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For 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 allâ??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, youâ??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
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Publisher : O’Reilly Media
Publication date : January 3, 2017
Edition : 1st
Language : English
Print length : 546 pages
ISBN-10 : 1491912057
ISBN-13 : 978-1491912058
Item Weight : 1.47 pounds
Dimensions : 5.91 x 0.59 x 9.84 inches
Customers say
Customers find this book to be an excellent guide for data science, particularly for new data scientists and machine learning projects. The book is well-written and easily executable, with one customer noting that each chapter includes well-designed examples.
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