You may be asking yourself: How can I learn R quickly? We'll break down our question into two parts to answer that question. We will discuss the core skills required to master R as well as the resources available to help you build these skills.
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Establish Your Motivation
Before you start learning R, it is important to ask yourself the following question: What are your motivations? You might find it helpful to have a clear understanding of your motivation to learn R. It will help you to resist the temptation to quit when you face a challenge.
Are you interested in analysing personal data? Do you want to be a data scientist? Do you enjoy working with data and are looking for a challenge? No matter what your motivation, be clear and precise. Ask yourself what data you are looking to analyse if you want to become a data scientist. Are you looking to analyse data from the stock market, healthcare, or sports?
Once you have established your motivation, it will be easier to start your journey to learn how to code in R.
Learning the Basics
Now that you've decided to learn R, your main focus should be on the basics. This will provide a solid foundation on which to build your skills. We'll help you get started by listing the most important skills that you should master.
Syntax and Variables
It is impossible to avoid learning the syntax of R, the rules that govern the language. This can be a difficult subject. The good news is that you won't have to learn the syntax again once you've mastered it.
Data Frames
Data frames are objects that store data within a table structure, with rows and columns. A data frame is similar to a spreadsheet but can be customised more.
Data Cleaning and Visualisation
Data cleaning is the process of creating a dataset for analysis. You must remove data that isn't relevant to your intended use case in order to clean up a dataset.
Visualisation is a method that transforms raw data into charts. These charts show your data visually.
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