Python Data Science Handbook essential tools for working with data
Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the new edition of Python Data Science Handbook do you get them all-...
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| Formato: | Otros |
| Idioma: | Inglés |
| Publicado: |
Beijing :
O'Reilly
[2023]
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| Edición: | Second edition |
| Materias: | |
| Ver en Biblioteca de la Universidad Pontificia de Salamanca: | https://koha.upsa.es/cgi-bin/koha/opac-detail.pl?biblionumber=1008089 |
Solicitar por préstamo interbibliotecario:
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| Formulario
| Sumario: | Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the new edition of Python Data Science Handbook do you get them all--IPython, NumPy, pandas, Matplotlib, Scikit-Learn, and other related tools.
Working scientists and data crunchers familiar with reading and writing Python code will find the second edition of this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. |
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| Descripción Física: | XXIV, 563 páginas |
| ISBN: | 9781098121228 |
