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Dataframe tutorials

These examples show various features of RDataFrame: ROOT's declarative analysis interface.

RDataFrame offers a high level interface for the analysis 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(); // Enable ROOT's implicit multi-threading
ROOT::RDataFrame d("myTree", "file_*.root"); // Interface to TTree and TChain
auto histoA = d.Histo1D("Branch_A"); // Book the filling of a histogram
auto histoB = d.Histo1D("Branch_B"); // Book the filling of another histogram
// Data processing is triggered by the next line, which accesses a booked result for the first time
// All booked results are evaluated during the same parallel event loop.
histoA->Draw(); // <-- event loop runs here!
histoB->Draw(); // HistoB has already been filled, no event loop is run here
#define d(i)
Definition RSha256.hxx:102
ROOT's RDataFrame offers a modern, high-level interface for analysis of data stored in TTree ,...
void EnableImplicitMT(UInt_t numthreads=0)
Enable ROOT's implicit multi-threading for all objects and methods that provide an internal paralleli...
Definition TROOT.cxx:539

Explore the examples below or go to RDataFrame's user guide.

Files

file  df000_simple.C
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Simple RDataFrame example in C++.
 
file  df000_simple.py
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Simple RDataFrame example in Python.
 
file  df001_introduction.C
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Basic RDataFrame usage.
 
file  df001_introduction.py
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Basic usage of RDataFrame from python.
 
file  df002_dataModel.C
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Show how to work with non-flat data models, e.g.
 
file  df002_dataModel.py
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Show how to work with non-flat data models, e.g.
 
file  df003_profiles.C
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Use TProfiles with RDataFrame.
 
file  df003_profiles.py
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Use TProfiles with RDataFrame.
 
file  df004_cutFlowReport.C
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Display cut/Filter efficiencies with RDataFrame.
 
file  df004_cutFlowReport.py
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Display cut/Filter efficiencies with RDataFrame.
 
file  df005_fillAnyObject.C
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Using the generic Fill action.
 
file  df006_ranges.C
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Use Range to limit the amount of data processed.
 
file  df006_ranges.py
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Use Range to limit the amount of data processed.
 
file  df007_snapshot.C
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Write ROOT data with RDataFrame.
 
file  df007_snapshot.py
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Write ROOT data with RDataFrame.
 
file  df008_createDataSetFromScratch.C
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Create data from scratch with RDataFrame.
 
file  df008_createDataSetFromScratch.py
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Create data from scratch with RDataFrame.
 
file  df009_FromScratchVSTTree.C
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Compare creation of a ROOT dataset with RDataFrame and TTree.
 
file  df010_trivialDataSource.C
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Use the "trivial data source", an example data source implementation.
 
file  df010_trivialDataSource.py
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Use the "trivial data source", an example data source implementation.
 
file  df012_DefinesAndFiltersAsStrings.C
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Use just-in-time-compiled Filters and Defines for quick prototyping.
 
file  df012_DefinesAndFiltersAsStrings.py
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Use just-in-time-compiled Filters and Defines for quick prototyping.
 
file  df013_InspectAnalysis.C
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Use callbacks to update a plot and a progress bar during the event loop.
 
file  df014_CSVDataSource.C
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Process a CSV file with RDataFrame and the CSV data source.
 
file  df014_CSVDataSource.py
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Process a CSV file with RDataFrame and the CSV data source.
 
file  df015_LazyDataSource.C
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Use the lazy RDataFrame data source to concatenate computation graphs.
 
file  df016_vecOps.C
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Process collections in RDataFrame with the help of RVec.
 
file  df016_vecOps.py
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Process collections in RDataFrame with the help of RVec.
 
file  df017_vecOpsHEP.C
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Use RVecs to plot the transverse momentum of selected particles.
 
file  df017_vecOpsHEP.py
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Use RVecs to plot the transverse momentum of selected particles.
 
file  df018_customActions.C
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Implement a custom action to fill THns.
 
file  df019_Cache.C
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Cache a processed RDataFrame in memory for further usage.
 
