This app provides an interface to customize boxplots and perform statistical analysis among data.
1K téléchargements
Mise à jour 25 mars 2022

Afficher la licence

Note de l’éditeur : This file was selected as MATLAB Central Pick of the Week

Main features:
Reads data from tables stored in .mat files
Reads data from tables stored in .xlsx files (one table per sheet)
Data loaded is shown within the app in a table
Boxplots are organized by conditions and coloured by groups. User can pick them in the desired order.
User is able to dinamically select groups and conditions from table columns
High customization (e.g. scatter, jitter, transparency, outliers, mean, group linking lines)
Easily pickable colours and color maps
Plot can be opened as a separate figure for further customization
Anova/Kruskalwallis and post-hoc test performed between groups and/or conditions
Statistical results shown in a table with significant values highlighted
Significance symbols (asteriscs/bullets) can be automatically added to the plot at customizable y positions
Allows checking data normality (visually + Shapiro-Wilk test)

Citation pour cette source

Carlos Borau (2024). BoxPlotPro (, MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2020a
Compatible avec les versions R2020a et ultérieures
Plateformes compatibles
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Publié le Notes de version

Added "auto-refresh" toggle button next to PLOT button. Now all plot options trigger the plot function when changed.
Layout and minor bugs fixing.


Fixed some scroll bugs with newer versions of Matlab.
Order of category picking now determines the order in the plot (before it was done alphabetically)


added the option to choose between parametric (anova) and non-parametric (kruskalwallis) tests.
added a button to check data normality


now, outliers w paramenter has no superior limit to allow including all points inside the whiskers


Added outliers w parameter. Points are outliers if they are greater than q3 + w × (q3 – q1) or less than q1 – w × (q3 – q1)


New screenshot