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
- https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/
- https://mothergeo-py.readthedocs.io/en/latest/development/how-to/venv-win.html
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
- Matplotlib:
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