vaex 4.17.0 documentation
What is Vaex?
Installation
Tutorials
Vaex introduction in 11 minutes
The escape hatch: apply
Machine Learning with vaex.ml
Jupyter integration: interactivity
Guides
Configuration
API
Datasets
FAQ
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repository
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Tutorials
ΒΆ
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