Patsy

1.0.2 · maintenance · verified Sun Mar 29

Patsy is a Python package for describing statistical models and for building design matrices, bringing R-style formulas to Python. The current version is 1.0.2. While no new feature development is planned, it maintains a maintenance cadence to ensure compatibility with current releases in the Python ecosystem.

Warnings

breaking Python 2.7 support was dropped in version 1.0.0. Projects still on Python 2 must use an older version of Patsy.
Fix: Upgrade to Python 3 or pin `patsy<1.0.0`.
gotcha Patsy automatically adds an intercept term and uses treatment coding for categorical variables (dropping one level). If you need to include all levels or omit the intercept, adjust your formula accordingly (e.g., `y ~ x1 + C(a) - 1` to remove intercept and explicitly code `a`).
Fix: Use `- 1` in the formula to remove the intercept, or `C(variable, contr.treatment)` for explicit coding options.
gotcha The `NA_action='drop'` is the default for `dmatrix` and `dmatrices`, which means rows containing any missing values will be silently dropped. This can lead to unexpected data loss if not anticipated.
Fix: Explicitly set `NA_action='raise'` to catch missing values or implement custom handling before calling Patsy functions.
gotcha Operators like `**` in Patsy formulas are interpreted as interaction effects, not Python's power operator. Use `I()` (identity function) to force Python's interpretation (e.g., `I(x**2)`).
Fix: Wrap expressions meant for literal Python evaluation in `I()`, like `I(x**2)`.
gotcha Patsy fixed compatibility issues with `numpy >= 2` in version 1.0.0. Older versions might not work correctly with newer NumPy.
Fix: Upgrade to `patsy>=1.0.0` if using `numpy>=2`.
gotcha Patsy fixed compatibility with Pandas 3's new `StringDtype` in version 1.0.2. Older versions may encounter issues with Pandas 3.
Fix: Upgrade to `patsy>=1.0.2` if using `pandas>=3`.
deprecated The project is explicitly stated as 'no longer under active development' for new features, with 'Formulaic' identified as its spiritual successor. For new projects, considering Formulaic might be beneficial.
Fix: Consider migrating to 'Formulaic' for new projects, while existing projects can continue to use Patsy for maintenance.

Install

pip install patsy Install stable version

Imports

dmatrix
```
from patsy import dmatrix
```
dmatrices
```
from patsy import dmatrices
```
demo_data
```
from patsy import demo_data
```
A utility function for quick examples and testing.

Quickstart

This quickstart demonstrates how to use `patsy.dmatrices` to generate design matrices from a formula string and a dictionary-like data source. It automatically handles categorical variables and adds an intercept term.

import numpy as np
from patsy import dmatrices, demo_data

# Create example data
data = demo_data("a", "b", "x1", "x2", "y")

# Generate design matrices for a linear model
y, X = dmatrices("y ~ x1 + x2 + a", data=data)

print("Dependent variable (y):")
print(y)
print("\nIndependent variables (X):")
print(X)

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