patsy
latest
  • Overview
  • Quickstart
  • How formulas work
  • Coding categorical data
  • Stateful transforms
  • Spline regression
  • Model specification for experts and computers
  • Using Patsy in your library
  • Differences between R and Patsy formulas
  • Python 2 versus Python 3
  • patsy API reference
  • patsy.builtins API reference
  • Changes
patsy
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  • patsy - Describing statistical models in Python
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patsy - Describing statistical models in Python¶

Contents:

  • Overview
    • Download
    • Requirements
    • Installation
    • Contact
    • License
    • Users
  • Quickstart
  • How formulas work
    • The formula language
    • From terms to matrices
    • Technical details
    • Footnotes
  • Coding categorical data
  • Stateful transforms
    • Builtin stateful transforms
    • Defining a stateful transform
  • Spline regression
    • General B-splines
    • Natural and cyclic cubic regression splines
    • Tensor product smooths
  • Model specification for experts and computers
    • The factor protocol
    • Alternative formula implementations
  • Using Patsy in your library
    • Using the high-level interface
    • Extending the formula syntax
  • Differences between R and Patsy formulas
  • Python 2 versus Python 3
  • patsy API reference
    • Basic API
    • Convenience utilities
    • Design metadata
    • Stateful transforms
    • Handling categorical data
    • Spline regression
    • Working with formulas programmatically
    • Working with the Python execution environment
    • Building design matrices
    • Missing values
    • Linear constraints
    • Origin tracking
  • patsy.builtins API reference
  • Changes
    • v0.5.1
    • v0.5.0
    • v0.4.1
    • v0.4.0
    • v0.3.0
    • v0.2.1
    • v0.2.0
    • v0.1.0

Indices and tables¶

  • Index
  • Search Page
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© Copyright 2011-2015, Nathaniel J. Smith Revision 4c613d0a.

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