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With an accelerated pace of data accumulation in the economy, there is a growing need for data literacy and practical skills to make use of data in the workforce. Applied economics programs have an important role to play in training students in those areas. Teaching tools of data exploration and visualization, also known as exploratory data analysis (EDA), would be a timely addition to existing curriculums. It would also present a new opportunity to engage students through hands-on exercises using real-world data in ways that differ from exercises in statistics. In this article, we review recent developments in the EDA toolkit for statistical computing freeware R, focusing on the tidy verse package. Our contributions are three-fold; we present this new generation of tools with a focus on its syntax structure; our examples show how one can use public data of the U.S. Census of Agriculture for data exploration; and we highlight the practical value of EDA in handling data, uncovering insights, and communicating key aspects of the data.


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