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hvPlot makes data analysis and visualization simple
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The 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.
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 hvplotor with pip:
pip install hvplotWork 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
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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