There are lots of resources available online which can teach you R. But most of those tutorials or lectures are not written keeping Beginners in mind.

rsz_r-tutorial-minAuthor got an opportunity to train 500+ Data Science beginners and this work is an attempt to cater to the needs of beginners who are searching for “R tutorials for beginners”

  1. Getting Started With Learning R: This is very basic lecture of R learning, where we talked about various types of variables, assignment, variable manipulation etc.
  2. Combine, Coerce and vector: In this tutorial you will learn about combine operator c(), coercing and basics of vectors
  3. Matrix in R: This article is dedicated to matrices in R, where you will learn creating matrix, manipulating them and matrix operations
  4. Arrays in R: The next data type i.e., Arrays are explained with simplest possible explanations and examples. You will learn how to create arrays? How to use arrays? etc.
  5. Basics of Data Frame: Dataframes are the most used data type in R. In this chapter we have covered basics of dataframe i.e., creation, operations etc.
  6. Basics of Data Frame – 2: In this tutorial we talk about how to access various parts of a dataframe like referencing by name, referencing by indices.
  7. Logical Operators in R: There are various logical operators which can be used in R. This part gives you an overview of different logical operators and their use.
  8. Sub-setting in R: When we work with data often we have to subset our data i.e., select a small part of it. In this tutorial you will come to know about various ways to subset your data in R.
  9. Lists and Factors in R: List and Factors are two very important data types in R. These are the two data types which will help you a lot if you use them correctly but are equally bad if you mistreat them.
  10. Missing values and type conversion: Missing values are important not only in R but in every programming language. Learn to identify and treat missing values in R
  11. Binding, merging and sorting in R: In most of the situations you will not get data in one combined file, rather the data will be available in different files. And, in these situations you will have to combine data to make a logical or analytical dataset. Let see how can we achieve the same in R.
  12. Working with Dates and Time in R: Dates and time-stamps are the datatype which are frequently used in R. But most probably they will come as character, factor formats. They will have different structure, Don’t worry – Learn to work with Date and Time in this tutorial
  13. Control Flow and Functions in R: Similar to other programming languages R also provides an option of creating control flow using if-else, For loop, While loop etc. – Learn how to use them in this tutorial. Article also talks about creating user defined functions in R to do a specific task in your program
  14. Aggregate Functions in R: Aggregation is similar to Group By in SQL, it’s basically to group observations and apply an aggregation function over the group
  15. apply Family in R: apply functions in R are one of the best features provided by R. This article provides the introduction to apply family in a most simpler way
  16. String Functions in R: Strings are the most commonly used data type in any programming language. Here, we have talked about few most frequently used string functions.
The following two tabs change content below.