LabPlot (labplot.org)

u/LabPlot@floss.social
54 posts · 55 comments

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@bigpEE in LabPlot you have a great control of graphing but your case is very specific and you'll still need some scripting to automate this workflow.

In LabPlot we allow to use the data analysis and graphing routines in external C++ applications via our SDK as described in https://docs.labplot.org/en/sdk.html.

For the next release we'll have Python bindings for this SDK and Python scripting within the application itself. You can check https://israelsgalaxy.hashnode.dev/gsoc24-final-blog-post to see what will become possible soon.

@blindbunny

#LabPlot isn't exactly an open-source #MATLAB, but it is a an open-source and cross-platform tool for visualizing and analyzing data.

It focuses on creating interactive scientific plots and offers features like curve fitting, Fourier and Hilbert transforms, data manipulation, and live data support.

Computing with e.g. #Python, #R, #Maxima is also possible with interactive notebooks available in LabPlot.

You can see a list of LabPlot features here:
➡️ https://labplot.org/features

@coucouf @europesays @labplot@lemmy.kde.social @dataisbeautiful

Thank you for your comment. For these types of charts describing variation in data, which also include upper and lower limits on the values that contain probable noise, not using 0 at the start on the y-axis makes sense, as it makes it easier to analyze this variation and detection of potential signals.

We believe that Howard Wainer certainly would not recommend blindly applying this principle to all cases.

@coucouf @europesays @labplot@lemmy.kde.social @dataisbeautiful

Let us reply by quoting Howard Wainer. In his well-known paper "How to Display Data Badly" he wrote:

"A second way to hide the data is in the scale. This corresponds to blowing up the scale (i.e., looking at the data from far away) so that any variation in the data is obscured by the magnitude of the scale. One can justify this practice by appealing to "honesty requires that we start the scale at zero," or other sorts of sophistry."

@europesays @labplot@lemmy.kde.social @dataisbeautiful

Simply asking two primary questions to guide any analysis will lead to a better understanding of variation and more effective decision making:

1️⃣ Is the process currently stable?
2️⃣ Based on this knowledge, what type of action makes sense?

👉 https://healthleadsusa.org/wp-content/uploads/2018/10/understanding-variation26-years-later.pdf

In this paper Thomas Nolan, Rocco J. Perla and Lloyd Provost explain why correctly assessing #variation is fundamental to sound decisions.

#DecisionMaking #Politics #Data #Business #News

@opensource @dumnezero

It depends on the expected functionality. You can check the existing features here:
➡️ https://labplot.org/features

We are currently working on expanding #LabPlot's functionality in these areas:

▶️ Live Data Analysis
▶️ #Python Scripting
▶️ Statistical Analysis
▶️ Quality Improvement Charts

@labplot@lemmy.kde.social

Since July you can enjoy the new 2.11.1 version of #LabPlot, an open-source data analysis and visualization software.

Check your current version and ask your package maintainer to provide the latest version for your #Linux and #FreeBSD distribution.

➡️ https://repology.org/project/labplot/versions

#DataAnalysis #Statistics #Research #Ubuntu #LinuxMint #ArchLinux #Slackware #Debian #Fedora #OpenSUSE #RedHat #HaikuOS #GNU #CentOS #FreeSoftware #OpenSource #Manjaro #Zorin #FOSS #FLOSS #KDE