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obscure_stats\n\n| | |\n| --- | --- |\n| CI/CD | [![CI](https://github.com/glevv/obscure_stats/actions/workflows/package.yml/badge.svg)](https://github.com/glevv/obscure_stats/actions/workflows/package.yml) [![CD](https://github.com/glevv/obscure_stats/actions/workflows/publish.yml/badge.svg)](https://github.com/glevv/obscure_stats/actions/workflows/publish.yml) [![Coverage](https://codecov.io/github/glevv/obscure_stats/coverage.svg?branch=main)](https://codecov.io/gh/glevv/obscure_stats) |\n| Security | [![CodeQL](https://github.com/glevv/obscure_stats/actions/workflows/codeql.yml/badge.svg)](https://github.com/glevv/obscure_stats/actions/workflows/codeql.yml) [![Dependabot](https://img.shields.io/badge/Dependabot-active-brightgreen.svg)](https://github.com/dependabot/dependabot-core) [![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/glevv/obscure_stats/badge)](https://securityscorecards.dev/viewer/?uri=github.com/glevv/obscure_stats) |\n| Package | [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/obscure_stats?logo=Python)](https://pypi.org/project/obscure_stats/) [![PyPI](https://img.shields.io/pypi/v/obscure_stats?logo=PyPI)](https://pypi.org/project/obscure_stats/) [![Downloads](https://static.pepy.tech/badge/obscure_stats)](https://pepy.tech/project/obscure_stats) |\n| Meta | [![Poetry](https://img.shields.io/endpoint?url=https://python-poetry.org/badge/v0.json)](https://python-poetry.org/) [![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff) [![Checked with mypy](https://www.mypy-lang.org/static/mypy_badge.svg)](https://mypy-lang.org/) [![License - MIT](https://img.shields.io/badge/license-MIT-9400d3.svg)](https://spdx.org/licenses/) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10206933.svg)](https://doi.org/10.5281/zenodo.10206933)\n\n## Highlights:\n\n`obscure_stats` is a small Python package that includes a lot of useful but lesser-known statistical functions and builds on top of `numpy` and `scipy`.\n\n## Current API list\n\n- Collection of measures of central tendency - `obscure_stats.central_tendency`:\n    * Contraharmonic Mean - `contraharmonic_mean`;\n    * Gastwirth's Location - `gastwirth_location`;\n    * Grenander's Mode - `grenanders_m`;\n    * Half-Sample Mode - `half_sample_mode`;\n    * Hodges-Lehmann-Sen Location - `hodges_lehmann_sen_location`;\n    * Midhinge - `midhinge`;\n    * Midmean - `midmean`;\n    * Midrange - `midrange`;\n    * Standard Trimmed Harrell-Davis Quantile - `standard_trimmed_harrell_davis_quantile`;\n    * Tau Measure of Location - `tau_location`;\n    * Trimean - `trimean`.\n- Collection of measures of dispersion - `obscure_stats.dispersion`:\n    * Coefficient of Range - `coefficient_of_range`;\n    * Coefficient of Variation - `coefficient_of_variation`;\n    * Cole's Index of Dispersion - `cole_index_of_dispersion`;\n    * Fisher's Index of Dispersion - `fisher_index_of_dispersion`;\n    * Gini Mean Difference - `gini_mean_difference`;\n    * Linear Coefficient of Variation - `coefficient_of_lvariation`;\n    * Inter-expectile Range - `inter_expectile_range`;\n    * Morisita Index of Dispersion - `morisita_index_of_dispersion`;\n    * Quartile Coefficient of Dispersion - `quartile_coefficient_of_dispersion`;\n    * Robust Coefficient of Variation - `robust_coefficient_of_variation`;\n    * Shamos Estimator - `shamos_estimator`;\n    * Standard Quantile Absolute Deviation - `standard_quantile_absolute_deviation`;\n    * Studentized Range - `studentized_range`.