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API

Utilities

.. currentmodule:: hvplot

.. autosummary::
   :toctree: generated/

   help
   hvplot_extension
   extension
   output
   render
   save
   show

(api-plotting)=

Plotting

hvPlot / .hvplot

hvPlot's plotting API is most often invoked by installing the hvplot namespace on a data source via a special import:

import pandas as pd
import hvplot.pandas  # noqa
df = pd.DataFrame()

df.hvplot.scatter()
# or
df.hvplot(kind='scatter')

Under the hood, these special imports like import hvplot.pandas register an accessor that returns an instance of an hvPlotBase class. Tabular-like data sources rely on the hvPlotTabular class and gridded-like sources on hvPlot (subclass of hvPlotTabular extended with methods like {meth}image <hvplot.hvPlot.image>):

  • hvPlotTabular: cuDF, Dask, Fugue, Ibis, Pandas
  • hvPlotTabularDuckDB: DuckDB
  • hvPlotTabularPolars: Polars
  • hvPlot: Xarray

Instead of using the hvplot namespace, one can directly generate hvPlot plots with these classes:

import pandas as pd
from hvplot import hvPlot
df = pd.DataFrame()

hvPlot(df).scatter()
# or
hvPlot(df)(kind='scatter')

This section documents all the plotting methods of the hvPlot class, which as described above are also available via the hvplot namespace.

Common

.. currentmodule:: hvplot

.. autosummary::

   hvPlot.area
   hvPlot.bar
   hvPlot.barh
   hvPlot.box
   hvPlot.bivariate
   hvPlot.dataset
   hvPlot.density
   hvPlot.errorbars
   hvPlot.heatmap
   hvPlot.hexbin
   hvPlot.hist
   hvPlot.kde
   hvPlot.labels
   hvPlot.line
   hvPlot.ohlc
   hvPlot.paths
   hvPlot.points
   hvPlot.polygons
   hvPlot.scatter
   hvPlot.step
   hvPlot.table
   hvPlot.vectorfield
   hvPlot.violin

Gridded

.. currentmodule:: hvplot

.. autosummary::

   hvPlot.contour
   hvPlot.contourf
   hvPlot.image
   hvPlot.quadmesh
   hvPlot.rgb

plotting module

hvPlot's structure is based on Pandas' plotting API and as such provides special plotting functions in the hvplot.plotting module.

.. currentmodule:: hvplot.plotting

.. autosummary::

