Paperback: 337 pages
Publisher: Apress; 1st ed. edition (August 21, 2015)
Product Dimensions: 7 x 0.8 x 10 inches
Shipping Weight: 12.6 ounces (View shipping rates and policies)
Average Customer Review: 3.3 out of 5 stars See all reviews (3 customer reviews)
Best Sellers Rank: #1,323,800 in Books (See Top 100 in Books) #253 in Books > Computers & Technology > Programming > Languages & Tools > Compilers #672 in Books > Computers & Technology > Databases & Big Data > Data Mining #862 in Books > Computers & Technology > Programming > Languages & Tools > Python
I am a blogger, writing articles for various programming languages, that I find interesting. Lately for Python. I was provided with a paper version of the book from Apress, after a request from my site.So, the book is named "Python Data Analytics" and it provides exactly what it says. It shows you how to use Python step-by-step for Data Analytics. The important libraries in Python - NumPy, Pandas, MatPlotLib are presented in literally step-by-step introduction - from their installation to about 70-80 % of their properties and functions. The step-by-step approach really shows you what to write in the Python shell and what to expect. Furthermore, some mathematical operations (e.g. matrix multiplication) are well explained with pictures.What a lot of people may not like is the way the book is written - one should copy and paste the code from the book to his PC manually. It is already 21. century outside, if you are writing a programming book, please share your code for everyone. The code, that was shared in the [...] site was really just a tiny part of the one in the book and it was mainly some useless outputs. :( Why did you share it at all? Who needs output of sample tables?Furthermore, the first chapter looks like a copy-paste from an introduction of a mediocre master thesis. It reminded me of mine. :) At the end of the hate section - there is a whole appendix with Mathematical Expressions with LaTeX, containing 10 pages. This would have been really useful ... 25 years ago (I am repeating myself - its 2015 outside, anyone who uses LaTeX probably can use search engines as well). The time when the books were ending at the end with copied libraries must be over. Or I have thought so.
Wishing to learn Pandas, I started by buying and reading "Python for Data Analysis" by Wes McKinney, the author of Pandas. I then went ahead and bought the other Pandas-related titles available on :"Learning the Pandas Library" by Matt Harrison, 212 pages, (self-)published in 2016, Â£18 for a hardcopy"Learning pandas" by Michael Heydt, 504 pages, Packt, 2015, Â£38"Mastering pandas" by Femi Anthony, 364 pages, Packt, 2015, Â£33"Python Data Analytics" by Fabio Nelli, 364 pages, Apress, 2015, Â£23pretty much for the sake of due diligence, not expecting any of the titles to beat "Python for Data Analysis", a definite keeper.I started with "Learning the Pandas library", the thinnest of the bunch, and quickly decided to send it back to : the book could not add to, or replace, "Python for Data Analysis".I reached the same conclusion on "Mastering pandas": the book could not compete with "Python for Data Analysis" on Pandas coverage, and sought to differentiate itself with statistics and machine-learning content, but the latter did not impress.Now, "Python Data Analytics" has by far the least - less than 50 pages? - to say about Pandas, which immediately removes it from consideration as a "Pandas book". Still, it makes a good impression. The book's core is probably coverage of matplotlib - basic, not long, but thoughtful and useful - and then it, like "Mastering pandas" before it, goes into machine-learning territory, and again does a basic but decent job. If I had to choose between "Mastering pandas" and "Python Data Analytics", I would immediately pick "Python Data Analytics".