colibripy 1.0.0

The package contains statsitical tests such as one-sample, two-sample and paired t-test. Residual analysis and plotting are also supported.

Colibripy is a python package for data evaluation using statistical tools. For now, the following methods are available:

one-sample t-test

two-sample t-test

paired t-test

Examples

all : https://github.com/MMateo1120/colibripy_examples

one-sample t-test : https://github.com/MMateo1120/colibripy_examples/blob/main/t_test_one_sample.ipynb

two-sample t-test : https://github.com/MMateo1120/colibripy_examples/blob/main/t_test_two_sample.ipynb

paired t-test : https://github.com/MMateo1120/colibripy_examples/blob/main/t_test_paired.ipynb

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Installation

User installation

To install colibripy and update dependencies use pip:

pip install -U colibripy

colibripy 1.0.0 requires Python 3.12 or newer.

Dependencies

colibripy requires:

• matplotlib >= 3.9.1

• numpy >= 2.0.1

• pandas >= 2.2.2

• pytest >= 8.3.2

• scikit_learn >= 1.5.1

• scipy >= 1.14.0

• seaborn >= 0.13.2

• statsmodels >= 0.14.2

• tabulate >= 0.9.0

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Important links

• Official source code repo: https://github.com/MMateo1120/colibripy

• Download releases: https://pypi.org/project/colibripy

• Issue tracker: https://github.com/MMateo1120/colibripy/issues