When working with GIS and statistical data there is an emerging need to know some scripting language. Python is one of the most widely used. It is not perfect but it is like a geographer: fairly good at nearly everything:
“For scientific purposes, when writing a small specialized script, Python may often be the second best choice: for linear algebra, Matlab may have nicer syntax; for statistics, R is probably nicer; for heavy regular expression usage, Perl (ugh) might still be nicer; if you want speed, Fortran or C(++) may be a better choice. To design a webpage; perhaps you want node.js. Python is not perfect for any of these, but is acceptable for all of them.” (Why Python is Better than Matlab for Scientific Software)
In every area, specialized languages are the best choice, but Python is the second best in more areas. But using Python is often a pain in the arse as it comes out of the bash-world and the pure Python editor looks like right out of the eighties. Using this, you will miss syntax highlighting, debugging and many other things. Anaconda is a nice alternative.
Anaconda is a free to use software developed and distributed by Continuum Analytics. It is so cool because it already has all the great packages embedded which are needed to do some great analysis: numpy, scipy, netcdf4, Matplotlib and many others…
What is very interesting at Anaconda is the “GUI” Notebook which is called by the command ipython notebook in the Windows Command Line Tool or in the linux terminal. I really like the idea behind as it is very intuitive, easy to install and has a nice look and feel which reminds me of the codeacademy which is a very nice and easy way to learn Python.
If you want to get to know Python and Anaconda: Feel free to give some credit to Charl Botha who has some nice tutorials here:
