Exploratory Data Analysis (EDA) is the initial task a data scientist or data analyst undertakes when they obtain new data. EDA refers to the critical process of conducting preliminary investigations on data to uncover patterns, spot anomalies, test hypotheses, and verify assumptions with the help of summary statistics and graphical representations.
The Effective Data Visualization and Reporting Tool (Edvart for short) is a tool that generates a report in the form of a Jupyter notebook, containing various analyses of the input data.
Edvart is available on PyPI and can be installed using pip:
pip install edvart
See the notebook api-example.ipynb for usage examples.
The user documentation is available at https://datamole-ai.github.io/edvart/.
Edvart is licensed under the MIT license. See the LICENSE file for more details.
See CONTRIBUTING.md.