Tabby Extension Example

Here is an example of grouped tabsets in Quarto created with the Tabby extension. Select Python to see both tabsets switch. The code is available on GitHub.

First tabset

R

data("mtcars")
mtcars$fuel_efficiency <- ifelse(mtcars$mpg > 20, "Efficient", "Not Efficient")

plot(
  mtcars$wt, mtcars$mpg,
  main = "MPG vs. Weight",
  xlab = "Weight (1000 lbs)", ylab = "MPG",
  col = ifelse(mtcars$fuel_efficiency == "Efficient", "green", "red"), pch = 19
)

legend("topright", legend = c("Efficient", "Not Efficient"), col = c("green", "red"), pch = 19)

Python

import pandas as pd
from plotnine import ggplot, aes, geom_point, theme_minimal

mtcars = pd.read_csv("https://raw.githubusercontent.com/mwaskom/seaborn-data/master/mpg.csv").dropna()
mtcars['fuel_efficiency'] = ['Efficient' if mpg > 20 else 'Not Efficient' for mpg in mtcars['mpg']]

plot = (
    ggplot(mtcars, aes(x='weight', y='mpg', color='fuel_efficiency')) +
    geom_point(size=3) +
    theme_minimal()
    )

plot.show()

Second tabset

R

library(gt)
towny <- gt::towny

towny_mini <- towny[order(-towny$density_2021), c("name", "website", "density_2021", "land_area_km2", "latitude", "longitude")]
towny_mini <- head(towny_mini, 10)

gt(towny_mini)

name	website	density_2021	land_area_km2	latitude	longitude
Toronto	https://www.toronto.ca	4427.75	631.10	43.74167	-79.37333
Brampton	https://www.brampton.ca	2468.99	265.89	43.68833	-79.76083
Mississauga	https://www.mississauga.ca	2452.56	292.74	43.60000	-79.65000
Newmarket	https://newmarket.ca	2284.21	38.50	44.05806	-79.45833
Richmond Hill	https://www.richmondhill.ca	2004.39	100.79	43.87139	-79.43722
Orangeville	https://www.orangeville.ca	1989.91	15.16	43.91528	-80.10861
Ajax	https://www.ajax.ca	1900.75	66.64	43.85833	-79.03639
Waterloo	https://www.waterloo.ca	1895.66	64.06	43.46667	-80.51667
Kitchener	https://www.kitchener.ca	1877.68	136.81	43.41861	-80.47278
Guelph	https://guelph.ca	1644.06	87.43	43.53583	-80.22889

Python

from great_tables import GT, html
from great_tables.data import towny

towny_mini = (
    towny[["name", "website", "density_2021", "land_area_km2", "latitude", "longitude"]]
    .sort_values("density_2021", ascending=False)
    .head(10)
)

(
    GT(towny_mini)
)

name	website	density_2021	land_area_km2	latitude	longitude
Toronto	https://www.toronto.ca	4427.75	631.1	43.741667	-79.373333
Brampton	https://www.brampton.ca	2468.99	265.89	43.688333	-79.760833
Mississauga	https://www.mississauga.ca	2452.56	292.74	43.6	-79.65
Newmarket	https://newmarket.ca	2284.21	38.5	44.058056	-79.458333
Richmond Hill	https://www.richmondhill.ca	2004.39	100.79	43.871389	-79.437222
Orangeville	https://www.orangeville.ca	1989.91	15.16	43.915278	-80.108611
Ajax	https://www.ajax.ca	1900.75	66.64	43.858333	-79.036389
Waterloo	https://www.waterloo.ca	1895.66	64.06	43.466667	-80.516667
Kitchener	https://www.kitchener.ca	1877.68	136.81	43.418611	-80.472778
Guelph	https://guelph.ca	1644.06	87.43	43.535833	-80.228889