Custom Row Selector in Great Tables

This short post shows how we can create custom row selectors in Great Tables by leveraging the row index. While it may or may not be adopted by the team, I thought it would be fun to document it here on the blog.

I recently created a utility called every_n_row(), designed to work with both Pandas and Polars DataFrames (support for pyarrow is still under investigation). With every_n_row(), we can easily target alternating rows—for example, select odd rows using every_n_row(2) and even rows using either every_n_row(2, 1) or ~every_n_row(2).

import polars as pl

from great_tables import GT, every_n_row, loc, style
from great_tables.data import countrypops

df_pd = countrypops.sample(5).loc[:, ["country_name", "year", "population"]]
df_pl = pl.from_pandas(df_pd)

(
    GT(df_pd)
    .tab_style(style=style.fill("lightblue"), locations=loc.body(rows=every_n_row(2)))
    .tab_style(style=style.fill("papayawhip"), locations=loc.body(rows=every_n_row(2, 1)))
    .opt_stylize(style=3, color="pink")
)

(
    GT(df_pl)
    .tab_style(style=style.fill("lightblue"), locations=loc.body(rows=every_n_row(2)))
    .tab_style(style=style.fill("papayawhip"), locations=loc.body(rows=~every_n_row(2)))
    .opt_stylize(style=3, color="pink")
)

Disclaimer

This post was drafted by me, with AI assistance to refine the content.