Welcome to ProgressiVis

ProgressiVis is a Python toolkit and scientific workflow system that implements a new programming paradigm that we call Progressive Analytics or Progressive Data Analysis and Visualization aimed at performing analytics in a progressive way. It allows analysts to see the progress of their analysis and to steer it interactively while the computation is being done.

Contents:

• Introduction
  • Why?
  • Benefits
  • Current State
  • Dependencies
• Installation of ProgressiVis
  • Installation for users
  • Installation for developers
• User Guide
  • Key concepts
  • Main Components
  • Running a Progressive Program
  • Dynamic Modification of a ProgressiVis Program
  • Communication between ProgressiVis and the Notebook
  • Dealing with Noisy Data
• Progressive Notebooks
  • Running Jupyter
  • Creating a progressive analysis
  • Replaying a progressive analysis
  • Do not cut and paste from a ProgressiBook to a standard Notebook
  • Chaining widgets
  • Navigation with the DAG Widget
  • A ProgressiBook user guide
  • Chaining widgets list
  • Recording a scenario
  • Replay a scenario
  • Chaining widgets’ persistent settings
  • How to create a chaining widget?
• Standalone widgets
  • The Sniffer
  • The DAG Widget
• Example Gallery
  • NYC Taxis / Precipitations scatterplot
  • NYC Taxis / Precipitations line chart
  • NYC Taxis / Correlation between the number of courses per day and precipitations
  • A scenario using progressivis snippets
  • A scenario using duckdb in a snippet
  • A multi-class density map for NYC Taxis data.
  • Progressive KMeans
  • TSNE 2D
• Library Reference
  • First level variables
  • Dataflow Management
  • Progressive Data Structures
  • Decorators
• Module Library
  • I/O Modules
  • Data Filtering Modules
  • Indexing Modules
  • Data Grouping/Joining/Aggregation Modules
  • Set and Flow Control Operations
  • Statistical Modules
  • Clustering Modules
  • Linear Algebra Modules
  • Visualisation
  • Utility
  • Format Adaptors
• Unit Tests
• Writing New Modules
  • Overview
  • The Module.run_step() method
  • Cooperative Scheduling
  • Example: The SimpleMax Module
  • Difference with the Max Module
  • Data Change Management
  • Interactive Behavior
  • Synchronization of Modules
• Dependencies
  • Datashape

Indices and tables

• Index

• Module Index

• Search Page