大葉大學圖書館 |

Learning scientific programming with Python[electronic resource] /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	005.133
書名/作者:	Learning scientific programming with Python/ Christian Hill.
作者:	Hill, Christian,
出版者:	Cambridge : : Cambridge University Press,, 2015.
面頁冊數:	vii, 452 p. : : ill., digital ;; 24 cm.
標題:	Science - Data processing.
標題:	Science - Mathematics.
標題:	Python (Computer program language)
ISBN:	9781139871754
ISBN:	9781107075412
ISBN:	9781107428225
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.
摘要、提要註:	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.
電子資源:	https://doi.org/10.1017/CBO9781139871754

Learning scientific programming with Python[electronic resource] /
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:

466953
Science
--Data processing.

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

Dewey Class. No.: 005.133

Learning scientific programming with Python[electronic resource] /
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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 466953
650 0 $a Science $x Mathematics. $3 560211
650 0 $a Python (Computer program language) $3 339754
856 4 0 $u https://doi.org/10.1017/CBO9781139871754