Exporting Images from Bokeh Python: A Step-by-Step Guide

When working with large datasets, it's often necessary to export images for further analysis or presentation. In this article, we'll explore how to use Bokeh, a popular data visualization library in Python, to export plots as images.

To get started, you need to have Datashader installed and configured properly. Once you've done that, you can generate raster images using Datashader's `render` function. However, these bare images may not be the most effective way to visualize your data, especially when it comes to exploring datasets at multiple scales.

This is where Bokeh comes in. By embedding Datashader-generated images into a plot using an external library like Matplotlib or Bokeh, you can create interactive and dynamic plots that are much easier to interpret.

To export your plots as images using Bokeh, you'll need to use the `export_svg` function from the `bokeh.io` module. This function allows you to save your plot as a Scalable Vector Graphics (SVG) image directly from your Python code.

Here's an example of how to use this function:

```

from bokeh.io import export_svg

# Create a Bokeh plot using figure()

plot_obj = figure()

# Customize the plot as needed

plot_obj.title.text = 'My Plot'

plot_obj.xaxis.axis_label = 'X Axis'

plot_obj.yaxis.axis_label = 'Y Axis'

# Export the plot as an SVG image

export_svg(plot_obj, filename='my_plot.svg')

```

This code creates a basic Bokeh plot with a title and axis labels, and then exports it as an SVG image named `my_plot.svg`.

In addition to exporting plots as SVG images, you can also use the `export_png` function to save your plots as PNG images. This function is similar to `export_svg`, but it allows you to specify the width and height of the exported plot.

Here's an example of how to use this function:

```

from bokeh.io import export_png

# Create a Bokeh plot using figure()

plot_obj = figure()

# Customize the plot as needed

plot_obj.title.text = 'My Plot'

plot_obj.xaxis.axis_label = 'X Axis'

plot_obj.yaxis.axis_label = 'Y Axis'

# Export the plot as a PNG image

export_png(plot_obj, filename='my_plot.png', width=800, height=600)

```

This code creates a basic Bokeh plot with a title and axis labels, and then exports it as a PNG image named `my_plot.png` with a width of 800 pixels and a height of 600 pixels.

In conclusion, exporting images from Bokeh Python is a simple process that can be achieved using the `export_svg` or `export_png` functions. By following these steps, you can create high-quality images of your plots that are perfect for presentation or further analysis.

Bokeh python export image