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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