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Learning scientific programming with...

Hill, Christian, (1974-)

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Learning scientific programming with Python /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Learning scientific programming with Python // Christian Hill.
作者:	Hill, Christian,
出版者:	Cambridge, UK :Cambridge University Press, : 2015.,
面頁冊數:	vii, 452 p. :ill. ;25 cm.
附註:	Includes index.
內容註:	Machine generated contents note: 1. Introduction; 2. The core Python language I; 3. Interlude: simple plotting with Pylab; 4. The core Python language II; 5. IPython and IPython notebook; 6. NumPy; 7. Matplotlib; 8. SciPy; 9. General scientific programming; Appendix A; Solutions; Index.
標題:	Science - Data processing. -
電子資源:	http://assets.cambridge.org/97811070/75412/cover/9781107075412.jpg
ISBN:	9781107075412

Learning scientific programming with Python /
Hill, Christian,1974-

Learning scientific programming with Python /Christian Hill. - Cambridge, UK :Cambridge University Press,2015. - vii, 452 p. :ill. ;25 cm.

Includes index.

Machine generated contents note: 1. Introduction; 2. The core Python language I; 3. Interlude: simple plotting with Pylab; 4. The core Python language II; 5. IPython and IPython notebook; 6. NumPy; 7. Matplotlib; 8. SciPy; 9. General scientific programming; Appendix A; Solutions; Index.

"Learn 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"--

ISBN: 9781107075412US99.99

LCCN: 2015017085Subjects--Topical Terms:

534323
Science
--Data processing.

LC Class. No.: Q183.9 / .H58 2015

Dewey Class. No.: 005.13/3

Learning scientific programming with Python /
LDR:02174cam a2200265 a 4500 001 2017886
003 DLC
005 20160405124811.0
008 160912s2015 enka 001 0 eng
010 $a 2015017085
020 $a 9781107075412 $q (hbk.) : $c US99.99
020 $a 1107075416 $q (hbk.)
020 $a 9781107428225 $q (pbk.)
020 $a 110742822X $q (pbk.)
040 $a DLC $b eng $c DLC
042 $a pcc
050 0 0 $a Q183.9 $b .H58 2015
082 0 0 $a 005.13/3 $2 23
084 $a SCI040000 $2 bisacsh
100 1 $a Hill, Christian, $d 1974- $3 2183547
245 1 0 $a Learning scientific programming with Python / $c Christian Hill.
260 $a Cambridge, UK : $b Cambridge University Press, $c 2015.
300 $a vii, 452 p. : $b ill. ; $c 25 cm.
500 $a Includes index.
505 8 $a Machine generated contents note: 1. Introduction; 2. The core Python language I; 3. Interlude: simple plotting with Pylab; 4. The core Python language II; 5. IPython and IPython notebook; 6. NumPy; 7. Matplotlib; 8. SciPy; 9. General scientific programming; Appendix A; Solutions; Index.
520 $a "Learn 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"-- $c Provided by publisher.
650 0 $a Science $x Data processing. $3 534323
650 0 $a Science $x Mathematics. $3 653973
650 0 $a Python (Computer program language) $3 729789
650 7 $a SCIENCE / Mathematical Physics. $2 bisacsh $3 2061870
856 4 2 $3 Cover image $u http://assets.cambridge.org/97811070/75412/cover/9781107075412.jpg