The Data Utils library is a versatile Python toolkit designed to streamline common data-related tasks and enhance the efficiency of your projects. It is intended to be a reusable and easily integratable solution for handling various aspects of data processing, cleaning, and analysis.

To use the Data Utils library in your projects, follow the steps below:

Make sure you have Poetry installed on your system. You can install Poetry by following the instructions on the official Poetry website.

Run the following command to install the project dependencies using Poetry:

poetry install

This will create a virtual environment and install the required dependencies specified in the pyproject.toml file.

If you want to create a distributable package or build for your Data Utils library, you can use the following Poetry command:

poetry build

DfCounter is a Python class designed to help you analyze and count duplicates in a Pandas DataFrame based on specified columns.

To use the functionality provided by DfCounter, follow the example below or use the main.py file.:

import pandas as pd
from data_utils.duplication import DfCounter


if __name__ == '__main__':
    test_df = pd.DataFrame(data=[
        ['A', 'a', 'x', 1],
        ['A', 'b', 'x', 1],
        ['A', 'c', 'x', 1],
        ['B', 'a', 'x', 1],
        ['B', 'b', 'x', 1],
        ['B', 'c', 'x', 1],
        ['A', 'a', 'y', 1],
    ],
        columns=['col1', 'col2', 'col3', 'col4']
    )
    test_cols = ['col1']
    counter = DfCounter(test_df, test_cols)

    print(counter.duplicates_stats())