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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

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