Vega-Altair is an open source declarative statistical visualization library for Python, based on Vega and Vega-Lite.
This means you can write Python but output Vega-Lite.
Vega-Altair is a visualization grammar (think Grammar of Graphics) that can be written as a JSON specification. Vega-lite provides most of the functionality of Vega more concisely, by relying on smart defaults and simpler encodings.
Key Features
- Simple, friendly and consistent API.
- Built on top of the powerful Vega-Lite JSON specification.
- Compound plot types that can be used to create stacked, layered, faceted, and repeated charts.
- Layered charts – allows you to overlay two different charts on the same set of axes. They can be useful, for example, when you wish to draw multiple marks for the same data.
- Horizontal Concatenation – display two plots side-by-side.
- Vertical Concatenation – offers vertical concatenation via the vconcat() function or the & operator.
- Repeated Charts – provides a convenient interface for a particular type of horizontal or vertical concatenation, in which the only difference between the concatenated panels is modification of one or more encodings.
- Faceted Charts – provide a more convenient API for creating multiple views of a dataset for a specific type of chart: one where each panel contains a different subset of data.
- Compound Charts and Data Specification – specify data in multiple places.
- Renderers for JupyterLab, nteract, Jupyter Notebook, and Google Colab.
- Customize renderers by allowing users to define and enable new MIME types.
- Data Transformations:
- Before the chart definition, using standard Pandas data transformations.
- Within the chart definition, using Vega-Lite’s data transformation tools.
- Save charts in a variety of formats: PNG, SVG, JSON, and HTML.
- Support for JupyterLab/nteract through MIME based rendering.
Declarative means you only have to declare links between data columns to the encoding channels. All the plot details are handled automatically.
Website: altair-viz.github.io
Support: GitHub Code Repository
Developer: Jake Vanderplas and Brian Granger together with the UW Interactive Data Lab
License: BSD 3-Clause “New” or “Revised” License
Vega-Altair is written in Python. Learn Python with our recommended free books and free tutorials.
Related Software
| Python Visualization Packages | |
|---|---|
| matplotlib | Python 2D plotting library which produces publication quality figures |
| Diagrams | Draw the cloud system architecture in Python code |
| Bokeh | Elegant, concise construction of versatile graphics |
| Dash | Python framework for building analytical web applications |
| seaborn | Python visualization library based on matplotlib |
| Plotly | Interactive, browser-based graphing library for Python |
| VisPy | Visualize massive datasets in real time |
| Vega-Altair | Declarative Visualization in Python |
| plotnine | Grammar of graphics for Python |
| PyQtGraph | Python graphics and GUI library built on PyQt4 / PySide and numpy |
| bqplot | Interactive Plotting Framework for the Jupyter Notebook |
| Vaex | Fast visualization of big data |
| PyVista | 3D plotting and mesh analysis |
| folium | Visualize data in a Leaflet map |
| HoloViews | Make Data Analysis and Visualization Seamless |
| Datashader | Generates aggregate arrays and representations of them as images |
| yt | Multi-code Toolkit for Analyzing and Visualizing Volumetric Data |
| Glumpy | Intuitive interface between NumPy and modern OpenGL |
| GeoViews | Explore and visualize geographical, meteorological, and oceanographic datasets |
| Pygal | Dynamic SVG charting library |
| Glue | Multi-dimensional linked-data exploration |
Read our verdict in the software roundup.
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