gt-fmt_auto – The gt package

The `fmt_auto()` function

Use the exibble dataset to create a gt table. Format all of the columns automatically with the fmt_auto() function.

exibble |>
  gt() |>
  fmt_auto()

num	char	fctr	date	time	datetime	currency	row	group
0.111	apricot	one	2015-01-15	13:35	2018-01-01 02:22	49.95	row_1	grp_a
2.222	banana	two	2015-02-15	14:40	2018-02-02 14:33	17.95	row_2	grp_a
33.33	coconut	three	2015-03-15	15:45	2018-03-03 03:44	1.39	row_3	grp_a
444.4	durian	four	2015-04-15	16:50	2018-04-04 15:55	65,100	row_4	grp_a
5,550	NA	five	2015-05-15	17:55	2018-05-05 04:00	1,325.81	row_5	grp_b
NA	fig	six	2015-06-15	NA	2018-06-06 16:11	13.255	row_6	grp_b
777,000	grapefruit	seven	NA	19:10	2018-07-07 05:22	NA	row_7	grp_b
8.880 × 10⁶	honeydew	eight	2015-08-15	20:20	NA	0.44	row_8	grp_b

Let’s now use the countrypops dataset to create another gt table. We’ll again use fmt_auto() to automatically format all columns but this time the choice will be made to opt for large-number suffixing instead of scientific notation. This is done by using the lg_num_pref = "suf" option.

countrypops |>
  dplyr::select(country_code_3, year, population) |>
  dplyr::filter(country_code_3 %in% c("CHN", "IND", "USA", "PAK", "IDN")) |>
  dplyr::filter(year > 1975 & year %% 5 == 0) |>
  tidyr::spread(year, population) |>
  dplyr::arrange(desc(`2020`)) |>
  gt(rowname_col = "country_code_3") |>
  fmt_auto(lg_num_pref = "suf")

	1980	1985	1990	1995	2000	2005	2010	2015	2020
CHN	981.2M	1.1B	1.1B	1.2B	1.3B	1.3B	1.3B	1.4B	1.4B
IND	696.8M	780.2M	870.5M	964.3M	1.1B	1.2B	1.2B	1.3B	1.4B
USA	227.2M	237.9M	249.6M	266.3M	282.2M	295.5M	309.3M	320.7M	331.5M
IDN	148.2M	165.8M	182.2M	198.1M	214.1M	228.8M	244M	259.1M	271.9M
PAK	80.6M	97.1M	115.4M	133.1M	154.4M	174.4M	194.5M	211M	227.2M

The fmt_auto() function

The `fmt_auto()` function