curve-distributions 0.3
Various functions on Gaussian and Binomial distributions
License: MIT

# Curve_distributions

## Description 
This is Curve Distribution package read in data from a txt file. The txt file should have
one number (float) per line. The numbers are stored and according there are several functions 
are present:
- Gaussian Distribution
- Binomial Distribution <br>
functions includes calculating mean,standard deviation,plotting in-from of histograms,getting
probability distribution function,plotting the normalized histogram of the data and a plot of 
the probability density function along the same range,etc.
 
## Classes
- 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
- 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


## Functions
List of all the functions present that can be performed with either of the  Gaussian or Binomial
distributions 
- ```read_data_file(self,file_name)```
    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.

        Args:
            file_name (string): name of a file to read from

        Returns:
            None
 
- ```calculate_mean(self)```
    Function to calculate the mean of the data set.

        Args:
            None

        Returns:
            float: mean of the data set
- ```calculate_stdev(self, sample=True)``` 
    Function to calculate the standard deviation of the data set.

        Args:
            sample (bool): whether the data represents a sample or population

        Returns:
            float: standard deviation of the data set
- ```plot_histogram(self)```
    Function to output a histogram of the instance variable data using
        matplotlib pyplot library.

        Args:
            None

        Returns:
            None
- ```pdf(self, 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(self, 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__(self, other)```
    Function to add together two Gaussian distributions

        Args:
            other (Gaussian): Gaussian instance

        Returns:
            Gaussian: Gaussian distribution
- ```__repr__(self)```
    Function to output the characteristics of the Gaussian instance

        Args:
            None

        Returns:
            string: characteristics of the Gaussian

## Installation
- Step 1: To install the package<br>
    ```pip install curve_distributions```
- Step 2: To import the package and classes<br>
    ```from curve_distributions import Gaussian,Binomial```