Tabular data package

[Elaine Angelino]

Hi there,

We are writing to announce the release of "Tabular", a package of Python
modules for working with tabular data.

Tabular is a package of Python modules for working with tabular data. Its
main object is the tabarray class, a data structure for holding and
manipulating tabular data. By putting data into a tabarray object, you’ll
get a representation of the data that is more flexible and powerful than a
native Python representation. More specifically, tabarray provides:

-- ultra-fast filtering, selection, and numerical analysis methods, using
convenient Matlab-style matrix operation syntax
-- spreadsheet-style operations, including row & column operations, 'sort',
'replace', 'aggregate', 'pivot', and 'join'
-- flexible load and save methods for a variety of file formats, including
delimited text (CSV), binary, and HTML
-- helpful inference algorithms for determining formatting parameters and
data types of input files
-- support for hierarchical groupings of columns, both as data structures
and file formats

You can download Tabular from PyPI
(http://pypi.python.org/pypi/tabular/<http://pypi.python.org/pypi/tabular/>)
or alternatively clone our hg repository from bitbucket (
http://bitbucket.org/elaine/tabular/ <http://bitbucket.org/elaine/tabular/>).
We also have posted tutorial-style Sphinx documentation (
http://www.parsemydata.com/tabular/).

The tabarray object is based on the record
array<http://docs.scipy.org/doc/numpy/reference/generated/numpy.recarray.html?highlight=recarray#numpy.recarray>object
from the Numerical Python package (
NumPy <http://numpy.scipy.org/>), and Tabular is built to interface well
with NumPy in general.  Our intended audience is two-fold: (1) Python users
who, though they may not be familiar with NumPy, are in need of a way to
work with tabular data, and (2) NumPy users who would like to do
spreadsheet-style operations on top of their more "numerical" work.

We hope that some of you find Tabular useful!

Best,

Elaine and Dan
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