deoga-distributions 0.4

Mathematical distributions

MATHEMATICAL DISTRIBUTION ANALYSER

Analyse distributions inlcuding their mean, standard deviation and plots. The below distributions can be analysed in this package:

• Binomial distribution
• Gassian distribution
• General distribution

Installation

Run the following code in your terminal pip install deoga_distribtions

Understanding the package

Generaldistribution.py - Initiates distribution class and contains the formulas(mu,sigma) for general distributions and reads file data using the read_data_file method. Gaussiandistribution.py - Inherits distribution class and contains the following methods *calculate_mean - Calculate the mean of a Gaussian distribution *calculate_stdev - Calculate the standard deviation of a Gaussian distribution *plot_histogram - Plot the Gaussian distribution *pdf - Calculate the probablility density function of the Gaussian distribution *plot_histogram_pdf - Plot a histogram of the probability density function of the gaussian distribution *__add__ - Add two Gaussians together *__repr__ - Print characteristics of Gaussian distribution

Binomialdistribution.py - Inherits distribution class and contains the following methods *calculate_mean - Calculate the mean of a Binomial distribution *calculate_stdev - Calculate the standard deviation of a Binomial distribution *replace_stats_with_data - replace hardcoded statistics with binomial data *plot_bar - Plot bar graph of the Binomial distribution *pdf - Calculate the probablility density function of the Binomial distribution *plot_bar_pdf - Plot a bar of the probability density function of the Binomail distribution *__add__ - Add two Binomials together *__repr__ - Print characteristics of Binomial distribution

Usage

Run scripts in a python compiler

Quick Tests

Some tests to check if package is working is to run the following in a python code executer from deoga_distributions import Gaussian, Binomial Gaussian(10, 7) Binomial(0.4, 16)

You should get a returned string describing the distribution characteristics with no errors.

Extending this

If you want to extend this work, here are a few places to start:

• Add new models to the distribution
• Add new plots to the models
• Add new statisticals analytical methods to the distributions

Credits

Lead Developer - Deoga Kofi