiving any updates.
Edvart
[!WARNING] This project is no longer maintained. We recommend using agentic coding tools to generate one-time EDA reports.
Edvart is an open-source Python library designed to simplify and streamline your exploratory data analysis (EDA) process.
Key Features
- One-line Reports: Generate a comprehensive set of pandas DataFrame
visualizations using a single Python statement.
Edvart supports:
- Data overview,
- Univariate analysis,
- Bivariate analysis,
- Multivariate analysis,
- Grouped analysis,
- Time series analysis.
- Customizable Reports: Produce, iterate, and style detailed reports in Jupyter notebooks and HTML formats.
- Flexible API: From high-level simplicity in a single line of code to detailed control, choose the API level that fits your needs.
- Interactive Visualizations: Many of the visualizations are interactive and can be used to explore the data in detail.
One-line Report
Installation
Edvart is available on PyPI and can be installed using pip:
pip install edvart
Usage
See the notebook examples/report-example.ipynb for an example report on a tabular dataset or examples/time-series-report-example.ipynb for an example report on a time-series dataset.
See the Usage section of the documentation for more information.
Creating a Default Report
import edvart
# Load a dataset to a pandas DataFrame
dataset = edvart.example_datasets.dataset_titanic()
# Create a default report
report = edvart.DefaultReport(dataset)
# Show the report in the current Jupyter notebook
report.show()
# Export the report to an HTML file
report.export_html("report.html")
# Export the code generating the report to a Jupyter notebook
report.export_notebook("report.ipynb")
User Documentation
The user documentation is available at https://datamole-ai.github.io/edvart/.
License
Edvart is licensed under the MIT license. See the LICENSE file for more details.
Contact
Edvart has a Gitter room for development-related and general discussions.
How to Contribute
See CONTRIBUTING.md.
Metadata
Release files for edvart 4.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| edvart-4.0.2.tar.gz | 1.2 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| edvart-4.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.5 MB
Release files / edvart-4.0.2.tar.gz
| Download URL | edvart-4.0.2.tar.gz |
|---|---|
| Size | 1.2 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / edvart-4.0.2-py3-none-any.whl
| Download URL | edvart-4.0.2-py3-none-any.whl |
|---|---|
| Size | 1.3 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Feb 17, 2026.
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