Numerisches Python: Arbeiten mit NumPy, Matplotlib und Pandas

Klein, Bernd

ISBN 10: 3446471707 / ISBN 13: 9783446471702

About this Item

Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Seller Inventory # M03446471707-V

Bibliographic Details

• Title: Numerisches Python: Arbeiten mit NumPy, Matplotlib und Pandas
• Language: German
• ISBN 10: 3446471707
• ISBN 13: 9783446471702
• Binding: Hardcover
• Edition: 2nd Edition
• Condition: very good

About this title

Synopsis

- Fundamentals for solving numerical problems with Python
- Processing large amounts of data with NumPy, e.g. B. in machine learning.
- Data visualisation with Matplotlib
- Ideal for people from science, engineering and data analysis
- Ideal for switching from Matlab to Python
- Introduction based on many examples and practice cases as well as sample solutions.
- Your exclusive advantage: e-book inside when buying the printed book.

This book conveys the Python fundamentals for solving numerical problems from the fields of "data science" and "machine learning".
The first part is about NumPy as the basis of numerical programming with Python. In depth, arrays are treated as the central data type for everything, numerical operations, broadcasting, and Ufuncs. Statistics and probability calculus is dedicated to a separate chapter, as is Boolean masking and file-handling.
Data visualization with Matplotlib forms the focus of the second part. First of all, it is about the concept of Matplotlib. It covers line, bar charts, histograms and contour plots.
The third part revolves around Pandas with its Series and DataFrames. It also covers the handling of various file formats such as Excel, CSV and JSON as well as incomplete data and NaN. The possibilities of data visualisation are shown directly with pandas.
The fourth part provides sample applications of the material learned, such as a household book and a practical income surplus account. There is also an introduction to image processing techniques.
Almost each of the 32 chapters contains additional exercises for testing and deepening what has been learned, the associated solutions are summarized in the fifth part.

From the contents //
NumPy
• Numerical operations on multi-dimensional arrays
• Broadcasting and Ufuncs
Matplotlib:
• Discrete and continuous graphene
• Bar and column charts, histograms, contour plots
Pandas:
• Series and DataFrames
• Work with Excel, csv and JSON files
• Incomplete data (NaN)
• Data visualisation
Practical examples:
• Image processing.
• Household book and surplus income invoice