Here's a summary of the themes expressed in the Hacker News discussion about LabPlot:
Database Connectivity Limitations and Expectations
A significant point of discussion revolves around LabPlot's database connectivity, specifically the perceived limitation to SQLite and user expectations for broader database support.
- RedShift1 expressed disappointment, stating, "Unfortunately the only database it supports is SQLite, I really wanted to hook this up directly to a database or REST API. Going back and forth between exporting files and importing them into LabPlot is just too much work..."
- This was met with surprise by esafak, who retorted, "Are you serious? 'Why don't you copy your data into a new database just to visualize it?'"
- mouz attempted to clarify by linking to documentation, asking, "The manual says otherwise: ... Are you talking about something else?"
- RedShift1 doubled down on their experience, saying, "I installed it and the only choice I got for selecting a database was SQLite."
- ognarb offered a potential explanation for this discrepancy: "On linux, you are also missing the db drivers for Qt for other database types."
- Later in the thread, carelyair suggested further desirable integrations: "Would be really helpful to add support for access to S3 buckets and other clouds object store. Iceberg support would also be super helpful as it is gaining lots of traction."
Target Audience and Use Cases: GUI-centric Data Visualization
Several users discussed who LabPlot is for, highlighting its appeal to those who prefer a graphical user interface (GUI) for data visualization and analysis, particularly those who may not want or need to extensively program.
- jtrueb questioned the motivation for using LabPlot when other powerful tools like Julia, Matlab, R, and Python exist, asking, "If you already have lab code in Julia, Matlab, R, Python, Excel, etc., what is the motivation to use this tool? Is this hot in a specific community?"
- jabl provided context, suggesting LabPlot fills a niche: "I suppose this is a FOSS solution for the roughly same space occupied by commercial tools like Origin, that are very popular in some scientific communities. They can be useful if you have other tools (e.g. measurement software) that already produces the data you want, and you just want a GUI tool to create plots, and maybe do some simple things like least squares curve fitting etc. If you already do a lot of data wrangling in something with a programming language and plotting libraries accessible from said language, like the ones you mention, yeah, this is not the tool for you."
- ajot confirmed this, recalling its use: "It is! I remember using this (or SciDavis, a related project) a couple of years back in college. It was not as powerful as Origin 10 years ago, but it ran on Linux. This is great for people who don't know nor want to learn to program."
- pvitz agreed: "Same experience here! We used Origin and/or QtiPlot in a physics lab for the graphs and quick regressions."
- goku12 offered an extensive explanation grounded in real-world engineering scenarios, emphasizing the speed and interactivity required for analytical workflows: "The application we used was very similar to Labplot... You don't have to select each parameter by text or GUI. There must be a way to either quickly launch a visualization or cycle through the parameters as the investigator closes each graph. You also don't have time to set zoom, pan and labels by text. It must be done using mouse (zoom & pan) and directly on the graph (labels and markers) in a WYSIWYG manner. And you don't want to run an FFT or a filter function, save the new series and then plot it - you want it done with a single menu selection. The difference is like using a C++ compiler vs Python in JupyterLab."
Comparison and Alternatives
Users frequently compared LabPlot to existing tools, both commercial and open-source, discussing their strengths and weaknesses.
- tonyarkles, who works with R, Python, Maxima, and MATLAB/Octave, saw potential value: "Having four completely different interfaces to these tools is a hassle. I'm also not a big fan of Jupyter and if this feels better for me it might be a decent Jupyter replacement even without the cross-language stuff."
- nixobject, a biostatistician, appreciated the complexity of statistical modeling: "I just needed to stop and say: as a biostatistician, boy do I love a beautiful complex longitudinal design: I remember my old professor asking us how at this point we would decompose into cross-sectional and longitudinal effects, Lord's paradox, etc... and I still don't fully understand Lord's paradox as well as I should."
- SubiculumCode detailed advanced statistical plotting needs, illustrating the complexity they handle in R: "Sure ggplot, for example, is finicky, and you need to fuss over it to get the look you are wanting, but then again, it is very flexible. Most of these solutions get frustrating as soon as you want to do, for example, spaghetti plots of within subject repeated measures using age (not time-point) of accelerated longitudinal design data, with fixed effect plots on top."
- benzofuran suggested an alternative for a similar use case: "Sounds like plotjuggler (https://github.com/facontidavide/PlotJuggler) could be worth checking into as well for you."
