Distributions-Package

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This package has functionality for different types of distribution frameworks. There is currently has functionality for Binomial and Guassian distributions.

Uploaded on pypi.org as part of an exercise for Udacity Machine Learning Engineer Nanodegree Program (Part 1).

Install:

pip install distributions_tl

Steps to upload to pypi

1. Create all relevant files and folders
   • setup.py file
   • distributions_tl folder
   • Distribution.py
   • Binomial.py
   • Gaussian.py
   • __ init__.py (import Gaussian and Binomial)
   • license.txt (Opensource - MIT license)
   • README.md
   • setup.cfg (state name of README)
2. In terminal go to relevant folder with setup.py

   cd Udacity_ML
   

3. Create virtual environment and activate

   python -m venv ml_venv
   ./ml_venv/Scripts/activate
   

4. Install package locally

   pip install .
   

5. Check it runs in python terminal ((ANS: mean 10, standard deviation 7)

   python
   from distributions_tl import Gaussian, Binomial
   Gaussian(10,7)
   

6. Upload to test.pypi cd Udacity_ML python setup.py sdist pip install twine twine upload --repository-url https://test.pypi.org/legacy/ dist/*

7. Install locally and then repeat step 5

   pip install --index-url https://test.pypi.org/simple/ dsnd-probability
   

8. Upload to pypi repository

   twine upload dist/*
   

About package

Distribution()

Attributes:

• mean
• standard deviation
• list of data

Methods:

• read_data_file(file_name): given a file of numbers, reads in data to create list of numbers

Binomial(Distribution)

Attributes:

• Distribution attributions
• probability
• size

Methods:

• calculate_mean(): assigns and returns the mean
• calculate_stdev(): assigns and returns the mean
• replace_stats_with_data(): assign prob, size, mean, stdev
• plot_bar(): plot bar graph of data
• pdf(k): Calculate the probability density
• plot_bar_pdf(): Plot bar graph of the pdf
• add(other): override +
• repr(): override print()

Gaussian(Distribution)

Attributes:

• Distribution attributes

Methods:

• calculate_mean(): assigns and returns the mean
• calculate_stdev(): assigns and returns the mean
• plot_histogram(): plot histogram of data
• pdf(x): Calculate the probability density
• plot_histogram_pdf(n_spaces): Plot histogram of the pdf
• add(other): override +
• repr(): override print()