{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "hvPlot supports [streamz](https://github.com/mrocklin/streamz) DataFrame and Series objects, automatically generating streaming plots in a Jupyter notebook or deployed as a [Bokeh Server app](https://bokeh.pydata.org/en/latest/docs/user_guide/server.html). \n", "\n", "All hvPlot methods on streamz objects return HoloViews `DynamicMap` objects that update the plot whenever `streamz` triggers an event. For more information on `DynamicMap` and HoloViews dynamic plotting support, see the [HoloViews User Guide](http://holoviews.org/user_guide); here we will focus on using the simple, high-level hvPlot API rather than on the details of how events and data flow behind the scenes.\n", "\n", "**All plots generated by the streamz plotting interface dynamically stream data from Python into the web browser. The web version for this page includes *screen captures* of the streaming visualizations, not live streaming data.**\n", "\n", "As for any of the data backends, we start by patching the streamz library with the plotting API:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import hvplot.streamz # noqa" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Basic plotting\n", "\n", "Throughout this section we will be using the ``Random`` object from streamz, which provides an easy way of generating a DataFrame of random streaming data but which could be substituted with any streamz ``DataFrame`` or ``Series`` driven by a live, external data source instead. To stop the ``Random`` stream you can call ``df.stop()`` at any point." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from streamz.dataframe import Random\n", "df = Random(interval='200ms', freq='50ms')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The plot method on Series and DataFrame is a simple wrapper around a\n", "line plot, which will plot all columns:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "df.hvplot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "