import pandas as pd
import servicex as sx
from func_adl_servicex import ServiceXSourceUpROOT
import matplotlib.pyplot as plt
plt.rcParams['figure.dpi'] = 200 # make figures bigger and more readable
dataset_name = "cms:DYJetsToLL_M-50_TuneCP5_13TeV-amcatnloFXFX-pythia8/RunIIAutumn18NanoAODv7-Nano02Apr2020_102X_upgrade2018_realistic_v21_ext2-v1/NANOAODSIM"
sx_dataset = sx.ServiceXDataset(dataset_name, "uproot")
ds = ServiceXSourceUpROOT(sx_dataset, "Events")
missing_ET = ds.Select(lambda event: event.MET_pt).AsAwkwardArray().value()
cms:DYJetsToLL_M-50_...: 0%| | 0/9000000000.0 [00:00]
cms:DYJetsToLL_M-50_... Downloaded: 0%| | 0/9000000000.0 [00:00]
missing_ET
<Array [46.6, 43.1, 22.5, ... 23.2, 98.6, 43.3] type='193119590 * float32'>
plt.hist([missing_ET], bins=100, range=(0, 100))
plt.xlabel(r'$E_\mathrm{T}^\mathrm{miss}$ [GeV]')
plt.ylabel('Events')
plt.show()