gnuplot
gnuplot
gnuplot
gnuplot
gnuplot
gnuplot
gnuplot
gnuplot
gnuplot
gnuplot
gnuplot

gnuplot

0 Reviews

FREE

App specs:

License

FREE

Version

gnuplot 5.4.8

LatestUpdate

Last updated

OS

Windows This is the portable version of the application. An installable version is also available

Language

EN

One way scientists, engineers or researchers can make more sense of the large chunk of data they manage is via graphic plots. Not only do graphs help you visualize the results better, but it can also help you detect patterns and trends.

gnuplot is a tool that addresses the aforementioned categories, as well as students and teachers in various scientific fields that entails working with large data. Considering that it has been under active development since 1986, it is a well-known name in the industry.

The program comes with a graphic interface and a CLI version, the consensus being that the latter provides more powerful tools. The GUI is more user-friendly and provides the means for entering commands as well as edit and manipulating data sets. You can load data from specific files, customize various aspects of the plots or specify the type of graph. The CLI does the same, with the distinction that it is better for automation and scripts.

Regardless of the data sources, the app allows you to create numerous 3D and 2D plots that can be annotated with labels, legends and other relevant elements. Depending on your field and type of data, you can create line plots, scatter plots, bar charts, histograms, surface plots, contour plots, pie charts, box plots or errors bars.

As previously mentioned, you can create scripts to use with the app, a feature that can help you automate mundane steps of the data analysis process. On the other hand, you need to have a good grasp of how to use certain commands to generate the optimal graphs, which can require some time and effort on your part.

Gnuplot is a reliable and versatile plot generating tool that can come in handy in numerous scientific fields that imply working with large data sets, including, but not limited to Physics, Engineering, Chemistry, Biology, Economics and Mathematics.

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