Updated README

README.md

@@ -1,16 +1,17 @@
+[![Test Pairwise Compare](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-wide pandas dataframe with ease.
-In this repo the capabilities of the PairwiseCompareManger 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.
-Although, most of the development efforts can be found in the `src` folder.
-Users should almost exclusively interact with the PairwiseCompareManager, however, there may be rare exceptions.
+This tool allows the user to compare groups of data specified in a tidy-wide pandas dataframe with ease.<br>
+In this repo the capabilities of the PairwiseCompareManger are shown through examples using a dataset from the [nf1_schwann_cell_painting_data](https://github.com/WayScience/nf1_schwann_cell_painting_data).<br>
+These examples can be found in the [docs](https://github.com/WayScience/pairwise_compare/tree/main/docs).<br>
+Although, most of the development efforts can be found in the `src` folder.<br>
+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.<br>
 If you choose to interact with another component of the tool, then there will be less input validation safeguards available.
 
 ## 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.
+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.<br>
+These columns are parameterized by `_same_columns` and `_different_columns`, respectively.<br>
+The column values in these columns uniquely define each group.<br>
+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.<br>
 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`:
@@ -19,11 +20,11 @@ One of the following column arguments conditions must be satisified when using t
 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` classes.
+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-wide 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` for details).
+This tool compares features between any two groups of a tidy-wide pandas dataframe.<br>
+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).