Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

Cover
"O'Reilly Media, Inc.", 08.10.2012 - 466 Seiten
2 Rezensionen

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.

  • Use the IPython interactive shell as your primary development environment
  • Learn basic and advanced NumPy (Numerical Python) features
  • Get started with data analysis tools in the pandas library
  • Use high-performance tools to load, clean, transform, merge, and reshape data
  • Create scatter plots and static or interactive visualizations with matplotlib
  • Apply the pandas groupby facility to slice, dice, and summarize datasets
  • Measure data by points in time, whether it’s specific instances, fixed periods, or intervals
  • Learn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples
 

Was andere dazu sagen - Rezension schreiben

LibraryThing Review

Nutzerbericht  - trilliams - LibraryThing

A great handbook for anyone looking to do break down data sets in Python. This won't teach you what to look for or how to do data analysis, but it will show you all the tools to get it done. Vollständige Rezension lesen

Helpful

Nutzerbericht  - OstkUser894211 - Overstock.com

Great book to work through. Vollständige Rezension lesen

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
Index
433
Urheberrecht

Andere Ausgaben - Alle anzeigen

Häufige Begriffe und Wortgruppen

Über den Autor (2012)

Wes McKinney is the main author of pandas, the popular open sourcePython library for data analysis. Wes is an active speaker andparticipant in the Python and open source communities. He worked as aquantitative analyst at AQR Capital Management and Python consultantbefore founding DataPad, a data analytics company, in 2013. Hegraduated from MIT with an S.B. in Mathematics.

Bibliografische Informationen