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df010_trivialDataSource.py
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## \file
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## \ingroup tutorial_dataframe
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## \notebook -draw
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## Use the "trivial data source", an example data source implementation.
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##
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## This tutorial illustrates how use the RDataFrame in combination with a
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## RDataSource. In this case we use a RTrivialDS, which is nothing more
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## than a simple generator: it does not interface to any existing dataset.
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## The RTrivialDS has a single column, col0, which has value n for entry n.
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##
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## Note that RTrivialDS is only a demo data source implementation and superior alternatives
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## typically exist for production use (e.g. constructing an empty RDataFrame as `RDataFrame(nEntries)`).
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##
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## \macro_image
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## \macro_code
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##
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## \date September 2017
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## \author Danilo Piparo (CERN)
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import
ROOT
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# Create the data frame
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MakeTrivialDataFrame = ROOT.RDF.MakeTrivialDataFrame
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nEvents = 128
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d_s = MakeTrivialDataFrame(nEvents)
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# Now we have a regular RDataFrame: the ingestion of data is delegated to
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# the RDataSource. At this point everything works as before.
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h_s = d_s.Define(
"x"
,
"1./(1. + col0)"
).Histo1D((
"h_s"
,
"h_s"
, 128, 0, .6),
"x"
)
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c = ROOT.TCanvas()
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c.SetLogy()
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h_s.Draw()
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c.SaveAs(
"df010_trivialDataSource.png"
)
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print(
"Saved figure to df010_trivialDataSource.png"
)
tutorials
analysis
dataframe
df010_trivialDataSource.py
ROOTmaster - Reference Guide Generated on Tue Oct 20 2026 15:13:13 (GVA Time) using Doxygen 1.10.0