Handbuch Data Science mit Python

Jake Vanderplas

ISBN 10: 3960092253 / ISBN 13: 9783960092254

Published by Dpunkt.Verlag Nov 2023, 2023

About this Item

Neuware -Der unverzichtbare Werkzeugkasten für Data Science in der 2. Auflagedpunkt.Verlag, Wieblinger Weg 17, 69123 Heidelberg 576 pp. Deutsch.

Seller Inventory # 9783960092254

Bibliographic Details

• Title: Handbuch Data Science mit Python
• Publisher: Dpunkt.Verlag Nov 2023
• Publication Date: 2023
• Language: German
• ISBN 10: 3960092253
• ISBN 13: 9783960092254
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

The indispensable tool box for data science in the 2nd Cushion

• The proven standard work now in a fully updated edition
• Covers the latest versions of IPython, NumPy, Pandas, Matplotlib and Scikit-Learn
• The easy-to-follow examples help you successfully set up and use the data science tools
• Includes Jupyter notebooks that allow you to try the code right when reading

For many data scientists, Python is the language of choice because numerous sophisticated libraries are available for storing, editing and evaluating data. Jake VanderPlas gathered in this 2nd Edition of his standard work all important data analysis tools in one volume and explains their use in practice. Described are IPython, Jupyter, NumPy, Pandas, Matplotlib, Scikit Learn and related tools.

For data analysts and data crunchers with Python knowledge, this comprehensive handbook is invaluable in completing their daily tasks. This includes manipulation, conversion, and cleanup of data, visualization of different types of data, as well as using data to create statistics and machine learning models.

This manual describes the following tools:

• IPython and Jupyter provide an environment for calculations used by many data scientists
• NumPy provides the ndarray for efficient storage and editing of densely packed data arrays
• Pandas has the DataFrameObject for storing and manipulating labeled and column-oriented data
• Matplotlib allows flexible and versatile visualization of data
• ScikitLearn supports the implementation of the most important and common algorithms for machine learning.

»Jake describes far more than the basics of these open source tools; he explains the underlying concepts, procedures, and abstractions in clear language and with understandable explanations.« -- Brian Granger, physics professor and co-founder of the Jupyter Project