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I'm interested in which program would you recommend for drawing graphs with x and y errors. Also to be able to analyse data and then graph it. My ideal graph would look like this:

Image1

Image2

Until now I was drawing my graph reports in Excel, but I feel like Excel is made more for an accountants than scientists. I would really like to work more in scientific based programs that could come in handy in the future (graduate and postgraduate work, research).

Any recommendation?

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    $\begingroup$ Some common options are Matlab, Maple, Mathematica, Python, etc. $\endgroup$ – AccidentalFourierTransform May 26 '18 at 21:07
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    $\begingroup$ And plot.ly . And Gnuplot. And Igor (Wavemetrics). $\endgroup$ – Pieter May 26 '18 at 21:24
  • $\begingroup$ You can easily make plots like that in MS Office, too. Honestly that's a pretty low bar. $\endgroup$ – Nat May 26 '18 at 21:24
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    $\begingroup$ In high energy particle physics, CERN's ROOT is widely used. It is basically a C/C++ interpreter, and has extensive plotting libraries that can be used in your analysis code, or on command-line for instant purposes. You can even implement a GUI with interactive plots and buttons if you have a routine analysis but need a specific interactive interface for your experiment. There is also a python version: PyROOT. $\endgroup$ – Oktay Doğangün May 26 '18 at 21:38
  • $\begingroup$ I use Mathematica and Igor Pro. $\endgroup$ – Samuel Weir May 26 '18 at 21:50
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Python is certainly a major language for scientific data analysis today. The three key words are: Numpy, Scipy and Matplotlib.

  • NumPy: it's the basic numerical analysis package in Python. It allows for array manipulation, matrix calculus, Fourier transforms, statistics, ...
  • SciPy: it's the extended version of numpy with more advanced built-in procedures: image and signal processing, optimization, graphs routines, more statsitic and so on. Importing SciPy makes essentially redundant importing NumPy.
  • Matplotlib: here we came to the standard for visualizing data in Python: you can do almost everything in 2D or 3D with this library. Take a look at this sample plots!

There is also a useful IDE for Python called PyZo, in case you want to have the shell and the editor in a single window. It makes the user experience and the debug a little bit easier.

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