snellscore 1.1.0

An Python implementation for Snell scoring

Snell Scoring Module

This module provides an implementation of the Snell scoring method for ordered categorical data. It includes functionality to compute scores based on a frequency table and standardize the results to a 0-100 scale if needed.

Installation

To use the module, clone the repository and install the necessary dependencies:

git clone [e-mail]:IgorekLoschinin/snellscore.git
cd .\snellscore
pip install -r requirements.txt

or

pip install snellscore

Usage

Import the Module

from snellscore import Snell
import pandas as pd

Prepare the Frequency Table

The input should be a pandas DataFrame where rows represent groups and columns represent categories.

# Example frequency table
data = {
    "Category1": [0, 6, 0, 0, 0, 2, 3, 0, 1, 2, 0, 5],
    "Category2": [0, 3, 0, 4, 0, 4, 4, 0, 2, 2, 0, 1],
    "Category3": [0, 1, 3, 1, 0, 3, 3, 1, 0, 2, 0, 1],
    "Category4": [3, 0, 2, 2, 0, 1, 0, 1, 0, 0, 0, 0],
    "Category5": [3, 1, 2, 4, 2, 0, 1, 1, 1, 2, 4, 1],
    "Category6": [2, 1, 4, 0, 5, 2, 1, 5, 4, 4, 1, 3],
    "Category7": [4, 0, 1, 1, 5, 0, 0, 4, 4, 0, 7, 1]
}
frequency_table = pd.DataFrame(data, index=[f"Group{item}" for item in range(1, 13)])

Initialize the Snell Object

Create an instance of the Snell class, optionally enabling score standardization.

snell = Snell(standard=True)

Run the Scoring Method

Pass the frequency table to the run method.

snell.run(frequency_table)

Retrieve the Scores

Get the calculated scores and standardized scores (if enabled):

# Get the calculated scores
scores = snell.score
print("Calculated Scores:")
print(scores)

# Get the standardized scores (0-100 scale)
standardized_scores = snell.score_standard
print("Standardized Scores:")
print(standardized_scores)

Output Example

For the example frequency table, the output might look like:

Snell Scores:
Category0   -1.072418
Category1    0.611888
Category2    1.602323
Category3    2.186739
Category4    2.837535
Category5    4.012972
Category6    5.850891
dtype: float64

Standardized Scores:
Category0      0
Category1     24
Category2     39
Category3     47
Category4     56
Category5     73
Category6    100
dtype: Int16

Testing

To run tests for the module, use pytest:

pytest tests/

References

1. https://www.icar.org/Guidelines/07.6-Functional-traits-Calving-Traits-in-Dairy-Cattle.pdf
2. https://cdnsciencepub.com/doi/pdf/10.4141/cjas77-001
3. https://www.jstor.org/stable/2528498?origin=JSTOR-pdf
4. https://github.com/pfpetrowski/rsnell

License

This project is licensed under the GNU General Public License. See the LICENSE file for details.