Sports Cars Performance Table

This example compares sports cars across performance metrics. We hide auxiliary columns, group by origin country, add a performance spanner, format prices, and highlight them with bold styling.

The data

using StyledTables, DataFrames

cars = DataFrame(
    origin = ["Italy", "Italy", "Germany", "Germany", "UK", "UK"],
    make = ["Ferrari", "Lamborghini", "Porsche", "BMW", "McLaren", "Aston Martin"],
    model = ["488 GTB", "Huracán", "911 GT3", "M8", "720S", "Vantage"],
    msrp_eur = [280_000, 210_000, 180_000, 130_000, 220_000, 155_000],
    year = [2022, 2022, 2022, 2022, 2022, 2022],
    hp = [660, 610, 503, 617, 710, 503],
    trq_nm = [760, 560, 470, 750, 770, 625],
    mpg = [15, 13, 22, 19, 21, 20],
)

6×8 DataFrame

Row	origin	make	model	msrp_eur	year	hp	trq_nm	mpg
	String	String	String	Int64	Int64	Int64	Int64	Int64
1	Italy	Ferrari	488 GTB	280000	2022	660	760	15
2	Italy	Lamborghini	Huracán	210000	2022	610	560	13
3	Germany	Porsche	911 GT3	180000	2022	503	470	22
4	Germany	BMW	M8	130000	2022	617	750	19
5	UK	McLaren	720S	220000	2022	710	770	21
6	UK	Aston Martin	Vantage	155000	2022	503	625	20

Step 1: Basic table with row groups

Group by :origin and hide the origin and year columns.

label_dict = Dict(
    :make => "Make",
    :model => "Model",
    :msrp_eur => "MSRP (€)",
    :hp => "HP",
    :trq_nm => "Torque (Nm)",
    :mpg => "MPG",
)

tbl = StyledTable(cars)
tab_rowgroup!(tbl, :origin)
cols_hide!(tbl, :origin, :year)
cols_label!(tbl, label_dict)
render(tbl)

Make	Model	MSRP (€)	HP	Torque (Nm)	MPG
Italy
Ferrari	488 GTB	280000	660	760	15
Lamborghini	Huracán	210000	610	560	13
Germany
Porsche	911 GT3	180000	503	470	22
BMW	M8	130000	617	750	19
UK
McLaren	720S	220000	710	770	21
Aston Martin	Vantage	155000	503	625	20

Step 2: Add a spanner for performance metrics

tab_spanner!(tbl, "Performance" => [:hp, :trq_nm, :mpg])
render(tbl)

			Performance
Make	Model	MSRP (€)	HP	Torque (Nm)	MPG
Italy
Ferrari	488 GTB	280000	660	760	15
Lamborghini	Huracán	210000	610	560	13
Germany
Porsche	911 GT3	180000	503	470	22
BMW	M8	130000	617	750	19
UK
McLaren	720S	220000	710	770	21
Aston Martin	Vantage	155000	503	625	20

Step 3: Reorder, format, and highlight

Format MSRP with a currency prefix, right-align numeric columns, bold the price values, and annotate the MPG column.

fmt!(tbl, :msrp_eur) do x
    replace(string(x), r"(\d)(?=(\d{3})+$)" => s"\1,") * "€"
end
cols_align!(tbl, [:msrp_eur, :hp, :trq_nm, :mpg] => :right)
tab_style!(tbl, :msrp_eur; bold = true)
tab_footnote!(tbl, "City/highway combined estimate" => :mpg)
tab_sourcenote!(tbl, "Source: manufacturer specifications")
render(tbl)

			Performance
Make	Model	MSRP (€)	HP	Torque (Nm)	MPG1
Italy
Ferrari	488 GTB	280,000€	660	760	15
Lamborghini	Huracán	210,000€	610	560	13
Germany
Porsche	911 GT3	180,000€	503	470	22
BMW	M8	130,000€	617	750	19
UK
McLaren	720S	220,000€	710	770	21
Aston Martin	Vantage	155,000€	503	625	20
Source: manufacturer specifications
1 City/highway combined estimate

The table groups cars by origin, spans the three performance columns, formats MSRP with a thousands separator and currency symbol, and bolds prices for emphasis. The MPG footnote clarifies the measurement basis.