In addition, multi-threading and other low-level optimisations allow users to exploit all the resources available on their machines transparently.
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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.
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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.
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file | df002_dataModel.C |
| This tutorial shows the possibility to use data models which are more complex than flat ntuples with RDataFrame
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file | df002_dataModel.py |
| This tutorial shows the possibility to use data models which are more complex than flat ntuples with RDataFrame
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file | df003_profiles.C |
| This tutorial illustrates how to use TProfiles in combination with the RDataFrame.
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file | df003_profiles.py |
| This tutorial illustrates how to use TProfiles in combination with the RDataFrame.
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file | df004_cutFlowReport.C |
| This tutorial shows how to get information about the efficiency of the filters applied
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file | df004_cutFlowReport.py |
| This tutorial shows how to get information about the efficiency of the filters applied
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file | df005_fillAnyObject.C |
| This tutorial shows how to fill any object the class of which exposes a Fill method.
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file | df006_ranges.C |
| This tutorial shows how to express the concept of ranges when working with the RDataFrame.
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file | df006_ranges.py |
| This tutorial shows how to express the concept of ranges when working with the RDataFrame.
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file | df007_snapshot.C |
| This tutorial shows how to write out datasets in ROOT formatusing the RDataFrame
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file | df007_snapshot.py |
| This tutorial shows how to write out datasets in ROOT formatusing the RDataFrame
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file | df008_createDataSetFromScratch.C |
| This tutorial shows how to create a dataset from scratch with RDataFrame
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file | df008_createDataSetFromScratch.py |
| This tutorial shows how to create a dataset from scratch with RDataFrame
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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.
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file | df010_trivialDataSource.C |
| This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
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file | df010_trivialDataSource.py |
| This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
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file | df011_ROOTDataSource.C |
| This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
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file | df011_ROOTDataSource.py |
| This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
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file | df012_DefinesAndFiltersAsStrings.C |
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file | df012_DefinesAndFiltersAsStrings.py |
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file | df013_InspectAnalysis.C |
| Showcase registration of callback functions that act on partial results while the event-loop is running using OnPartialResult and OnPartialResultSlot .
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file | df014_CSVDataSource.C |
| This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
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file | df014_CSVDataSource.py |
| This tutorial illustrates how use the RDataFrame in combination with a RDataSource.
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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.
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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.
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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.
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file | df017_vecOpsHEP.C |
| This tutorial shows how VecOps can be used to slim down the programming model typically adopted in HEP for analysis.
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file | df017_vecOpsHEP.py |
| This tutorial shows how VecOps can be used to slim down the programming model typically adopted in HEP for analysis.
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file | df018_customActions.C |
| This tutorial shows how to implement a custom action.
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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.
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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.
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file | df020_helpers.C |
| This tutorial shows usage of the RDF helper tools, contained in ROOT/RDFHelpers.hxx
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file | df021_createTGraph.C |
| This tutorial shows how to fill a TGraph using the Dataframe.
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file | df021_createTGraph.py |
| This tutorial shows how to fill a TGraph using the Dataframe.
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file | df022_useKahan.C |
| This tutorial shows how to implement a Kahan summation custom action.
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file | df023_aggregate.C |
| This tutorial shows how to use the Aggregate action to evaluate the product of all the elements of a column.
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file | df024_Display.C |
| This tutorial shows how to use the Display action
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file | df024_Display.py |
| This tutorial shows how to use the Display action
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file | df025_RNode.C |
| RNode is a generic type which represents any transformation node in the computation graph.
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file | df026_AsNumpyArrays.py |
| This tutorial shows how read data of a RDataFrame into Numpy arrays.
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file | df027_SQliteDependencyOverVersion.C |
| Plot the ROOT downloads based on the version reading a remote sqlite3 file with RSqliteDS.
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file | df028_SQliteIPLocation.C |
| Plot the location of ROOT downloads reading a remote sqlite3 file with RSqliteDS.
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file | df029_SQlitePlatformDistribution.C |
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file | df030_SQliteVersionsOfROOT.C |
| Plot the downloads of different ROOT versions reading a remote sqlite3 file with RSqliteDS.
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file | df031_Stats.C |
| Extract the statistics relative to RDataFrame columns and store them in TStatistic instances.
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file | df031_Stats.py |
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file | df101_h1Analysis.C |
| This tutorial illustrates how to express the H1 analysis with a RDataFrame.
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file | df102_NanoAODDimuonAnalysis.C |
| This tutorial illustrates how NanoAOD files can be processed with ROOT dataframes.
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file | df102_NanoAODDimuonAnalysis.py |
| This tutorial illustrates how NanoAOD files can be processed with ROOT dataframes.
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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.
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