\n- Collection of measures of skewness - `obscure_stats.skewness`:\n    * Area Under the Skewness Curve - `auc_skew_gamma`;\n    * Bickel Mode Skewness Coefficient - `bickel_mode_skew`;\n    * Bowley Skewness Coefficient - `bowley_skew`;\n    * Cumulative Skewness Coefficient - `cumulative_skew`;\n    * Forhad-Shorna Rank Skewness Coefficient - `forhad_shorna_rank_skew`;\n    * Groeneveld Range Skewness Coefficient - `groeneveld_range_skew`;\n    * Hossain-Adnan Skewness Coefficient - `hossain_adnan_skew`;\n    * Kelly Skewness Coefficient - `kelly_skew`;\n    * Left Quantile Weight - `left_quantile_weight`;\n    * Medeen Skewness Coefficient - `medeen_skew`;\n    * Pearson Median Skewness Coefficient - `pearson_median_skew`;\n    * Pearson Mode Skewness Coefficient - `pearson_mode_skew`;\n    * Right Quantile Weight - `right_quantile_weight`.\n- Collection of measures of kurtosis - `obscure_stats.kurtosis`:\n    * Crow-Siddiqui Kurtosis Coefficient - `crow_siddiqui_kurt`;\n    * Hogg Kurtosis Coefficient - `hogg_kurt`;\n    * Moors Kurtosis Coefficient - `moors_kurt`;\n    * Moors Octile Kurtosis Coefficient - `moors_octile_kurt`;\n    * Reza-Ma Kurtosis Coefficient - `reza_ma_kurt`;\n    * Schmid-Trede measure of Peakedness - `schmid_trede_peakedness`;\n    * Staudte Kurtosis Coefficient - `staudte_kurt`.\n- Collection of measures of association - `obscure_stats.association`:\n    * Blomqvist's Beta - `blomqvist_beta`;\n    * Concordance Correlation Coefficient - `concordance_correlation`;\n    * Concordance Rate - `concordance_rate`;\n    * Fechner Correlation Coefficient - `fechner_correlation`;\n    * Gaussian Rank Correlation Coefficient - `gaussain_rank_correlation`;\n    * Morisita-Horn Similarity - `morisita_horn_similarity`;\n    * Normalized Chatterjee Xi Correlation Coefficient - `normalized_chatterjee_xi`;\n    * Quantile Correlation Coefficient - `quantile_correlation`;\n    * Rank Minrelation Coefficient - `rank_minrelation_coefficient`;\n    * Rank-Turbulence Divergence - `rank_divergence`;\n    * Symmetric Chatterjee Xi Correlation Coefficient - `symmetric_chatterjee_xi`;\n    * Tanimoto Similarity - `tanimoto_similarity`;\n    * Tukey's Correlation Coefficient - `tukey_correlation`;\n    * Winsorized Correlation Coefficient - `winsorized_correlation`;\n    * Zhang I Correlation Coefficient - `zhang_i`.\n- Collection of measures of qualitative variation - `obscure_stats.variation`:\n    * AVDev - `avdev`;\n    * B Index - `b_index`;\n    * Gibbs M1 - `gibbs_m1`;\n    * Gibbs M2 - `gibbs_m2`;\n    * McIntosh's D - `mcintosh_d`;\n    * ModVR - `mod_vr`;\n    * Negative Extropy - `negative_extropy`;\n    * RanVR - `range_vr`;\n    * Rényi entropy - `renyi_entropy`.\n\n## Installation\n\n```bash\n\u003e\u003e\u003e pip install obscure_stats\n```\n\n## Usage Example\n\n```python\n\u003e\u003e\u003e from obscure_stats.central_tendency import standard_trimmed_harrell_davis_quantile\n\u003e\u003e\u003e from obscure_stats.dispersion import standard_quantile_absolute_deviation\n\n\u003e\u003e\u003e data = [1.83, 1.01, 100.12, 1.20, 0.99, 0.87, 1.13, 100.01, 0.75, 1.03]\n\u003e\u003e\u003e central_tendency = standard_trimmed_harrell_davis_quantile(data)\n\u003e\u003e\u003e dispersion = standard_quantile_absolute_deviation(data)\n\u003e\u003e\u003e print(f\"Robust measure of central tendency = {central_tendency:.2f}±{dispersion:.2f}\")\n```\n\n```\nOut[1]:\nRobust measure of central tendency = 1.09±0.42\n```\n\n## Code of Conduct\n\nCode of Conduct for this project can be found [here](CODE_OF_CONDUCT.md).\n\n## Contributing\n\nContribution guidelines for this project can be found [here](CONTRIBUTING.md).\n\n## Security Policy\n\nSecurity Policy for this project can be found [here](SECURITY.md).\n\n## License\n\nThe content of this repository is licensed under a [MIT license](https://github.com/glevv/obscure_stats/blob/main/LICENSE.txt).\n\nThis repository bundles several libraries that are compatibly licensed. A full list can be found [here](https://github.com/glevv/obscure_stats/blob/main/LICENSES_bundled.txt).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fglevv%2Fobscure_stats","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fglevv%2Fobscure_stats","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fglevv%2Fobscure_stats/lists"}