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statistics package

Project description

Python Versions License: GPL v3 pre-commit Language grade: Python Total alerts

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Current release info

Name Downloads Version Platforms
Conda Recipe Conda Downloads Downloads Downloads Downloads PyPI - Downloads Conda Version PyPI version Anaconda-Server Badge Conda Platforms Join the chat at https://gitter.im/Hapi-Nile/Hapi

statista - Statistics package

statista is a statistics package

statista

Main Features

  • Statistical Distributions
    • GEV
    • GUMBL
    • Normal
    • Exponential
  • Parameter estimation methods
    • Lmoments
    • ML
    • MOM
  • One-at-time (O-A-T) Sensitivity analysis.
  • Sobol visualization
  • Statistical descriptors
  • Extreme value analysis

Installing statista

Installing statista from the conda-forge channel can be achieved by:

conda install -c conda-forge statista

It is possible to list all of the versions of statista available on your platform with:

conda search statista --channel conda-forge

Install from Github

to install the last development to time you can install the library from github

pip install git+https://github.com/MAfarrag/statista

pip

to install the last release you can easly use pip

pip install statista==0.5.0

Quick start

  >>> import statista

other code samples

======= History

0.1.0 (2022-05-24)

  • First release on PyPI.

0.1.7 (2022-12-26)

  • lock numpy to version 1.23.5

0.1.8 (2023-01-31)

  • bump up versions

0.2.0 (2023-02-08)

  • add eva (Extreme value analysis) module
  • fix bug in obtaining distribution parameters using optimization method

0.3.0 (2023-02-19)

  • add documentations for both GEV and gumbel distributions.
  • add lmoment parameter estimation method for all distributions.
  • add exponential and normal distributions
  • modify the pdf, cdf, and probability plot plots
  • create separate plot and confidence_interval modules.

0.4.0 (2023-11-23)

  • add Pearson 3 distribution
  • Use setup.py instead of pyproject.toml.
  • Correct pearson correlation coefficient and add documentation .
  • replace the pdf and cdf by the methods from scipy package.

0.5.0 (2023-12-11)

  • Unify the all the methods for the distributions.
  • Use factory design pattern to create the distributions.
  • add tests for the eva module.
  • use snake_case for the methods and variables.

Project details


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