Metadata-Version: 2.1
Name: datasette-seaborn
Version: 0.2a0
Summary: Statistical visualizations for Datasette using Seaborn
Home-page: https://github.com/simonw/datasette-seaborn
Author: Simon Willison
License: Apache License, Version 2.0
Project-URL: Issues, https://github.com/simonw/datasette-seaborn/issues
Project-URL: CI, https://github.com/simonw/datasette-seaborn/actions
Project-URL: Changelog, https://github.com/simonw/datasette-seaborn/releases
Description: # datasette-seaborn
        
        [![PyPI](https://img.shields.io/pypi/v/datasette-seaborn.svg)](https://pypi.org/project/datasette-seaborn/)
        [![Changelog](https://img.shields.io/github/v/release/simonw/datasette-seaborn?include_prereleases&label=changelog)](https://github.com/simonw/datasette-seaborn/releases)
        [![Tests](https://github.com/simonw/datasette-seaborn/workflows/Test/badge.svg)](https://github.com/simonw/datasette-seaborn/actions?query=workflow%3ATest)
        [![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://github.com/simonw/datasette-seaborn/blob/main/LICENSE)
        
        Statistical visualizations for Datasette using Seaborn
        
        ## Installation
        
        Install this plugin in the same environment as Datasette.
        
            $ datasette install datasette-seaborn
        
        ## Usage
        
        Navigate to the new `.seaborn` extension for any Datasette table.
        
        The `_seaborn` argument specifies a method on `sns` to execute, e.g. `?_seaborn=relplot`.
        
        Extra arguments to those methods can be specified using e.g. `&_seaborn_x=column_name`.
        
        ## Configuration
        
        The plugin implements a default rendering time limit of five seconds. You can customize this limit using the `render_time_limit` setting, which accepts a floating point number of seconds. Add this to your `metadata.json`:
        
        ```json
        {
            "plugins": {
                "datasette-seaborn": {
                    "render_time_limit": 1.0
                }
            }
        }
        ```
        
        ## Development
        
        To set up this plugin locally, first checkout the code. Then create a new virtual environment:
        
            cd datasette-seaborn
            python3 -mvenv venv
            source venv/bin/activate
        
        Or if you are using `pipenv`:
        
            pipenv shell
        
        Now install the dependencies and tests:
        
            pip install -e '.[test]'
        
        To run the tests:
        
            pytest
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
Provides-Extra: test
