bokeh save hvplot to pdf python

Guri Bee

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21-10-2024

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Saving Bokeh Plots Generated by hvPlot to PDF in Python

Bokeh and hvPlot are powerful tools for creating interactive visualizations in Python. Sometimes, you might need to save these visualizations as static images, such as PDFs, for sharing or inclusion in reports. This article will guide you through the process of saving hvPlot-generated Bokeh plots as PDFs.

Understanding the Process

1. hvPlot Generation: hvPlot is built on top of Bokeh and provides a convenient way to create interactive plots using pandas DataFrames.
2. Bokeh Rendering: hvPlot generates Bokeh objects under the hood. These objects hold the visual representation of your plot.
3. PDF Export: You'll need to leverage Bokeh's export capabilities to save the Bokeh object as a PDF.

Example: Saving a Scatter Plot as PDF

Let's illustrate this with a simple example. We'll use the gapminder dataset available through the hvplot library.

import hvplot.pandas
import pandas as pd

# Load the gapminder dataset
gapminder = pd.read_csv("https://raw.githubusercontent.com/vega/vega-datasets/master/data/gapminder.csv")

# Create an interactive scatter plot with hvPlot
plot = gapminder.hvplot.scatter(x="year", y="pop", 
                                 groupby="continent", 
                                 title="Population Growth by Continent")

# Export the plot as a PDF
from bokeh.io import export_png
export_png(plot, filename="population_growth.pdf")

In this example, we:

1. Load data: Import hvplot.pandas and pandas to load the gapminder dataset.
2. Create plot: Generate a scatter plot using hvplot.scatter to visualize population growth across continents.
3. Export to PDF: Use bokeh.io.export_png to save the plot as a population_growth.pdf file.

Note: While export_png is used in this example, Bokeh also supports other file formats like PNG and SVG.

Important Considerations

• Image Quality: Experiment with Bokeh's export_png function's parameters like width and height to control the size and resolution of your output PDF.
• Interactive Features: Saving to PDF will result in a static image. Interactive elements like zooming or tooltips will be lost.
• Customization: Customize the Bokeh plot directly before saving it as a PDF to achieve desired formatting and aesthetics.

Additional Resources

• Bokeh Documentation: https://docs.bokeh.org/en/latest/ - Dive deeper into Bokeh's customization options and export capabilities.
• hvPlot Documentation: https://hvplot.holoviz.org/ - Learn about hvPlot's features and integration with Bokeh.

This guide has provided a basic framework for saving hvPlot plots to PDF using Bokeh. You can further enhance your workflow by utilizing Bokeh's rich customization options and exploring advanced techniques for generating high-quality PDF visualizations.