Saving Altair Charts

Altair chart objects have a Chart.save() method which allows charts to be saved in a variety of formats.

PNG and SVG format

To save an Altair chart object as a PNG or SVG image, you can use

chart.save('chart.png')
chart.save('chart.svg')

However, saving these images requires some additional dependencies to run the javascript code necessary to interpret the Vega-Lite specification and output it in the form of an image.

Altair is set up to do this conversion using selenium and headless Chrome or Firefox, which requires the following:

  • the Selenium python package. This can be installed using:

    $ conda install selenium
    

    or:

    $ pip install selenium
    
  • a recent version of Google Chrome or Mozilla Firefox. Please see the Chrome or Firefox installation page for installation details for your own operating system.

  • Chrome Driver or Gecko Driver, which allows Chrome or Firefox respectively to be run in a headless state (i.e. to execute Javascript code without opening an actual browser window). If you use homebrew on OSX, this can be installed with:

    $ brew install chromedriver
    $ brew install geckodriver
    

    See the chromedriver or geckodriver documentation for details on installation.

Once those dependencies are installed, you should be able to save charts as png or svg.

Figure Size/Resolution

When using chart.save() above, the resolution of the resulting PNG is controlled by the resolution of your screen. The easiest way to produce a higher-resolution PNG image is to scale the image to make it larger, and thus to contain more pixels at a given resolution.

This can be done with the scale_factor argument, which defaults to 1.0:

chart.save('chart.png', scale_factor=2.0)

JSON format

The fundamental chart representation output by Altair is a JSON string format; one of the core methods provided by Altair is Chart.to_json(), which returns a JSON string that represents the chart content. Additionally, you can save a chart to a JSON file using Chart.save(), by passing a filename with a .json extension.

For example, here we save a simple scatter-plot to JSON:

import altair as alt
from vega_datasets import data

chart = alt.Chart(data.cars.url).mark_point().encode(
    x='Horsepower:Q',
    y='Miles_per_Gallon:Q',
    color='Origin:N'
)

chart.save('chart.json')

The contents of the resulting file will look something like this:

{
  "$schema": "https://vega.github.io/schema/vega-lite/v2.json",
  "config": {
    "view": {
      "height": 300,
      "width": 400
    }
  },
  "data": {
    "url": "https://vega.github.io/vega-datasets/data/cars.json"
  },
  "encoding": {
    "color": {
      "field": "Origin",
      "type": "nominal"
    },
    "x": {
      "field": "Horsepower",
      "type": "quantitative"
    },
    "y": {
      "field": "Miles_per_Gallon",
      "type": "quantitative"
    }
  },
  "mark": "point"
}

This JSON can then be inserted into any web page using the vegaEmbed library.

HTML format

If you wish for Altair to take care of the embedding for you, you can save a file using

chart.save('chart.html')

This will create a simple HTML template page that loads Vega, Vega-Lite, and vegaEmbed, such that when opened in a browser the chart will be rendered.

For example, saving the above scatter-plot to HTML creates a file with the following contents, which can be opened and rendered in any modern javascript-enabled web browser:

<!DOCTYPE html>
<html>
<head>
  <script src="https://cdn.jsdelivr.net/npm/vega@3"></script>
  <script src="https://cdn.jsdelivr.net/npm/vega-lite@2"></script>
  <script src="https://cdn.jsdelivr.net/npm/vega-embed@3"></script>
</head>
<body>
  <div id="vis"></div>
  <script type="text/javascript">
    var spec = {
      "$schema": "https://vega.github.io/schema/vega-lite/v2.json",
      "config": {
        "view": {
          "height": 300,
          "width": 400
        }
      },
      "data": {
        "url": "https://vega.github.io/vega-datasets/data/cars.json"
      },
      "encoding": {
        "color": {
          "field": "Origin",
          "type": "nominal"
        },
        "x": {
          "field": "Horsepower",
          "type": "quantitative"
        },
        "y": {
          "field": "Miles_per_Gallon",
          "type": "quantitative"
        }
      },
      "mark": "point"
    };
    var opt = {"renderer": "canvas", "actions": false};
    vegaEmbed("#vis", spec, opt);
  </script>
</body>
</html>

You can view the result here: chart.html.