Software Alternatives, Accelerators & Startups

LabPlot VS ggplot2

Compare LabPlot VS ggplot2 and see what are their differences

LabPlot logo LabPlot

LabPlot is a KDE-application for interactive graphing and analysis of scientific data.

ggplot2 logo ggplot2

Application and Data, Libraries, and Charting Libraries
  • LabPlot
    Image date //
    2024-09-02
  • LabPlot
    Image date //
    2024-09-02
  • LabPlot
    Image date //
    2024-09-02
  • LabPlot
    Image date //
    2024-09-02
  • LabPlot
    Image date //
    2024-09-02
  • LabPlot
    Image date //
    2024-09-02
  • LabPlot
    Image date //
    2024-09-05
  • LabPlot
    Image date //
    2024-09-05
  • LabPlot
    Image date //
    2024-09-05

LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone and trusted by professionals.

FEATURE HIGHLIGHTS

  • High-quality data visualization and interactive plotting
  • Data analysis, statistics, nonlinear regression, curve and peak fitting
  • Fast computing with interactive notebooks (for Python, R, Julia, Maxima and more)
  • Data extraction from images (Plot Digitizer)
  • Smooth data import and export to and from multiple formats (CSV, JSON, ODS, XLSX, Origin, SAS, Stata, SPSS, MATLAB, SQL, MQTT, BLF, HDF5, FITS, ROOT (CERN), LTspice, Ngspice and more)
  • Available for Windows, macOS, Linux, FreeBSD, Haiku, GNU

A full list of features: https://labplot.kde.org/features

Video tutorials: https://www.youtube.com/@LabPlot

Communication channels: https://labplot.kde.org/support

Get it here: https://labplot.kde.org/download

  • ggplot2 Landing page
    Landing page //
    2023-02-27

LabPlot features and specs

  • Open Source
    LabPlot is free and open source, allowing users to modify and distribute the software without any cost.
  • Integration with KDE
    LabPlot is part of the KDE software collection, offering seamless integration with other KDE applications and a consistent look and feel.
  • Multiplatform Support
    LabPlot is available on various platforms, including Linux, Windows, and macOS, making it accessible to a wide range of users.
  • Extensive Plotting Features
    LabPlot offers a wide range of plotting capabilities, including 2D and 3D plots, which can accommodate diverse scientific and engineering needs.
  • Customizability
    Users can customize plots extensively in LabPlot, adjusting parameters such as plot style, color, and data presentation to suit their specific needs.

Possible disadvantages of LabPlot

  • Steeper Learning Curve
    Due to its comprehensive features, new users might find LabPlot challenging to learn and may require time to become proficient.
  • Limited Community Support
    While there is a community around LabPlot, the size is relatively small compared to more widely used plotting tools, potentially limiting peer support.
  • Performance Issues with Large Datasets
    LabPlot may experience performance slowdowns when handling very large datasets, which can hinder productivity for users working with such data.
  • Less Frequent Updates
    LabPlot may receive updates less frequently than some commercial software, possibly affecting the pace of new feature integration.

ggplot2 features and specs

  • Elegant Data Visualization
    ggplot2 offers a high level of abstraction for creating complex multi-layered graphics using a coherent and consistent syntax.
  • Grammar of Graphics
    It is built around the Grammar of Graphics, allowing users to build plots by combining different components in a clear and structured manner.
  • Extensibility
    ggplot2 is highly extensible, enabling users and developers to create their own geoms, stats, and themes.
  • Integration with Tidyverse
    It is part of the tidyverse, thus integrating smoothly with other tools and packages for data manipulation and cleaning, like dplyr and tidyr.
  • Wide Range of Plot Types
    Users can create a diverse array of plots from simple bar graphs to complex multi-panel plots seamlessly.

Possible disadvantages of ggplot2

  • Steep Learning Curve
    New users may find the syntax and grammar approach unfamiliar and difficult initially, which can make simple plotting tasks feel complicated.
  • Performance with Large Datasets
    Rendering plots with ggplot2 can be slower than base R graphics when dealing with very large datasets.
  • Complex Customization
    While customization is robust, it can become cumbersome and verbose for users needing plots with high levels of customization.
  • Limited Interactivity
    ggplot2 primarily focuses on static plotting; additional libraries are needed to create interactive plots.

