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from plotapi import Chord

Chord(matrix, names).show()

Visualizations Terminus

Pixels per percentage

Let's look at a percentage-based approach to handling data with very high values or many sources and targets.

For example, if we had a dataset that included values that were in the millions, Terminus may end up trying to process and display a million or more pixels on-screen simultaneously. The result would likely be crashing the tab or browser! Whilst that can be managed with the previously discussed pixel_batch_size and pixel_journey_duration, that approach will likely result in an animation that lasts too long.

Instead, we can start representing our data as a percentage. For example, we could represent 1 with 10, 100, or 1000 pixels.

Let's demonstrate this with a high-value dataset.

Sample data

Let's import PlotAPI and load our sample data.

from plotapi import Terminus

links = [
    {"source":"England", "target":"Germany", "value": 100000},
    {"source":"England", "target":"France", "value": 300000},
    {"source":"England", "target":"Spain", "value": 500000},
    {"source":"England", "target":"Italy", "value": 400000},
    {"source":"England", "target":"Japan", "value": 8000},

    {"source":"Ireland", "target":"Germany", "value": 350000},
    {"source":"Ireland", "target":"France", "value": 375000},
    {"source":"Ireland", "target":"Spain", "value": 175000},
    {"source":"Ireland", "target":"Italy", "value": 5000},
    {"source":"Ireland", "target":"Japan", "value": 40000},


We can see that we're working with a dataset that contains higher values than usual. Let's address this by setting percentage_by_source=True, which enables the percentage feature, and then pixels_per_percentage=100, which means we will be using 100 pixels to represent a single percent of a value. This also means our stats panel will display a percentage rather than the raw value.

Terminus(links, stats_text_width=100, colors="cool",
         percentage_by_source=True, pixels_per_percentage=100).show()