file  df019_Cache.py
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Cache a processed RDataFrame in memory for further usage.
 
file  df020_helpers.C
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Show usage of RDataFrame's helper tools, contained in ROOT/RDFHelpers.hxx.
 
file  df021_createTGraph.C
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Fill a TGraph using RDataFrame.
 
file  df021_createTGraph.py
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Fill a TGraph using RDataFrame.
 
file  df022_useKahan.C
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Implement a custom action that evaluates a Kahan sum.
 
file  df023_aggregate.C
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Use the Aggregate action to specify arbitrary data aggregations.
 
file  df024_Display.C
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Use the Display action to inspect entry values.
 
file  df024_Display.py
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Use the Display action to inspect entry values.
 
file  df025_RNode.C
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Manipulate RDF objects in functions, loops and conditional branches.
 
file  df026_AsNumpyArrays.py
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Read data from RDataFrame into Numpy arrays.
 
file  df027_SQliteDependencyOverVersion.C
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Plot the ROOT downloads based on the version reading a remote sqlite3 file.
 
file  df028_SQliteIPLocation.C
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Plot the location of ROOT downloads reading a remote sqlite3 file.
 
file  df029_SQlitePlatformDistribution.C
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Use RDataFrame to display data about ROOT downloads.
 
file  df030_SQliteVersionsOfROOT.C
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Read an sqlite3 databases with RDataFrame and plot statistics on ROOT downloads.
 
file  df031_Stats.C
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Use the Stats action to extract the statistics of a column.
 
file  df031_Stats.py
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Use the Stats action to extract the statistics of a column.
 
file  df032_RDFFromNumpy.py
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Read data from Numpy arrays into RDataFrame.
 
file  df033_Describe.py
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Get information about the dataframe with the convenience method Describe.
 
file  df034_SaveGraph.C
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Basic SaveGraph usage.
 
file  df034_SaveGraph.py
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Basic SaveGraph usage.
 
file  df035_RDFFromPandas.py
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Read data from Pandas Data Frame into RDataFrame.
 
file  df036_missingBranches.C
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file  df037_TTreeEventMatching.C
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file  df101_h1Analysis.C
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Show how to express ROOT's standard H1 analysis with RDataFrame.
 
file  df102_NanoAODDimuonAnalysis.C
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Show how NanoAOD files can be processed with RDataFrame.
 
file  df102_NanoAODDimuonAnalysis.py
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Show how NanoAOD files can be processed with RDataFrame.
 
file  df103_NanoAODHiggsAnalysis.C
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An example of complex analysis with RDataFrame: reconstructing the Higgs boson.
 
file  df103_NanoAODHiggsAnalysis.py
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An example of complex analysis with RDataFrame: reconstructing the Higgs boson.
 
file  df103_NanoAODHiggsAnalysis_python.h
 Header file with functions needed to execute the Python version of the NanoAOD Higgs tutorial.
 
file  df104_HiggsToTwoPhotons.py
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The Higgs to two photons analysis from the ATLAS Open Data 2020 release, with RDataFrame.
 
file  df105_WBosonAnalysis.py
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The W boson mass analysis from the ATLAS Open Data release of 2020, with RDataFrame.
 
file  df106_HiggsToFourLeptons.C
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The Higgs to four lepton analysis from the ATLAS Open Data release of 2020, with RDataFrame.
 
file  df106_HiggsToFourLeptons.py
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The Higgs to four lepton analysis from the ATLAS Open Data release of 2020, with RDataFrame.
 
file  df107_SingleTopAnalysis.py
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A single top analysis using the ATLAS Open Data release of 2020, with RDataFrame.
 
file  distrdf001_spark_connection.py
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Configure a Spark connection and fill two histograms distributedly.
 
file  distrdf002_dask_connection.py
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Configure a Dask connection and fill two histograms distributedly.
 
file  distrdf003_live_visualization.py
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Configure a Dask connection and visualize the filling of a 1D and 2D histograms distributedly.