Manipulate R data frames using SQL in RStudio


Manipulate data from R data frames using SQL SELECT statements

Manipulate R data frames using SQL SELECT statements and SQL operators together with the WHERE clause

Perform data aggregation and summarization using SQL aggregate functions

2 hours

Have you ever wondered how SQL queries work in R? Have you ever thought about whether it is possible to use or write SQL queries in R? Then, you are in the right place. This project-based course Manipulate R data frames using SQL in RStudio is for people who are learning R and who may be well-versed in SQL or even for experienced R programmers who seek useful ways for data manipulation in R. It is for people who are interested in advancing their knowledge and skills in using SQL in R. In this project, we will write very nice queries to manipulate the gapminder and UCBAdmissions R data frames using the sqldf package in RStudio. This project is extremely important for you as an R and SQL user. You will understand how the SQL SELECT statement works to interact with R to get the desired result. We will start this hands-on project by installing and importing the required packages and data sets for this project. Be rest assured that you will learn a ton of good work here. By the end of this 2-hour-long project, you will be able to use SELECT statements together with the WHERE clause to set conditions on data retrieved from R data frames. Also, you will understand how to use the WHERE clause together with other SQL operators like AND, OR, IN, NOT IN, BETWEEN- AND, NOT BETWEEN- AND, and other comparison operators to retrieve data from the data frames. Going forward, we will consider how to use wildcard characters with the LIKE and NOT LIKE operators for pattern matching. By extension, we will learn how to create data summaries or aggregates using SQL aggregate functions. In this project, we will move systematically by first introducing the SELECT statements using simple examples. Then, we will write slightly complex queries to solve some SQL challenges. Therefore, to complete this project, it is required that you have prior experience with using SQL and R. I recommend that you should complete the projects titled: “Getting Started with R” and “Querying Databases using SQL SELECT statements” before you take this current project. These introductory projects in using SQL and R will provide every necessary foundation to complete this current project. However, if you are comfortable writing queries in SQL, please join me on this wonderful ride! Let’s get our hands dirty!


  • Data Manipulation

  • R Programming

  • data querying

  • SQL Operators

  • SQL



  1. Getting Started

  2. Import and Explore the data sets

  3. SELECT and FROM Statements

  4. WHERE and SQL Operators - I

  5. WHERE and SQL Operators - II

  6. Wildcard Characters

  7. Aggregating Data

  8. Wrap up