Data is Beautiful

A practical book on data visualisation that shows you how to create static and interactive visualisations that are engaging and beautiful.

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League of Legends - Class Combinations

Dr. Shahin Rostami

2020-06-29

8 min read

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Contents Chat Share Follow Download Source

Preamble
Introduction

The Dataset

Data Wrangling
Chord Diagram with Names
Conclusion

Made with Plotapi

You can create beautiful, interactive, and engaging visualisations like this one with Plotapi in any programming language. Learn how to make beautiful visualisations with the book, Data is Beautiful.

Plotapi - Chord Diagram

Preamble¶

In [1]:

import numpy as np                   # for multi-dimensional containers 
import pandas as pd                  # for DataFrames
import itertools
from plotapi import Chord
Chord.set_license("your username", "your license key")

Introduction¶

In previous sections, we visualised co-occurrences of Pokémon type. Whilst it was interesting to look at, the dataset only contained Pokémon from the first six geerations. In this section, we're going to use the Pokemon with stats Generation 8 dataset to visualise the co-occurrence of Pokémon types from generations one to eight.

The Dataset¶

The dataset documentation states that we can expect 13 variables per each of the 1017 Pokémon of the first eight generations.

Let's download the mirrored dataset and have a look for ourselves.

In [2]:

data_url = 'https://datacrayon.com/datasets/lol/champion.json'
data = pd.read_json(data_url)
data.head()

Out[2]:

	type	format	version	data
Aatrox	champion	standAloneComplex	10.13.1	{'version': '10.13.1', 'id': 'Aatrox', 'key': ...
Ahri	champion	standAloneComplex	10.13.1	{'version': '10.13.1', 'id': 'Ahri', 'key': '1...
Akali	champion	standAloneComplex	10.13.1	{'version': '10.13.1', 'id': 'Akali', 'key': '...
Alistar	champion	standAloneComplex	10.13.1	{'version': '10.13.1', 'id': 'Alistar', 'key':...
Amumu	champion	standAloneComplex	10.13.1	{'version': '10.13.1', 'id': 'Amumu', 'key': '...

In [ ]:

It looks good so far, but let's confirm the 13 variables against 1017 samples from the documentation.

In [3]:

data = pd.DataFrame(data.data.tolist()).set_index(data.index)

In [4]:

data

Out[4]:

