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hvPlot provides a familiar, high-level API for visualizationThe API is based on the familiar Pandas .plot
API and the innovative .interactive
API.
hvPlot
hvPlot is the simplest way to benefit from the HoloViz ecosystem for data exploration.
hvPlot can be used for exploration, reporting and data appsCheck 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
:
or with pip
:
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:
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))How to find documentation from your notebook or editor
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
and SHIFT+TAB
completion will help you navigate.hvPlot is completely free and open-source. It is licensed under the BSD 3-Clause License.
For more detail check out the HoloViz Community Guide.
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.
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