| 000 | a | ||
|---|---|---|---|
| 999 |
_c30856 _d30856 |
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| 008 | 220601b xxu||||| |||| 00| 0 eng d | ||
| 020 | _a9781108745918 | ||
| 082 |
_a005.133 _bHIL |
||
| 100 | _aHill, Christian | ||
| 245 | _aLearning scientific programming with Python | ||
| 250 | _a2nd ed. | ||
| 260 |
_bCambridge University Press, _c2020 _aCambridge : |
||
| 300 |
_axi, 557 p. ; _bill., _c25 cm |
||
| 365 |
_b34.99 _cGBP _d102.80 |
||
| 504 | _aIncludes bibliographical references and index. | ||
| 520 | _aLearn 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 | _aPython | ||
| 650 | _aAnonymous functions | ||
| 650 | _aBoolean indexing | ||
| 650 | _a Camel Case | ||
| 650 | _aDebye theory | ||
| 650 | _aEuler's totient function | ||
| 650 | _aFaddeeva function | ||
| 650 | _a Gaussian function | ||
| 650 | _a Haversine formula | ||
| 650 | _aIpython help | ||
| 650 | _aJulia set | ||
| 650 | _aLorentzian function | ||
| 650 | _aMonte Carlo method | ||
| 650 | _aOverdetermined problem | ||
| 650 | _aPascal's triangle | ||
| 650 | _a Random walks | ||
| 650 | _aSinc function | ||
| 650 | _aString methods | ||
| 650 | _aTheis equation | ||
| 650 | _aUniversal functions | ||
| 650 | _aVariational principle | ||
| 650 | _aWeather data analysis | ||
| 650 | _aData cleaning | ||
| 650 | _a Charts | ||
| 650 | _aOop | ||
| 942 |
_2ddc _cBK |
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