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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -5,7 +5,7 @@
grplot: lazy statistical data visualization
=======================================

[![PyPI Version](https://img.shields.io/pypi/v/grplot.svg)](https://pypi.org/project/grplot/) [![License](https://img.shields.io/pypi/l/grplot.svg)](https://github.com/ghiffaryr/grplot/blob/master/LICENSE.md) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.17159965.svg)](https://doi.org/10.5281/zenodo.17159965) [![Anaconda-Server Badge](https://anaconda.org/conda-forge/grplot/badges/latest_release_date.svg)](https://anaconda.org/conda-forge/grplot) [![PyPI Downloads](https://static.pepy.tech/personalized-badge/grplot?period=total&units=INTERNATIONAL_SYSTEM&left_color=BLACK&right_color=GREEN&left_text=downloads)](https://pepy.tech/projects/grplot) ![Coverage Badge](https://gist.githubusercontent.com/ghiffaryr/8fce7554f72160b59527bd0deecf7666/raw/coverage-badge.svg?sanitize=true)
[![PyPI Version](https://img.shields.io/pypi/v/grplot.svg)](https://pypi.org/project/grplot/) [![License](https://img.shields.io/pypi/l/grplot.svg)](https://github.com/ghiffaryr/grplot/blob/master/LICENSE) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.17159965.svg)](https://doi.org/10.5281/zenodo.17159965) [![Anaconda-Server Badge](https://anaconda.org/conda-forge/grplot/badges/latest_release_date.svg)](https://anaconda.org/conda-forge/grplot) [![PyPI Downloads](https://static.pepy.tech/personalized-badge/grplot?period=total&units=INTERNATIONAL_SYSTEM&left_color=BLACK&right_color=GREEN&left_text=downloads)](https://pepy.tech/projects/grplot) ![Coverage Badge](https://gist.githubusercontent.com/ghiffaryr/8fce7554f72160b59527bd0deecf7666/raw/coverage-badge.svg?sanitize=true)


grplot is a Python visualization library based on numpy, scipy, matplotlib, seaborn, squarify, pandas, and ipython. It supports human laziness in drawing complete and attractive statistical graphs in just one function.
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2 changes: 1 addition & 1 deletion docs/plots/boxenplot.rst
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Expand Up @@ -51,7 +51,7 @@ Draw an enhanced box plot for larger datasets.
Method to use for the width of the letter value boxes: - "exponential": Represent the corresponding percentile - "linear": Decrease by a constant amount for each box - "area": Represent the density of data points in that box

``k_depth`` *(str or int, default: 'tukey')*
The number of levels to compute and draw in each tail: - "tukey": Use log2(n) - 3 levels, covering similar range as boxplot whiskers - "proportion": Leave approximately outlier_prop fliers - "trusthworthy": Extend to level with confidence of at least trust_alpha - "full": Use log2(n) + 1 levels and extend to most extreme points
The number of levels to compute and draw in each tail: - "tukey": Use log2(n) - 3 levels, covering similar range as boxplot whiskers - "proportion": Leave approximately outlier_prop fliers - "trustworthy": Extend to level with confidence of at least trust_alpha - "full": Use log2(n) + 1 levels and extend to most extreme points

``outlier_prop`` *(float, default: 0.007)*
Proportion of data expected to be outliers; used when k_depth="proportion".
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