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vaex 4.16.0 documentation

  • What is Vaex?
  • Installation
  • Tutorials
  • Guides
    • Advanced plotting examples
    • Arrow
    • Async programming with Vaex
    • Caching
    • Dask
    • Data Types
    • GraphQL
    • I/O Kung-Fu: get your data in and out of Vaex
    • Handling missing or invalid data
    • Machine Learning: the Iris dataset
    • Machine Learning: the Titanic dataset
    • Performance notes
    • Progress Bars
    • Vaex server
  • Configuration
  • API
  • Datasets
  • FAQ

Guides¶

  • Advanced plotting examples
    • A single plot
    • Multiple plots of the same type
    • Multiple plots, same axes, different statistics
    • Multiple plots, different axes, different statistics
    • Slices in a 3rd dimension
    • Many plots with wrapping
    • Plotting selections
    • Overplotting a vector field on a heatmap
    • Plotting a healpix map
  • Arrow
    • Opens instantly
    • Quick viz of 146 million rows
    • Data cleansing: outliers
    • Shallow copies
    • Virtual column
    • Result
    • Interoperability
    • Tutorial
  • Async programming with Vaex
    • Using delay=True
    • Using the @delayed decorator
    • Async await
    • Async auto execute
  • Caching
  • Dask
    • Dask.array
  • Data Types
    • Supported Data Types in Vaex
    • General advice on data types in Vaex
    • Higher dimensional arrays
    • String support in Vaex
  • GraphQL
    • Pandas support
    • Server
    • GraphiQL
  • I/O Kung-Fu: get your data in and out of Vaex
    • Data input
    • Data export
  • Handling missing or invalid data
    • “nan” vs “missing” vs “na”
    • Examples
  • Machine Learning: the Iris dataset
    • PCA
    • Gradient boosting trees
    • Automatic pipelines
    • Production
    • Performance
  • Machine Learning: the Titanic dataset
    • Adjusting matplotlib parmeters
    • Get the data
    • Feature engineering
    • Modeling (part 1): gradient boosted trees
    • Modeling (part 2): Linear models & Ensembles
  • Performance notes
    • Virtual columns
    • Materializing the columns
    • Consideration in backends with multiple workers
  • Progress Bars
    • Basic progress bars
    • Rich based progress bars
  • Vaex server
    • Why
    • Starting the dataframe server
    • Python API
    • REST API
    • Example using plotly.js
Jupyter integration: interactivity Advanced plotting examples

© Copyright 2014, Maarten A. Breddels.

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