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Learning scientific programming with...

Hill, Christian, (1974-)

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Learning scientific programming with Python

Record Type:	Electronic resources : Monograph/item
Title/Author:	Learning scientific programming with Python/ Christian Hill.
Author:	Hill, Christian,
Published:	Cambridge :Cambridge University Press, : 2015.,
Description:	vii, 452 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Subject:	Science - Data processing. -
Online resource:	https://doi.org/10.1017/CBO9781139871754
ISBN:	9781139871754

Learning scientific programming with Python
Hill, Christian,1974-

Learning scientific programming with Python[electronic resource] /Christian Hill. - Cambridge :Cambridge University Press,2015. - vii, 452 p. :ill., digital ;24 cm.

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: 9781139871754Subjects--Topical Terms:

534323
Science
--Data processing.

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

Dewey Class. No.: 005.133

Learning scientific programming with Python
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100 1 $a Hill, Christian, $d 1974- $3 2183547
245 1 0 $a Learning scientific programming with Python $h [electronic resource] / $c Christian Hill.
260 $a Cambridge : $b Cambridge University Press, $c 2015.
300 $a vii, 452 p. : $b ill., digital ; $c 24 cm.
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.
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
856 4 0 $u https://doi.org/10.1017/CBO9781139871754