O'Reilly Python for Data Analysis, 2e

Great book, covers all the basics for data analysis in python

This is the best reference I use for dealing with python, numpy and mainly pandas. Must have for anyone learning or using pandas. The author (who actually wrote pandas)style is into the point, clear and with simple examples that demonstrate the usage in real world.Also this book has all the info to help you prepare data for sci-kit learn and tf .

Original book is printed in colors this one came black and white less color interaction in jupter notebook code. Also all charts are in black and white!

This book is generally considered a classic but I am in 2 minds over it. It gives an introduction to the Python language, which is nice for a beginner. It also gives very good introductions to numpy, pandas, matplotlib and seaborn. I had not heard of the latter so the book was of great value there. However, all of these libraries are huge; pandas alone is massive. This leaves the author being stuck in terms of how deep to go. Some areas are well covered and others are just skimmed over forcing you to look deeper on the internet. Adding to the problem is that these libraries are being continually updated. I was left with a growing feeling that books like this are becoming redundant. There is so much free material online now that if someone stole this book from me it would not make a jot of difference.

I have purchased other books for jumping into machine learning using Python but they always somewhat gloss over the basics, and you have to accept a bit of magic around Pandas, Matplotlib etc to follow along. I'm so glad I went back to build a solid foundation with this book, so I'm no longer fumbling around with magic commands or spending a huge proportion of time trawling Stack Overflow.Probably my favourite aspect of this book is that you can just read it- every single concept is demonstrated in code, on the paper, with the full input and outputs. The only time I've opened my editor is to play around with concepts I wanted to clarify- the rest has been just a good solid read with everything clearly demonstrated. It's well structured and builds concepts as you progress but is also an excellent reference book I can see myself dipping back into time and again.I think this is essential foundational material for starting your journey into data analysis and/or machine learning with Python.

A good reference book. It did a reasonable job in breaking python data analysis down into consumable chunks, however there are many free resources out there that would do an equally good job. This book rarely focuses on the bigger picture, it rather gives you line of code after line of code without ever going into real world usage of that code/construct. To use an analogy, If I was looking to build a tree house this book gave me hammer and nails without providing a blueprint on how to build that house.Look for a book that takes a project based approach to learning if you are looking to get into python data analysis.

The content of the book is good. The print quality is bad. I can see the texts through the pages. Most of the figures are poorly printed, looks like run out of ink. I can understand that this is paperback print, but I would expect better quality for £30 book. It is too much hassle to return this in the current situation.

Wes is a great writer and teacher, I feel I am learning more about data analysis with python by tracing out the code in the book (Wes refers to this as strengthening one's "muscle memory") in my Juptyer notebooks on my laptop than I had from trying moocs on data analysis.