   andrews_curves
   lag_plot
   parallel_coordinates
   scatter_matrix

:hidden: true
:maxdepth: 2
:titlesonly: true

hvplot.hvPlot.area <manual/hvplot.hvPlot.area>
hvplot.hvPlot.bar <manual/hvplot.hvPlot.bar>
hvplot.hvPlot.barh <manual/hvplot.hvPlot.barh>
hvplot.hvPlot.box <manual/hvplot.hvPlot.box>
hvplot.hvPlot.bivariate <manual/hvplot.hvPlot.bivariate>
hvplot.hvPlot.contour <manual/hvplot.hvPlot.contour>
hvplot.hvPlot.contourf <manual/hvplot.hvPlot.contourf>
hvplot.hvPlot.dataset <manual/hvplot.hvPlot.dataset>
hvplot.hvPlot.density <manual/hvplot.hvPlot.density>
hvplot.hvPlot.errorbars <manual/hvplot.hvPlot.errorbars>
hvplot.hvPlot.heatmap <manual/hvplot.hvPlot.heatmap>
hvplot.hvPlot.hexbin <manual/hvplot.hvPlot.hexbin>
hvplot.hvPlot.hist <manual/hvplot.hvPlot.hist>
hvplot.hvPlot.image <manual/hvplot.hvPlot.image>
hvplot.hvPlot.kde <manual/hvplot.hvPlot.kde>
hvplot.hvPlot.labels <manual/hvplot.hvPlot.labels>
hvplot.hvPlot.line <manual/hvplot.hvPlot.line>
hvplot.hvPlot.ohlc <manual/hvplot.hvPlot.ohlc>
hvplot.hvPlot.paths <manual/hvplot.hvPlot.paths>
hvplot.hvPlot.points <manual/hvplot.hvPlot.points>
hvplot.hvPlot.polygons <manual/hvplot.hvPlot.polygons>
hvplot.hvPlot.quadmesh <manual/hvplot.hvPlot.quadmesh>
hvplot.hvPlot.rgb <manual/hvplot.hvPlot.rgb>
hvplot.hvPlot.scatter <manual/hvplot.hvPlot.scatter>
hvplot.hvPlot.step <manual/hvplot.hvPlot.step>
hvplot.hvPlot.table <manual/hvplot.hvPlot.table>
hvplot.hvPlot.vectorfield <manual/hvplot.hvPlot.vectorfield>
hvplot.hvPlot.violin <manual/hvplot.hvPlot.violin>
hvplot.plotting.andrews_curves <manual/hvplot.plotting.andrews_curves>
hvplot.plotting.lag_plot <manual/hvplot.plotting.lag_plot>
hvplot.plotting.parallel_coordinates <manual/hvplot.plotting.parallel_coordinates>
hvplot.plotting.scatter_matrix <manual/hvplot.plotting.scatter_matrix>

(api-networkx)=

NetworkX

The hvPlot NetworkX plotting API is meant as a drop-in replacement for the networkx.draw methods.

:::{note} Please chime in this issue if you have opinions about NetworkX plotting API in hvPlot. :::

.. currentmodule:: hvplot.networkx

.. autosummary::
   :toctree: generated/

   draw
   draw_networkx
   draw_networkx_nodes
   draw_networkx_edges
   draw_networkx_labels
   draw_circular
   draw_kamada_kawai
   draw_random
   draw_planar
   draw_shell
   draw_spectral
   draw_spring

Explorer

The explorer interface can easily be created from the hvPlot / .hvplot namespace:

.. currentmodule:: hvplot

.. autosummary::

    hvPlot.explorer

:hidden: true
:maxdepth: 2
:titlesonly: true

hvplot.hvPlot.explorer <manual/hvplot.hvPlot.explorer>

It is also available from the top-level explorer function:

.. currentmodule:: hvplot.ui

.. autosummary::
   :toctree: generated/

    explorer

Calling the explorer function/method returns an hvPlotExplorer object:

.. autosummary::
   :toctree: generated/

    hvPlotExplorer
    hvPlotExplorer.hvplot
    hvPlotExplorer.plot_code
    hvPlotExplorer.save
    hvPlotExplorer.servable
    hvPlotExplorer.settings
    hvPlotExplorer.show

Sample Data

The sampledata module provides convenient access to sample datasets from hvsampledata for learning and prototyping. While hvPlot itself does not require these datasets to function, installing hvsampledata allows you to easily reproduce the examples in the documentation, gallery and tutorials locally.

Installation

If you installed hvPlot with minimal dependencies, you may need to install hvsampledata separately:

::::{tab-set}

:::{tab-item} pip

pip install hvsampledata

:::

:::{tab-item} conda

conda install conda-forge::hvsampledata

::: ::::

Usage

import hvplot.pandas  # noqa
import hvplot.xarray  # noqa

penguins = hvplot.sampledata.penguins("pandas")
air_temp = hvplot.sampledata.air_temperature("xarray")
landsat = hvplot.sampledata.landsat_rgb("rioxarray")
us_states = hvplot.sampledata.us_states("geopandas")

:::{admonition} Notes :class: note

  • All datasets include comprehensive metadata and documentation
  • Some datasets require additional dependencies e.g geopandas for Geographic datasets, xarray for Gridded datasets etc.
  • Data types and schemas are preserved across different engines where possible

See the GitHub Repository for more information. :::