Highlight interactive
---
-title: 'Altair: a declarative statistical visualization library for Python'
+title: 'Altair: interactive statistical visualizations for Python'
tags:
- Python
- visualization
@@ -48,18 +48,19 @@ bibliography: paper.bib
# Summary
-Altair is a statistical visualization library for Python.
+Altair is a declarative statistical visualization library for Python.
Statistical visualization is a constrained subset of data visualization focused on the creation of visualizations
that are helpful in statistical modeling. The constrained model of statistical visualization is usually expressed
in terms of a visualization grammar [2005-grammar] that specifies how input data is transformed and mapped to visual
properties (position, color, size, etc.).
Altair is based on the Vega-Lite visualization grammar [@2017-vega-lite], which allows a wide range of statistical
-visualizations to be expressed using a small number of grammar primitives. Vega-Lite is declarative; visualizations
-are specified using JSON data that follows the [Vega-Lite JSON schema](https://github.com/vega/schema).
-As a Python library, Altair provides an API oriented towards scientists and data scientists doing exploratory data
-analysis [@1977-exploratory]. Altair's Python API emits Vega-Lite JSON data, which is then rendered in a user-interface
-such as the Jupyter Notebook, JupyterLab or nteract using the
+visualizations to be expressed using a small number of grammar primitives. Vega-Lite implements a view composition
+algebra in conjunction with a novel grammar of interactions [@2017-vega-lite] that allow users to specify interactive
+charts in an few lines of code. Vega-Lite is declarative; visualizations are specified using JSON data that follows the
+[Vega-Lite JSON schema](https://github.com/vega/schema). As a Python library, Altair provides an API oriented towards
+scientists and data scientists doing exploratory data analysis [@1977-exploratory]. Altair's Python API emits Vega-Lite
+JSON data, which is then rendered in a user-interface such as the Jupyter Notebook, JupyterLab, or nteract using the
[Vega-Lite JavaScript library](https://vega.github.io/vega-lite/). Vega-Lite JSON is compiled to a full Vega
specification [@2016-reactive-vega-architecture], which is then parsed and executed using a reactive runtime that
internally makes use of D3.js [@2011-d3].
@@ -70,8 +71,7 @@ from the Vega-Lite JSON schema, ensuring strict conformance with the Vega-Lite s
produced by Altair and consumed by Vega-Lite provides a natural serialization and file format for statistical
visualizations. This is leveraged by JupyterLab, which provides built-in rendering of these files. Third, the JSON data
provides a clean integration point for non-programming based visualization user-interfaces such as Voyager
-[@2016-voyager,@2017-voyager2]. Fourth, Vega-Lite implements a view composition algebra in conjunction with a novel
-grammar of interactions [@2017-vega-lite] that allow users to specify interactive charts in an few lines of code.
+[@2016-voyager,@2017-voyager2].
In addition to [static documentation](https://altair-viz.github.io/), Altair includes a set of Jupyter Notebooks with
examples and an interactive tutorial. These notebooks can be read by anyone with only a web-browser through
