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Collection of lesser-known statistical functions

Project description

obscure_stats

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Highlights:

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.

Current API list

  • Collection of measures of central tendency - obscure_stats/central_tendency:
    • Contraharmonic Mean;
    • Half-Sample Mode;
    • Hodges-Lehmann-Sen Location;
    • Midhinge;
    • Midmean;
    • Midrange;
    • Standard Trimmed Harrell-Davis Quantile;
    • Trimean.
  • Collection of measures of dispersion - obscure_stats/dispersion:
    • Coefficient of Variation;
    • Dispersion Ratio;
    • Linear Coefficient of Variation;
    • Lloyds Index;
    • Morisita Index;
    • Quartile Coefficient of Dispersion;
    • Robust Coefficient of Variation;
    • Shamos Estimator;
    • Standard Quantile Absolute Deviation;
    • Studentized Range.
  • Collection of measures of skewness - obscure_stats/skewness:
    • Area Under the Skewness Curve (weighted and unweighted);
    • Bickel Mode Skewness Coefficient;
    • Bowley Skewness Coefficient;
    • Forhad-Shorna Rank Skewness Coefficient;
    • Groeneveld Skewness Coefficient;
    • Hossain-Adnan Skewness Coefficient;
    • Kelly Skewness Coefficient;
    • L-Skewness;
    • Medeen Skewness Coefficient;
    • Pearson Median Skewness Coefficient;
    • Pearson Mode Skewness Coefficient.
  • Collection of measures of kurtosis - obscure_stats/kurtosis:
    • Crow-Siddiqui Kurtosis;
    • L-Kurtosis;
    • Hogg Kurtosis;
    • Moors Kurtosis;
    • Moors Octile Kurtosis;
    • Reza-Ma Kurtosis.
  • Collection of measures of association - obscure_stats/association:
    • Chatterjee Xi correlation Coefficient (original and symmetric versions);
    • Concordance Correlation Coefficient;
    • Concordance Rate;
    • Tanimoto Similarity;
    • Zhang I Correlation Coefficient.
  • Collection of measures of qualitative variation - obscure_stats/variation:
    • AVDev;
    • B Index;
    • Extropy;
    • Gibbs M1;
    • Gibbs M2;
    • ModVR;
    • RanVR.

Installation

pip install obscure_stats

Usage Example

>>> from obscure_stats.central_tendency import standard_trimmed_harrell_davis_quantile
>>> from obscure_stats.dispersion import standard_quantile_absolute_deviation

>>> data = [1.83, 1.01, 100.12, 1.20, 0.99, 0.87, 1.13, 100.01, 0.75, 1.03]
>>> central_tendency = standard_trimmed_harrell_davis_quantile(data)
>>> dispersion = standard_quantile_absolute_deviation(data)
>>> print(f"Robust measure of central tendency = {central_tendency:.2f}, Robust measure of dispersion = {dispersion:.2f}")
Out[1]:
Robust measure of central tendency = 1.09, Robust measure of dispersion = 0.42

Code of Conduct

This projects adopts Python Software Foundation Code of Conduct, please read it here.

License

The content of this repository is licensed under a MIT license.

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