Python for Data Analysis

http://www.johndcook.com/blog/2012/10/24/python-for-data-analysis/

by anotherbot • 14 years ago

120 28 14 years ago

I personally prefer Python to R for mathematical computing as well. I find it much more comfortable.

jmduke• 14 years ago

From a novice's perspective, this book is incredible. The fact that it's on the O'Reilly network (pay once -- get it in any format, DRM-free) is icing on the cake.

dbecker• 14 years ago

I think the book is excellent for advanced users too.

bduerst3• 14 years ago

Wait, how have you read this? Amazon is only accepting preorders.

dekayed• 14 years ago

You can order the e-book on O'Reilly's website:

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

NyxWulf• 14 years ago

You can get the kindle version now. John Cook may have gotten an advance copy of the book.

incision• 14 years ago

Yep, it's on my Safari bookshelf right now.

From the insert date, it appears the rough cut became available there way back in May.

gjm11• 14 years ago

Blogspam, copied (without author's permission?) from http://www.johndcook.com/blog/2012/10/24/python-for-data-ana... . [EDITED to add: actually, it looks like it was with the author's position. Still blogspam. Incidentally, John Cook's blog is frequently updated and frequently interesting, at least for anyone with an interest in mathematics and software.]

rolux• 14 years ago

Given that the posting has risen quite high on the front page, can the link be changed to the URL of the original?

Not that there was much meat in the article, anyway, but at least the following is mildly insightful:

I prefer Python to R for mathematical computing because mathematical computing doesn’t exist in a vacuum; there’s always other stuff to do. I find doing mathematical programming in a general-purpose language is easier than doing general-purpose programming in a mathematical language.

anotherbot2• 14 years ago

Spamming not intended. And yep, John Cook's blog is fantastic. Concise but powerful ideas like the one quoted below.

keithpeter• 14 years ago

http://www.johndcook.com/blog/2012/10/22/fixing-computers/

Yes, some interesting stuff.

ipython notebook looks nice. Two month wait for paper version in the UK so I'll set the environment up first.

brunosan• 14 years ago

Instead of following the Amazon link, you can go to O'reilly page and use the code CFSTNY to get 50% off. (almost no difference with Amazon.com Kindle version, but you also get the pdf)

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

jagatsastry• 14 years ago

"You did not meet the criteria for this discount" Know what the reason could be?

beagle3• 14 years ago

expired at 12pm PDT (3pm EDT)?

or you tried to get anything other than pure PDF (discount does not apply to dead tree format)

nourishingvoid• 14 years ago

Thanks, I just picked up a copy.

runjake2• 14 years ago

As others have mentioned, this is blogspam. Also note the submitter's submission history. Might be time to ban user anotherbot?

sologoub• 14 years ago

all submissions from dzone and no comments... looks like a bot to me.

anotherbot2• 14 years ago

Nope, person. Try to only post interesting stuff.

danso• 14 years ago

I bought this book when it was in beta form. Thanks for reminding me that I need to update my version. I don't know Python but this book's existence has piqued my interest into moving into it.

elements• 14 years ago

This is great; I've been looking forward to this book for a while. I'd recommend the author's blog, Quant Pythonista (http://blog.wesmckinney.com/), where he posts details of his various quantitative Python projects. It's great for a beginner such as myself to see real-world applications outside of my own projects.

mynegation• 14 years ago

Author, Wes McKinney, is an HN user wesm. Congratulations, Wes!

thronemonkey• 14 years ago

Hmmm I use python for most scientific computing applications, but I do a lot of statistical things in R. I've been interested in trying pandas for a while, might be time to give it a shot . . .

goronbjorn• 14 years ago

I read the pre-release version, and it's honestly very, very good. pandas is such a useful package.

vinayak• 14 years ago

I have been using Pandas and R for sometime now. I found Pandas is a little rough and fragile around the edges (for example, it was really hard to figure out how to get the median of a distribution in a dataframe as compared to R - fairly basic stuff really). Things do not quite work they way you want them. As for R inspite of the arcane syntax, the quality and number of packages, the help and the IDE (rstudio) is really good.

oracuk• 14 years ago

I'm about halfway through this on my Kindle.

I had seen Pandas referenced online and had been meaning to look at it at some point. Reading this book has forced me to pay attention. The Pandas dataframe type is well explained here and is now firing my mind, I'm just spinning off into various applications that hadn't occurred to me before reading this book.

In summary, I would definitely recommend it so far.

Python for Data Analysis

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