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The API is based on the familiar Pandas .plot
API and the innovative .interactive
API.
hvPlot
- supports a wide range of data sources including Pandas, XArray, Dask, Streamz, Intake, GeoPandas and NetworkX.
- supports the plotting backends Bokeh, Matplotlib and Plotly.
- exposes the powerful tools from the HoloViz ecosystem in a familiar and convenient API.
hvPlot is the simplest way to benefit from the HoloViz ecosystem for data exploration.
Check out this blog post to see how easy it is to create an interactive dashboard with hvPlot and Panel.
Head over to the getting started guide for more!
hvPlot can be installed on Linux, Windows, or Mac with conda
:
conda install -c pyviz hvplot
or with pip
:
pip install hvplot
Please note that for versions of jupyterlab<3.0
, you must install the JupyterLab extension manually with:
jupyter labextension install @pyviz/jupyterlab_pyviz
Work with your data source:
import numpy as np
import pandas as pd
idx = pd.date_range('1/1/2000', periods=1000)
df = pd.DataFrame(np.random.randn(1000, 4), index=idx, columns=list('ABCD')).cumsum()
Import the hvPlot extension for your data source and optionally set the plotting backend:
import hvplot.pandas
# Optional: hvplot.extension('matplotlib') or hvplot.extension('plotly')
Use the .hvplot
API as you would use the Pandas or Xarray .plot
API:
df.hvplot()
Just add .interactive
and replace your normal arguments with Panel widgets or Ipywidgets.
import panel as pn
pn.extension()
df.interactive(width=600).head(n=pn.widgets.IntSlider(start=1, end=5, value=3))
To see the available arguments for a specific kind
of plot run
hvplot.help(kind='scatter')
In a notebook or ipython environment the usual
help
and?
will provide you with documentation.TAB
andSHIFT+TAB
completion will help you navigate.
hvPlot is completely free and open-source. It is licensed under the BSD 3-Clause License.
Get support from or provide feedback to the HoloViz Community.
We would love to work with you no matter whether you want to contribute to issue management, PRs, documentation, blog posts, community support or social media communication.
To get started with the code or docs check out the Developer Guide.
Reach out on Gitter to discuss with the developers, join the weekly triaging or join the bi-weekly HoloViz call.