For almost any chart, reach for viridis — it is perceptually uniform, colorblind-safe, and still readable in greyscale, so you rarely go wrong with it. When you need curated sequential, diverging, or qualitative sets (thematic maps, grouped bars), use RColorBrewer. Go beyond those two only for a specific look — scientific-journal (ggsci), Wes Anderson, or the base-R classics. Avoid plain rainbow() for data: it is not perceptually uniform and breaks under colorblindness.

viridis and its variants (magma, plasma, inferno, cividis) are colorblind-safe by design. In RColorBrewer, restrict yourself to the palettes flagged safe by display.brewer.all(colorblindFriendly = TRUE). Whatever you pick, sanity-check it the way the colorblind-safe section shows — simulate deuteranopia and view the plot in greyscale — and never rely on color as the only signal.

Map the palette to the relevant scale. For a discrete grouping use scale_color_viridis_d() / scale_fill_viridis_d(), scale_color_brewer(palette = "Set2"), or a manual vector with scale_color_manual(values = my_colors); for a numeric variable use the _c twins (scale_fill_viridis_c()). The dedicated ggplot2 Colors lesson covers color vs fill, coloring by group, and continuous gradients in full.