DataStories SDK Documentation 1.8

• Installation
  • Prerequisites
  • Optional dependencies
  • Procedure
  • Jupyter Notebook
• SDK Reference
  • General Interfaces
    • get_version()
    • Base classes and interfaces
    • Errors
    • Constants and Enumerations
  • License Management
    • get_activation_info()
    • LicenseManager
    • License
  • Data
    • Base Classes
    • Data Frame Preparation
    • Summary Calculation
    • Outlier Detection
  • Classification
    • Feature Ranking
  • Correlation
    • compute_correlations()
    • CorrelationResult
    • Prototype Detection
  • Model
    • Base Classes
    • Prediction
  • Optimization
    • create_optimizer()
    • Optimizer
    • OptimizerType
    • OptimizationResult
    • OptimizationSpecification
    • datastories.optimization.OptimizationDirection
    • VariableRange
    • VariableMapper
    • Sum
    • VariableSpec
    • AtMost
    • AtLeast
    • InInterval
    • IsEqual
    • Minimize
    • Maximize
  • Story
    • load()
    • load_result()
    • StoryBase
    • Predict Single KPI
    • Predict Multiple KPIs
    • Check Data Health
  • Story Results
    • General Results
    • Predict Multiple KPI Story Specific Results
  • Visualization
    • Display Utils
    • Plots
  • MLflow Support
    • Story modelling
    • Optimizer modelling
• SDK Use Cases
  • How to use Optimizers?
    • How to define optimizers
    • Invoking an optimizer
    • Using Optimization models in MLflow
  • How to inject What-Ifs in existing documents?
    • Exporting the JavaScript library
    • Example use case
    • Deploying the example
  • How to integrate with MLflow?
    • MLflow integration
  • How to run the SDK within Docker?
    • Base Docker image
    • Linking with a license
    • Extended Docker image
• End User License Agreement (EULA)

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