Found 14 comments on HN
pixelmonkey · 2017-08-30 · Original thread
The Wes McKinney Pandas book has a 2nd edition coming out next month. Raw edition is already available on Safari here.

http://shop.oreilly.com/product/0636920050896.do

Release date slated for October 2017.

dwrench07 · 2017-08-30 · Original thread
I use this along with Chris Albons similar repo of recipes (http://shop.oreilly.com/product/0636920023784.do).

It is a great compliment to Wear McKinney's "Python for Data Analysis" it is more like a recipe book than the internals as Wes' book is. Also, JVP includes more than just Pandas and NumPy goodies.

Highly Recommend, and fork to create your own curated handbook.

kbd · 2017-02-24 · Original thread
> Wes wrote his book in Py2 and did not have any desire for Py3

I find it hard to believe you're citing a book that was published in 2012[1], when it made sense to still target Python 2, as relevant to today's argument. The new version is updated for Python 3.5[2].

[1] http://shop.oreilly.com/product/0636920023784.do

[2] https://www.safaribooksonline.com/library/view/python-for-da...

TallGuyShort · 2014-12-05 · Original thread
For those interested in this topic, I just finished and highly recommend http://shop.oreilly.com/product/0636920023784.do. It covers IPython, NumPy, Pandas and matplotlib. It doesn't cover algorithms and analysis so much, but it's great for learning the tools if you already know the statistics.
Bootvis · 2014-10-20 · Original thread
In my eyes, you both make a valid point: yes there's plenty of documentation but sometimes I just can't find what I'm looking for. I like how the book[1] is structured, it really helped me but it isn't complete.

Don't get me wrong, I'm grateful for all the work and I know I haven't contributed much but I think the online could be improved with more examples and recipes.

Edit: There really is no excuse, getting started is easy[2].

[1]: http://shop.oreilly.com/product/0636920023784.do

[2]: http://pandas.pydata.org/developers.html

cessor · 2014-06-07 · Original thread
I am not sure there is a generic answer to your inquiry. If you want to understand python itself you would be best off checking out the source code, building it yourself and then try to change some language features for fun.

Other than that I'd recommend that you find a domain you are particularily interested in and get some books on the specific aspects of that, for example Python for Data Analysis. http://shop.oreilly.com/product/0636920023784.do

This allows you to focus on what to do with python and the eco system of frameworks and so on.

If you want to learn how to use Python effectively, I believe you should decide what domain to apply it in. Python is no end in itself, as is the case with most other tools...

wcbeard10 · 2014-05-06 · Original thread
If you're interested in python, my wife says good things about "Python for Data Analysis." Supposedly quite readable and practical.

http://shop.oreilly.com/product/0636920023784.do

jmduke · 2013-03-05 · Original thread
The creator of pandas wrote a book, Python on Data Analysis, which covers NumPy and Pandas. I found it an excellent primer.

http://oreilly.com/shop/product/0636920023784.html

cgopalan · 2013-02-05 · Original thread
For people who are not satisfied with knowing just Numpy and want to delve into its applications, I would recommend Wes McKinney's book "Python for data analysis":

http://shop.oreilly.com/product/0636920023784.do

I have the book and its been great reading so far. Ch 4 gives a nice introduction to Numpy (about 30 pages). Concise but also useful for immediate real-world usage.

dekayed · 2012-10-25 · Original thread
You can order the e-book on O'Reilly's website:

http://shop.oreilly.com/product/0636920023784.do?code=CFSTNY

pav3l · 2012-10-08 · Original thread
While we are on the topic, the much anticipated Python for Data Analysis (http://shop.oreilly.com/product/0636920023784.do) is supposed to come out this month. I'm wondering if anyone here has tried the early release and what are your thoughts?
birken · 2012-10-04 · Original thread
I'm a huge fan of pandas (http://pandas.pydata.org/) for data analysis. It offers a lot of the basic functionality of R, but everything is in python. The original author of pandas, Wes McKinney, even wrote a book about it: Python for Data Analysis (http://shop.oreilly.com/product/0636920023784.do).

One caveat I would mention about data analysis would be that statistics is not just number crunching. It is really a bit of an art to making sure you are looking at the right sample of data in the right way, and ensure you are accounting for all potential biases. Surprisingly, I have noticed as I've gotten more experience doing data analysis, it takes me longer to do and I make less confident assertions. But on the other hand, I now very rarely make assertions which were incorrect, which is extremely important. I believe that incorrect data analysis is significantly worse than no data analysis.

So, the advice I would give to people getting started is whenever you come to a conclusion by analyzing a particular piece of data, ask your "if I look at the data differently, can I come to the opposite conclusion?". You would be surprised how often the answer to this question is yes, and that is a good indicator that you a) need more data or b) cannot make a significant conclusion. This can be especially difficult when you are already sure you know the answer to a question even before you do the data analysis, but you really have to be disciplined about it.

dbecker · 2012-06-29 · Original thread
Wes: Thanks!

Anyone reading this who wants to get started with Pandas: The early release of "Python for Data Analysis" (http://shop.oreilly.com/product/0636920023784.do) is already very helpful.

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