what is gnu plot??

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Gnu plot

gnuplot is a command-line program that can generate two- and three-dimensional plots of functions, data, and data fits. It is frequently used for publication-quality graphics as well as education. The program runs on all major computers and operating systems (GNU/Linux, Unix, Microsoft Windows, Mac OS X, and others). It is a program with a fairly long history, dating back to 1986. Despite its name, this software is not distributed under the GNU General Public License (GPL),

Plotting Data with gnu plot

This tutorial is intended as a supplement to the information contained on the Physics' Department website: Plotting and Fitting Data and Plotting Data with Kaleidagraph. It shows how to perform the same functions described in those tutorials using gnuplot, a command-line-driven plotting program commonly available on Unix machines (though available for other platforms as well). You may find it helpful to look at the other tutorials as well; this one is intended to follow them quite closely.

The instructions and samples given correspond to version 3.7 running under Linux, but the results should be similar everywhere. If you are using an older version, however, you might find a few of the more advanced features missing.


gnuplot seems almost the antithesis of Kaleidagraph: the the Kaleidagraph tutorial calls Kaleidagraph "an easy-to-use if somewhat limited graphics program". gnuplot is a not-quite-as-easy-to use, though extremely powerful, command-line plotting program.

Running gnuplot is easy: from a command prompt on any system, type gnuplot. It is even possible to do this over a telnet or ssh connection, and preview the graphs in text mode! For best results, however, you should run gnuplot from within X Window, so that you can see better previews of your plots.

Entering Data

All the data sets you use in gnuplot should be typed into a text file first. There should be one data point per line. Each data point will consist of several numbers: the independent variable, the dependent variable, and optionally error bars. Each of these fields should be separated by a tab.

Actually, any number of fields may be specified on each line; this is useful if you have multiple measurements for each data point, for instance. For information about how to access this additional information in your plots, 

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