gauss-binomial-mp99

Python package for calculating and visualizing Gaussian and Binomial distributions. The package contains methods for performing computations pertaining to Guassian and Binomial distributions.

Link to the PyPI project: https://pypi.org/project/gauss-binomial-mp99/

Installation

$ pip install gauss-binomial-mp99

Files

Generaldistribution.py

The parent class, contains __init__ and read_data_file methods.

Import:

>>> from gauss_binomial_mp99 import Gaussian, Binomial
>>> gauss = Gaussian()
>>> gauss.read_data_file('sample.txt') 

Gaussiandistribution.py

Gaussian distribution class for calculating and visualizing a Gaussian distribution. Methods to compute Gaussian distribution features include-

• calculate_mean(): Function to calculate the mean of the data set.
• calculate_stdev(): Function to calculate the standard deviation of the data set.
• plot_histogram(): Function to output a histogram of the instance variable data using matplotlib pyplot library.
• pdf(x): Probability density function calculator for the gaussian distribution.
• plot_histogram_pdf: Function to plot the normalized histogram of the data and a plot of the probability density function along the same range

Default: mu= 0 and sigma=1 Form: guass(mu, sigma)

Example:

>>> gauss.calculate_mean()
78.0909090909091
>>> gauss.calculate_stdev()
92.87459776004906

Provides the functionality of adding two Gaussian distribution objects.

Binomialdistribution.py

Binomial distribution class for calculating and visualizing a Binomial distribution. Methods to compute Gaussian distribution features include-

• calculate_mean(): Function to calculate the mean from p= probability and n= size
• calculate_stdev(): Function to calculate the standard deviation from p and n.
• plot_bar(): Function to output a histogram of the instance variable data using matplotlib pyplot library.
• pdf(x): Probability density function calculator for the gaussian distribution.
• plot_bar_pdf: Function to plot the pdf of the binomial distribution.

Default: p= 0.5 and n=20 Form: bin(p, n)

>>> bin= Binomial(.45, 78)
>>> bin.pdf(34)
0.08798942891783665

Provides the functionality of adding two Binomial distribution objects with the same probablity.