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Tutorials

• Vaex introduction in 11 minutes
  • DataFrame
    • Columns
    • Virtual columns
    • Selections and filtering
  • Statistics on N-d grids
  • Getting your data in
  • Plotting
    • 1-D and 2-D
    • Selections for plotting
    • Advanced Plotting
    • Slices in a 3rd dimension
    • Visualization of smaller datasets
    • In control
    • Healpix (Plotting)
  • xarray suppport
  • Interactive widgets
  • Joining
  • Group-by
  • String processing
  • Propagation of uncertainties
  • Just-In-Time compilation
  • Parallel computations
  • Extending Vaex
    • Adding functions
    • Adding DataFrame accessors
  • Convenience methods
    • Get column names
• The escape hatch: apply
  • When not to use apply
• Machine Learning with vaex.ml
  • Preprocessing
    • Scaling of numerical features
    • Encoding of categorical features
  • Feature Engineering
    • KBinsDiscretizer
    • GroupBy Transformer
    • CycleTransformer
  • Dimensionality reduction
    • Principal Component Analysis
    • Incremental PCA
    • Random projections
  • Clustering
    • K-Means
  • Supervised learning
    • Scikit-Learn example
    • XGBoost example
    • CatBoost example
    • Keras example
    • River example
  • Metrics
  • State transfer - pipelines made easy
• Jupyter integration: interactivity
  • Introduction
  • An interactive xarray DataArray display
  • Interactive plots
  • Selection widgets
  • Axis control widgets
  • A nice container
  • Interactive plots
  • Creating your own visualizations
    • ipyvolume example
    • plotly example

Installing Vaex introduction in 11 minutes