Altair - Altair is a declarative statistical visualization library for Python.From the comments of others not tried by me There is a nice overview here of some of the less painful to use visualisation tools. The old favourite matplotlib - very powerful but not necessarily the easiest to use and many of the examples you will find are based on the pyplot MATLAB style concept of the current current figure/axis - however it also provides an OO interface some examples of which you can find here so simply use it that way instead. Because, python matplotlib for 2D and sometimes for 3D give your so many facilities similar than the plot options in matlab, you can use also gnuplot too, which is focused on graphs with a big data.4 gives a much more restrictive number of charts but aims to make life a lot simpler, (and more Object Oriented).ggplot - To quote the authors "ggplot sacrafices highly customization in favor of generall doing "what you'd expect".".'Multiple interactive windowing toolkits and non-interactive backends are supported' is the primary reason people pick matplotlib over the competition.
#Veusz matplotlib pro#
Get it here Recommend 5 - Veusz My Rec ommendation for Veusz My Recommendation for Veusz Add Video or Image All 4 Pros 3 Cons 1 Top Pro Can be scripted Comes with a scripting interface. matplotlib, Veusz, and Plotly are probably your best bets out of the 3 options considered. bokeh - again nice graphs - can be used from R, Scala & Julia as well as python. Matplotlib includes an object oriented interface as well as a Matlab-inspired functional interface.
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