Because of the vast amount of Big Data available to Corporations and Businesses in today’s Technology world. R Programming has become an increasingly popular choice among Programmers and Organisations. R Programming Language is very powerful when it comes to exploring data, visualising data, and developing new statistical models. R is an implementation of the S programming Language but there are differences. R is an Object-Oriented Language much of it’s functions work in C and Fortran.
R first appeared in 1996 when statistics Professors Ross Ihaka and Robert Gentleman of the University of Auckland, in New Zealand released the code as a free software package.
R is particulary useful because it contains a number of built-in mechanisms for organising data, running calculations on the information and creating graphical representations of data sets.
Packages written for R add advanced algorithms, coloured and textured graphs and mining techniques to dig deeper into databases. The Financial Services community has demonstrated a particular affinity for R; dozens of packages exist for derivatives analysis alone.
“The great beauty of R is that you can modify it to do all sorts of things,” said Hal Varian, Chief Economist at Google.
R Software is an open source and is free to download, simply google www.r-project.org and follow the download instructions for your pc or laptop.
R supports matrix mathematics and it’s data structures include vectors, matrices, arrays, data frames similar to tables and lists. R can be used as a calculator for example if you input 1+1 in the R command prompt you would receive the answer 2.
Luckily R has some sample data sets to play around with. One of these is Volcano a 3D maps of a dormant volcano in New Zealand.
It’s simply a 87 X 61 matrix with elation values, but it shows the power of R’s matrix visualisations.
The image function will create a heat map.
Plotting A Graph in R
For this part I downloaded a .csv file from Met Eireann website, for the monthly rainfall in Dublin for the past 30 years. The file was too big so I took the 12 months 2014 to make it easier to work with.
In order to plot a graph in R the data has to be in length form to do this I put in the following script.
The above graph shows the amount of rainfall in Dublin last year 2014, amounts are given monthly. I found R language to be a very unforgiving at times. Mainly because the amount of error messages that came up. The graph is not as good as it should be, I’ll have to keep practicing the R language.