000 -LEADER |
fixed length control field |
a |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
220601b xxu||||| |||| 00| 0 eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781108745918 |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
005.133 |
Item number |
HIL |
100 ## - MAIN ENTRY--PERSONAL NAME |
Personal name |
Hill, Christian |
245 ## - TITLE STATEMENT |
Title |
Learning scientific programming with Python |
250 ## - EDITION STATEMENT |
Edition statement |
2nd ed. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Name of publisher, distributor, etc |
Cambridge University Press, |
Date of publication, distribution, etc |
2020 |
Place of publication, distribution, etc |
Cambridge : |
300 ## - PHYSICAL DESCRIPTION |
Extent |
xi, 557 p. ; |
Other physical details |
ill., |
Dimensions |
25 cm |
365 ## - TRADE PRICE |
Price amount |
34.99 |
Price type code |
GBP |
Unit of pricing |
102.80 |
504 ## - BIBLIOGRAPHY, ETC. NOTE |
Bibliography, etc |
Includes bibliographical references and index. |
520 ## - SUMMARY, ETC. |
Summary, etc |
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 gain proficiency quickly. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving on to the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualization, this textbook also discusses the use of Jupyter Notebooks to build rich-media, shareable documents for scientific analysis. The second edition features a new chapter on data analysis with the pandas library and comprehensive updates, and new exercises and examples. A final chapter introduces more advanced topics such as floating-point precision and algorithm stability, and extensive online resources support further study. This textbook represents a targeted package for students requiring a solid foundation in Python programming. |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Python |
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Anonymous functions |
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Boolean indexing |
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Camel Case |
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Debye theory |
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Euler's totient function |
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Faddeeva function |
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Gaussian function |
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Haversine formula |
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Ipython help |
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Julia set |
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Lorentzian function |
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Monte Carlo method |
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Overdetermined problem |
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Pascal's triangle |
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Random walks |
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Sinc function |
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String methods |
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Theis equation |
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Universal functions |
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Variational principle |
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Weather data analysis |
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Data cleaning |
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Charts |
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Topical term or geographic name as entry element |
Oop |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
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Item type |
Books |