LabPlot Features
General Features
Project based management of data
Tree-like organization of created objects
Quick navigation, searching and filtering of objects using the Project Explorer
Easy customization of objects and methods using the Properties Explorer
Folders support for a better object management
Spreadsheet and Matrix – data-container serving as the data source used in data analysis and visualization
Spreadsheet linking to synchronize the number of rows across multiple spreadsheets
Worksheet – area for placing different visualization objects (plots, labels, images, etc) supporting different layouts, zooming and navigation mode
Notes – a text container which can simply be used to write comments into a project
The undo history dialog
Locale-sensitive functionality
Autosave to prevent potential data loss
Support for CLI parameters (e.g. to start LabPlot directly in the Presenter Mode)
Support for multiple application color schemes, including dark themes
Customizable application layouts using a full featured window docking system
Data Visualization
High-quality, interactive and very fast data visualization optimized for large data sets
Arbitrary number of plots in the plot area
Highly configurable and publication-quality 2D Plots: scatter plots, line plots, histograms, box plots, bar plots, rug plots, KDE plots, Q-Q plots, Lollipop plots
Support for multiple, freely positionable axes, inverse axis scales and multiple ranges for plots
Smooth and fast zooming and navigation modes for plots
Function plotting with Cartesian, Polar and Parametric equations
Customizable and positionable plot legends, text labels, info elements, images, reference lines and reference ranges for plots
Color Maps Browser with an extensive support for scientific and color-vision deficiency friendly color schemes like ColorBrewer, ColorCET, Scientific Colour Maps, cocean, viridis
Multiple default and user-defined themes for Worksheets and plots, including Edward Tufte’s ‘Maximal Data, Minimal ink’ theme,
User-defined plot templates that make it easy to create and customize plots that are intended to be used multiple times
Cursor – tool to measure positions and distances in plots
Dynamic Presenter Mode for worksheets with the full-screen mode and the navigation panel
Sparklines in the header of a spreadsheet
Preview panel for all available worksheets in the project
Support for Latex syntax in plot labels, plot titles, Computational Notebooks and multiple dialogs
A possibility to use multiple LaTeX engines (LuaLaTex, pdfLaTex, LaTex)
Data Analysis and Statistics
Column statistics spreadsheet – child spreadsheet showing various statistical properties of the parent spreadsheet
Linear and non-linear regression analysis and curve fitting, support for several predefined and user-defined fit models – Basic Functions like polynomial, power or exponential; Peak Functions like Gaussian, Cauchy-Lorentz, Pseudo-Voigt, hyperbolic secant, logistic; Growth Functions like Gompertz, Hill, Gudermann, inverse tangent, logistic and error functions; Statistical Functions like Gaussian, exponential, power, log-normal, binomial, Poisson, Rayleigh, Landau, Pareto, Weibull and many more
Maximum Likelihood estimation for fitting statistical distributions like Gaussian Poisson, Exponential, Laplace, Binomial, Cauchy-Lorentz and more
Baseline subtraction (background correction) with the asymmetrically re-weighted penalized least squares (arPLS) algorithm
Data reduction by removing data points using multiple algorithms (Douglas-Peucker, Visvalingam-Whyatt, Reumann-Witkam, Opheim, Lang and other algorithms)
Numerical differentiation (up to the 6th order) and numerical integration (rectangular, trapezoid and Simpson methods)
Smoothing of data with moving average, Savitzky-Golay and percentile filter methods
Interpolation of data, support for many methods (linear, polynomial, splines, piecewise cubic Hermite polynomial, etc.)
Fourier transform of the input data with support for many different window functions (Welch, Hann, Hamming, Blackman, etc.)
Fourier Filter – low-pass, high-pass, band-pass and band-reject filters of different types (Butterworth, Chebyshev I+II, Legendre, Bessel-Thomson)
Hilbert Transform including envelope
Convolution and de-convolution of data sets (sampling interval, linear/circular, normalization, wrap, standard kernel)
Auto-correlation and cross-correlation of data sets (sampling interval, linear/circular, normalization)
Quick statistical previews available in spreadsheets that consist of multiple location, dispersion and shape measures for quantitative and categorical data and statistical plots like histograms, KDE plots, Q-Q plots, box plots, Pareto plot
Extensive parser for mathematical expressions supporting a great number of functions and constants used for data generation in spreadsheets and further data analysis and visualization
Function values dialog (editor) with the syntax highlighting and support for reference to arbitrary cells of columns and other moving functions
Computational Notebooks
An interactive and animated front-end to powerful mathematics and statistics packages and programming languages like Maxima, Octave, R, Scilab, Sage, KAlgebra, Qalculate!, Python, Julia, Lua
Support for using multiple notebooks and languages at the same time
Notebook variables holding array-like data (Maxima lists, Python lists and tuples, etc.) can be used as the source for interactive plots
Ability to show variable statistics and to plot data from the context menu in the project explorer for variables created in a Notebook
Extensive edition capability
Support for plotting
Markdown and LaTeX syntax
Ability to read Jupyter and Cantor projects
Syntax highlighting
Integrated help for CAS systems and programming languages (downloading, searching, navigating documentation etc.)
Support for exporting Notebooks to PDF
Plot Digitization
Easy extraction of data from external image files
Cartesian, polar, logarithmic and ternary coordinate system
Symmetric and asymmetric error bars
Manual point-by-point extraction of data points or (semi-)automated extraction of curve segments
Multiple curves on the image can be read
Basic image editing capabilities to reduce the image information to the relevant minimum
Extracted data is added to a spreadsheet and is directly ready to use
Data Generation and Processing
Support for Tidy Data in spreadsheets, i.e. variables are stored in columns, each observation is stored in a row and the values for each observation is stored in its respective cell
Quantitative and categorical data types: Integer, Double, Big Integer (64 bit), Date and Time, Text (Categorical)
Data sorting
Extended search and replace with the support for regular expressions
Data transformation, normalization and standardization
Random number generation with support for multiple probability distributions
Data sampling (random and periodic methods)
Data ‘flattening’ – converting pivoted data to the column-based format
Support for dropping and masking of data in spreadsheets
Heatmap formatting with the support for scientific and color-vision deficiency friendly color maps
Documentation and Support
Extensive user manual and tutorials
Short, instructional video tutorials
Project examples and educational data sets available through LabPlot’s dialogs
Relation type based gallery of plots with downloadable project files
LabPlot is an open-source project offered in multiple languages
Available for Windows, macOS, Linux, FreeBSD and Haiku
LabPlot team offers multiple channels of communication