Metadata-Version: 2.1
Name: statannotations
Version: 0.5.0
Summary: add statistical significance or custom annotations on seaborn plots. Based on statannot 0.2.3
Home-page: https://github.com/trevismd/statannotations
Maintainer: Florian Charlier
Maintainer-email: trevis@cascliniques.be
License: MIT License
Description: [![Active Development](https://img.shields.io/badge/Maintenance%20Level-Actively%20Developed-brightgreen.svg)](https://gist.github.com/cheerfulstoic/d107229326a01ff0f333a1d3476e068d) 
        ![coverage](https://raw.githubusercontent.com/trevismd/statannotations/master/coverage.svg)  
        ![Python](https://img.shields.io/badge/Python-3.6%2B-blue)
        [![Documentation Status](https://readthedocs.org/projects/statannotations/badge/?version=latest)](https://statannotations.readthedocs.io/en/master/?badge=latest)
        
        ## What is it
        
        Python package to optionally compute statistical test and add statistical
        annotations on plots generated with seaborn.
        
        ## Derived work
        
        This repository is based on
        [webermarcolivier/statannot](https://github.com/webermarcolivier/statannot)
         (commit 1835078 of Feb 21, 2020, tagged "v0.2.3").
        
        Additions/modifications since that version are below represented **in bold**
        (previous fixes are not listed).
        
        **! From version 0.4.0 onwards (introduction of `Annotator`), `statannot`'s API 
        is no longer usable in `statannotations`**. 
        Please use the latest v0.3.2 release if you must keep `statannot`'s API in your 
        code, but are looking for bug fixes we have covered.
        
        `statannot`'s interface, at least until its version 0.2.3, is usable in 
        statannotations until v.0.3.x, which already provides additional features (see
        corresponding branch).
        
        ## Features
        
        - Single function to add statistical annotations on plots
          generated by seaborn:
            - Box plots
            - Bar plots
            - **Swarm plots**
            - **Strip plots**
            - **Violin plots** 
            - Supporting `FacetGrid`
        - Integrated statistical tests (binding to `scipy.stats` methods):
            - Mann-Whitney
            - t-test (independent and paired)
            - Welch's t-test
            - Levene test
            - Wilcoxon test
            - Kruskal-Wallis test
            - **Brunner-Munzel test**
        - **Interface to use any other function from any source with minimal extra
          code**
        - Smart layout of multiple annotations with correct y offsets.
        - **Support for vertical and horizontal orientation**
        - Annotations can be located inside or outside the plot.
        - **Corrections for multiple testing can be applied
          (binding to `statsmodels.stats.multitest.multipletests` methods):**
            - Bonferroni
            - Holm-Bonferroni
            - Benjamini-Hochberg
            - Benjamini-Yekutieli
        - **And any other function from any source with minimal extra code**
        - Format of the statistical test annotation can be customized:
              star annotation, simplified p-value format, or explicit p-value.
        - Optionally, custom p-values can be given as input.
              In this case, no statistical test is performed, but **corrections for
              multiple testing can be applied.**
        - Any text can be used as annotation
        - And various fixes (see
          [CHANGELOG.md](https://github.com/trevismd/statannotations/blob/master/CHANGELOG.md)).
        
        ## Installation
        
        From version 0.3.0 on, the package is distributed on PyPi.
        The latest stable release (v0.5.0) can be downloaded and installed with:
        ```bash
        pip install statannotations
        ```
        
        or, after cloning the repository,
        ```bash
        pip install .
        
        # OR, to have optional dependencies too (multiple comparisons & testing)
        pip install -r requirements.txt .
        ```
        
        ## Important note
        
        **! Seaborn ≥ v0.12 is not officially supported, we know there are at least 
        some bugs. Issues can still be reported (and upvoted) in order to plan further
        development to support these versions. Also see 
        [discussion](https://github.com/trevismd/statannotations/discussions/81)**.
        
        ## Usage
        
        Here is a minimal example:
        
        ```python
        import seaborn as sns
        
        from statannotations.Annotator import Annotator
        
        df = sns.load_dataset("tips")
        x = "day"
        y = "total_bill"
        order = ['Sun', 'Thur', 'Fri', 'Sat']
        
        ax = sns.boxplot(data=df, x=x, y=y, order=order)
        
        pairs=[("Thur", "Fri"), ("Thur", "Sat"), ("Fri", "Sun")]
        
        annotator = Annotator(ax, pairs, data=df, x=x, y=y, order=order)
        annotator.configure(test='Mann-Whitney', text_format='star', loc='outside')
        annotator.apply_and_annotate()
        ```
        
        ## Examples
        
        ![Example 2](https://raw.githubusercontent.com/trevismd/statannotations/master/usage/example_hue_layout.png)
        
        ![Example 3](https://raw.githubusercontent.com/trevismd/statannotations/master/usage/flu_dataset_log_scale_in_axes.svg)
        
        ![Example 4](https://raw.githubusercontent.com/trevismd/statannotations/master/usage/HorizontalBarplotOutside.png)
        
        ![Example 5](https://raw.githubusercontent.com/trevismd/statannotations/master/usage/example_2facets.png)
        
        ## Documentation
        
        - Usage examples in a jupyter notebook [usage/example.ipynb](https://github.com/trevismd/statannotations/blob/master/usage/example.ipynb),
        - A multipart step-by-step tutorial in a separate [repository](https://github.com/trevismd/statannotations-tutorials) 
          &mdash; [First part here](https://github.com/trevismd/statannotations-tutorials/blob/main/Tutorial_1/Statannotations-Tutorial-1.ipynb),
          also as a blog post on [Medium](https://levelup.gitconnected.com/statistics-on-seaborn-plots-with-statannotations-2bfce0394c00). 
        - *In-progress* sphinx documentation in `/docs`, available on https://statannotations.readthedocs.io/en/latest/index.html
        
        ## Requirements
        
        + Python >= 3.6
        + numpy >= 1.12.1
        + seaborn >= 0.9,<0.12
        + matplotlib >= 2.2.2
        + pandas >= 0.23.0
        + scipy >= 1.1.0
        + statsmodels (optional, for multiple testing corrections)
        
        ## Contributing
        
        **Opening issues and PRs are very much welcome!** (preferably in that order).  
        In addition to git's history, contributions to statannotations are logged in
        the changelog.  
        If you don't know where to start, there may be a few ideas in opened issues or
        discussion, or something to work for the documentation.
        NB: More on [CONTRIBUTING.md](CONTRIBUTING.md)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
