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Visualizing streamz
===================
A variety of tools are available to help you understand, debug,
visualize your streaming objects:
- Most Streamz objects automatically display themselves in Jupyter
notebooks, periodically updating their visual representation as text
or tables by registering events with the Tornado IOLoop used by Jupyter
- The network graph underlying a stream can be visualized using `dot` to
render a PNG using `Stream.visualize(filename)`
- Streaming data can be visualized using the optional separate packages
hvPlot, HoloViews, and Panel (see below)
hvplot.streamz
--------------
hvPlot is a separate plotting library providing Bokeh-based plots for
Pandas dataframes and a variety of other object types, including
streamz DataFrame and Series objects.
See `hvplot.holoviz.org <https://hvplot.holoviz.org>`_ for
instructions on how to install hvplot. Once it is installed, you can
use the Pandas .plot() API to get a dynamically updating plot in
Jupyter or in Bokeh/Panel Server:
.. code-block:: python
import hvplot.streamz
from streamz.dataframe import Random
df = Random()
df.hvplot(backlog=100)
See the `streaming section
<https://hvplot.holoviz.org/user_guide/Streaming.html>`_ of the hvPlot
user guide for more details, and the `dataframes.ipynb` example that
comes with streamz for a simple runnable example.
HoloViews
---------
hvPlot is built on HoloViews, and you can also use HoloViews directly
if you want more control over events and how they are processed. See
the `HoloViews user guide
<http://holoviews.org/user_guide/Streaming_Data.html>`_ for more
details.
Panel
-----
Panel is a general purpose dashboard and app framework, supporting a
wide variety of displayable objects as "Panes". Panel provides a
`streamz Pane
<https://panel.holoviz.org/reference/panes/Streamz.html>`_ for
rendering arbitrary streamz objects, and streamz DataFrames are
handled by the Panel `DataFrame Pane
<https://panel.holoviz.org/reference/panes/DataFrame.html>`_.
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