Python Data Analysis

Python Data Analysis claims to "contain all the basic ingredients you need to become an expert data analyst.” Unfortunately, the book is seriously flawed. First, it is a mile wide and barely an inch deep. For many parts of the book, all you get is a paragraph mentioning something and a snippet of source code with no deeper explanation of what’s going on or how it works or nuances of usage. For instance, the section on pivot tables in pandas is just a page, most of it source code, and only demonstrates one way to use the pivot-table functionality without clearly explaining what’s going on. Similarly, with machine learning or databases the book may whet your appetite but you’ll have to read elsewhere to really learn how to use the tools available. Even with plotting, though the subject takes up 20 pages, there’s hardly any explanation of the matplotlib “axes” system of plotting.Second, the book is riddled with errors, some that are inexcusable and should have been found by an editor. For instance, several times within the first 50 pages the book seems to accidentally include the Python source code used to produce the text of the book (followed by the text produced by such source code)! (It’s hard to explain this, but if you look at the preview pages 43-46 (some parts missing), you’ll get the point; also see p. 33-35 for another example). These are totally wasted pages you’re paying for.Another example of bad editing occurs on page 32, where the author writes, “We have already learned about the reshape() function,” even though (as far as I can tell) it hadn’t been mentioned prior to that (the index only points us to p. 35).The writing style is excruciating, with phrasing like this being common: “After connecting to a database, we need a cursor. That’s generally how it works with databases by the way. A database cursor is similar to a cursor in a text editor, in concept at least. We are required to close the cursor as well.” Ugh.I give 2 stars only because there is some useful information throughout the book, as shallow as it may be, and because the author has at least used a variety of datasets in the examples.

If Data Analysis is your true interest, then you should probably pick Python Machine Learning by Sebastian Raschka also published by Packt. The book by Idris is much less directed towards Dara Analysis and much more about detailed description of the Python packages that you may need for Math and Data Analysis. idris's book could be used as a companion to Raschka's, covering package details not exposed in the latter.

Great place to start for beginning to learn the vast number of analytical tools in python. Doesn't work on ipython too much tho

Useful book -- quickly developed an analysis & viz. scheme for a project running on a linux system

I found this book is too shallow! As one of the reviewer who gave 2 stars said: 'for many parts of the book, all you get is a paragraph mentioning something and a snippet of source code with no deeper explanation of what's going on or how it works or nuances of usage'. I totally agree, most of the time, it only gives you a very brief concept, or just give you a link to wikipedia. So if you want to learn these concepts from this book, it is very difficult, you need spend a lot of time online to figure out some of the details. Also, for the example code, this book usually shows you a very simple example without deeper explanation, a lot of these examples you can easily find online. Some of the code make me even doubt whether the author really understand this (sorry about saying this, I think the author may understand the concept, but just didn't write it out), for example, in the Fourier analysis example, the author do the real value fft, then shift it. But when he plotted the spectrum, he even didn't plot the x-axis as frequency, but just a sequential number. From all the reasons above, I don't think it is a good book to learn data analysis.The reason I gave this book 3 stars is because this book covers a lot of information in 12 chapters, even it is very shallow on most of the stuff, I do learn something from this book. The stuff listed by the author gives me a quick view of data analysis, so I just quickly browse through the book, and find the things I don't know well, and then learn from online tutorials or other books. This is maybe the most useful part of this book to me.