Description

Looking for complete instructions on manipulating, processing, cleaning, and crunching structured data in Python? This hands-on book is packed with practical cases studies that show you how to effectively solve a broad set of data analysis problems, using several Python libraries.

Reviews

On May 9 Marco Dinacci wrote: Good pandas tutorial/reference
The book is essentially a reference on how to use the pandas Python library.It is well written and can be used both as a tutorial for learning about a particular aspect of the library and as a reference... Full Review  >

Rating: 4.0

On Jan 19 Peter Georgeson wrote:
Full Review  >

Rating: 4.0

On Dec 6 Mikael Puhakka wrote:
Full Review  >

Rating: 4.0

On Dec 1 Tuomo Kalliokoski wrote:
Full Review  >

Rating: 3.0

On Nov 30 Juan Jose de Leon wrote:
Python for Data Analysis is a book about the parties and Python libraries needed to resolve many problems of data analysis and statistics. Full Review  >

Rating: 4.0

On Nov 19 Mat Powell wrote: Python for Data Analysis
A great book on statistical analysis with Python utilizing big-data. I was skeptical about this title at first (I’m not much of a mathematician at all) I was overall pleased with the experience and flow of this book. Mostly focusing on Pandas, this book also cameos IPython and Num-Py. Recommended for anyone who’s doing some serious number crunching or analysis with large datasets. Full Review  >

Rating: 4.0

On Nov 11 Kenta Hood wrote:
Full Review  >

Rating: 4.0

On Oct 22 Rob Friesel wrote: dive into pandas and NumPy
Wes McKinney's Python for Data Analysis (O'Reilly, 2012) is a tour pandas and NumPy (mostly pandas) for folks looking to crunch big-ish� data with Python. The target audience is not Pythonistas, but rather scientists, educators, statisticians, financial analysts, and the rest of the non-programmer� cohort that is finding more and more these days that it needs to do a little bit-sifting to get the rest of their jobs done. Full Review  >

Rating: 3.0