國立虎尾科技大學 |

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 :Cambridge University Press, : 2015.,
面頁冊數:	vii, 452 p. :ill., digital ; : 24 cm.;
標題:	Science - Data processing. -
電子資源:	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:

528623
Science
--Data processing.

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

Dewey Class. No.: 005.133

Learning scientific programming with Python
LDR:02153nam a2200265 a 4500 001 949321
003 UkCbUP
005 20160216110118.0
006 m d
007 cr nn 008maaau
008 200620s2015 enk o 1 0 eng d
020 $a 9781139871754 $q (electronic bk.)
020 $a 9781107075412 $q (hardback)
020 $a 9781107428225 $q (paperback)
035 $a CR9781139871754
040 $a UkCbUP $b eng $c UkCbUP $d GP
041 0 $a eng
050 4 $a Q183.9 $b .H58 2015
082 0 4 $a 005.133 $2 23
090 $a Q183.9 $b .H645 2015
100 1 $a Hill, Christian, $d 1974- $3 1238347
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 528623
650 0 $a Science $x Mathematics. $3 677365
650 0 $a Python (Computer program language) $3 566246
856 4 0 $u https://doi.org/10.1017/CBO9781139871754