Metadata-Version: 2.1
Name: statannot
Version: 0.2.3
Summary: add statistical annotations on an existing boxplot/barplot generated by seaborn.
Home-page: https://github.com/webermarcolivier/statannot
Author: Marc Weber
Author-email: webermarcolivier@gmail.com
License: UNKNOWN
Description: ## What is it
        
        Python package to optionnally compute statistical test and add statistical annotations on an existing boxplot/barplot generated by seaborn.
        
        ## Features
        
        - Single function to add statistical annotations on an existing boxplot/barplot generated by seaborn boxplot.
        - 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
        - Smart layout of multiple annotations with correct y offsets.
        - Annotations can be located inside or outside the plot.
        - Format of the statistical test annotation can be customized: star annotation, simplified p-value, or explicit p-value.
        - Optionally, custom p-values can be given as input. In this case, no statistical test is performed.
        
        ## Installation
        
        The latest stable release can be installed from PyPI:
        
        ```python
        pip install statannot
        ```
        You may instead want to use the development version from Github:
        
        ```python
        pip install git+https://github.com/webermarcolivier/statannot.git
        ```
        
        ## Documentation
        
        See example jupyter notebook `example/example.ipynb`.
        
        ## Usage
        
        Here is a minimal example:
        
        ```python
        import seaborn as sns
        from statannot import add_stat_annotation
        
        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)
        test_results = add_stat_annotation(ax, data=df, x=x, y=y, order=order,
                                           box_pairs=[("Thur", "Fri"), ("Thur", "Sat"), ("Fri", "Sun")],
                                           test='Mann-Whitney', text_format='star',
                                           loc='outside', verbose=2)
        test_results
        ```
        
        More examples are available in the jupyter notebook `example/example.ipynb`.
        
        
        ## Examples
        
        ![Example 1](/example/example_non-hue_outside.png)
        
        ![Example 2](/example/example_hue_layout.png)
        
        ## Requirements
        
        + Python >= 3.5
        + numpy >= 1.12.1
        + seaborn >= 0.8.1
        + matplotlib >= 2.2.2
        + pandas >= 0.23.0
        + scipy >= 1.1.0
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.5
Description-Content-Type: text/markdown