LabPlot videos

How to fit a curve using LabPlot

More videos:

  • Tutorial - Quick Statistics and Visual Overview of Data in LabPlot
  • Tutorial - How to export publication-quality plots from LabPlot
  • Tutorial - Your First Data Import and Visualization in LabPlot

ggplot2 videos

Learn R: An Introduction to ggplot2

More videos:

  • Review - Review ggplot2 Line Graph Exercise
  • Review - Code-through and review of Ggplot2 in 2

Category Popularity

0-100% (relative to LabPlot and ggplot2)
Technical Computing
80 80%
20% 20
Data Visualization
0 0%
100% 100
Office & Productivity
100 100%
0% 0
Data Dashboard
0 0%
100% 100

User comments

Share your experience with using LabPlot and ggplot2. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare LabPlot and ggplot2

LabPlot Reviews

  1. LabPlot provides extensive capabilities for data import and export, along with tools for analysis, curve fitting, nonlinear regression and interactive visualization, including live data support. Users can export graphs in various formats and utilize a built-in plot digitizer to extract data from existing charts. Additionally, if users are familiar with programming languages such as Python or R, they can leverage these within LabPlot's interactive notebooks.

ggplot2 Reviews

5 Best Python Libraries For Data Visualization in 2023
ggplot is a system for creating graphics declaratively. Itโ€™s based on the Grammar of Graphics of R programming language and is tightly integrated with Pandas. ggplot just requires you to declare how to map the variables to aesthetics and primitives to use and handles the rest automatically. Remember, ggplot is not recommended for creating highly customized graphics.
Top 8 Python Libraries for Data Visualization
Ggplot is a Python data visualization library that is based on the implementation of ggplot2 which is created for the programming language R. Ggplot can create data visualizations such as bar charts, pie charts, histograms, scatterplots, error charts, etc. using high-level API. It also allows you to add different types of data visualization components or layers in a single...

Social recommendations and mentions

Based on our record, ggplot2 seems to be more popular. It has been mentiond 12 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

LabPlot mentions (0)

We have not tracked any mentions of LabPlot yet. Tracking of LabPlot recommendations started around Mar 2021.

ggplot2 mentions (12)

  • Plotnine
    Plotnine is heavily inspired by the ggplot2 library, which uses the + operator in the same way: https://ggplot2.tidyverse.org/#usage. - Source: Hacker News / about 2 months ago
  • Ask HN: What plotting tools should I invest in learning?
    For random, quick and dirty, ad-hoc plotting tasks my default is GNUPlot[1]. Otherwise I tend to use either Python with matplotlib, or R with ggplot2. I keep saying I'm going to invest the time to properly learn D3[4] or something similar for doing web-based plotting, but somehow never quite seem to find time to do it. sigh [1]: http://www.gnuplot.info/ [2]: https://matplotlib.org/ [3]:... - Source: Hacker News / about 3 years ago
  • Relative frequency of letters in five-letter English words (Wordle aid) [OC]
    I got the list of five-letter words from the words package in R, created the QWERTY keyboard grid with base R and tibble, and visualized the data with geom_tile in the ggplot2 package. Source: about 3 years ago
  • [OC] U.S. News & World Report Best Colleges: 2002 to 2023
    Thanks, it's an interesting idea! I definitely could implement this with scale_fill_gradientn) in ggplot2. Source: about 3 years ago
  • Facts about Aaron Boone's Ejections as Manager
    I used the ggplot2 package in R to create these figures. Source: about 3 years ago
View more

What are some alternatives?

When comparing LabPlot and ggplot2, you can also consider the following products

SciDaVis - SciDAVis is a free application for Scientific Data Analysis and Visualization.

Matplotlib - matplotlib is a python 2D plotting library which produces publication quality figures in a variety...

RJS Graph - RJS Graph is an artificial intelligence-based data management platform that allows users or developers to organize the data by manipulating the binaries, scientific, mathematical, and other insights with accurate results.

Plotly - Low-Code Data Apps

OriginPro - OriginLab OriginPro is a comprehensive interface-based data management platform that allows users to calculate or visualize the data insights in various fields like engineering, scientific domain, or multi-sector industrial stats.

Bokeh - Bokeh visualization library, documentation site.