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Statistics distributions from 265

Project description

stats265 package

A pip package which will hopefully have all the distributions from STATS265(Stats 1) - Ualberta soon

Currently:

  • Bernoulli
  • Binomial
  • Gaussian (Normal)
  • Poisson

If you are risk averse, you can try it out on a virtual environment first

Testing was done using unittest library https://docs.python.org/3/library/unittest.html

Documentation:

* Calling a distribution
    * from stats265 import Bernoulli
        * g = Bernolli(p = 0.7)
    * from stats265 import Gaussian
        * g = Gaussian(mean, stdev)
    * from stats265 import Binomial
        * g = Binomial(p = 0.7, n = 20)
    * from stats265 import Poisson
        * g = Poisson(mean)

* Methods of distributions (varies for obvious reasons)
    * read_data_file(file_name)
        reads the data in said file into our object, and now we can play around with the data

    * calculate_mean()
        calculates and returns the mean
        
    * calculate_stdev()
        calculates and returns the standard deviation of the distribution

    * plot_histogram()
        plots a histogram of the data

    * pdf(x)
        returns probability density function for a value x

    * plot_histogram_pdf()
        Plots histogram of data and pdf

    * Distribution_1 + Distribution_2 (__add__)
        Add a two distributions
            same type only for now

    * print(Distribution) (__repr__)
        Allows for representation on a print call

Installation and Dependencies:

  • Installation:

    • pip install stats265
  • Dependencies:

    • Matplotlib:
      • pip install matplotlib

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