Software Engineer at Anaconda, maintaining and improving the open-source data viz libraries of the HoloViz ecosystem. Previously a civil engineer specialized in flood risk assessment, making flood maps with hydraulic simulation software.
hvPlot is a Python package part of the HoloViz suite of tools. Its original design was based on reproducing and extending the familiar and effective Pandas
.plot API, allowing regular data practitioners to have easy access to powerful, but somewhat difficult to use, features offered by the HoloViz tools. This includes handling large data with Datashader, geographic data with GeoViews and many features of HoloViews such as its support of different plotting backends (Bokeh, Matplotlib, Plotly). hvPlot is nowadays no longer limited to its
.plot API and provides two other and newer functionalities dedicated to making data exploration easier. With the
.interactive API, Panel/IPyWidgets widgets can be injected into a processing pipeline (e.g. a pipeline of Pandas or Xarray methods) to interactively control its parameters; when a widget value changes
.interactive takes care of re-evaluating the pipeline and updating its output. The latest addition to hvPlot is the Explorer, a graphical interface that offers a low-code experience to data exploration and with which it is simple to create customized plots, selecting the plot options directly from widgets. This talk will focus on describing in more details
.interactive and the Explorer, and will then show how they can be used together with the
.plot API to set up an approachable and interactive workflow to data exploration in a notebook.