Metadata-Version: 2.1
Name: gauss-binomial-mp99
Version: 0.1.3
Summary: Gaussian and Binomial distributions
Home-page: https://github.com/manan-paneri-99/gauss-binomial-mp99
Author: Manan Paneri
Author-email: mananpaneri28@gmail.com
License: UNKNOWN
Description: # gauss-binomial-mp99 package
        
        The package contains methods for performing computations pertaining to Guassian and Binomial distributions.
        
        # 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.
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
