Data Science Utils

Data Science Utils extends the Scikit-Learn API and Matplotlib API to provide simple methods that simplify tasks and visualizations for data science projects.

Contents:

• Installation Guide
  • 1. Install from PyPI (Recommended)
  • 2. Install from Source
  • 3. Install using Anaconda
  • Note on Dependencies
  • Staying Updated
• Math Utils
  • Safe Percentile
• Metrics
  • Plot Confusion Matrix
  • Plot Metric Growth per Labeled Instances
  • Visualize Accuracy Grouped by Probability
  • Receiver Operating Characteristic (ROC) Curve with Probabilities (Thresholds) Annotations
  • Precision-Recall Curve with Probabilities (Thresholds) Annotations
• Preprocess
  • Visualize Feature
  • Get Correlated Features
  • Visualize Correlations
  • Plot Correlation Dendrogram
  • Plot Features’ Interaction
  • Extract Statistics DataFrame per Label
  • Compute Mutual Information
• Strings
  • Append Tags to Frame
  • Significant Terms
• Unsupervised
  • Plot Cluster Cardinality
  • Plot Cluster Magnitude
  • Magnitude vs. Cardinality
  • Optimum Number of Clusters
• XAI (Explainable AI)
  • Draw Tree
  • Draw Dot Data
  • Generate Decision Paths
  • Plot Feature Importance
• Contributing
  • How to Contribute
  • Coding Guidelines
  • Getting Help
  • Why Contribute?

Indices and tables

• Index

• Search Page