Metadata-Version: 2.1
Name: kavanaghdistributions
Version: 1
Summary: Various Functions and Methods for sample distributions
Home-page: https://github.com/BAK2K3/kavanaghdistributions
Author: Benjamin Kavanagh
Author-email: benjamin.a.kavanagh@gmail.com
License: MIT
Description: # kavanaghdistributions
        
        kavanaghdistributions is a python package for generating samples from Normal, Poisson and Binomial Distributions.
        
        ## Installation
        
        Use the package manager [pip](https://pip.pypa.io/en/stable/) to install kavanaghdistributions.
        
        ```bash
        pip install kavanaghdistributions
        ```
        
        ## Usage
        
        ```python
        from kavanaghdistributions.functions import random_draw
        from kavanaghdistributions.classes import NormalDistribution, PoissonDistribution, BinomialDistribution
        
        #random_draw function 
        
        random_draw(sample_shape=5, distribution='normal', mean=1, sd=2)
        # generates: array([1.82261281, 0.81926903, 3.06892213, 1.62636623, 2.05127246])
        
        random_draw(sample_shape=5, distribution='poisson', lam=10)
        # generates: array([12,  8,  7, 14,  8])
        
        random_draw(sample_shape=(2,2), distribution='binomial', num=2, prob=0.3)
        #generates: array([[0, 0],
        #                  [1, 0]])
        
        
        #NormalDistribution
        
        nd = NormalDistribution(mean=3, sd=1, sample_shape=5)
        nd.draw()
        #generates array([3.59149631, 3.13146966, 3.98872244, 3.59125381, 4.36412151])
        nd.summarise()
        #generates:
        #Min: 3.1314696620512454
        #Max: 4.3641215077437945
        #Mean: 3.733412745193425
        #Standard Deviation: 0.41609169604466906
        
        #PoissonDistribution
        
        pd = PoissonDistribution(lam=(2,3,2), sample_shape=[2,2,3])
        pd.draw()
        #generates:
        #array([[[0, 0, 2],
        #        [2, 1, 1]],
        #
        #       [[3, 3, 1],
        #       [2, 1, 3]]])
        pd.summarise()
        #generates:
        #Min: 0
        #Max: 3
        #Mean: 1.5833333333333333
        #Standard Deviation: 1.0374916331657276
        
        #BinomialDistribution
        
        bd = BinomialDistribution(num=4, prob=0.5, sample_shape=6)
        bd.draw()
        #generates: array([2, 3, 2, 1, 1, 1])
        bd.summarise()
        #generates: 
        #Min: 1
        #Max: 3
        #Mean: 1.6666666666666667
        #Standard Deviation: 0.74535599249993
        
        ```
        
        
        
        ## License
        [MIT](https://choosealicense.com/licenses/mit/)
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
