Financial Database Management with R

 

In this post, we will be sharing some tips on getting started with R! 

Tip #1 Download RStudio

Downloading RStudio which is a graphical user interface for R could be a great way for beginners starting their R journey. RStudio’s visual nature makes it more user- friendly for the beginners.

You could easily familiarise yourself with the various components and functionality of it by downloading a cheatsheet of the RStudio environment from the RStudio GitHub.

The 4 Quadrants of R


1. The console

This is where you type and execute commands, and where the output of said command is displayed.​

2. The environment/history

The environment tab
Any object that you create in R can be viewed in the Environment quadrant.

 

The history tab
Here you will see the commands that we have run in a session of R. The history tab
 

3. The source/The script editor panel

This is where you store the R commands that you want to save for later, either as a record of what you did or as a way to rerun code.

4. Files/help/plots/packages panel

The files tab

In Files, you can see all of the files in your current working directory.

 

The plots tab

In the Plots tab, if you generate a plot with your code, it will appear here. 

The packages tab

Here you can see all the packages you have installed, load and unload these packages, and update them.

The help tab

The Help tab is where you find the documentation for your R packages and various functions. In the upper right of this panel there is a search function for when you have a specific function or package in question.

 

Tip #2 Taking Baby Steps 

Although, our main aim in learning R is to be able to perform financial analysis using quantitative modelling.

Understanding of basic concepts and learning the ABCs of R is crucial before we take this step.

 

Here is a list of topics in which proficiency is important:

  1. Generating R code

  2. Understanding data structures

  3. Creating functions

  4. Conditional formatting

  5. Looping, list

  6. Using R studio

  7. Scripts, Text editors for R 

  8. Installing packages and libraries

  9. Variable classes (factor, numeric, logical, complex, missing), 

  10. Matrices operations

  11. Summarizing and exploring data

  12. Data cleaning and mining

  13. Using data from external files & writing data to external files

  14. Creating and storing R workspaces

  15. Basic exploratory graphics

This list is in no way exhaustive. First aim of any beginner  should be getting acquainted with the above terms. Don’t worry, if you do not understand many of the terms mentioned here. You can just google them and find numerous videos on these topics.

 

Tip #3 Online Video/ Course

A large number of reputed universities provide courses on R! You can easily enroll yourself in one of these courses and get started with your journey. If you don’t want to enroll yourself in a paid course, there are a number of free options as well. This way, you would not only learn a new skill but also a certificate for your CV.

 

In case you don’t wish to be tied up to a single course, you can also take up youtube. A large number of content creators frequently share a large number of videos. These videos are made for beginners as well as experts so you need to start with basics. Trying to skip the basics and jumping straight to advanced concepts can become detrimental and make you give up!

 

Everyone has different time commitments and you need to choose your option as per your convenience but if you can devote 2- 3 hours a week , then going for a course would be a better choice for you!

 

Tip #4 Books

Although a large number of good books are written on literally every aspect of R, it is always advisable to not take them up first!

 

R isn’t a theoretical subject where you can just mug up your theories. You need to spend time and explore R for yourself. It’s advisable to first go through a concept via a video, then try it out and then move to toy rbooks. It would make your learning experience even more enriching.

 

Moreover, you might fight a large book of 300+ books on  exploratory graphics. If you are able to go through the entire book that would be great but if you even undertsand the basics that is enough for financial analysis!