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dsldPy — Python Interface to DSLD

Statistical and graphical tools for detecting and measuring discrimination and bias in datasets, Python interfaces available via rpy2. dsldPy wraps the R package dsld with a Python-friendly API using the same underlying R implementations.

Relevant links:

• Quarto Book: Paper - Important statistical principles and applications.
• Research Paper: Paper - Package implementation details.

Overview

DSLD addresses two main types of bias analysis:

• Estimation analysis: quantify possible discrimination by estimating effects of a sensitive variable S on an outcome Y, while adjusting for confounders C.

• Prediction analysis (fair ML): build predictive models that limit the influence of S and its proxies O, trading off fairness and utility.

dsldPy provides wrappers for all 24 R functions.

Prerequisites

• R installed and on PATH (R 4.x recommended)
• R package dsld installed (CRAN or GitHub)
• Python 3.8+

Install dsld in R:

install.packages("dsld")

## or latest development version
# install.packages("remotes")
remotes::install_github("matloff/dsld", force = TRUE)

Tip: Ensure rpy2 can find R. From a terminal: R RHOME should print your R home. If Python cannot find R, set R_HOME in your environment per rpy2’s documentation.

Installation

Install the Python package from this repository (subdirectory inst):

pip install dsldPy

This will install dsldPy and its Python dependencies (pandas, numpy, rpy2, etc.). The user still needs to manually download R and the dsld package, as noted above.

Quickstart

Please refer to the instructional jupyter notebooks provided under examples/ folder. These illustrate examples of all 24 dsldPy functions.

Jupyter notebooks are available in this repository:

• inst/examples/graphical.ipynb
• inst/examples/tabular.ipynb
• inst/examples/machine_learning.ipynb

Available Wrappers

• Analytical: dsldPyLinear, dsldPyLogit, dsldPyML, dsldPyMatchedATE, dsldPyTakeALookAround, dsldPyConfounders, dsldPyCHunting, dsldPyOHunting

• Fair ML: dsldPyFrrm, dsldPyFgrrm, dsldPyNclm, dsldPyZlm, dsldPyZlrm, dsldPyQeFairKNN, dsldPyQeFairRF, dsldPyQeFairRidgeLin, dsldPyQeFairRidgeLog, , dsldPyFairUtils

• Graphical: dsldPyFreqPCoord, dsldPyScatterPlot3D, dsldPyConditDisparity, dsldPyDensitybyS, dsldPyFrequencybyS, dsldPyIamb

Function names mirror the R package. Arguments use standard Python types (pandas.DataFrame, dict, bool, etc.) with the same call forms as the R functions.

Troubleshooting

• rpy2 cannot find R: confirm R RHOME works; if not, add R to PATH or set R_HOME. See rpy2 docs for your OS.
• dsld not installed in R: run install.packages("dsld") in an R session.

Authors

• Norm Matloff
• Aditya Mittal
• Taha Abdullah
• Arjun Ashok
• Shubhada Martha
• Billy Ouattara
• Jonathan Tran
• Brandon Zarate

For issues, contact Aditya Mittal at mittalaa@uci.edu

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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