Analyze with R

Aside from python, I’ve been using R for data science projects. This chapter relates to the use of R in data analysis and data science projects.

We’ll skip the steps needed to load R onto your system and will jump into RStudio and version control.

I happen to be using RStudio Desktop and what we’ll cover relates to the use of that platform. Of course many of the commands can be used directly in your console, or cmd prompt depending on which system you’ll use some details will be different.

  • So, to start using R in RStudio along with version control, please visit R Setup page.

  • The second process we’ll cover is data Import & Export, even though we’re a bit too early on the Export part, both processes are in the same section.

  • EDA - Exploratory Data Analysis is an important section, this is where we get to test our hypotheses or come up with new ones, as we play around with the data

  • Tidy Data is where we have already cleaned the data and have transformed it into a Tidy dataset.

I will not go through all the other links in this section as most titles are self-explanatory.

Good luck