New Release Pandas 0.4.0

See http://pandas.sourceforge.net/


pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. It is already well on its way toward this goal.
pandas is well suited for many different kinds of data:

• Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet
• Ordered and unordered (not necessarily fixed-frequency) time series data.
• Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels
• Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure

Read more on http://pandas.sourceforge.net/

New release iPython

Interesting review of the new version

Innovations in iPython

One of the highlights of SciPy 2011 was a demonstration of the upcoming release of iPython 0.11 (which is likely to become version 1.0, eventually). Fernando Perez calls iPython a "tool for manipulating namespaces", but this dry, technical definition belies the productivity-boosting power of this project. I have been using iPython for a few years as a replacement for the standard shell because it affords users easier access to debugging tools, command history and the underlying file system. Version 0.11 adds to this a variety of enhancements that further improve its utility and usability. A full account of it many features can be found in the iPython documentation, but I want to highlight a couple of the recent innovations that users might not be aware of. ...read More...

Cloudnumbers: Your Python Application in the Cloud

cloudnumbers.com supports the interpreted, interactive, object-oriented and extensible programming language Python (http://www.python.org/). Python is a user-friendly open source programming language that is used in many areas. It has become really popular since many programmers consider it to be one of the easiest programming languages to study and work with.
cloudnumbers.com combines High-Performance Computing (HPC) and Python in order to provide a fully scalable platform for all your calculations. Combining Python´s ease-of-use with high performance computing means that ideas can more quickly become applications, increasing the productivity of developers, while overcoming any limitations.
HPC support for Python is provided with the following libraries:

• mpi4py (http://mpi4py.scipy.org/): This module provides the binding of the Message Passing Interface (MPI) standard to the Python programming language. It allows any Python program to exploit multiple processors.
• pp (http://www.parallelpython.com/): This module provides mechanism for parallel execution of Python code on multicore machines and on computer clusters.

Fractal (and Quantum) Finance back again: Try out Fraclab

Fraclab is a Matlab-based toolbox for image and signal processing mainly developed and maintained by people at INRIA. It seems to include powerfull fractal modules used in
Astrophysics, Biomedical, Chemical engineering, Fluid dynamics, Food engineering, Geophysics, Internet traffic, Mathematical analysis, Signal and image processing, Statistics and...Finance.
An interesting feature is also that you do not need to have Matlab installed to get it run since there is a standalone packaged version available (that, by the way, installs a run-time Matlab version on your system during the install process).

Fraclab is available for Windows, Mac OS X and Linux.

Rattle: A Graphical User Interface for Data Mining using R

In addition to Rstudio the following tool looks promising: Rattle
Rattle (the R Analytical Tool To Learn Easily) presents statistical and visual summaries of data, transforms data into forms that can be readily modelled, builds both unsupervised and supervised models from the data, presents the performance of models graphically, and scores new datasets.

Numpy and Scipy Ports for IronPython (.NET)

Here is Codeplex wiki entry for the port of  Numpy and Scipy for IronPython 2.7. Please note that not all Scipy features have been ported yet but sounds like a good start.

Amended IAS 19 released: Is the Glass half-full or half-empty?

The IAS Board has eventually released the long-awaited amended standard IAS 19 Employee Benefits (a 175+ pages document!).  The main changes consist of:

• eliminating an option to defer the recognition of gains and losses, known as the ‘corridor method’, targeting improvement of comparability and faithfulness of presentation. 
• suppression of the concept of expected return on assets  and explicit requirements to consider the tax on contribution effect on DBO.
• streamlining the presentation of changes in assets and liabilities arising from defined benefit plans, including requiring remeasurements to be presented in other comprehensive income (OCI), thereby separating those changes from changes that many perceive to be the result of an entity’s day-to-day operations.
• enhancing the disclosure requirements for defined benefit plans, providing better information about the characteristics of defined benefit plans and the risks that entities are exposed to through participation in those plans. 
• amending the treatment of Termination Benefits by excluding stay-bonuses from this category and distinguishing termination as a result of employer's or the employee's decision. 

These changes - effective as from FY 2013 -  bring IAS 19 more in line with the IFRS framework. However, we can doubt they will effectively contribute to give a more reliable economic view on the financial position of the reporting entities (mthe obligation mresaurement remain highly volatile)  if as noted by many obsevers a second Phase does not complete the revision process. It is indeed not clear whether the IASB (currently in a transition phase: members have to be replaced) intends to take this on the agenda at short notice. In this case, entities would have to cope with a half-revised standard. So,...

More specifically, from a Belgian viewpoint: 

• the accounting of DC plans would not be affected by the amendments because the IAS Board eventually decided to remove the modification of back-loaded plan rule that would have seriously affected them.
• the tax impact on DBO may be significant.
• we advise to pay special attention  to the treatment of Employee contribution and Termination Benefits as well as to the impact of the suppression of the expected return on assets.