Learning gt: Creating a Retro League Table – schochastics

It has been way too long since I had time to prepare a blog post that is neither a story about Open Source Development, or an announcement of yet another R package.

I meant to look into gt, a package to create wonderful-looking tables in R, for a very long time but everytime I get some sort of motivation, I shy away because of how complicated it looks to built a table. Hundreds of lines of codes for a 10 line table? Yeah no thank you knitr::kable() it is. But not this time.

Learning by breaking

Whenever I want to learn something new in R, I need a personal project for which this might be relevant. I am very bad at following tutorials. Basically all my data science, web scrapping, and javascript knowledge comes from my football analytics website that I have been maintaining for about 8 years. So I decided, why not football data again and decided to create a simple league table, but with a twist. I try to do something mildly absurd that requires enough extra effort to learn as much about the package as possible. When I wanted to built my first quarto website, I created quartocities, an homage to geocities and the beauty of 90s webpages. I didn’t break quarto, but got to learn so much about Lua, shortcodes, filters just to get those funky gifs everywhere. I am not gonna add that level of absurdity to the league table. For whatever reason, I decided that the table should have a vintage look. With this, I was hopping to get into as many of the styling elements as possible.

Setup

Besides the gt package, I will also use the gtExtras package which offers even more styling possibilities.

library(gt)
library(gtExtras)
library(tidyverse)

# some retro color palettes
cols <- c("#FAEBCC", "#b3e3e0", "#68C7C1", "#FACA78", "#F57F5B", "#DD5341", "#794A3A")
wld <- c("#354065", "#711233", "#666666")

The underlying data (current league table and results) was obtained from weltfussball.de.

Vanilla table

Here is the table without any form of styling.

tbl1 <- tbl |>
    gt()

tbl1

number	img	mannschaft	pk	sp	wdl	tore	dif	form
1	crests/bayern-munchen-2017-2025-logo.png	Bayern München	26	10	8, 2, 0	33:7	26	W, W, W, W, D, D, W, W, W, W
2	crests/rb-leipzig-2020-logo.png	RB Leipzig	21	10	6, 3, 1	15:5	10	W, W, D, D, W, W, W, W, L, D
3	crests/eintracht-frankfurt-1998-logo.png	Eintracht Frankfurt	20	10	6, 2, 2	26:16	10	L, W, W, W, W, D, L, D, W, W
4	crests/bayer-04-leverkusen-2005-logo.png	Bayer Leverkusen	17	10	4, 5, 1	21:16	5	W, L, W, W, D, D, W, D, D, D
5	crests/sc-freiburg-2008-logo.png	SC Freiburg	17	10	5, 2, 3	13:11	2	W, L, W, W, L, W, W, L, D, D
6	crests/union-berlin-1966-logo.png	1. FC Union Berlin	16	10	4, 4, 2	9:8	1	D, W, D, W, L, W, W, D, L, D
7	crests/borussia-dortmund-1993-logo.png	Borussia Dortmund	16	10	5, 1, 4	18:18	0	W, D, W, L, W, L, W, L, W, L
8	crests/werder-bremen-1987-logo.png	Werder Bremen	15	10	4, 3, 3	17:21	-4	D, D, W, L, W, L, W, D, L, W
9	crests/borussia-monchengladbach-1999-logo.png	Bor. Mönchengladbach	14	10	4, 2, 4	15:14	1	L, W, L, L, W, L, W, D, W, D
10	crests/mainz-2018-logo.png	1. FSV Mainz 05	13	10	3, 4, 3	15:14	1	D, D, L, W, L, W, L, D, D, W
11	crests/vfb-stuttgart-2014-logo.png	VfB Stuttgart	13	10	3, 4, 3	19:19	0	L, D, W, W, D, D, L, W, D, L
12	crests/vfl-wolfsburg-2002-logo.png	VfL Wolfsburg	12	10	3, 3, 4	19:18	1	L, W, L, L, D, W, L, D, D, W
13	crests/fc-augsburg-2002-logo.png	FC Augsburg	12	10	3, 3, 4	13:20	-7	D, L, W, L, L, W, L, W, D, D
14	crests/1-fc-heidenheim-2007-logo.png	1. FC Heidenheim 1846	10	10	3, 1, 6	13:15	-2	W, W, L, L, W, L, L, D, L, L
15	crests/tsg-1899-hoffenheim-2014-logo.png	1899 Hoffenheim	9	10	2, 3, 5	13:19	-6	W, L, L, L, L, D, W, D, L, D
16	crests/st-pauli-2005-logo.png	FC St. Pauli	8	10	2, 2, 6	7:12	-5	L, L, L, D, W, L, L, D, W, L
17	crests/holstein-kiel.png	Holstein Kiel	5	10	1, 2, 7	12:25	-13	L, L, L, D, L, D, L, L, W, L
18	crests/vfl-bochum-2000-logo.png	VfL Bochum	2	10	0, 2, 8	10:30	-20	L, L, L, D, L, L, L, L, L, D

Two things might catch your eye. There seem to be two list columns (wdl and form). We will deal with them later. In general, these types of columns are usually used to create som visualization WITHIN the column.

The column img contains paths to crests of the clubs. These can be displayed with the gt_img_rows() function from gtExtras. We also align the imiges with cols_align().

tbl1 <- tbl1 |>
    gt_img_rows(img, img_source = "local", height = "25px") |>
    cols_align(
        align = "center",
        columns = img
    )
tbl1

number	mannschaft	pk	sp	wdl	tore	dif	form
1	Bayern München	26	10	8, 2, 0	33:7	26	W, W, W, W, D, D, W, W, W, W
2	RB Leipzig	21	10	6, 3, 1	15:5	10	W, W, D, D, W, W, W, W, L, D
3	Eintracht Frankfurt	20	10	6, 2, 2	26:16	10	L, W, W, W, W, D, L, D, W, W
4	Bayer Leverkusen	17	10	4, 5, 1	21:16	5	W, L, W, W, D, D, W, D, D, D
5	SC Freiburg	17	10	5, 2, 3	13:11	2	W, L, W, W, L, W, W, L, D, D
6	1. FC Union Berlin	16	10	4, 4, 2	9:8	1	D, W, D, W, L, W, W, D, L, D
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