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Introduction
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Matplotlib graphs data in Figures, each of which can contain components that can be manipulated: axis, legend, labels, etc.
Many kinds of plots can be produced: scatter plots, bar plots, pie charts, and many more
HEP styling is available via the mplhep package, with recommended plotting styles from LHC experiments
Matplotlib can take objects containing data and bin them to produce histograms (which are very common in HEP)
Check the Matplotlib documentation for getting details on all the available options
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Coffee break
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Physics background
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Higgs search
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In High-energy physics, histograms are used to analyze different data and MC distributions.
With Matplotlib, data can be binned and histograms can be plotted in a few lines.
Using Uproot and Matplotlib, data in ROOT files can be display without need of a full ROOT installation.
Histograms can be stacked and/or overlapped to make comparison between recorded and simulated data.
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Plotting with mplhep for HEP style plotting
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Mplhep is a wrapper for easily apply plotting styles approved in the HEP collaborations.
Styles for LHC experiments (CMS, ATLAS, LHCb and ALICE) are available.
If you would like to include a style for your collaboration, ask for it opening an issue!
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Coffee break
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Dimuon spectrum
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Any data format that can be loaded as an object in Python can be plotted using Matplotlib.
Not always the default values will provide meaningful plots. When needed try to zoom changing the ranges in the distributions.
When in doubt, check the documentation! The web is also full of good examples.
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