	version	id	key	name	title	blurb	info	image	tags	partype	stats
Aatrox	10.13.1	Aatrox	266	Aatrox	the Darkin Blade	Once honored defenders of Shurima against the ...	{'attack': 8, 'defense': 4, 'magic': 3, 'diffi...	{'full': 'Aatrox.png', 'sprite': 'champion0.pn...	[Fighter, Tank]	Blood Well	{'hp': 580, 'hpperlevel': 90, 'mp': 0, 'mpperl...
Ahri	10.13.1	Ahri	103	Ahri	the Nine-Tailed Fox	Innately connected to the latent power of Rune...	{'attack': 3, 'defense': 4, 'magic': 8, 'diffi...	{'full': 'Ahri.png', 'sprite': 'champion0.png'...	[Mage, Assassin]	Mana	{'hp': 526, 'hpperlevel': 92, 'mp': 418, 'mppe...
Akali	10.13.1	Akali	84	Akali	the Rogue Assassin	Abandoning the Kinkou Order and her title of t...	{'attack': 5, 'defense': 3, 'magic': 8, 'diffi...	{'full': 'Akali.png', 'sprite': 'champion0.png...	[Assassin]	Energy	{'hp': 575, 'hpperlevel': 95, 'mp': 200, 'mppe...
Alistar	10.13.1	Alistar	12	Alistar	the Minotaur	Always a mighty warrior with a fearsome reputa...	{'attack': 6, 'defense': 9, 'magic': 5, 'diffi...	{'full': 'Alistar.png', 'sprite': 'champion0.p...	[Tank, Support]	Mana	{'hp': 600, 'hpperlevel': 106, 'mp': 350, 'mpp...
Amumu	10.13.1	Amumu	32	Amumu	the Sad Mummy	Legend claims that Amumu is a lonely and melan...	{'attack': 2, 'defense': 6, 'magic': 8, 'diffi...	{'full': 'Amumu.png', 'sprite': 'champion0.png...	[Tank, Mage]	Mana	{'hp': 613.12, 'hpperlevel': 84, 'mp': 287.2, ...
...	...	...	...	...	...	...	...	...	...	...	...
Zed	10.13.1	Zed	238	Zed	the Master of Shadows	Utterly ruthless and without mercy, Zed is the...	{'attack': 9, 'defense': 2, 'magic': 1, 'diffi...	{'full': 'Zed.png', 'sprite': 'champion4.png',...	[Assassin]	Energy	{'hp': 584, 'hpperlevel': 85, 'mp': 200, 'mppe...
Ziggs	10.13.1	Ziggs	115	Ziggs	the Hexplosives Expert	With a love of big bombs and short fuses, the ...	{'attack': 2, 'defense': 4, 'magic': 9, 'diffi...	{'full': 'Ziggs.png', 'sprite': 'champion4.png...	[Mage]	Mana	{'hp': 536, 'hpperlevel': 92, 'mp': 480, 'mppe...
Zilean	10.13.1	Zilean	26	Zilean	the Chronokeeper	Once a powerful Icathian mage, Zilean became o...	{'attack': 2, 'defense': 5, 'magic': 8, 'diffi...	{'full': 'Zilean.png', 'sprite': 'champion4.pn...	[Support, Mage]	Mana	{'hp': 504, 'hpperlevel': 82, 'mp': 452, 'mppe...
Zoe	10.13.1	Zoe	142	Zoe	the Aspect of Twilight	As the embodiment of mischief, imagination, an...	{'attack': 1, 'defense': 7, 'magic': 8, 'diffi...	{'full': 'Zoe.png', 'sprite': 'champion4.png',...	[Mage, Support]	Mana	{'hp': 560, 'hpperlevel': 92, 'mp': 425, 'mppe...
Zyra	10.13.1	Zyra	143	Zyra	Rise of the Thorns	Born in an ancient, sorcerous catastrophe, Zyr...	{'attack': 4, 'defense': 3, 'magic': 8, 'diffi...	{'full': 'Zyra.png', 'sprite': 'champion4.png'...	[Mage, Support]	Mana	{'hp': 504, 'hpperlevel': 79, 'mp': 418, 'mppe...

148 rows × 11 columns

Perfect, that's exactly what we were expecting.

Data Wrangling¶

We need to do a bit of data wrangling before we can visualise our data. We can see from the columns names that the Pokémon types are split between the columns Type 1 and Type 2.

In [5]:

pd.DataFrame(data.columns.values.tolist())

Out[5]:

	0
0	version
1	id
2	key
3	name
4	title
5	blurb
6	info
7	image
8	tags
9	partype
10	stats

So let's select just these two columns and work with a list containing only them as we move forward.

Without further investigation, we can see that we have at least a few NaN values in the table above. We are only interested in co-occurrence of types, so we can remove all samples which contain a NaN value.

We can also see an instance where the type Fighting at index $1014$ is followed by \n. We'll strip all these out before continuing.

Our chord diagram will need two inputs: the co-occurrence matrix, and a list of names to label the segments.

First we'll populate our list of type names by looking for the unique ones.

In [6]:

types = [item for sublist in data.tags.tolist() for item in sublist]
names = np.unique(types).tolist()
pd.DataFrame(names)

Out[6]:

	0
0	Assassin
1	Fighter
2	Mage
3	Marksman
4	Support
5	Tank

Now we can create our empty co-occurrence matrix using these type names for the row and column indeces.

