pairwise-compare 0.1.3
Allows the user to compare groups of data specified in a tidy pandas dataframe with ease.
License: BSD 3-Clause
Requires Python: <3.13,>=3.10

[![Tests](https://github.com/WayScience/pairwise_compare/actions/workflows/python-app.yml/badge.svg)](https://github.com/WayScience/pairwise_compare/actions/workflows/python-app.yml)
# Pairwise Compare
This tool allows the user to compare groups of data specified in a [tidy](https://tidyr.tidyverse.org/articles/tidy-data.html) pandas dataframe with ease.
In this repo the capabilities of the PairwiseCompareManager are shown through examples using a dataset from the [nf1_schwann_cell_painting_data](https://github.com/WayScience/nf1_schwann_cell_painting_data).
These examples can be found in the [docs](https://github.com/WayScience/pairwise_compare/tree/main/docs).
Although, most of the development efforts can be found in the `src` folder.
Users should almost exclusively interact with the [PairwiseCompareManager](https://github.com/WayScience/pairwise_compare/blob/main/src/comparison_tools/PairwiseCompareManager.py), however, there may be rare exceptions.
If you choose to interact with another component of the tool, then there will be less input validation safeguards available.

## Installation
For Python versions 3.10 through 3.12 (inclusive), you can install this tool with either of the following commands:<br>
`pip install pairwise-compare`<br>
`pip install git+https://github.com/WayScience/pairwise_compare.git`<br>
<br>
Note it is highly recommended to use a package manager such as Conda to install this tool.<br>
Once installed you can use subtools such as the `PairwiseCompareManager` with:<br>
`from comparison_tools.PairwiseCompareManager import PairwiseCompareManager`

## Data Formats
When passing arguments to the `PairwiseCompareManager` you can specify the columns that remain the same in each group-to-group comparison, and the columns that will be different in these comparisons.
These columns are parameterized by `_same_columns` and `_different_columns`, respectively.
The column values in these columns uniquely define each group.
During pairwise comparisons of groups, all of the column values of the columns specified in `_same_columns` will be the same between both groups compared for all paired combinations of groups.
Likewise, all of the column values of the columns specified in `_different_columns` will be different between both groups compared for all paired combinations of groups.

One of the following column arguments conditions must be satisified when using the `PairwiseCompareManager`:
1. `_same_columns` must include at least one list element if `_different_columns` has less than two list elements.
2. `_different_columns` must contain one or more list elements.
3. `_same_columns` and `_different_columns` should not contain any of the same columns.

## Limitations
1. Input validation is enforced in the `PairwiseCompareManager` and [PairwiseCompare](https://github.com/WayScience/pairwise_compare/blob/main/src/comparison_tools/PairwiseCompare.py) classes.
2. Additional column values are not tracked aside from columns used to compare groups (_same_columns, _different_columns).
3. Output and input python data structures are limited.
4. All of the data, in the supplied pandas dataframe, is used to compute comparisons.

## Extensibility
This tool compares features between any two groups of a tidy pandas dataframe.
To incorporate additional comparators for making comparisons, you must introduce the functionality as a class and inherit from the `Comparator` class (See [Comparator.py](https://github.com/WayScience/pairwise_compare/blob/main/src/comparators/Comparator.py) for details).