On 09/09/11 11:44, kitty wrote:
...I have been an R user for 7 years and and am
finding it difficult to do even basic things in python,
If you are trying to do the kinds of things that R is good at in Python
you will find it involves a lot more work. That's because Python is a
general purpose programming language and R is a special purpose one,
optimised to its task. You can do most things in Python but it can never
compete with a specialised language in that language's area.
On the other hand if you try writing networking applications or
GUIs in R you will likely find that's harder than using Python.
Choosing the right tool for the job is always a choice between a
specialist tool or a general purpose one. If you do a specialised job a
specialised tool is probably a better choice.
In R I would just
data<-read.table("FILE PATH\\Road.density.municipio.all.txt", header=T)
names(data)
attach(data)
subset<-change.dens[area<2000&area>700]
random<-sample(subset,1)
My question is how do I get python to do this???
Sorry I know it is very basic but I just cant seem to get going,
And there's the rub, it may be very basic in R but its quite a challenge
in Python, you need to get into a lot more detail.
But the good news is that there is an interface between Python
and R - called RPy - that you can use to get the best of both worlds.
Use Python for the general stuff and use RPy for the analytical work...
You can get RPy here:
http://rpy.sourceforge.net/rpy2.html
And there is a simple introduction and comparison of R and
Python benefits here:
http://www.bytemining.com/2010/10/accessing-r-from-python-using-rpy2/
HTH,
--
Alan G
Author of the Learn to Program web site
http://www.alan-g.me.uk/
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