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010   $a3-032-00721-6
024 7 $a10.1007/978-3-032-00721-6
035   $a(CKB)44769977900041
035   $a(MiAaPQ)EBC32484389
035   $a(Au-PeEL)EBL32484389
035   $a(DE-He213)978-3-032-00721-6
035   $a(EXLCZ)9944769977900041
100   $a20260102d2026      u|         0
101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aOpen Source Tools for Physics Data Analysis $eAn Introduction /$fby Sebastiano Vasi, Ulderico Wanderlingh, Giuseppe Mandaglio
205   $a1st ed. 2026.
210  1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2026.
215   $a1 online resource (272 pages)
225 1 $aUndergraduate Texts in Physics,$x2510-4128
311 08$a3-032-00723-2 
311 08$a3-032-00720-8 
327   $aIntroduction -- Operative systems and Linux Shells -- Rudimental in programming -- Why Object Oriented programming -- Analysis Framework -- Data elaboration and visualization -- Experimental data acquisition and analysis.
330   $aThis textbook aims to provide computing skills to analyze data collected by means of several types of experiments. Generally speaking, the analysis of data is complementary to experimental and/or theoretical activities, but, as a matter of fact, a fundamental part of the training process in scientific degree courses (such as physics, mathematics, chemistry, biology, and engineering) consists in different laboratory activities, collecting data and then analyzing and interpreting them. Different analysis tools are available for this purpose, including commercial and open-sources ones. Some of them allow to analyze data in a user-friendly manner, and it can be helpful for the first approach for a student to a data analysis problem, but, at the same time, it represents a limit on the real possibility that students can achieve by using the computation potentiality offered by a good knowledge of programming languages. For this reason, at least a computing course is generally present in scientific degree courses, as well as in experimental laboratories in which part of the training time is devoted to analyze and visualize data. Part of the book is devoted to furnish the rudiments of programming in C++, Python, and other open-source languages. In the second part, Root, a powerful and open-source data analysis framework, and the universe of the Python libraries will be introduced as a complete tool for data analysis, as well as their application and examples regarding physics experiments performed in laboratories.
410  0$aUndergraduate Texts in Physics,$x2510-4128
606   $aMathematical physics
606   $aComputer simulation
606   $aOpen source software
606   $aQuantitative research
606   $aComputational Physics and Simulations
606   $aOpen Source
606   $aData Analysis and Big Data
615  0$aMathematical physics.
615  0$aComputer simulation.
615  0$aOpen source software.
615  0$aQuantitative research.
615 14$aComputational Physics and Simulations.
615 24$aOpen Source.
615 24$aData Analysis and Big Data.
676   $a530.10285
700   $aVasi$b Sebastiano$01889999
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9911049220803321
996   $aOpen Source Tools for Physics Data Analysis$94531546
997   $aUNINA