000			01967nam a2200253 a 4500
001			58566
005			20260219124007.0
020			_a9781491912058
040			_aAIS _dAIS
100			_aJake Vanderplas
245			_aPython Data Science Handbook: Essential Tools for Working with Data
082			_a006.312
260			_aSebastopol, CA _bO'Reilly _c2017
520			_aFor many researchers, Python is a first-class tool mainly 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 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 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 to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
655			_aProgramming
655			_aComputer Science
655			_aComputers
655			_aCoding
655			_aTechnology
655			_aTechnical
655			_aArtificial Intelligence
655			_aNonfiction
650			_a(ICE-2702) Applied Data Science with Python
999			_c58566 _d58566