- Paperback: 472 pages
- Publisher: O′Reilly; 1 edition (26 October 2012)
- Language: English
- ISBN-10: 1449319793
- ISBN-13: 978-1449319793
- Product Dimensions: 17.8 x 2.3 x 23.3 cm
- Average Customer Review: 1 customer review
- Amazon Bestsellers Rank: #50,543 in Books (See Top 100 in Books)
Other Sellers on Amazon
+ 80.00 Delivery charge
Includes Import Fees Deposit
+ 296.69 Delivery charge
Python for Data Analysis Paperback – 26 Oct 2012
Frequently bought together
Customers who viewed this item also viewed
Data Wrangling with Pandas, NumPy, and IPython
About the Author
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.
Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.
To get the free app, enter mobile phone number.
What other items do customers buy after viewing this item?
Top customer reviews
There was a problem filtering reviews right now. Please try again later.
Most helpful customer reviews on Amazon.com
In particular, see sections: Tutorials, Intro to Data Structures - Series and DataFrame, and Essential Basic Functionality.
The remaining 1/4 of the book had very useful concentrated intro to NumPy, Advanced NumPy, and Python Essentials reference. This book does not cover the newer development of R function calls from Python. In my opinion, R is winning the R vs Pandas argument due to ggplot2 and statistical learning professors publishing code first in R. Since R is now easy to use from within Python, Pandas might not get as much use. But it's still useful to know how to use Pandas as part of a data analyst's toolkit.
I also want to warn buyers about faint printing on several physical copies of this book. I bought from Amazon AND directly from O'Reilly Media in trying to get a physical book that had good, solid printing on all pages. This was not possible. The physical book from O'Reilly had even fainter/worse printing than the version I got from Amazon. Better to save your money and just get with the eBook version if you are OK with that, which you can usually find cheaper online. O'Reilly puts on excellent conferences, but may be getting out of the printed book business. I guess most programmers buy eBooks now. I just find eBooks difficult to deal with when it comes to dense, technical books. I am fine with eBooks for fiction or more narrative non-fiction such as economics, popular science, or history.
However, it would be better if concept and conventions in pandas can be introduced first, and later comes with more specifics, applications of using pandas to solve data tasks, it would be better. Some examples are good, but feels taking too long to get the understanding the concepts.