dataframe Directory Reference

Directory dependency graph for dataframe:

Files
file	df001_introduction.C [code]
	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 [code]
	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 [code]
	This tutorial shows the possibility to use data models which are more complex than flat ntuples with RDataFrame
file	df002_dataModel.py [code]
	This tutorial shows the possibility to use data models which are more complex than flat ntuples with RDataFrame
file	df003_profiles.C [code]
	This tutorial illustrates how to use TProfiles in combination with the RDataFrame.
file	df003_profiles.py [code]
	This tutorial illustrates how to use TProfiles in combination with the RDataFrame.
file	df004_cutFlowReport.C [code]
	This tutorial shows how to get information about the efficiency of the filters applied
file	df004_cutFlowReport.py [code]
	This tutorial shows how to get information about the efficiency of the filters applied
file	df005_fillAnyObject.C [code]
	This tutorial shows how to fill any object the class of which exposes a Fill method.
file	df006_ranges.C [code]
	This tutorial shows how to express the concept of ranges when working with the RDataFrame.
file	df006_ranges.py [code]
	This tutorial shows how to express the concept of ranges when working with the RDataFrame.
file	df007_snapshot.C [code]
	This tutorial shows how to write out datasets in ROOT formatusing the RDataFrame
file	df007_snapshot.py [code]
	This tutorial shows how to write out datasets in ROOT formatusing the RDataFrame
file	df008_createDataSetFromScratch.C [code]
	This tutorial shows how to create a dataset from scratch with RDataFrame
file	df008_createDataSetFromScratch.py [code]
	This tutorial shows how to create a dataset from scratch with RDataFrame
file	df009_FromScratchVSTTree.C [code]
	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 [code]
	This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
file	df010_trivialDataSource.py [code]
	This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
file	df012_DefinesAndFiltersAsStrings.C [code]
file	df012_DefinesAndFiltersAsStrings.py [code]
file	df013_InspectAnalysis.C [code]
	Showcase registration of callback functions that act on partial results while the event-loop is running using OnPartialResult and OnPartialResultSlot.
file	df014_CSVDataSource.C [code]
	This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
file	df014_CSVDataSource.py [code]
	This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
file	df015_LazyDataSource.C [code]
	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 [code]
	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 [code]
	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 [code]
	This tutorial shows how VecOps can be used to slim down the programming model typically adopted in HEP for analysis.
file	df017_vecOpsHEP.py [code]
	This tutorial shows how VecOps can be used to slim down the programming model typically adopted in HEP for analysis.
file	df018_customActions.C [code]
	This tutorial shows how to implement a custom action.
file	df019_Cache.C [code]
	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 [code]
	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 [code]
	This tutorial shows usage of the RDF helper tools, contained in ROOT/RDFHelpers.hxx
file	df021_createTGraph.C [code]
	This tutorial shows how to fill a TGraph using the Dataframe.
file	df021_createTGraph.py [code]
	This tutorial shows how to fill a TGraph using the Dataframe.
file	df022_useKahan.C [code]
	This tutorial shows how to implement a Kahan summation custom action.
file	df023_aggregate.C [code]
	This tutorial shows how to use the Aggregate action to evaluate the product of all the elements of a column.
file	df024_Display.C [code]
	This tutorial shows how to use the Display action
file	df024_Display.py [code]
	This tutorial shows how to use the Display action
file	df025_RNode.C [code]
	RNode is a generic type which represents any transformation node in the computation graph.
file	df026_AsNumpyArrays.py [code]
	This tutorial shows how read data of a RDataFrame into Numpy arrays.
file	df027_SQliteDependencyOverVersion.C [code]
	Plot the ROOT downloads based on the version reading a remote sqlite3 file with RSqliteDS.
file	df028_SQliteIPLocation.C [code]
	Plot the location of ROOT downloads reading a remote sqlite3 file with RSqliteDS.
file	df029_SQlitePlatformDistribution.C [code]
file	df030_SQliteVersionsOfROOT.C [code]
	Plot the downloads of different ROOT versions reading a remote sqlite3 file with RSqliteDS.
file	df031_Stats.C [code]
	Extract the statistics relative to RDataFrame columns and store them in TStatistic instances.
file	df031_Stats.py [code]
file	df101_h1Analysis.C [code]
	This tutorial illustrates how to express the H1 analysis with a RDataFrame.
file	df102_NanoAODDimuonAnalysis.C [code]
	This tutorial illustrates how NanoAOD files can be processed with ROOT dataframes.
file	df102_NanoAODDimuonAnalysis.py [code]
	This tutorial illustrates how NanoAOD files can be processed with ROOT dataframes.
file	df103_NanoAODHiggsAnalysis.C [code]
	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.
file	df103_NanoAODHiggsAnalysis.py [code]
	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.
file	df103_NanoAODHiggsAnalysis_python.h [code]
	Header file with functions needed to execute the Python version of the NanoAOD Higgs tutorial.
file	df104_HiggsToTwoPhotons.py [code]
	This tutorial is the Higgs to two photons analysis from the ATLAS Open Data release in 2020 (http://opendata.atlas.cern/release/2020/documentation/).
file	df105_WBosonAnalysis.py [code]
	This tutorial is the analysis of the W boson mass taken from the ATLAS Open Data release in 2020 (http://opendata.atlas.cern/release/2020/documentation/).
file	df106_HiggsToFourLeptons.py [code]
	This tutorial is the Higgs to four lepton analysis from the ATLAS Open Data release in 2020 (http://opendata.atlas.cern/release/2020/documentation/).