Beanplot: A Boxplot Alternative for Visual Comparison of Distributions

By Peter Kampstra. 2008

732 citations recorded by the source corpus.

Boxplots and variants thereof are frequently used to compare univariate data. Boxplots have the disadvantage that they are not easy to explain to non-mathematicians, and that some information is not visible. A beanplot is an alternative to the boxplot for visual comparison of univariate data between groups. In a beanplot, the individual observations are shown as small lines in a one-dimensional scatter plot. Next to that, the estimated density of the distributions is visible and the average is shown. It is easy to compare different groups of data in a beanplot and to see if a group contains enough observations to make the group interesting from a statistical point of view. Anomalies in the data, such as bimodal distributions and duplicate measurements, are easily spotted in a beanplot. For groups with two subgroups (e.g., male and female), there is a special asymmetric beanplot. For easy usage, an implementation was made in R.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d3b30b9b81d4e9367a496040fe546401df895581

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Citations in the corpus

An Empirical Comparison of Model Validation Techniques for Defect Prediction Models (2017, background): “…estimates differ from the model performance on unseen data?) and variance (i.e., how much do performance estimates vary when the experiment is repeated on the same data?) of model validation techniques when they are applied to defect prediction models [34], [68], [73], [77], [92], [114].”
When (ish) is My Bus?: User-centered Visualizations of Uncertainty in Everyday, Mobile Predictive Systems (2016, background): “For example, density plots encode the PDF as distance from the x-axis, violin plots encode it as width [1,22,31], and gradient plots encode it as opacity.”
Evaluation of CADD Scores in Curated Mismatch Repair Gene Variants Yields a Model for Clinical Validation and Prioritization (2015, unknown): “Beanplot [Kampstra, 2008] showing the data points (green) and density estimation (purple) of the scaled CADD C-score per InSiGHT class.”
Letter-Value Plots: Boxplots for Large Data (2017, background): “The overview article by Wickham and Stryjewski (2012) discusses these alternatives, in particular vase (Benjamini 1988), violin (Hintze and Nelson 1998), bean (Kampstra 2008), box-percentile (Esty and Banfield 2003), and high-density region (Hyndman 1996) plots.”
Raincloud plots: a multi-platform tool for robust data visualization (2018, methodology): “To this end, similar but distinct plotting strategies include beanplots (Kampstra, 2008), estimation plots (Ho, Tumkaya, Aryal, Choi, & ClaridgeChang, 2018), pirateplots (Phillips, 2016), sinaplots (Sidiropoulos et al.”
Income projections for climate change research: A framework based on human capital dynamics (2017, background): “Beanplots (see Kampstra (2008)) can be interpreted as density trace plots and have clear advantages as compared to boxplots when it comes to representing graphically data whose distribution is multi-modal.”
Convergent contemporary software peer review practices (2013, methodology): “For each finding, we place it in the context of the Software Engineering literature on peer review, summarize it in a “Convergent Practice” box, and then discuss the evidence that we have for each practice.”