Getting ready for the PyCon Pandas tutorial

Today I received an email with a link to instructions for preparing a computer for the PyCon Tutorial: Data analysis in Python with pandas, complete with the following instructions for:

Installing PyQt on OS X and Linux
Installation of PyQt from source on OS X and Linux is much more involved.
OS X: http://www.oak-tree.us/blog/index.php/2009/05/12/pyqt-mac

Note the lack of instructions for installing on Linux.  Thrown to the wolves, I guess...

In the interest of helping other Linux users (or at least Ubuntu 10.10 users) out, here are the steps for setting up a Python virtual environment with the necessary libraries, using virtualenvwrapper and pip.

mkvirtualenv pandas

pip install numpy
pip install scipy
pip install matplotlib
pip install ipython
sudo apt-get install libzmq-dev
pip install pyzmq
pip install pygments
pip install pandas
pip install python-dateutil
pip install pyqt
pip install tornado
ipython notebook --pylab=inline

Here is a list of the library versions that were installed:
(pandas)tylere@tylere-laptop:~$ pip freeze

Pygments==1.4
ipython==0.12
matplotlib==1.1.0
numpy==1.6.1
pandas==0.7.0
python-dateutil==1.5
pyzmq==2.1.11
scipy==0.10.0
tornado==2.2
wsgiref==0.1.2
yolk==0.4.3




pyKML at the 2012 American Meteorological Society Annual Meeting

Tomorrow I am giving a talk at the American Meteorological Society Annual Meeting entitled:

Using the pyKML Library to Format Weather and Climate Data for Viewing in Google Earth

It is at 11:45, if you happen to be at the meeting.  The talk presents numerous examples of using pyKML, but because of the static format required by the conference (i.e. Powerpoint or PDF) I thought it might be useful to provide a number of links to related content. Enjoy!

pyKML:

• pyKML Source Code (Google Code)
• pyKML packages (PyPI)
• pyKML Documentation  (PyPI)
• Google Geo Developers blog post
• FOSS4G presentation created in pyKML

Examples:

• Unidata Weather Forecast Time Series
• Visualizing Atmospheric Carbon
• OpenClimateGIS Web Service

Misc:

• lxml included in experimental Google App Engine Python 2.7
• lxml