Bernd Klein | Numeric Python. Python Data Analysis with NumPy, Pandas, and Matplotlib (2026) [PDF]
Автор: Bernd Klein
Издательство: Hanser Publications
ISBN: 978-1569904954
Жанр: Object-Oriented Software Design, Python Programming, Computer Programming Languages
Язык: Английский
Формат: PDF
Качество: Изначально электронное (ebook)
Иллюстрации: Цветные и черно-белые
Описание:- Numerical computing with NumPy arrays, dtypes, vectorized operations
- Data analysis using Pandas DataFrames, grouping, pivoting, and time series
- Scientific visualization with Matplotlib plots, layouts, and contour graphics
- Real-world data work: files, missing data, binning, and indexing
- Applied Python: image processing, probability, and practical projects
This book teaches the Python fundamentals required to solve numerical problems in data science and machine learning.
The first part focuses on NumPy as the foundation of numerical programming, covering arrays as the core data type, numerical operations, broadcasting, and universal functions, as well as statistics, probability, Boolean masking, and file handling.
The second part is devoted to data visualization with Matplotlib, ranging from core concepts to line, bar, histogram, and contour plots. The third part introduces Pandas, including Series and DataFrames, importing and exporting Excel, CSV, and JSON files, handling missing data, and visualization directly within Pandas.
The fourth part presents practical applications, including a household budget project, an incomeexpenditure analysis, and an introduction to image processing.
The book concludes with a fifth part containing solutions to the numerous exercises that accompany almost every one of the 33 chapters.
Preface
1 Introduction
2 Numerical Programming
3 Installation of NumPy, Matplotlib, Pandas, and JupyterLab
4 NumPy Introduction
5 Creation and Structure of Arrays
6 Data Type Object: dtype
7 Combining and Reshaping Arrays
8 Numerical Operations on NumPy Arrays
9 Statistics and Probability
10 Boolean Masking and Indexing
11 Reading and Writing Data Files
12 Introduction
13 Object-Oriented Plotting
14 Multiple Plots and Dual Axes
15 Axes and Tick Marks
16 Legends and Annotations
17 Contour Plots
18 Histograms and Diagrams
19 Pandas:Series
20 DataFrame
21 Styling
22 File Processing
23 Pandas
24 Pivot Tables
25 Handling NaN
26 Binning
27 Multi-level Indexing
28 Data Visualization with Pandas
29 Time and Date
30 Time Series
31 Image Processing Techniques
32 Financial Management with Pandas
33 Solutions to the Exercises
Index
Скриншоты:
Время раздачи: с 10 до 20 (минимум до появления первых 3-5 скачавших) 
