This release is a pre-release and may not be stable for production use.
hvPlot makes data analysis and visualization simple
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Home | Installation instructions | Getting Started Guide | Gallery | Reference | Examples | License | Support
hvPlot provides a familiar, high-level API for visualization
The API is based on the familiar Pandas .plot API and the innovative .interactive API.
hvPlot works with the tools you know and love
hvPlot
- supports a wide range of data sources including Pandas, Polars, 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.
hvPlot can be used for exploration, reporting and data apps
Check out this blog post to see how easy it is to create an interactive dashboard with hvPlot and Panel.
Mini getting-started
Head over to the getting started guide for more!
Install
hvPlot can be installed on Linux, Windows, or Mac with conda:
conda install hvplot
or with pip:
pip install hvplot
Plotting data
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()
Interactive data apps
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
helpand?will provide you with documentation.TABandSHIFT+TABcompletion will help you navigate.
License
hvPlot is completely free and open-source. It is licensed under the BSD 3-Clause License.
Support & Feedback
- Usage questions and showcases -> HoloViz Community
- Bug reports and feature requests -> Github
- Developer discussions -> Discord
For more detail check out the HoloViz Community Guide.
Contributions
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.
Release files for hvplot 0.12.1a1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| hvplot-0.12.1a1.tar.gz | 7.1 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hvplot-0.12.1a1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.3 MB
Release files / hvplot-0.12.1a1.tar.gz
| Download URL | hvplot-0.12.1a1.tar.gz |
|---|---|
| Size | 7.1 MB |
| Tags | Source |
|
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Transparency logRelease files / hvplot-0.12.1a1-py3-none-any.whl
| Download URL | hvplot-0.12.1a1-py3-none-any.whl |
|---|---|
| Size | 175.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Aug 28, 2025.
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