Last updated:

ROOT Framework Quick-Start Guide

What is ROOT?

ROOT is an open-source C++ and Python framework developed at CERN for data processing, statistical analysis, visualization, and storage in high-energy physics (HEP). It is the standard tool for analyzing particle physics data and is used by virtually every experiment at CERN.

ROOT provides specialized data structures (such as TTree for columnar data), histogramming, curve fitting, and a powerful I/O system based on the .root file format. It also includes CLING, an interactive C++ interpreter, and PyROOT, a Python interface to all ROOT classes.

Zero-Install Option: SWAN

If you want to start using ROOT immediately without installing anything, CERN provides SWAN (Service for Web-based ANalysis) at swan.cern.ch. SWAN is a JupyterHub-based service that gives you a notebook environment with ROOT, PyROOT, and many other scientific Python packages pre-installed.

Simply log in with your CERN credentials, choose a software stack, and start coding. SWAN connects to your EOS storage, so you can access your data files directly. This is the fastest way to get started with ROOT at CERN.

Installation Methods

Conda (Recommended for personal machines)

The easiest way to install ROOT on your personal machine is via conda-forge:

conda create -n root-env
conda activate root-env
conda install -c conda-forge root

Snap (Linux)

On Linux distributions that support Snap packages:

sudo snap install root-framework

Homebrew (macOS)

On macOS with Homebrew installed:

brew install root

Pre-built Binaries

Download pre-compiled binaries for your platform from the official ROOT website at root.cern/install. Extract the archive and source the setup script:

tar -xzf root_v6.XX.YY.Linux-ubuntu22-x86_64-gcc11.4.tar.gz
source root/bin/thisroot.sh

On lxplus (CVMFS)

On CERN's lxplus machines, ROOT is available through CVMFS without any installation. Simply set up the LCG software environment:

# List available LCG releases
ls /cvmfs/sft.cern.ch/lcg/views/


Set up a specific LCG release (example)


source /cvmfs/sft.cern.ch/lcg/views/LCG_105/x86_64-el9-gcc13-opt/setup.sh


Verify ROOT is available


root --version

First Steps with ROOT

Interactive C++ (CLING)

Launch ROOT's interactive C++ interpreter by typing root in your terminal:

$ root
root [0] TH1F *h = new TH1F("h", "My Histogram", 100, -5, 5);
root [1] h->FillRandom("gaus", 10000);
root [2] h->Draw();
root [3] .q

PyROOT

Use ROOT from Python with the PyROOT bindings:

import ROOT


Create and fill a histogram


h = ROOT.TH1F("h", "Gaussian Distribution;x;Entries", 100, -5, 5)
h.FillRandom("gaus", 10000)


Draw on a canvas


c = ROOT.TCanvas("c", "My Canvas", 800, 600)
h.Draw()
c.SaveAs("histogram.png")

Reading .root Files

Open and explore an existing ROOT file:

import ROOT


f = ROOT.TFile.Open("data.root")
f.ls()           # List contents
tree = f.Get("Events")  # Get a TTree
tree.Print()     # Show branches
tree.Draw("pt")  # Quick plot of a branch

NumPy / pandas Integration

Convert ROOT data to NumPy arrays or pandas DataFrames for use with the broader Python ecosystem:

import ROOT
import numpy as np


Using RDataFrame (modern ROOT approach)


df = ROOT.RDataFrame("Events", "data.root")
npy = df.AsNumpy(["pt", "eta"])  # Returns dict of NumPy arrays


Convert to pandas DataFrame


import pandas as pd
pdf = pd.DataFrame(npy)

Essential Resources

Common First-Week Tasks