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LabPlot VS GenStat

Compare LabPlot VS GenStat and see what are their differences

LabPlot logo LabPlot

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

GenStat logo GenStat

GenStat is a statistical and data analysing tools that is basically the pack of statistic tools and packages.
  • LabPlot Landing page
    Landing page //
    2022-02-14
  • GenStat Landing page
    Landing page //
    2023-07-26

LabPlot videos

Your First Data Import and Visualization in LabPlot

More videos:

  • Review - LabPlot, interactive graphing and analysis of scientific data - Garvit Khatri - FOSSASIA Summit 2016
  • Review - Data Picker - Simplified Workflow in LabPlot 2.7
  • Review - Histogram in LabPlot (KDE edu)

GenStat videos

Multi-treatment meta analysis with Genstat

More videos:

  • Review - Genstat Installation Window
  • Review - Importing an Excel Data Range into Genstat

Category Popularity

0-100% (relative to LabPlot and GenStat)
Technical Computing
75 75%
25% 25
Business & Commerce
0 0%
100% 100
Numerical Computation
100 100%
0% 0
Office & Productivity
68 68%
32% 32

User comments

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What are some alternatives?

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

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

MyAnalytics - MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.

GnuPlot - Gnuplot is a portable command-line driven interactive data and function plotting utility.

Azure Databricks - Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.

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

GraphPad Prism - Overview. GraphPad Prism, available for both Windows and Mac computers, combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization.