Python for Data Analysis, 2e By Wes Mckinney

Superb. Covering numpy, pandas and matplotlib. Extensive coverage for cleaning data, also comparing different ways of doing it. I got this book when I was transitioning to doing data science with Python and was struggling to become familiar with standard tools. It's written by the creator of Pandas, and follows the style of the Pandas documentation: dense, telegraphic, peppered with examples.It's hard work because Wes McKinney often does not articulate why you would need to do something (assuming you are already knowledgeable on the underlying process), and writes like an impatient person who would rather be doing something else. Additionally examples often suffer from being both too long and too short too long in that almost every example is on a toy dataset created from scratch, too short in that most of those datasets have only 5 or 10 elements and do not always showcase complex operations. Other examples (particularly involving time series) have an overabundance of data that make the critical results hard to spot. Frankly, my first month with Pandas was a miserable one.But I give the book 5 stars both because I came to love Pandas as I got familiar with it, and because while McKinney is not fun to read, he does pack the book with useful information and it is (mostly) well organized. If anything it would benefit from being longer and with a patient treatment of larger and concrete datasets (eg the Titanic passenger dataset used in the Pandas documentation). The initial chapter on the basics of using Python could go if you need this book, then you don't want to be trying to learn the rudiments of Python from it. If you can accept that you'll need a lot of bookmarks or margin notes to get through a rather steep learning curve, it will reward your persistence. very clearly explains what I need to know and just the amount of details I want, overall very short chapters but enough to solve my problems Wes is a great writer and teacher, I feel I am learning 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 This is a great book written by the author of pandasFor a bit background and explanations then the Chen book works well with this.

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A great and very useful book that really helps. A good technical book explaining how to use Pandas with strong supporting tutorials and data. Well laid out and passed well. No complaints. I'm not the kind of person that gives 5 stars, but every once in a while i just have to.If your looking to get into data science with python this and hands on machine learning with scikit learn and tensorflow are solid buys. 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 Awesome book if you need/want to go deeper with Pandas.