Plotting is among the most effective ways to quickly and accurately describe a probability distribution. It makes often complex information accessible, enabling intuition for respective outcomes at a glance. Matters complicate, however, for mixed-type distributions. Mixed-type distributions contain both continuous and discrete components, and accurately portraying those on a single axis can prove difficult—misleading intuition as a consequence of pulling two otherwise disjoint components into focus together. This article examines the challenges of maintaining the simple, concise, and accurate format of traditional probability distribution plots for mixed-type distributions. We illustrate issues arising within this plot classification paradigm, and why a secondary axis is uniquely suited to improve its communication. An algorithm is devised to consistently scale such plots so that they better coincide with intuition. National Football League football starting field position, meteorological data, and financial instruments provide examples demonstrating effectiveness of this plot technique.

中文翻译：

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混合型分布图

绘图是快速准确描述概率分布的最有效方法之一。它通常可以访问复杂的信息，使对各自结果的直觉一目了然。然而，对于混合类型的分布，事情变得复杂。混合型分布同时包含连续和离散分量，在单个轴上准确描绘这些分量可能很困难——由于将两个原本不相交的分量集中在一起而导致误导直觉。本文探讨了保持混合类型分布的传统概率分布图的简单、简洁和准确格式的挑战。我们说明了这个情节分类范式中出现的问题，以及为什么辅助轴特别适合改善其交流。设计了一种算法来一致地缩放此类图，以便它们更好地符合直觉。美国国家橄榄球联盟足球起始场地位置、气象数据和金融工具提供了证明这种绘图技术有效性的示例。