LabPlot

LabPlot

Screenshot of LabPlot of 2022
Original author(s)	Stefan Gerlach
Developer(s)	KDE
Initial release	2001 (2001) (version 0.1, under the name QPlot) 2003 (2003) (version 1.0, renamed to LabPlot)
Stable release	2.11.1 / 16 July 2024 (2024-07-16)
Repository	invent.kde.org/education/labplot
Written in	C, C++
Operating system	Microsoft Windows OS X Linux FreeBSD Haiku
Type	Scientific plotting Data analysis Curve fitting Regression analysis Statistical analysis Data processing Plot digitization Notebook interface Real-time data
License	GPL-2.0-or-later
Website	labplot.kde.org

LabPlot is a free and open-source, cross-platform computer program for interactive scientific plotting, curve fitting, nonlinear regression, data processing and data analysis. LabPlot is available, under the GPL-2.0-or-later license, for Windows, macOS, Linux, FreeBSD and Haiku operating systems.

It has a graphical user interface, a command-line interface and an interactive and animated notebook interface to mathematical and statistical packages and programming languages.

Community

The LabPlot team promotes a collaborative community through various communication channels. The developers strongly support the idea of mentorship of students and actively participate in such programs as the Season of KDE (SoK) or Google Summer of Code .

User privacy and data confidentiality

The LabPlot team aims at protecting users privacy and data confidentiality. LabPlot is designed to be compliant with KDE Telemetry Policy, which forbids the usage of unique identification.

General features

LabPlot is a project-based data management, visualization and analysis tool with a tree-like structure for organizing objects. It features data containers like Spreadsheets and Matrices, and a Worksheet for flexible visualization. The program offers Notes for annotations, undo history, autosave, and locale-sensitive features. It supports command-line parameters, multiple color schemes, and customizable layouts through a window docking system, providing a comprehensive and tailored user experience for data analysis and visualization.

Data visualization

LabPlot is a powerful data visualization and analysis tool designed for large datasets. It offers a wide range of 2D plotting options, including scatter plots, line plots, bar plots, histograms, box plots, rug plots, KDE plots, Q-Q plots, Pareto plots, sparklines and Lollipop plots, with extensive customization capabilities. The software supports multiple axes, flexible positioning of elements, and smooth navigation. It provides various color map options, user-defined themes, and advanced features like LaTeX support. Balancing analytical power with user-friendliness, this versatile tool is suitable for both casual users and professionals in scientific and technical fields.

Data analysis and statistics

The program features a column statistics spreadsheet that details statistical properties and excels in regression analysis with both linear and non-linear curve fitting using the Levenberg–Marquardt algorithm, supporting numerous predefined and user-defined models. It includes Maximum likelihood estimation for fitting various statistical distributions and offers advanced data processing like baseline subtraction, data reduction (line simplification) with e.g. the Ramer–Douglas–Peucker algorithm, numerical differentiation and integration, and data smoothing. Sophisticated signal processing functions such as Fourier transforms and filtering, Hilbert transforms, convolution, and correlation analyses are supported. Quick statistical previews and visualizations are available for quantitative and categorical data. Enhanced functionality includes a mathematical expression parser and a function values dialog with syntax highlighting for complex data generation and manipulation.

Notebook interface

Labplot features an interactive and animated computational notebook that integrates with mathematics and statistics packages and programming languages like Python, R, Julia, Maxima, GNU Octave, Scilab, SageMath, KAlgebra, Qalculate!, Lua. It supports multiple notebooks and languages simultaneously, enhancing productivity. Users can create interactive plots from notebook variables and display statistics and plots directly from the context menu. The program offers extensive editing capabilities, robust plotting, Markdown, and LaTeX support. It can read Jupyter and Cantor projects, provides syntax highlighting, integrated help, and supports exporting notebooks to PDF for easy sharing and presentation.

Data import and export

LabPlot offers extensive features for data handling and analysis. It has no practical limits on data size other than the physical constraints of your computer. LabPlot supports importing various file formats like CSV, Microsoft Excel, ODF, SAS, SPSS, MATLAB, SQL, JSON, binary files, HDF5, MQTT, FITS, NetCDF, ROOT (CERN), LTspice, Ngspice and more, ensuring compatibility with diverse data sources. Real-time data can be read through Unix/ UDP/ TCP sockets and serial ports. Users can export data to formats such as PDF, PNG, JPG, SVG, and BMP, or directly to the clipboard, and print notes, worksheets, and plots. Data can be exported to CSV, Microsoft Excel, SQL databases, and LaTeX tables. The drag and drop functionality and templates for import filters simplify the process. Sharing the project via email, Nextcloud, etc. directly from the main menu is also supported. Additionally, the program includes nearly 2000 real-world data sets, making it a valuable resource for educators and students.

Plot digitization

LabPlot efficiently extracts and analyzes data from image files across various coordinate systems. It supports error bar analysis and offers both manual and automated data extraction methods. The software can process multiple curves from a single image, includes basic image editing tools, and integrates extracted data into spreadsheets for immediate use. These features significantly streamline the data processing workflow, saving time and effort for users.

Data generation and processing

LabPot offers a robust suite of features for enhanced data management and analysis in spreadsheets. It adheres to Tidy Data principles, supports various data types, and provides efficient sorting and search capabilities. The software includes tools for data transformation, normalization, and standardization, as well as random number generation and sampling methods. It offers functionality to restructure pivoted data, selectively drop or mask data, and create heat map visualizations with color-vision deficiency friendly options. This versatile tool caters to data scientists, analysts, and researchers across various fields.

Documentation

LabPlot features a user guide, tutorials, and instructional videos to facilitate learning. Users can access project examples and educational data sets for hands-on experience. The software includes a gallery of plots with downloadable project files, allowing for customization and exploration of visualization options. It is available in multiple languages.

History

LabPlot was initiated by Stefan Gerlach, a scientist and IT administrator at the University of Konstanz.

External links

• LabPlot Homepage
• LabPlot source code at KDE invent
• LabPlot project page at Source Forge
• LabPlot account at Mastodon
• LabPlot account at X
• LabPlot tutorials on YouTube
• LabPlot tutorials on PeerTube
• LabPlot account at Lemmy
• LabPlot room on Matrix

See also

• List of statistical software
• List of information graphics software
• Comparison of numerical-analysis software