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In this chapter, data analysis and the visualization of results through high-quality figures are performed exclusively using code written with open-source libraries. Specifically, the chapter presents macros based on the ROOT framework, Python scripts that leverage powerful libraries such as NumPy, Pandas, and Anaconda, and the lightweight yet versatile Gnuplot. Additionally, it presents some ROOT applications integrated with Python via PyROOT. The provided code enables the computation of histograms, signal and background identification, background subtraction, signal yield estimation, data representation, and statistical analysis.

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Data Elaboration and Visualization

  • 章节

  • 发表日期：

    2026年

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  • Sebastiano Vasi,
  • Ulderico Wanderlingh,
  • Giuseppe Mandaglio

摘要

In this chapter, data analysis and the visualization of results through high-quality figures are performed exclusively using code written with open-source libraries. Specifically, the chapter presents macros based on the ROOT framework, Python scripts that leverage powerful libraries such as NumPy, Pandas, and Anaconda, and the lightweight yet versatile Gnuplot. Additionally, it presents some ROOT applications integrated with Python via PyROOT. The provided code enables the computation of histograms, signal and background identification, background subtraction, signal yield estimation, data representation, and statistical analysis.