GT.sub_zero

GT.sub_zero(self, columns=None, rows=None, zero_text='nil')

Substitute zero values in the table body.

Wherever there is numerical data that are zero in value, replacement text may be better for explanatory purposes. The sub_zero() function allows for this replacement through its zero_text= argument.

Parameters

Name	Type	Description	Default
`columns`	`SelectExpr`	The columns to target. Can either be a single column name or a series of column names provided in a list.	`None`
`rows`	`int` \| `list`[`int`] \| None	In conjunction with `columns=`, we can specify which of their rows should be scanned for zeros. The default is all rows, resulting in all rows in all targeted columns being considered for this substitution. Alternatively, we can supply a list of row indices.	`None`
`zero_text`	`str`	The text to be used in place of zero values in the rendered table. We can optionally use the `md()` or `html()` functions to style the text as Markdown or to retain HTML elements in the text.	`'nil'`

Returns

Type	Description
GT	The GT object is returned. This is the same object that the method is called on so that we can facilitate method chaining.

Examples

Let’s generate a simple table that contains an assortment of values that could potentially undergo some substitution via the sub_zero() method (i.e., there are two 0 values). The ordering of the fmt_scientific() and sub_zero() calls in the example below doesn’t affect the final result since any sub_*() method won’t interfere with the formatting of the table.

from great_tables import GT
import polars as pl

single_vals_df = pl.DataFrame(
    {
        "i": range(1, 8),
        "numbers": [2.75, 0, -3.2, 8, 1e-10, 0, 2.6e9]
    }
)

GT(single_vals_df).fmt_scientific(columns="numbers").sub_zero()

i	numbers
1	2.75
2	nil
3	−3.20
4	8.00
5	1.00 × 10⁻¹⁰
6	nil
7	2.60 × 10⁹