Data Frame tutorials

These examples show the functionalities of RDataFrame: ROOT's declarative analysis interface.

ROOT's RDataFrame offers a high level interface for analyses of data stored in TTrees, CSV files and other data formats.

In addition, multi-threading and other low-level optimisations allow users to exploit all the resources available on their machines transparently.

In a nutshell:

ROOT::EnableImplicitMT(); // Tell ROOT you want to go parallel
ROOT::RDataFrame d("myTree", "file_*.root"); // Interface to TTree and TChain
auto myHisto = d.Histo1D("Branch_A"); // This happens in parallel!
myHisto->Draw();

Explore the examples below or go to RDataFrame user guide.

Files
file	df001_introduction.C
	This tutorial illustrates the basic features of the RDataFrame class, a utility which allows to interact with data stored in TTrees following a functional-chain like approach.
file	df001_introduction.py
	This tutorial illustrates the basic features of the RDataFrame class, a utility which allows to interact with data stored in TTrees following a functional-chain like approach.
file	df002_dataModel.C
	This tutorial shows the possibility to use data models which are more complex than flat ntuples with RDataFrame
file	df002_dataModel.py
	This tutorial shows the possibility to use data models which are more complex than flat ntuples with RDataFrame
file	df003_profiles.C
	This tutorial illustrates how to use TProfiles in combination with the RDataFrame.
file	df003_profiles.py
	This tutorial illustrates how to use TProfiles in combination with the RDataFrame.
file	df004_cutFlowReport.C
	This tutorial shows how to get information about the efficiency of the filters applied
file	df004_cutFlowReport.py
	This tutorial shows how to get information about the efficiency of the filters applied
file	df005_fillAnyObject.C
	This tutorial shows how to fill any object the class of which exposes a Fill method.
file	df006_ranges.C
	This tutorial shows how to express the concept of ranges when working with the RDataFrame.
file	df006_ranges.py
	This tutorial shows how to express the concept of ranges when working with the RDataFrame.
file	df007_snapshot.C
	This tutorial shows how to write out datasets in ROOT formatusing the RDataFrame
file	df007_snapshot.py
	This tutorial shows how to write out datasets in ROOT formatusing the RDataFrame
file	df008_createDataSetFromScratch.C
	This tutorial shows how to create a dataset from scratch with RDataFrame
file	df008_createDataSetFromScratch.py
	This tutorial shows how to create a dataset from scratch with RDataFrame
file	df009_FromScratchVSTTree.C
	This tutorial illustrates how simpler it can be to use a RDataFrame to create a dataset with respect to the usage of the TTree interfaces.
file	df010_trivialDataSource.C
	This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
file	df010_trivialDataSource.py
	This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
file	df011_ROOTDataSource.C
	This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
file	df011_ROOTDataSource.py
	This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
file	df012_DefinesAndFiltersAsStrings.C
file	df012_DefinesAndFiltersAsStrings.py
file	df013_InspectAnalysis.C
	Showcase registration of callback functions that act on partial results while the event-loop is running using OnPartialResult and OnPartialResultSlot.
file	df014_CSVDataSource.C
	This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
file	df014_CSVDataSource.py
	This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
file	df015_LazyDataSource.C
	This tutorial illustrates how to take advantage of a lazy data source creating a data frame from columns of one or multiple parent dataframe(s), delaying the creation of the columns to the actual usage of the daughter data frame.
file	df016_vecOps.C
	This tutorial shows the potential of the VecOps approach for treating collections stored in datasets, a situation very common in HEP data analysis.
file	df016_vecOps.py
	This tutorial shows the potential of the VecOps approach for treating collections stored in datasets, a situation very common in HEP data analysis.
file	df017_vecOpsHEP.C
	This tutorial shows how VecOps can be used to slim down the programming model typically adopted in HEP for analysis.
file	df017_vecOpsHEP.py
	This tutorial shows how VecOps can be used to slim down the programming model typically adopted in HEP for analysis.
file	df018_customActions.C
	This tutorial shows how to implement a custom action.
file	df019_Cache.C
	This tutorial shows how the content of a data frame can be cached in memory in form of a data frame.
file	df019_Cache.py
	This tutorial shows how the content of a data frame can be cached in memory in form of a data frame.
file	df020_helpers.C
	This tutorial shows usage of the RDF helper tools, contained in ROOT/RDFHelpers.hxx
file	df021_createTGraph.C
	This tutorial shows how to fill a TGraph using the Dataframe.
file	df021_createTGraph.py
	This tutorial shows how to fill a TGraph using the Dataframe.
file	df022_useKahan.C
	This tutorial shows how to implement a Kahan summation custom action.
file	df023_aggregate.C
	This tutorial shows how to use the Aggregate action to evaluate the product of all the elements of a column.
file	df024_Display.C
	This tutorial shows how to use the Display action
file	df024_Display.py
	This tutorial shows how to use the Display action
file	df025_RNode.C
	RNode is a generic type which represents any transformation node in the computation graph.
file	df101_h1Analysis.C
	This tutorial illustrates how to express the H1 analysis with a RDataFrame.
file	df102_NanoAODDimuonAnalysis.C
	This tutorial illustrates how NanoAOD files can be processed with ROOT dataframes.
file	df103_NanoAODHiggsAnalysis.C
	This tutorial is a simplified but yet complex example of an analysis reconstructing the Higgs boson decaying to two Z bosons from events with four leptons.