R or R not?

If you're reading this, you're probably thinking about learning R, the powerful and versatile programming language for data analysis. Maybe you're a beginner who has never written a line of code before, or maybe you're a more experienced programmer looking to add R to your toolkit. Either way, you're in the right place! I am a total beginner, so it will be interesting to record my progress in the field.

So lets start by install R and RStudio. R is the programming language (the base), and RStudio is the Integrated Development Environment (IDE) that makes it easy to write and run your code. You can download them for free from their respective websites.

Some basics.

 R is an object-oriented language, which means that everything in R is an object (e.g., numbers, strings, vectors, etc.). Objects have different types and can be manipulated in various ways using functions. I am  learning now about the different types of objects and how to use functions to manipulate them.

Import and export data.

 R has a number of functions for importing and exporting data from various sources (e.g., CSV files, Excel files, databases, etc.). These functions allow you to bring your data into R and save it in a format that you can use for analysis.

Its always a good idea to practice with small datasets in the beginning. Once we have some data in R, start practicing with small datasets to get a feel for how to manipulate them. Use functions like subset(), sort(), and merge() to extract, rearrange, and combine our data.

The next step is to visualize your data.

 R has a number of powerful functions for creating beautiful visualizations of our data. There we can use functions like ggplot(), hist(), barplot(), and scatterplot() to explore your data and gain insights from it.

The visuals are maybe the most important part of this procedure, because through them, we will communicate our results to the people that are interested.