000			02045nam a2200205Ia 4500
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020			_a9789355422552 _qpbk
041			_aeng
082			_a006.312 _bVAN
100			_aVanderplas T Jacob
245		0	_aPython data science handbook : essential tools for working with data _c/Jacob T. Vanderplas
250			_a2nd ed.
260			_c2023. _aSebastopol, CA, _bO'Reilly Media, Incorporated
300			_axxiv, 563 pages : _billustrations ,; _c23 cm.
504			_aindex
520			_aPython 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;Python, 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. With this handbook, you'll learn how: IPython and Jupyter provide computational environments for scientists using Python NumPy includes the ndarray for efficient storage and manipulation of dense data arrays Pandas contains the DataFrame for efficient storage and manipulation of labeled/columnar data Matplotlib includes capabilities for a flexible range of data visualizations Scikit-learn helps you build efficient and clean Python implementations of the most important and established machine learning algorithms
650			_aComputer Science Data mining Exploration de données (Informatique) Python (Computer program language) Python (Langage de programmation)
942			_cREF
999			_c543017 _d543017