Description

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.

In this second edition, 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:

   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

Book Details

   Language: English
   Published: 2022
   ISBN: 9781098121204
   Format: EPUB