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