In [7]:

matrix = pd.DataFrame(0, index=names, columns=names)
matrix

Out[7]:

	Assassin	Fighter	Mage	Marksman	Support	Tank
Assassin	0	0	0	0	0	0
Fighter	0	0	0	0	0	0
Mage	0	0	0	0	0	0
Marksman	0	0	0	0	0	0
Support	0	0	0	0	0	0
Tank	0	0	0	0	0	0

We can populate a co-occurrence matrix with the following approach. We'll start by creating a list with every type pairing in its original and reversed form.

Which we can now use to create the matrix.

In [8]:

len(data.tags[0])

Out[8]:

In [9]:

for x in data.tags:
    if(len(x) == 2):
        matrix.at[x[0], x[1]] += 1
        matrix.at[x[1], x[0]] += 1
    if(len(x) == 1):
        matrix.at[x[0], x[0]] += 1

matrix = matrix.values.tolist()

We can list DataFrame for better presentation.

In [10]:

pd.DataFrame(matrix)

Out[10]:

	0	1	2	3	4	5
0	5	17	8	5	1	0
1	17	3	6	1	3	34
2	8	6	13	6	21	4
3	5	1	6	13	2	0
4	1	3	21	2	1	4
5	0	34	4	0	4	1

In [11]:

colors = ["#80FF72","#ffce2b","#FA7E07","#ff006e","#8338ec","#3a86ff"]

Chord(matrix, names, colors=colors, curved_labels=True).show()

Plotapi - Chord Diagram

Chord Diagram with Names¶

It would be nice to show a list of Pokémon names and images when hovering over co-occurring Pokémon types. To do this, we can make use of the optional details parameter.

Let's also add a column to our dataset to store URLs that point to the images.

In [12]:

data['URL'] = ""

for index, row in data.iterrows():
    #url = f"http://127.0.0.1:8000/images/data-is-beautiful/lol/champion/{row.name}.png"
    url = f"https://shahinrostami.com/images/data-is-beautiful/lol/champion/{row.name}.png"
    data.at[index,'URL'] = url

In [13]:

data.URL

Out[13]:

Aatrox     https://shahinrostami.com/images/data-is-beaut...
Ahri       https://shahinrostami.com/images/data-is-beaut...
Akali      https://shahinrostami.com/images/data-is-beaut...
Alistar    https://shahinrostami.com/images/data-is-beaut...
Amumu      https://shahinrostami.com/images/data-is-beaut...
                                 ...                        
Zed        https://shahinrostami.com/images/data-is-beaut...
Ziggs      https://shahinrostami.com/images/data-is-beaut...
Zilean     https://shahinrostami.com/images/data-is-beaut...
Zoe        https://shahinrostami.com/images/data-is-beaut...
Zyra       https://shahinrostami.com/images/data-is-beaut...
Name: URL, Length: 148, dtype: object

In [14]:

data.loc['Akali']

Out[14]:

version                                              10.13.1
id                                                     Akali
key                                                       84
name                                                   Akali
title                                     the Rogue Assassin
blurb      Abandoning the Kinkou Order and her title of t...
info       {'attack': 5, 'defense': 3, 'magic': 8, 'diffi...
image      {'full': 'Akali.png', 'sprite': 'champion0.png...
tags                                              [Assassin]
partype                                               Energy
stats      {'hp': 575, 'hpperlevel': 95, 'mp': 200, 'mppe...
URL        https://shahinrostami.com/images/data-is-beaut...
Name: Akali, dtype: object

In [15]:

names

Out[15]:

['Assassin', 'Fighter', 'Mage', 'Marksman', 'Support', 'Tank']

Next, we'll create an empty multi-dimensional arrays with the same shape as our matrix for our details and thumbnail images.

