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Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
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- Published on: 1600
- Binding: Paperback
Most helpful customer reviews
5 of 5 people found the following review helpful.
Good for beginners. Faint printing problem. Somewhat outdated in 2016.
By J. Yoon
Pretty good resource for a beginner to Python's data analysis libraries. This book is not for a Python beginner. Although Wes McKinney wrote Pandas, I feel that the Pandas part of the book is somewhat outdated or redundant in 2016. There is an excellent online resource maintained by Wes and other key contributors that is up-to-date, and, in my opinion, has better content for beginners learning Pandas. Because of several different contributors' perspectives, I find the examples and explanations better than those in the book. In 2012, when this book was published, that online resource may not have been as good. I found the Pandas Time Series and Financial Applications chapters interesting, but they are also replicated on the website. So the book was improved upon by the author's own website (with the help of other contributors). :-)
See[...]
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.
3 of 3 people found the following review helpful.
This is an excellent book, assuming you like the author's approach to ...
By Thomas T Foley
This is an excellent book, assuming you like the author's approach to computation/data. This is in a sense also a review for pandas. I should emphasize I am NOT a programmer, in the proper sense. I am a (computational) physicist and have transitioned all of my data storage/analysis to pandas, for reasons I'll explain.
A large portion of my work is "exploratory", where I try out many different ideas, hoping something sticks. I've wasted a large amount of time hacking away trying to piece together a somewhat complicated calculation on fairly abstract data sets, only to eventually lose track of what physics I'm trying to do because of how sloppy things get. Again, I am not a programmer! Computation is a tool to me, and time spent trying to make a tool work is time away from the actual job.
Though I have only used it in earnest for a few months now, Pandas has increased my productivity tremendously. The organization/philosophy behind the program is amazing. Often (though less and less, thankfully) I find myself reverting to my old habits of working with a sloppy mixture of dicts,np.arrays, and classes, because I feel like I can do it faster/easier than setting it up in pandas. I am never right. Once I set up the problem in pandas, everything I could possibly want to do flows naturally.
If you work with physical data and perform relatively complex calculations/transformations on it, I strongly recommend pandas and this book. Regarding the book, I will only say that by reading the author's (of the code and book!) perspective you quickly gain an appreciation for how powerful pandas can be.
0 of 0 people found the following review helpful.
Nice book but could be better if concept and conventions can be introduced first, before going into details.
By IPStone
Pandas is a great package, and this book serves a good beginner's book to pandas and also to python.
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.
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