Data visualizations and infographics

Data visualizations push our content beyond the boundaries of plain text. They illustrate our story narratives and in some cases, they are the story. Understanding how to responsibly wield their visual power is essential.

The Visual Style Guide

This Guide will help creators make charts and graphics that are meaningful and responsible. The intent of this Guide is to help creators understand the values we at AP instill in our graphics.

Simple rules make all the difference: always use data from trusted, authoritative sources, establish a focal point, create a visual hierarchy within your work — and remember to have fun doing it!

Visual Guide Cover Edit v2

Essential structure

Your graphic should be accompanied by a captivating headline that pulls in readers. Don’t simply repeat the existing text story headline, craft a new headline that summarizes the main point of the graphic.

Descriptive intros are welcome, but not always necessary, and the same applies to subheads. Remember to include a source line and any footnotes to provide readers with full transparency about information sources.

Standard markup

The magic of color

The tones and hues of your color choices can provide focus and clarity within a data visualization. However, when misused or misapplied, they can also misrepresent your data, or worse — run the risk of being offensive.

The Guide outlines the standard colors and gradients that should be used in our graphics. However, this list is not finite, and creativity is always encouraged.

Gradients

Accessibility for all

Hundreds of millions of people across the world have a type of color vision deficiency. We must design responsibly and take this into consideration in all our work.

The Guide touches on best practices using our brand set of AP colors and supplements them with a few others where needed. Sites like Viz Palette can provide additional guidance for making responsible color choices.

Colorblind

Best practices in charting

Each chart type has unique rules and best practices for building responsible data visualizations. Knowing how to leverage the characteristics of your desired chart type is critical, so that you can convey data effectively and clearly to readers.

Best practices