In [16]:

data[['tag_1','tag_2']] = pd.DataFrame(data.tags.tolist(), index= data.index)

In [17]:

data

Out[17]:

	version	id	key	name	title	blurb	info	image	tags	partype	stats	URL	tag_1	tag_2
Aatrox	10.13.1	Aatrox	266	Aatrox	the Darkin Blade	Once honored defenders of Shurima against the ...	{'attack': 8, 'defense': 4, 'magic': 3, 'diffi...	{'full': 'Aatrox.png', 'sprite': 'champion0.pn...	[Fighter, Tank]	Blood Well	{'hp': 580, 'hpperlevel': 90, 'mp': 0, 'mpperl...	https://shahinrostami.com/images/data-is-beaut...	Fighter	Tank
Ahri	10.13.1	Ahri	103	Ahri	the Nine-Tailed Fox	Innately connected to the latent power of Rune...	{'attack': 3, 'defense': 4, 'magic': 8, 'diffi...	{'full': 'Ahri.png', 'sprite': 'champion0.png'...	[Mage, Assassin]	Mana	{'hp': 526, 'hpperlevel': 92, 'mp': 418, 'mppe...	https://shahinrostami.com/images/data-is-beaut...	Mage	Assassin
Akali	10.13.1	Akali	84	Akali	the Rogue Assassin	Abandoning the Kinkou Order and her title of t...	{'attack': 5, 'defense': 3, 'magic': 8, 'diffi...	{'full': 'Akali.png', 'sprite': 'champion0.png...	[Assassin]	Energy	{'hp': 575, 'hpperlevel': 95, 'mp': 200, 'mppe...	https://shahinrostami.com/images/data-is-beaut...	Assassin	None
Alistar	10.13.1	Alistar	12	Alistar	the Minotaur	Always a mighty warrior with a fearsome reputa...	{'attack': 6, 'defense': 9, 'magic': 5, 'diffi...	{'full': 'Alistar.png', 'sprite': 'champion0.p...	[Tank, Support]	Mana	{'hp': 600, 'hpperlevel': 106, 'mp': 350, 'mpp...	https://shahinrostami.com/images/data-is-beaut...	Tank	Support
Amumu	10.13.1	Amumu	32	Amumu	the Sad Mummy	Legend claims that Amumu is a lonely and melan...	{'attack': 2, 'defense': 6, 'magic': 8, 'diffi...	{'full': 'Amumu.png', 'sprite': 'champion0.png...	[Tank, Mage]	Mana	{'hp': 613.12, 'hpperlevel': 84, 'mp': 287.2, ...	https://shahinrostami.com/images/data-is-beaut...	Tank	Mage
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
Zed	10.13.1	Zed	238	Zed	the Master of Shadows	Utterly ruthless and without mercy, Zed is the...	{'attack': 9, 'defense': 2, 'magic': 1, 'diffi...	{'full': 'Zed.png', 'sprite': 'champion4.png',...	[Assassin]	Energy	{'hp': 584, 'hpperlevel': 85, 'mp': 200, 'mppe...	https://shahinrostami.com/images/data-is-beaut...	Assassin	None
Ziggs	10.13.1	Ziggs	115	Ziggs	the Hexplosives Expert	With a love of big bombs and short fuses, the ...	{'attack': 2, 'defense': 4, 'magic': 9, 'diffi...	{'full': 'Ziggs.png', 'sprite': 'champion4.png...	[Mage]	Mana	{'hp': 536, 'hpperlevel': 92, 'mp': 480, 'mppe...	https://shahinrostami.com/images/data-is-beaut...	Mage	None
Zilean	10.13.1	Zilean	26	Zilean	the Chronokeeper	Once a powerful Icathian mage, Zilean became o...	{'attack': 2, 'defense': 5, 'magic': 8, 'diffi...	{'full': 'Zilean.png', 'sprite': 'champion4.pn...	[Support, Mage]	Mana	{'hp': 504, 'hpperlevel': 82, 'mp': 452, 'mppe...	https://shahinrostami.com/images/data-is-beaut...	Support	Mage
Zoe	10.13.1	Zoe	142	Zoe	the Aspect of Twilight	As the embodiment of mischief, imagination, an...	{'attack': 1, 'defense': 7, 'magic': 8, 'diffi...	{'full': 'Zoe.png', 'sprite': 'champion4.png',...	[Mage, Support]	Mana	{'hp': 560, 'hpperlevel': 92, 'mp': 425, 'mppe...	https://shahinrostami.com/images/data-is-beaut...	Mage	Support
Zyra	10.13.1	Zyra	143	Zyra	Rise of the Thorns	Born in an ancient, sorcerous catastrophe, Zyr...	{'attack': 4, 'defense': 3, 'magic': 8, 'diffi...	{'full': 'Zyra.png', 'sprite': 'champion4.png'...	[Mage, Support]	Mana	{'hp': 504, 'hpperlevel': 79, 'mp': 418, 'mppe...	https://shahinrostami.com/images/data-is-beaut...	Mage	Support

