Get the Books

Enjoying these notebooks and want to support the work? Check out the practical books on Data Science, Visualisation, and Evolutionary Algorithms.

Get the books

Animal Crossing Villager Species and Personality

Support this work

You can support this work by getting the e-books. This notebook will always be available for free in its online format.

Preamble

In [1]:
from plotapi import Chord
import json

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

Introduction

In this notebook we're going to use Plotapi Chord to visualise the co-occurrences between the species and personality of Aniaml Crossing villagers. We"ll use Python, but Plotapi can be used from any programming language.

In a chord diagram (or radial network), entities are arranged radially as segments with their relationships visualised by ribbons that connect them. The size of the segments illustrates the numerical proportions, whilst the size of the arc illustrates the significance of the relationships. Chord diagrams are useful when trying to convey relationships between different entities, and they can be beautiful and eye-catching.

Dataset

We're going to use data from Animal Crossing New Horizons data. Previously, we made use of the data available in this repository. However, since the 2.0 update, we've created our own! Let's get loading the data.

In [2]:
with open("ac_species_personality.json", "r") as f:
    data = json.load(f)

Visualisation

Let's use Plotapi Chord for this visualisation, you can see more examples in the Gallery.

We're going to adjust some layout and template parameters, and flip the intro animation on too.

Because we're using a data-table, we can also click on any part of the diagram to "lock" the selection.

In [3]:
Chord(
    data["matrix"],
    data["names"],
    colors=data["colors"],
    details=data["details"],
    details_thumbs=data["details_thumbs"],
    noun="villagers!",
    thumbs_width=50,
    curved_labels=True,
    popup_width=600,
    bipartite=True,
    bipartite_idx=data["bipartite_idx"],
    bipartite_size=0.4,
    padding=0.0,
    width=800,
    data_table_column_width=100,
    font_size_large="16px",
    data_table=data["data_table"],
    data_table_show_indices=False
).show()

Support this work

You can support this work by getting the e-books. This notebook will always be available for free in its online format.

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