optimask: Data Masking Optimization Package

optimask is a Python package that provides tools for optimizing data masking strategies based on NaN values in a given data array or DataFrame. The package contains the OptiMask class, which facilitates the arrangement of NaN values to remove rows and columns from the input data while maximizing the data coverage.

Installation

You can install optimask using pip:

pip install optimask

Usage

Import the OptiMask class from the optimask package and use its methods to optimize data masking:

from optimask import OptiMask
import numpy as np

# Create a sample data array with NaN values
data = np.array([[1, 2, np.nan],
                 [4, np.nan, 6],
                 [7, 8, 9]])

# Solve the optimization problem
optimized_rows, optimized_cols = OptiMask.solve(data)

# Print the optimized rows and columns
print("Optimized Rows:", optimized_rows)
print("Optimized Columns:", optimized_cols)

Contributing

Contributions to optimask are welcome! If you find a bug, have a feature request, or want to contribute code, please feel free to open an issue or submit a pull request.