What I want to do in this post is a development environment in my PC. I am not going to explain the all of the software installation other than R installation because there are plenty of web blog related to open-source installation.
Because I use window XP as a main operating system in my computer, I have to choose an virtual environment. I've chosen an Oracle virtual box which is free as an virtualization software. And I've decided an Ubuntu 2.4 as my main operating system.
Once you've finished fundamental installation, you can add on another software in Linux environment. If you have a preferable environment, then you can choose what you want.
I've already explained how to install R software in Window environment in another post, but this time I will show show you how to install R in linux environment.
Of course, detailed install guide can be found in R official web page.
First, visit main web page http://www.r-project.org/
Then, go to download page and click your preferable mirror site.
Now, you can see different kinds of R software versions in terms of OS. (Click Linux version)
After that, you can find a install guide on the below. I will briefly show you how to executed in my PC environment.
1) To obtain the latest R packages, add an entry in your /etc/apt/sources.list file
My favorit cran mirro site is like this.
deb http://cran.stat.sfu.ca//bin/linux/ubuntu precise/
Thursday, 21 November 2013
Thursday, 31 October 2013
Introduction of this Blog
This blog is series of R self study ( http://flydokyun.blogspot.kr/ )
I've made a decision to open a new blog which has a different title.
Previous R self study was focused on the statistic concept but this post is going to be more practical basis because I am going to analyse with a real data. Furthermore, I am going to introduce an IT environment such as DBMS, Linux, Hadoop.
I think, data analysis which is conducting in an enterprise is executed by large IT system environment which has a huge data. Therefore, It is also important to understand IT environment and programming language, such as python or java.
I hope, you will be happy with my blog.
Followings are development environment in my PC.
Those IT environment will be covered more detail in next post.
1. OS : Ubuntu 12.04.2 LTS
2. DBMS : Server version: 5.5.32-0ubuntu0.12.04.1 (Ubuntu)
3. R : R version 2.14.1 (2011-12-22)
4. JAVA : java version "1.7.0_40"
5. HADOOP : hadoop-1.2.1
6. Python : Python 2.7
7. Test Data source : http://www.nbastuffer.com , www.nba.com
I've made a decision to open a new blog which has a different title.
Previous R self study was focused on the statistic concept but this post is going to be more practical basis because I am going to analyse with a real data. Furthermore, I am going to introduce an IT environment such as DBMS, Linux, Hadoop.
I think, data analysis which is conducting in an enterprise is executed by large IT system environment which has a huge data. Therefore, It is also important to understand IT environment and programming language, such as python or java.
I hope, you will be happy with my blog.
Followings are development environment in my PC.
Those IT environment will be covered more detail in next post.
1. OS : Ubuntu 12.04.2 LTS
2. DBMS : Server version: 5.5.32-0ubuntu0.12.04.1 (Ubuntu)
3. R : R version 2.14.1 (2011-12-22)
4. JAVA : java version "1.7.0_40"
5. HADOOP : hadoop-1.2.1
6. Python : Python 2.7
7. Test Data source : http://www.nbastuffer.com , www.nba.com
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