This article highlights the critical role of data visualization in applied economics education and outreach. We first outline some general principles for teaching graph literacy and data visualization principles in and out of the classroom. We then discuss the mechanics of visualizing data—collection, preparation, and visualization—with an emphasis on how instructors can teach each step using the R and/or Python statistical environments. We ultimately contend that the requisite skills for successful data visualization are indispensable for students trained in today’s agricultural and applied economics programs to communicate their research effectively.

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