viziblr

In preparation for some posts on analytics and visualization, I was inspired by this video of Wes McKinney introducing a PyCon audience to Pandas. I needed a low-friction tool to interactively work with tabular data and for now Pandas looks like the right choice.

I also wanted to take this opportunity to learn how to use PyPI to install packages instead of relying on binary installers. Unfortunately getting this done end-to-end isn't entirely clear so I've put up my steps below.

State of My System Before I started

• Operating System: Windows 7 SP1
• Python Components: Python 2.7.3 and PyWin32–217.

Step 1 Install SetupTools

Go here: http://pypi.python.org/pypi/setuptools and find the binary installer for Python 2.7

I downloaded this version: setuptools-0.6c11.win32-py2.7.exe

Yes, this is a binary installer. But once we have setuptools everything else is easy and will not require an installer.

Look in the C:\Python27\Scripts folder. You'll see that it contains an EXE called easy_install.

Step 2 Install NumPy

Start a cmd shell are this simple command

C:\>Python27\Scripts\easy_install.exe numpy

This command will start and eventually after spitting out a lot of text numpy will be installed.

Step 3 Install dateutil

This package is actually called “python-dateutil” so we need to use that name instead with easy_install

C:\>Python27\Scripts\easy_install.exe python-dateutil

Step 4 Install Pandas

You can see where this is going …

C:\>Python27\Scripts\easy_install.exe pandas

Step 5: Verify Pandas is working

We are done with the installation, let's make sure it actually works by running a quick script.

import numpy
import pandas

df = pandas.DataFrame( { "A": [11, 12, 13], "B": [34,78,109] } )

df.sum()

Parting Thoughts

• easy_install versus pip: It's generally recommended that one use pip instead of easy_install. I chose not to in this example because I was having problems with pip.
• What next: Sometime soon I'll go through some simple pandas scenarios, focusing getting good analytics out of a bug tracking database.