Replace ipyvega with jupyterlab_vega in docs

README.md

@@ -21,7 +21,8 @@ as well as Altair's [Tutorial Notebooks](altair/notebooks/01-Index.ipynb).
 
 ## Example
 
-Here is an example using Altair to quickly visualize and display a dataset with the native Vega-Lite renderer in the Jupyter Notebook:
+Here is an example using Altair to quickly visualize and display a dataset with
+the native Vega-Lite renderer in the Jupyter Notebook:
 
 ```python
 from altair import Chart, load_dataset
@@ -51,8 +52,8 @@ manner. By statistical visualization we mean:
 The Altair API contains no actual visualization rendering code but instead
 emits JSON data structures following the
 [Vega-Lite](https://github.com/vega/vega-lite) specification. For convenience,
-Altair can optionally use [ipyvega](https://github.com/vega/ipyvega) to
-display client-side renderings seamlessly in the Jupyter notebook.
+Altair can optionally use [jupyterlab_vega](https://github.com/altair-viz/jupyterlab_vega) to
+display client-side renderings seamlessly in the Jupyter Notebook.
 
 ## Features
 
@@ -168,10 +169,11 @@ Altair requires the following dependencies:
 * [traitlets](https://github.com/ipython/traitlets)
 * [IPython](https://github.com/ipython/ipython)
 
-For visualization in the IPython/Jupyter notebook using the Vega-Lite renderer, Altair additionally requires
+For visualization in the IPython/Jupyter Notebook using the Vega-Lite renderer,
+Altair additionally requires
 
 * [Jupyter Notebook](https://jupyter.readthedocs.io/en/latest/install.html)
-* [ipyvega](https://github.com/vega/ipyvega)
+* [jupyterlab_vega](https://github.com/altair-viz/jupyterlab_vega)
 
 If you have cloned the repository, run the following command from the root of the repository:
 
@@ -193,6 +195,7 @@ To run the tests, use
 ```
 py.test --pyargs altair
 ```
+
 (you can omit the `--pyargs` flag if you are running the tests from a source checkout).
 
 ## Feedback and Contribution
@@ -205,10 +208,13 @@ as much bigger than Altair itself: the Vega and Vega-Lite specifications are
 perhaps the best existing candidates for a principled *lingua franca* of data
 visualization.
 
-To contribute additional examples to the documentation please add or
-update notebooks in `altair/notebooks/*.ipynb` and open a pull request.
-Be sure to add links to `01-Index.ipynb` if needed. Thanks!
+To contribute additional examples to the documentation please add or update
+notebooks in `altair/notebooks/*.ipynb` and open a pull request. Be sure to add
+links to `01-Index.ipynb` if needed. Thanks!
 
 ## Whence Altair?
 
-Altair is the [brightest star](https://en.wikipedia.org/wiki/Altair) in the constellation Aquila, and along with Deneb and Vega forms the northern-hemisphere asterism known as the [Summer Triangle](https://en.wikipedia.org/wiki/Summer_Triangle).
+Altair is the [brightest star](https://en.wikipedia.org/wiki/Altair) in the
+constellation Aquila, and along with Deneb and Vega forms the
+northern-hemisphere asterism known as the [Summer
+Triangle](https://en.wikipedia.org/wiki/Summer_Triangle).

altair/api.py

@@ -322,7 +322,7 @@ def serve(self, ip='127.0.0.1', port=8888, n_retries=50, files=None,
             dictionary of extra content to serve
         jupyter_warning : bool (optional)
             if True (default), then print a warning if this is used
-            within the Jupyter notebook
+            within the Jupyter Notebook
         open_browser : bool (optional)
             if True (default), then open a web browser to the given HTML
         http_server : class (optional)

altair/utils/server.py

@@ -13,7 +13,7 @@
 from ._py3k_compat import server, IO
 
 JUPYTER_WARNING = """
-Note: if you're in the Jupyter notebook, Chart.serve() is not the best
+Note: if you're in the Jupyter Notebook, Chart.serve() is not the best
       way to view plots. Consider using Chart.display().
 You must interrupt the kernel to cancel this command.
 """

doc/documentation/displaying.rst

@@ -51,9 +51,11 @@ Displaying Plots in Jupyter Notebook
 
 Perhaps the most straightforward way to interactively create and render
 Altair visualizations is in the `Jupyter Notebook`_.
-If you have installed correctly configured the `ipyvega`_ package
-(See :ref:`Installation`), then a chart on the last line of a code cell
-will automatically be represented within the notebook as a rendered plot:
+
+`jupyterlab_vega`_ is an extension for both Jupyter Notebook and JupyterLab.
+Once installed and enabled, it will render all Altair charts using vega-embed.
+You can render a chart by returning it (calling it on the last line of a code
+cell) or using ``.display()`` on a Altair ``Chart`` object.
 
 .. altair-plot::
 
@@ -66,9 +68,6 @@ will automatically be represented within the notebook as a rendered plot:
         color='Origin:N',
     )
 
-Alternatively, you can use ``chart.display()`` to more explicitly display
-any chart object
-
 .. _displaying-plots-html:
 
 Outputting Plots as HTML
@@ -195,4 +194,4 @@ please send comments or contributions via Altair's
 .. _Vega-Lite Online Editor: https://vega.github.io/vega-editor/?mode=vega-lite
 .. _Vega-Lite: https://github.com/vega/vega-lite
 .. _Jupyter Notebook: https://jupyter.readthedocs.io/en/latest/install.html
-.. _ipyvega: http://github.com/vega/ipyvega
+.. _jupyterlab_vega: https://github.com/altair-viz/jupyterlab_vega

doc/installation.rst

@@ -8,12 +8,14 @@ Altair can be installed via the Python Package Index with the following:
 
     $ pip install altair
     $ pip install --upgrade notebook
-    $ jupyter nbextension install --sys-prefix --py vega
+    $ pip install jupyterlab_vega
+    $ jupyter nbextension install --sys-prefix --py jupyterlab_vega
+    $ jupyter nbextension enable --sys-prefix --py jupyterlab_vega
 
-The additional commands serve to set-up the `ipyvega`_ module to automatically
-render Altair plots within the Jupyter notebook (see :ref:`displaying-plots-jupyter`)
-Alternatively, you can install with conda_, which handles the Jupyter notebook
-setup within the single install command:
+The additional commands serve to set-up the `jupyterlab_vega`_ package to
+automatically render Altair plots within the Jupyter Notebook (see
+:ref:`displaying-plots-jupyter`) Alternatively, you can install with conda_,
+which handles the Jupyter Notebook setup within the single install command:
 
 .. code-block:: bash
 
@@ -33,7 +35,7 @@ Additionally, the following optional dependencies are required to use Altair
 within the Jupyter Notebook:
 
 - `Jupyter Notebook`_
-- ipyvega_
+- jupyterlab_vega_
 
 Development Install
 -------------------

setup.py

@@ -23,7 +23,7 @@
 .. _Altair Github Repository: http://github.com/altair-viz/altair/
 .. _Altair Documentation: http://altair-viz.github.io/
 .. _Vega-Lite: https://github.com/vega/vega-lite
-.. _ipyvega: https://github.com/vega/ipyvega
+.. _jupyterlab_Vega: https://github.com/altair-viz/jupyterlab_vega
 """
 
 DESCRIPTION         = "Altair: A declarative statistical visualization library for Python."