148 rows × 14 columns

In [18]:

#data.loc[data.tag_2.isna(), 'tag_2'] = data[data.tag_2.isna()].tag_1

In [19]:

details = np.empty((len(names),len(names)),dtype=object)
details_thumbs = np.empty((len(names),len(names)),dtype=object)

Now we can populate the details array with lists of Pokémon names in the correct positions.

In [20]:

data[(data['tag_1'] == "Assassin") & (data["tag_2"].isnull())]

Out[20]:

	version	id	key	name	title	blurb	info	image	tags	partype	stats	URL	tag_1	tag_2
Akali	10.13.1	Akali	84	Akali	the Rogue Assassin	Abandoning the Kinkou Order and her title of t...	{'attack': 5, 'defense': 3, 'magic': 8, 'diffi...	{'full': 'Akali.png', 'sprite': 'champion0.png...	[Assassin]	Energy	{'hp': 575, 'hpperlevel': 95, 'mp': 200, 'mppe...	https://shahinrostami.com/images/data-is-beaut...	Assassin	None
Khazix	10.13.1	Khazix	121	Kha'Zix	the Voidreaver	The Void grows, and the Void adapts—in none of...	{'attack': 9, 'defense': 4, 'magic': 3, 'diffi...	{'full': 'Khazix.png', 'sprite': 'champion1.pn...	[Assassin]	Mana	{'hp': 572.8, 'hpperlevel': 85, 'mp': 327.2, '...	https://shahinrostami.com/images/data-is-beaut...	Assassin	None
Shaco	10.13.1	Shaco	35	Shaco	the Demon Jester	Crafted long ago as a plaything for a lonely p...	{'attack': 8, 'defense': 4, 'magic': 6, 'diffi...	{'full': 'Shaco.png', 'sprite': 'champion3.png...	[Assassin]	Mana	{'hp': 587, 'hpperlevel': 89, 'mp': 297.2, 'mp...	https://shahinrostami.com/images/data-is-beaut...	Assassin	None
Talon	10.13.1	Talon	91	Talon	the Blade's Shadow	Talon is the knife in the darkness, a merciles...	{'attack': 9, 'defense': 3, 'magic': 1, 'diffi...	{'full': 'Talon.png', 'sprite': 'champion3.png...	[Assassin]	Mana	{'hp': 588, 'hpperlevel': 95, 'mp': 377.2, 'mp...	https://shahinrostami.com/images/data-is-beaut...	Assassin	None
Zed	10.13.1	Zed	238	Zed	the Master of Shadows	Utterly ruthless and without mercy, Zed is the...	{'attack': 9, 'defense': 2, 'magic': 1, 'diffi...	{'full': 'Zed.png', 'sprite': 'champion4.png',...	[Assassin]	Energy	{'hp': 584, 'hpperlevel': 85, 'mp': 200, 'mppe...	https://shahinrostami.com/images/data-is-beaut...	Assassin	None

In [21]:

for count_x, item_x in enumerate(names):
    for count_y, item_y in enumerate(names):
        if(item_y == item_x):
            details_urls = data[
                (data['tag_1'] == item_x) & (data["tag_2"].isnull())]['URL'].to_list()

            details_names = data[
                (data['tag_1'] == item_x) & (data["tag_2"].isnull())]['name'].to_list()
        else:
            details_urls = data[
                (data['tag_1'].isin([item_x, item_y])) &
                (data['tag_2'].isin([item_y, item_x]))]['URL'].to_list()

            details_names = data[
                (data['tag_1'].isin([item_x, item_y])) &
                (data['tag_2'].isin([item_y, item_x]))]['name'].to_list()
        
        urls_names = np.column_stack((details_urls, details_names))
        if(urls_names.size > 0):
            details[count_x][count_y] = details_names
            details_thumbs[count_x][count_y] = details_urls

        else:
            details[count_x][count_y] = []
            details_thumbs[count_x][count_y] = []

details=pd.DataFrame(details).values.tolist()
details_thumbs=pd.DataFrame(details_thumbs).values.tolist()

