📚 Scikit-plots Documentation
0.5.dev0+git.20260824.c8953a1 - August 24, 2026 15:07 UTC

User Guide

nearest neighbor

• ANNoy
  • Vector Similarity Search
    • Vector similarity search
    • Vector database vs “vector index library”
    • Pros and cons of vector search
    • 5 practical tips
    • Open source options
    • How to choose (simple rules)
  • Index Inheritance
    • Index + mixins
    • Mixins only (independence + MRO scan)
    • Notes and Limitations
  • ANNoy Cython
  • Public Python API
  • Workflow
  • Quick start
  • Notes
  • High-level wrapper: Index
  • Mixins used by the high-level wrapper
  • Further reading
  • References

metric analysis

• Metric Performance
  • Decomposition
    • Principal Component Analysis (PCA)
  • Estimators
    • Regressor Model
    • Classifier Model
    • Cluster Model
  • Metrics
    • Regression metrics
    • Classification metrics
    • Clustering metrics

remarks citation generation

• Corpus
  • Corpus (Remarks Citation) Generation
  • Quick start

live, on demand generation

• Cython
  • Instant PKG/MOD Generation
    • Cython templates

decile-wise analysis

• Decile-Wise Performance
  • KeyToDataScience
    • kds Plots
  • ModelPlotPy
    • ModelPlotPy Plots
    • modelplotpy financial

data imputation

• Impute
  • ANNImputer
  • TL;DR
  • Overview
  • Motivation
  • Mechanism
  • Notes
  • Comparison

logging system

• Logging
  • Configuring the logging system

memory mapping

• MemMap
  • Conceptual overview
  • What this module is
  • What this module is NOT
  • Typical use cases
  • Design principles
  • Relationship to other APIs
  • Platform notes
  • Notes for developers

model context protocol

• Mcp
  • Scientific grounding: evidence, not absolute truth
  • How the pieces fit
  • At a glance
  • Choose your scenario
  • Quick start
  • Scenario 1: connect a local assistant
  • Scenario 2: test before connecting anything
  • Scenario 3: search your own documentation
  • Scenario 4: build a curated corpus
  • Scenario 5: add semantic retrieval with Annoy
  • Scenario 6: combine lexical and semantic evidence
  • Scenario 7: make CI detect the wrong corpus
  • Scenario 8: run a local HTTP endpoint
  • Scenario 9: run in Docker
  • Scenario 10: serve remote or team clients safely
  • How a documentation search works
  • Read retrieval results scientifically
  • Security by design
  • Reliable operation
  • Useful runtime controls
  • Common problems
    • The command appears to hang
    • The health check passes but search is wrong
    • My JSONL file is rejected
    • No documentation matches
    • The top result is relevant but the claim is still wrong
    • A non-local HTTP bind is refused
    • A production container rebuilds on import
  • Designed to grow without changing the basic workflow
  • Keep the user guide simple
  • Where to go next

workflow automation

• MLflow

lightweight high-performance

• Nc

data preprocessing

• Preprocessing
  • DummyCodeEncoder
  • GetDummies

random generator

• Random

seaborn based

• Seaborn
  • AUC Plot (experimental)
  • Eval Plot (experimental)
  • Decile Plot (experimental)

extended by astropy

• Stats
  • Astrostatistics Tools (experimental)
  • Tweedie Distribution (generalized family)
    • Common Applications

tensorflow keras

• Visualkeras
  • Visualkeras Visualization
  • Graphical Visualization
  • Layered Visualization
  • Visualization Helper

array api dispatching

• Array API support
  • Example usage
  • Support for Array API-compatible inputs
  • Common estimator checks

branding

• Brand
  • CLI Banner
  • Logo

Under Development

development

• C-Experimental (experimental)
• C-Externals (experimental)
• Experimental (experimental)
• Externals (experimental)
• Externals (experimental)