Python for Data Analysis"O'Reilly Media, Inc.", 2013 - 452 Seiten Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language. Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.
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Inhalt
Chapter 1 Preliminaries | 1 |
Chapter 2 Introductory Examples | 17 |
An Interactive Computing and Development Environment | 45 |
Arrays and Vectorized Computation | 79 |
Chapter 5 Getting Started with pandas | 111 |
Chapter 6 Data Loading Storage and File Formats | 155 |
Clean Transform Merge Reshape | 177 |
Chapter 8 Plotting and Visualization | 219 |
Chapter 9 Data Aggregation and Group Operations | 251 |
Chapter 10 Time Series | 289 |
Chapter 11 Financial and Economic Data Applications | 329 |
Chapter 12 Advanced NumPy | 353 |
Appendix Python Language Essentials | 385 |
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Python for Data Analysis: Data Wrangling with Pandas, NumPy, and Jupyter Wes McKinney Keine Leseprobe verfügbar - 2022 |
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