Data Science with R

I am in the process of learning Data Science with R language. I created this site in an attempt to document my journey through the process. If you are new to data science and are interested in learning it, this is probably a good start.

Why R? (and not Python)¶

No specific reason. I personally prefer Python because it is a proper programming language. From what I learned on the internet, usually those from technical or coding backgrounds tend to prefer Python over R for several reasons: it's easier to learn than R, it's like writing in English and easier to debug, and it can be quickly deployed in production environments. R, on the other hand, has been a standard langauge for statistician for a long time. I heard it's good for academics than for production, but things appear to be changing. It doesn't follow the modern programming language syntax, but has it's own coding style similar to the ancient ForTran. It is said that R has a steeper learning curve but good for someone who doesn't have any programming background as they don't have to re-adapt to a different coding style. I want to see how I'll fair with R.

My working environment¶

R and Rstudio, the tools required for working on R, should normally work with any modern computer. I read that R uses system memory (RAM) to load the data and could be one of the limitations of using R as data science usually deals with big amounts of data. I want to test if this can be achieved on a low end computer.

For this project, I'll be working a 13 year old laptop (bought in 2007) and see how far it goes.

• Intel core 2 duo processor underclocked to 0.98 GHz (very slow).
• 4 GB DDR2 RAM (old and slow RAM).
• 1280 x 800 (pretty basic resolution. May have to resize Rstudio to fit within the screen)

If something works on this, it should work anywhere :-)

Proceed to Table of Contents

Last updated 2020-04-15 11:47:03.927946 IST