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4 of 4 people found the following review helpful
5.0 out of 5 stars Excellent introduction to the Pandas library for Python
I'm still ploughing through this book, but I've already found it incredibly useful.

I've heard of the Pandas library for Python before - I heard that it provided similar functionality to the data.frame object in R. I believe this book is written by the author of the Pandas library. It certainly provides an excellent description of the library.

There...
Published 20 months ago by Ewan Nicolson

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0 of 3 people found the following review helpful
3.0 out of 5 stars Wide ranging coverage of Pandas
Well written book, however one does need to supplement some of the examples with research on line, to get the latest info.
Also I did install the latest version on my PC.
Published 13 months ago by AndyC


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4 of 4 people found the following review helpful
5.0 out of 5 stars Excellent introduction to the Pandas library for Python, 6 Dec 2012
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This review is from: Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython (Kindle Edition)
I'm still ploughing through this book, but I've already found it incredibly useful.

I've heard of the Pandas library for Python before - I heard that it provided similar functionality to the data.frame object in R. I believe this book is written by the author of the Pandas library. It certainly provides an excellent description of the library.

There are plenty of practical examples in this book as well, but it is really the introduction to Pandas that I've found useful. It has revolutionised the way I write my code for data analysis.

One final thing; if you find the Pandas library useful, I'd suggest having a look at the Ramp library for machine learning:

[...]

It says it is a wrapper for various Python machine learning libraries using the Pandas framework. I've used it briefly and it looks very promising.
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9 of 10 people found the following review helpful
5.0 out of 5 stars Worth the time and money spent on it., 8 Jan 2013
I started reading at this particular book being sceptical. Although I most O'Reilly books I've read deliver, this one promises to introduce you to a field that is vast. Python's various usages in data analysis. Does this one deliver? Certainly!

Let me be more specific. In the interest of full disclosure, I should note that I got this book for free via O'Reilly's Blogger Review program. I have some experience in Python and, during the time of my exposure to it, I always read that Python was very powerful in the Data Analysis field, be it Scientific Computing, Financial Computing (up to a point, of course) and others, so naturally, I wanted to read a book to get to study Python's usage in this field. What got me more hooked into reading this book is that this particular one was written by an expert on the field. The author of the book is also the author of the Pandas library. When I finally got through it, here are my comments on it:

- First this book gives you some information on why the data analysis field matters. For instance it refers to an example, using data analysis to come up with data sets to feed a machine learning algorithm.
- The book has short and concise (and above all, easy to follow) code examples that demonstrate the point of the text very quickly.
- The book provides several realistic use cases of the demonstrated content, so that you can get a good idea of what data analysis is all about.
- Covers (in varying degrees) xml parsing, interaction with HTML and databases. It even makes a small reference to MongoDB!
- It also covers string manipulation (including regular expressions) which is very nice!
- Has a whole chapter dedicating to plotting and visualizing.
- Has several chapters on Numpy and Pandas!
- Has a great chapter focusing on date and time data manipulation and the relevant modules in the Python lib.
- Although this book is better read if you have some Python knowledge already and want to extend your Python knowledge, it also has an appendix which goes through the essential knowledge of the Python programming Language, so even beginners with Python should feel comfortable with it.

Overall, I recommend this book if you want to get a good idea about Python's usage in Data Analysis, whether you are a Python novice or a Python expert.
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1 of 1 people found the following review helpful
4.0 out of 5 stars Good book, 14 July 2013
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Quite a good book, although a bit heavy on the Pandas section - which may be good if thats what you want - I didn't. Never the less I have learned a great deal from it, and would recommend it
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1 of 1 people found the following review helpful
5.0 out of 5 stars great introduction to pandas, 15 Mar 2013
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Mr. Andrew Burrows (UK) - See all my reviews
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This review is from: Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython (Kindle Edition)
I already do a lot of this kind of stuff in numpy and scipy but wanted to learn about pandas so I only read the chapters on pandas but they were excellent as you'd expect from the creator of the library.
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5.0 out of 5 stars Perfect for a keen beginner eager to dive into Python, 28 May 2014
After attending a two-day introduction to Python programming at work, I was keen to delve further into the language and its capabilities in statistics and number crunching despite never having programmed before.

Many beginners programming books spend hundreds of pages on background and tediously basic tasks (I remember one that had six pages on "Hello World".) The genius of this book is that it manages both to cover the basics of python scripting whilst getting you on to the more interesting and advanced topics pretty quickly. There is even a short crash course to the language basics at the back for people who haven't used Python before, which is where I started.

You can only really learn to code by having a go yourself, which is what this book allows you to do. Even if your interests are broader than data analysis, this will set the groundwork for you to teach yourself the rest!
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5.0 out of 5 stars Python (but really Pandas) for Data Analysis, 16 May 2014
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Python has an especially strong and widespread usage in scientific/engineering/data-analysis computing. Until a few years ago, an important tool that was missing from python was the ability to handle a so-called "data-frame", which in very basic terms is a spreadsheet-like data structure that contains heterogeneous data types in its columns (this type of structure is a main component of, for example, the R programming language for statistical computing). Around 4 years ago, this and related data-structures, and a great big set of tools for working with them, were provided by the pandas library and now pandas is *the* vital component for doing data-analysis in python.
This book is really about pandas (the author is the main author of pandas, after all), and less about either numpy or ipython or other tools. I don't mean that as a criticism. It is precisely as it should be. If you are doing strictly data analysis in python, it is pandas primarily that is center stage, with tools like numpy/ipython etc playing supporting roles. What this book does convey, however, is just how well all these tools work together and how they form a big team for scientific/numerical computing in python.
This book is detailed and extensive. It is entirely focused on well thought out follow-along-yourself code examples, and this makes it a remarkable effective way to learn pandas especially, but also to learn more about numpy/ipython/matplotlib etc.
If you do data analysis in python, this book is a must have. It is highly recommended too for anyone doing scientific/numerical computing in python generally.
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5.0 out of 5 stars A very well written book, 25 April 2014
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P. Bennett (Manchester, UK) - See all my reviews
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This review is from: Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython (Kindle Edition)
This book is a great introduction to python pandas. A good practical background in Python is useful before buying this book, although there is a very useful condensed language summary at the back of the book. Most of the examples in the book are practical and real-world. In general, the book is extremely well written and is very concise.
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5.0 out of 5 stars Best book on programming topic I've ever read, 30 Mar 2014
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I'd like to believe I've read quite a few books on programming, but this one is by far the best I've read. Excellent structure, writing style, real-world examples, so it makes it relevant from day 1. I'm really looking forward for more books coming from Mr. McKinney!
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5.0 out of 5 stars Introduction to some fantastic tools for data analysis, 22 July 2014
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although a lot of this text is available in tutorials and guides on the pandas website, I bought this book as a desk reference and to support Wes McKinney for developing a product I use more and more in my work.
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0 of 3 people found the following review helpful
3.0 out of 5 stars Wide ranging coverage of Pandas, 7 Jun 2013
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Well written book, however one does need to supplement some of the examples with research on line, to get the latest info.
Also I did install the latest version on my PC.
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