<jupyter_start><jupyter_text>Old Collection Access PatternThe non-typed way of accessing xAOD collections is supported for now, but is depreciated, and eventually, will stop working. There isn't a lot different from the typed method. However, much less of the xAOD is defined, so watch out for holes.<jupyter_code>from config import ds_zee_untyped

import matplotlib.pyplot as plt
jets = (ds_zee_untyped
          .SelectMany(lambda e: (e.Jets("AntiKt4EMTopoJets")))
          .Where(lambda j: (j.pt()/1000)>30)
          .Select(lambda j: (j.pt()/1000.0))
          .AsPandasDF("JetPt")
          .value())<jupyter_output><empty_output><jupyter_text>There are several things to note. First, you'll see two warning messages if you are running in local mode:```textWarning: assuming that the method 'xAOD::Jet::pt(...)' has return type 'double'. Use cpp_types.add_method_type_info to suppress (or correct) this warning.Warning: assuming that the method 'xAOD::Jet::pt(...)' has return type 'double'. Use cpp_types.add_method_type_info to suppress (or correct) this warning.``` Those indicate that the backend wasn't sent type information and so made the assumption that jet `pt` was a double return type. In this case, a good guess.A few other things:* No corrections were applied. These are the raw data from the xAOD file. This is a DAOD_PHYS file, so that won't be correct.* Only a limited number of collections are known (Jets, Muons, Electrons, Tracks).<jupyter_code>plt.hist(jets.JetPt, bins=100, range=(0, 100))
plt.xlabel('Jet $p_T$ [GeV]')
plt.ylabel('Number of jets')
_ = plt.title('Jet $p_T$ distribution for Zee events')<jupyter_output><empty_output>
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