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- ROOT: analyzing petabytes of data, scientifically. - ROOT
ROOT Data Analysis Framework About; Install; Manual; Contribute; For Developers; Source; Toggle search Toggle menu
- Tutorials - ROOT
A collection of C++ macros, Python scripts and notebooks helping to learn ROOT by example Get started If you have never used ROOT before and don’t know where to start, we recommend that you first explore the ROOT introductory course You can also watch the recording of the course, but you should follow the material along on your PC
- A ROOT Guide For Beginners
The ROOT Data Analysis Framework itself is written in and heavily relies on the C++ programming language: some knowledge about C++ is required Jus take advantage from the immense available literature about C++ if you do not have any idea of what this language is about
- ROOT: Dataframe tutorials
Write ROOT data with RDataFrame file df007_snapshot py Write ROOT data with RDataFrame file df008_createDataSetFromScratch C Create data from scratch with RDataFrame file df008_createDataSetFromScratch py Create data from scratch with RDataFrame file df009_FromScratchVSTTree C
- ROOT: Data analysis tutorials
ROOT master - Reference Guide Generated on Wed Jul 9 2025 15:45:04 (GVA Time) using Doxygen 1 10 0
- ROOT: RooDataSet Class Reference
The binned equivalent is RooDataHist In RooDataSet, each data point in N-dimensional space is represented by a RooArgSet of RooRealVar, RooCategory or RooStringVar objects, which can be retrieved using get() Since RooDataSet saves every event, it allows for fits with highest precision With a large amount of data, however, it could be beneficial to represent them in binned form, i e
- “DivingIntoROOT”
Chapter1 MotivationandIntroduction Welcome to data analysis! Comparisonofmeasurementstotheoreticalmodelsisoneofthestandardtasksinexperimentalphysics
- ROOT: ROOT::RDataFrame Class Reference
Columns containing non-fundamental types (e g , objects, strings) will result in NumPy arrays with dtype=object Collection Columns If your column contains collections of fundamental types (e g , std::vector<int>), AsNumpy() produces a NumPy array with dtype=object where each element is a NumPy array representing the collection for its corresponding entry in the column
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