Become Competent within One Day in Generating Boxplots and Violin Plots for a Novice without Prior R Experience

The boxplot is a powerful visualization tool of sampled continuous data sets because of its rich information delivered, compact size, and effective visual expression. The advantage of boxplots is not widely appreciated. Many top journals suggest that boxplots should be used in place of bar charts, b...

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Published inMethods and protocols Vol. 3; no. 4; p. 64
Main Author Hu, Kejin
Format Journal Article
LanguageEnglish
Published MDPI 23.09.2020
MDPI AG
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Abstract The boxplot is a powerful visualization tool of sampled continuous data sets because of its rich information delivered, compact size, and effective visual expression. The advantage of boxplots is not widely appreciated. Many top journals suggest that boxplots should be used in place of bar charts, but have been wrongly replaced by bar charts. One technical barrier to the usage of boxplots in reporting quantitative data is that bench scientists are not competent in generating boxplots, and are afraid of R, a programming tool. This tutorial provides an effective training material in that even a novice without prior R experience can become competent, within one day, in generating professional boxplots. The available R scripts for boxplots are very limited in scope and are aimed at specialists, and the bench scientists have difficulty in following these scripts. This tutorial provides extensive step-by-step R scripts and instructions, as well as 29 illustrations for customizing every detail of the boxplot structures. Basic R commands and concepts are introduced for users without prior R experiences, which can be skipped by audiences with R knowledge. Violin plots are the enhanced version of boxplots, and therefore, this tutorial also provides a brief introduction and usage of the R package vioplot with one additional illustration. While the protocol is prepared for the newbies and trainees it will be a handy tool for infrequent users, and may benefit the experienced users as well since it provides scripts for customizing every detail of boxplots.
AbstractList The boxplot is a powerful visualization tool of sampled continuous data sets because of its rich information delivered, compact size, and effective visual expression. The advantage of boxplots is not widely appreciated. Many top journals suggest that boxplots should be used in place of bar charts, but have been wrongly replaced by bar charts. One technical barrier to the usage of boxplots in reporting quantitative data is that bench scientists are not competent in generating boxplots, and are afraid of R, a programming tool. This tutorial provides an effective training material in that even a novice without prior R experience can become competent, within one day, in generating professional boxplots. The available R scripts for boxplots are very limited in scope and are aimed at specialists, and the bench scientists have difficulty in following these scripts. This tutorial provides extensive step-by-step R scripts and instructions, as well as 29 illustrations for customizing every detail of the boxplot structures. Basic R commands and concepts are introduced for users without prior R experiences, which can be skipped by audiences with R knowledge. Violin plots are the enhanced version of boxplots, and therefore, this tutorial also provides a brief introduction and usage of the R package vioplot with one additional illustration. While the protocol is prepared for the newbies and trainees it will be a handy tool for infrequent users, and may benefit the experienced users as well since it provides scripts for customizing every detail of boxplots.
The boxplot is a powerful visualization tool of sampled continuous data sets because of its rich information delivered, compact size, and effective visual expression. The advantage of boxplots is not widely appreciated. Many top journals suggest that boxplots should be used in place of bar charts, but have been wrongly replaced by bar charts. One technical barrier to the usage of boxplots in reporting quantitative data is that bench scientists are not competent in generating boxplots, and are afraid of R, a programming tool. This tutorial provides an effective training material in that even a novice without prior R experience can become competent, within one day, in generating professional boxplots. The available R scripts for boxplots are very limited in scope and are aimed at specialists, and the bench scientists have difficulty in following these scripts. This tutorial provides extensive step-by-step R scripts and instructions, as well as 29 illustrations for customizing every detail of the boxplot structures. Basic R commands and concepts are introduced for users without prior R experiences, which can be skipped by audiences with R knowledge. Violin plots are the enhanced version of boxplots, and therefore, this tutorial also provides a brief introduction and usage of the R package vioplot with one additional illustration. While the protocol is prepared for the newbies and trainees it will be a handy tool for infrequent users, and may benefit the experienced users as well since it provides scripts for customizing every detail of boxplots.
The boxplot is a powerful visualization tool of sampled continuous data sets because of its rich information delivered, compact size, and effective visual expression. The advantage of boxplots is not widely appreciated. Many top journals suggest that boxplots should be used in place of bar charts, but have been wrongly replaced by bar charts. One technical barrier to the usage of boxplots in reporting quantitative data is that bench scientists are not competent in generating boxplots, and are afraid of R, a programming tool. This tutorial provides an effective training material in that even a novice without prior R experience can become competent, within one day, in generating professional boxplots. The available R scripts for boxplots are very limited in scope and are aimed at specialists, and the bench scientists have difficulty in following these scripts. This tutorial provides extensive step-by-step R scripts and instructions, as well as 29 illustrations for customizing every detail of the boxplot structures. Basic R commands and concepts are introduced for users without prior R experiences, which can be skipped by audiences with R knowledge. Violin plots are the enhanced version of boxplots, and therefore, this tutorial also provides a brief introduction and usage of the R package vioplot with one additional illustration. While the protocol is prepared for the newbies and trainees it will be a handy tool for infrequent users, and may benefit the experienced users as well since it provides scripts for customizing every detail of boxplots.The boxplot is a powerful visualization tool of sampled continuous data sets because of its rich information delivered, compact size, and effective visual expression. The advantage of boxplots is not widely appreciated. Many top journals suggest that boxplots should be used in place of bar charts, but have been wrongly replaced by bar charts. One technical barrier to the usage of boxplots in reporting quantitative data is that bench scientists are not competent in generating boxplots, and are afraid of R, a programming tool. This tutorial provides an effective training material in that even a novice without prior R experience can become competent, within one day, in generating professional boxplots. The available R scripts for boxplots are very limited in scope and are aimed at specialists, and the bench scientists have difficulty in following these scripts. This tutorial provides extensive step-by-step R scripts and instructions, as well as 29 illustrations for customizing every detail of the boxplot structures. Basic R commands and concepts are introduced for users without prior R experiences, which can be skipped by audiences with R knowledge. Violin plots are the enhanced version of boxplots, and therefore, this tutorial also provides a brief introduction and usage of the R package vioplot with one additional illustration. While the protocol is prepared for the newbies and trainees it will be a handy tool for infrequent users, and may benefit the experienced users as well since it provides scripts for customizing every detail of boxplots.
Author Hu, Kejin
AuthorAffiliation Department of Biochemistry and Molecular Genetics, School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA; kejinhu@uab.edu
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boxplot
RStudio
violin plot
vioplot
Title Become Competent within One Day in Generating Boxplots and Violin Plots for a Novice without Prior R Experience
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