000			02050cam0a2200325 4500
001			15945
009			195456882
003			http://www.sudoc.fr/195456882
005			20250630092550.0
010			_a9781107428225 _bbr.
073		0	_a9781107428225
090			_a15945
099			_tOUVR _zALEX31632
100			_a20160930d2015 |||||frey50 ba
101	0		_aeng _2639-2
102			_aGB
105			_ay |||||||||
181			_6z01 _ctxt _2rdacontent
181		1	_6z01 _ai# _bxxxe##
182			_6z01 _cn _2rdamedia
182		1	_6z01 _an
183		1	_6z01 _anga _2RDAfrCarrier
200	1		_aLearning scientific programming with Python _fChristian Hill,...
214		0	_aCambridge _cCambridge University Press
214		4	_dC 2015
215			_a1 vol. (452 p.) _cill. _d25cm
320			_aRef. bibliogr. en fin de chapitres. Index
330			_aLearn to master basic programming tasks from scratch with real-life scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to quickly gain proficiency. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving onto the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualisation, this textbook also discusses the use of IPython notebooks to build rich-media, shareable documents for scientific analysis. Including a final chapter introducing challenging topics such as floating-point precision and algorithm stability, and with extensive online resources to support advanced study, this textbook represents a targeted package for students requiring a solid foundation in Python programming
606			_3051626225 _aPython (langage de programmation) _2rameau
700		1	_3197397840 _aHill _bChristian _4070