In [22]:

pd.DataFrame(details)

Out[22]:

	0	1	2	3	4	5
0	[Akali, Kha'Zix, Shaco, Talon, Zed]	[Ekko, Fiora, Fizz, Irelia, Jax, Kayn, Lee Sin...	[Ahri, Evelynn, Kassadin, Katarina, LeBlanc, M...	[Quinn, Teemo, Tristana, Twitch, Vayne]	[Pyke]	[]
1	[Ekko, Fiora, Fizz, Irelia, Jax, Kayn, Lee Sin...	[Gangplank, Mordekaiser, Rek'Sai]	[Diana, Elise, Gragas, Rumble, Ryze, Swain]	[Jayce]	[Kayle, Taric, Thresh]	[Aatrox, Blitzcrank, Camille, Darius, Dr. Mund...
2	[Ahri, Evelynn, Kassadin, Katarina, LeBlanc, M...	[Diana, Elise, Gragas, Rumble, Ryze, Swain]	[Annie, Aurelion Sol, Brand, Cassiopeia, Karth...	[Azir, Ezreal, Jhin, Kennen, Kog'Maw, Varus]	[Anivia, Bard, Fiddlesticks, Heimerdinger, Ive...	[Amumu, Cho'Gath, Galio, Maokai]
3	[Quinn, Teemo, Tristana, Twitch, Vayne]	[Jayce]	[Azir, Ezreal, Jhin, Kennen, Kog'Maw, Varus]	[Aphelios, Caitlyn, Corki, Draven, Graves, Jin...	[Ashe, Senna]	[]
4	[Pyke]	[Kayle, Taric, Thresh]	[Anivia, Bard, Fiddlesticks, Heimerdinger, Ive...	[Ashe, Senna]	[Rakan]	[Alistar, Braum, Leona, Tahm Kench]
5	[]	[Aatrox, Blitzcrank, Camille, Darius, Dr. Mund...	[Amumu, Cho'Gath, Galio, Maokai]	[]	[Alistar, Braum, Leona, Tahm Kench]	[Shen]

Finally, we can put it all together but this time with the details matrix passed in.

In [23]:

Chord(
    matrix,
    names,
    colors=colors,
    details=details,
    details_thumbs=details_thumbs,
    noun="Champions",
    thumbs_width=70,
    thumbs_margin=1,
    popup_width=670,
    thumbs_font_size=10,
    credit=True,
    padding=0.05,
    arc_numbers=True,
    curved_labels=True,
    verb="appear together in"
).show()

Chord(
    matrix,
    names,
    colors=colors,
    details=details,
    details_thumbs=details_thumbs,
    noun="Champions",
    thumbs_width=70,
    thumbs_margin=1,
    popup_width=670,
    thumbs_font_size=10,
    credit=True,
    padding=0.05,
    arc_numbers=True,
    curved_labels=True,
    reverse_gradients=True,
    verb="appear together in"
).show()

Plotapi - Chord Diagram

Conclusion¶

In this section, we demonstrated how to conduct some data wrangling on a downloaded dataset to prepare it for a chord diagram. Our chord diagram is interactive, so you can use your mouse or touchscreen to investigate the co-occurrences!

Made with Plotapi

You can create beautiful, interactive, and engaging visualisations like this one with Plotapi in any programming language. Learn how to make beautiful visualisations with the book, Data is Beautiful.

Data is Beautiful

A practical book on data visualisation that shows you how to create static and interactive visualisations that are engaging and beautiful.

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