

Pandas (Python data analysis tookit) version 0.8.0 released - wesm
http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-8-0-june-29-2012

======
choffstein
wesm, I can't thank you enough for this library.

I own and operate a quantitative finance business. Pandas (+ numpy) has been a
godsend. Not only do I not have to pay for matlab licenses, but even the less
experience programmers on my team have been insanely productive.

Thank you.

~~~
skierscott
What do you see the advantages of Python/pandas/numpy/etc over matlab as? Do
you use any toolboxes?

~~~
choffstein
Basically, pandas, numpy, and matplotlib give me everything I could have
wanted out of matlab from a numerical capabilities and graphing perspective.

In my opinion, matlab's excellent object inspection and debugging capabilities
can be replaced with strict testing standards in your code-base.

On top of that, I get to use a whole slew of libraries that are non
mathematically related -- frameworks for web services, accessing ftp servers,
sending e-mails -- a lot of automated "utility" stuff.

And it is all "free". Fantastic.

------
monk_the_dog
Pandas is outstanding, I love it.

This may not be the place for this, but...

I just built pandas 0.8.0 and it would not build with MinGW 0.5. The problem
is -mno-cygwin is no longer recognized by MinGW's gcc. My solution was to edit
distutils/cygwincompiler.py and remove references to -mno-cygwin. THIS IS NOT
PANDAS'S FAULT! I just thought I'd point it out in case other people run into
the same problem.

------
dbecker
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.

------
etrain
This release looks like a great upgrade to a great library. The idea of using
python as my "one language" is really appealing, but I still find myself
falling back on R pretty consistently when it comes to data
manipulation/analysis. As pandas matures I see myself doing this less and
less.

Thanks Wes and everyone else who pitched in!

~~~
wesm
I'd be interested to see some of your R use cases where you perceive that
things could be improved in pandas; a year ago there were lots of things you
couldn't do, but a lot has changed :) Nowadays, the tables have turned and
there are lots of things you can do in pandas that are nearly impossible to do
in a non-kludgy way in R (particularly many things with hierarchical
indexing).

~~~
thmcmahon
Wes - I think that the reason I would keep using R over pandas is all the
packages in the R universe. Which I suppose is the reason why you would use
pandas over R if you had more experience with python.

E.g. ggplot2 still seems to be quite a bit better than matplotlib. Also for
the random data examination/sketching I absolutely love rstudio due to it's
integrated help/plotting/file browsing.

------
ig1
Can someone give a rundown about how Pandas compares with numpy ?

~~~
redstripe
It's intended to be a library for working with data stored in multi
dimensional in-memory tables. Think loading a .csv file or relational table
into memory, performing some transformations, adding columns, merging with
other tables, and grouping data, filtering, sorting, all while handling
missing data gracefully.

Maybe I would describe it as combing a spreadsheet with SQL data
transformation capabilities - but better.

It requires numpy because it uses ndarray as it's underlying data structure
and you can also use many/most? of the numpy data analysis functions.

------
petergx
Awesome to see this release. Great stuff for timeseries data analysis among
other things. Thanks Pandas!

