03396cam a22005778i 45000010014000000030008000140050017000220060019000390070015000580080041000730400031001140200027001450200015001720200043001870200040002300200042002700200039003120200030003510200031003810240031004120350022004430350024004650500016004890720025005050720025005300720025005550720015005801000100005952450073006952500020007682640040007883000023008283360026008513370026008773380036009034900039009395201259009785880047022376500046022846500026023306500034023566500030023906500053024206500040024736500055025138300047025688560072026158560102026879420012027899990017028019781032673950FlBoTFG20251030122304.0m     o  d        cr |||||||||||240416s2025    flu     ob    001 0 eng    aOCoLC-PbengerdacOCoLC-P  a9781032673950q(ebook)  a1032673958  a9781040119631q(electronic bk. : EPUB)  a1040119638q(electronic bk. : EPUB)  a9781040119570q(electronic bk. : PDF)  a1040119573q(electronic bk. : PDF)  z9781032650333q(hardback)  z9781032673905q(paperback)7 a10.1201/97810326739502doi  a(OCoLC)1430983275  a(OCoLC-P)143098327500aQA76.73.P98 7aCOMx0590002bisacsh 7aCOMx0070002bisacsh 7aCOMx0620002bisacsh 7aPH2bicssc1 aPine, David J.,eauthor.1https://id.oclc.org/worldcat/entity/E39PCjwyQgvQ67kfKPmFgBQFGb99599810aIntroduction to Python for science and engineering /cDavid J. Pine.  aSecond edition. 1aBoca Raton, FL :bCRC Press,c2025.  a1 online resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier1 aSeries in computational biophysics  a"Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and "bottom up," which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed. Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms. Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments. All the major Python libraries for science and engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead"--cProvided by publisher.  aOCLC-licensed vendor bibliographic record. 0aPython (Computer program language)964608 0aComputer programming. 0aEngineeringxData processing. 0aSciencexData processing. 7aCOMPUTERS / Computer Engineering2bisacsh964152 7aCOMPUTERS / CAD-CAM2bisacsh995999 7aCOMPUTERS / Data Modeling & Design2bisacsh965185 0aSeries in computational biophysics.996000403Taylor & Francisuhttps://www.taylorfrancis.com/books/9781032673950423OCLC metadata license agreementuhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf  cE-Books  c68235d68235