pycvcqv

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Find homogeneity with confidence.

Python port of cvcqv

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Introduction

pycvcqv provides some easy-to-use functions to calculate the Coefficient of Variation (cv) and Coefficient of Quartile Variation (cqv) with confidence intervals provided with all available methods.

Install

pip install pycvcqv

Usage

import pandas as pd
from pycvcqv import coefficient_of_variation, cqv

coefficient_of_variation(
    data=[
        0.2, 0.5, 1.1, 1.4, 1.8, 2.3, 2.5, 2.7, 3.5, 4.4,
        4.6, 5.4, 5.4, 5.7, 5.8, 5.9, 6.0, 6.6, 7.1, 7.9
    ],
    multiplier=100,
    ndigits=2
)
# {'cv': 57.77, 'lower': 41.43, 'upper': 98.38}
cqv(
    data=[0.2, 0.5, 1.1, 1.4, 1.8, 2.3, 2.5, 2.7, 3.5, 4.4, 4.6, 5.4, 5.4],
    multiplier=100,
)
# 51.7241
data = pd.DataFrame(
    {
        "col-1": pd.Series([0.2, 0.5, 1.1, 1.4, 1.8, 2.3, 2.5, 2.7, 3.5]),
        "col-2": pd.Series([5.4, 5.4, 5.7, 5.8, 5.9, 6.0, 6.6, 7.1, 7.9]),
    }
)
coefficient_of_variation(data=data, num_threads=3)
#   columns      cv      lower      upper
# 0   col-1  0.6076     0.3770     1.6667
# 1   col-2  0.1359     0.0913     0.2651
cqv(data=data, num_threads=-1)
#   columns      cqv
# 0   col-1  0.3889
# 1   col-2  0.0732

Credits

This project was generated with python-package-template