- dima55 mentioned their current workflow: "Using vnlog for data storage (like what you described, but with better tooling support) and feedgnuplot/gnuplotlib for visualization. Works great. The learning curve is really easy, you can get going and start analyzing stuff FAST."
- wodenokoto expressed interest in a drag-and-drop functionality: "Haven't tried this tool yet, but if it lets me drag and drop my data and visuals, that sounds like a great addition to those tools."
- coldcode provided historical context on charting software evolution: "It's so interesting to see how much of a commodity charting/graphing has become. When we started building Deltagraph in late 1988, what we made become a kind of standard since we targeted Postscript and Illustrator output, and included almost every kind of chart we could find with ridiculous options for everything, so people used it world wide, especially if targeting print."
- dcreater lamented the continued prevalence of proprietary software: "And yet it's still not sufficiently commoditized and widespread. The majority of the working force is using proprietary solutions that are out of date - Tableau, JMP in HW engineering, SAS and Excel"
- tau255 shared their experience with related software: "I used SciDavis a lot and before that tried QtiPlot. When I had a chance to I used Origin. SciDavis was clunky and had some issues (liked to crash) but it worked well enough for what I wanted... There is also a AlphaPlot, a more or less alive fork of SciDavis. Still have its own issues but still has the same issue with yyyy-MM-dd hh:mm:ss.zzz dates. Other than that it is a useful bit of kit." They also praised gnuplot for batch processing: "But when I want to do some batch processing and generate multiple plots, automate and have it reproducible I go with gnuplot. The learning curve is steep, but after writing gnuplot scripts few time you just have a personal template and know relevant parts. It is really good."
- anigbrowl wished for clearer comparisons to existing tools: "Looks cool, but I wish there was a section explaining 'here's why it's better than matplotlib or [other popular charting tools]'. I looked through the feature list but I didn't feel like mentally constructing a comparison matrix. I see lots of things to like about it, but I would really appreciate case studies or something to explain why I might want to invest time in learning this new thing."
Documentation and User Experience Issues
Several commenters highlighted issues with LabPlot's documentation and overall user experience, particularly regarding import and external resource access.
- tau255 critiqued the documentation structure: "Tried LabPlot recently and had issues with csv import with datetime data not really recognising date and time series format even after using advanced import options and setting it myself manually. Tried to find some solutions, the LabPlot manual website is just a bunch of youtube videos [1]. That is really not helpful, I am not browsing manual to be forced to watch clips of what I already tried. Developers really need to think about making traditional manual."
The Role of LLMs in Data Visualization
The increasing capability of Large Language Models (LLMs) in generating code for data visualization was brought up as a potential factor influencing the utility of tools like LabPlot for some users.
- MostlyStable mused on the impact of LLMs: "I'm someone who enjoys figuring out the details of making a nice looking plot (in base R, I can't stand ggplot), but even as someone who enjoys it, LLMs are pretty much good enough that if I explain to them how I want the plot to look and how my data is structured, they can generate code that works first shot. It seems to me that, at this point, if you are already doing some coding in one of the above languages but either don't like or aren't comfortable making the plots using them, that LLMs can solve it for you."
- MostlyStable further elaborated on their preference against ggplot: "I think it's just too different from base R, and I had spent too long in base R before tidyverse/ggplot became a thing. By the time it came around, I was already good enough to do basically all my plotting without it, and having to learn an entirely new set of syntax just annoyed me. My reaction is much more emotional than rational."
- tonyarkles responded to this, sharing a contrasting experience with ggplot: "In a very similar way (with a different outcome), my first real introduction to R was due to the 'A Layered Grammar of Graphics' paper while doing some tangential research during grad school. I fell in love with the abstractions in the paper and reluctantly learned R so that I could get access to ggplot :)."
Licensing Clarity
A brief question was raised regarding the software's license, which was promptly answered.
- ntxvega1975 asked simply, "I can't tell what license is applicable."
- echoangle provided the answer fetched from the official website: "On https://labplot.org/frequently-asked-questions/, under "Under what license is LabPlot released?", it says this: > LabPlot is licensed under GNU General Public License, version 2.0 or later, so to put it in a few sentences: > You are free to use LabPlot, for any purpose > You are free to distribute LabPlot > You can study how LabPlot works and change it > You can distribute changed versions of LabPlot > In the last case you have the obligation to also publish the changed source code as GPL."