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Numbering the Outer Arc

Made with Plotapi

You can create beautiful, interactive, and engaging visualisations like this one with Plotapi in any programming language.

Preamble

In [1]:
from plotapi import Chord

Chord.set_license("your username", "your license key")

Introduction

Depending on our data, displaying the quantity associated with each segment as a label may be useful.

As we can see, we have set our license details in the preamble with Chord.set_license()

Dataset

Chord expects a list of names (list[str]) and a co-occurence matrix (list[list[float]]) as input.

In [2]:
matrix = [
    [0, 5, 6, 4, 7, 4],
    [5, 0, 5, 4, 6, 5],
    [6, 5, 0, 4, 5, 5],
    [4, 4, 4, 0, 5, 5],
    [7, 6, 5, 5, 0, 4],
    [4, 5, 5, 5, 4, 0],
]

names = ["Action", "Adventure", "Comedy", "Drama", "Fantasy", "Thriller"]

It may look more clear if we present this as a table with the columns and indices labelled. This is entirely optional.

In [3]:
import pandas as pd
pd.DataFrame(matrix, columns=names, index=names)
Out[3]:
Action Adventure Comedy Drama Fantasy Thriller
Action 0 5 6 4 7 4
Adventure 5 0 5 4 6 5
Comedy 6 5 0 4 5 5
Drama 4 4 4 0 5 5
Fantasy 7 6 5 5 0 4
Thriller 4 5 5 5 4 0

Visualisation

The visibility of quantity labels can be controlled with the arc_numbers parameter. Setting it to True will enable them.

Be sure to interact with the visualisation to see what the default settings can do!

In [4]:
Chord(matrix, names, arc_numbers=True).show()
Plotapi - Chord Diagram

You can do so much more than what's presented in this example, and we'll cover this in later sections. If you want to see the full list of growing features, check out the Plotapi Documentation. and the Plotapi Gallery.

Made with Plotapi

You can create beautiful, interactive, and engaging visualisations like this one with Plotapi in any programming language.

Plotapi, beautiful by default.

Let plotapi do the heavy lifting – enabling beautiful interactive visualisations with a single line of code (instead of hundreds).

Get Plotapi