mlnd-distributions 1.0
Gaussian and Binomial distributions

# MLND-distributions package

This package provides the Gaussian distribution and Binomial distribution classes.

* Gaussian - Gaussian distribution class for calculating and visualizing a Gaussian distribution.
Attributes:
		mean (float) - representing the mean value of the distribution.
		stdev (float) - representing the standard deviation of the distribution.
		data_list (list of floats) - a list of floats extracted from the data file.

Methods:
		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.
		read_data_file(filename) - Function to read in data from a txt file. The txt file should have one number (float) per line. The numbers are stored in the data attribute.
		pdf(x) - Probability density function calculator for the gaussian distribution
			Args:
				x (float): point for calculating the probability density function
			Returns:
				float: probability density function output
		plot_histogram_pdf(n_spaces = 50) - Function to plot the normalized histogram of the data and a plot of the probability density function along the same range
			Args:
				n_spaces (int): number of data points
			Returns:
				list: x values for the pdf plot
				list: y values for the pdf plot
		__add__(other) - Function to add together two Gaussian distributions
		Args:
			other (Gaussian): Gaussian instance
		Returns:
			Gaussian: Gaussian distribution
 		__repr__() - Function to output the characteristics of the Gaussian instance


* Binomial - Binomial distribution class for calculating and visualizing a Binomial distribution.
 Attributes:
		mean (float) representing the mean value of the distribution
		stdev (float) representing the standard deviation of the distribution
		data_list (list of floats) a list of floats to be extracted from the data file
		p (float) representing the probability of an event occurring
		n (int) number of trials

Methods:
		calculate_mean() - Function to calculate the mean from p and n.
		calculate_stdev() - Function to calculate the standard deviation from p and n.
		read_data_file(filename) - Function to read in data from a txt file. The txt file should have one number (float) per line. The numbers are stored in the data attribute.
		replace_stats_with_data() - Function to calculate p and n from the data set
		Args:
			None
		Returns:
			float: the p value
			float: the n value
		plot_bar() - Function to output a histogram of the instance variable data using matplotlib pyplot library.
		pdf(k) - Probability density function calculator for the gaussian distribution.
		Args:
			x (float): point for calculating the probability density function
		Returns:
			float: probability density function output
		plot_bar_pdf() - Function to plot the pdf of the binomial distribution
		Args:
			None
		Returns:
			list: x values for the pdf plot
			list: y values for the pdf plot
		__add__(other) - Function to add together two Binomial distributions with equal p
		Args:
			other (Binomial): Binomial instance
		Returns:
			Binomial: Binomial distribution
		__repr__() - Function to output the characteristics of the Binomial instance.



# Files
* Generaldistribution.py - contains Distribution class, its attributes and methods being inherited by Gaussian and Binomial class.
* Gaussiandistribution.py - contains Gaussian class, its attributes and methods stated above in udc-dsnd-distributions package summary.
* Binomialdistribution.py - contains Binomial class, its attributes and methods stated above in udc-dsnd-distributions package summary.

# Installation
* The code should run with no issues using Python versions 3.*.
* No extra besides the built-in libraries from Anaconda needed to run this project
		Math
		matplotlib