Metadata-Version: 2.1
Name: ProfessorRegressor
Version: 1.1
Summary: Statistical python model for comparison of species using pairwise regression
Home-page: https://github.com/chdwck9/professorRegressor
Author: Susan & Richard Dykes
Author-email: chdwck9@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.0

# professorRegressor
Statistical python model for comparison of species using pairwise regression.

### Usage
It's import to provide PR with a 2xn pandas matrix where the first column contains a categorical variable, like the species or the specimens that your study wishes to compare, and the second containing non-null numerical observations relating to the first variable.

You need at least 2 observations per specimen/species and more will provide greater statistical accuracies.

Note: at the time of first publication, there are no failsafes for null values in the dataset. Please remove these as part of pre-processing.

To install, use pip:
pip install professorRegressor

To use in your program, first initialise by passing your pandas dataset. Thereafter you can export using the getDataFrame method. Here is an example:

import professorRegressor
pr = professorRegressor(iris)
pr_df = pr.getDataFrame()

