[ANN] scikits.timeseries 0.91.0

[matt knox]

We are pleased to announce the release of scikits.timeseries 0.91.0

This is the first official public release of the scikits.timeseries module.
Due to the long birthing period, the api is considered stable and the version
number was chosen to reflect the relative maturity of the initial release
compared to a typical first release.

Home page: http://pytseries.sourceforge.net/
Please see the website for installation requirements and download details.
Note that the recently released numpy 1.3.0 is a strict requirement.

Windows binaries are provided for Python 2.5 and 2.6.

About the package
=================

The scikits.timeseries module provides classes and functions for
manipulating, reporting, and plotting time series of various frequencies. The
focus is on convenient data access and manipulation while leveraging the
existing mathematical functionality in numpy and scipy.

If the following scenarios sound familiar to you, then you will likely
find the scikits.timeseries module useful:

   * Compare many time series with different ranges of data (eg. stock
     prices);
   * Create time series plots with intelligently spaced axis labels;
   * Convert a daily time series to monthly by taking the average value
     during each month;
   * Work with data that has missing values;
   * Determine the last business day of the previous month/quarter/year for
     reporting purposes;
   * Compute a moving standard deviation efficiently;

These are just some of the scenarios that are made very simple with the
scikits.timeseries module.

Thanks,
Matt Knox & Pierre Gerard-Marchant