Column Selection

The columns= argument for methods like GT.tab_spanner(), GT.cols_move(), and GT.tab_style allows a range of options for selecting columns.

The simplest approach is just a list of strings with the exact column names. However, we can specify columns using any of the following:

a single string column name.
an integer for the column’s position.
a list of strings or integers.
a Polars selector.
a function that takes a string and returns True or False.

from great_tables import GT
from great_tables.data import exibble

lil_exibble = exibble[["num", "char", "fctr", "date", "time"]].head(4)
gt_ex = GT(lil_exibble)

gt_ex

num	char	fctr	date	time
0.1111	apricot	one	2015-01-15	13:35
2.222	banana	two	2015-02-15	14:40
33.33	coconut	three	2015-03-15	15:45
444.4	durian	four	2015-04-15	16:50

Using integers

We can use a list of strings or integers to select columns by name or position, respectively.

gt_ex.cols_move_to_start(columns=["date", 1, -1])

date	char	time	num	fctr
2015-01-15	apricot	13:35	0.1111	one
2015-02-15	banana	14:40	2.222	two
2015-03-15	coconut	15:45	33.33	three
2015-04-15	durian	16:50	444.4	four

Note the code above moved the following columns:

The string "date" matched the column of the same name.
The integer 1 matched the second column (this is similar to list indexing).
The integer -1 matched the last column.

Moreover, the order of the list defines the order of selected columns. In this case, "data" was the first entry, so it’s the very first column in the new table.

Using Polars selectors

When using a Polars DataFrame, you can select columns using Polars selectors. The example below uses Polars selectors to move all columns that start with "c" or "f" to the start of the table.

import polars as pl
import polars.selectors as cs

pl_df = pl.from_pandas(lil_exibble)

GT(pl_df).cols_move_to_start(columns=cs.starts_with("c") | cs.starts_with("f"))

char	fctr	num	date	time
apricot	one	0.1111	2015-01-15	13:35
banana	two	2.222	2015-02-15	14:40
coconut	three	33.33	2015-03-15	15:45
durian	four	444.4	2015-04-15	16:50

In general, selection should match the behaviors of the Polars DataFrame.select() method.

pl_df.select(cs.starts_with("c") | cs.starts_with("f")).columns

['char', 'fctr']

See the Selectors page in the polars docs for more information on this.

Using functions

A function can be used to select columns. It should take a column name as a string and return True or False.

gt_ex.cols_move_to_start(columns=lambda x: "c" in x)

char	fctr	num	date	time
apricot	one	0.1111	2015-01-15	13:35
banana	two	2.222	2015-02-15	14:40
coconut	three	33.33	2015-03-15	15:45
durian	four	444.4	2015-04-15	16:50