Metadata-Version: 1.0
Name: mango_coding_test_pl_sept20
Version: 2.0.0
Summary: Solutions to Mango's Python Coding Test
Home-page: UNKNOWN
Author: UNKNOWN
Author-email: UNKNOWN
License: UNKNOWN
Description: # mango_test
        
        Package containing Peter Ling's solutions to the Mango Python coding test, September 2020.
        
        ## Installation
        
        The package can be installed from PyPI via the command line by typing
        `pip install mango_coding_test_pl_sept20`.
        
        ## Usage
        
        The solutions can then be used in a Python 3 environment after using the import statement
        `from mango_test import mango_test as mt`
        
        #### Functions
        The 'Functions' part of the exercise is called with the `random_draw(nsamples, dist, **params)` function, where `params` relate to the given distribution.
        
        ##### Examples
        To return a 10 random samples (as a numpy array) from a Normal distribution with mean 100 and standard deviation 10:
        
            mt.random_draw(10, 'normal', mean=100, sd=10)
        
        To return a 20 random samples from a Binomial distribution with _n_=100, _p_=0.5:
        
            mt.random_draw(20, 'binomial', n=100, p=0.5)
        
        To return a 100 random samples from a Poisson distribution with $\lambda$=100:
        
            mt.random_draw(100, 'poisson', lam=100)
        
        #### Object-oriented Programming
        The 'Object-oriented Programming' part of the exercise is called with the `Sample` class.
        
        ##### Example
        To create an instance of the `Sample` class, using the Normal distribution:
        
            s = mt.Sample('normal')
        
        To set the parameters of `s` (mean and standard deviation):
        
            s.mean = 100
            s.sd = 100
        
        To draw a 1000 samples from `s`, then summarise:
        
            s.draw(1000)
            s.summarise()
         
Platform: UNKNOWN
