Joining Data in SQL
Join two or three tables together into one, combine tables using set theory, and work with subqueries in PostgreSQL.
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Course Description
Now that you've learned the basics of SQL in our <a href="https://www.datacamp.com/courses/intro-to-sql-for-data-science">Intro to SQL for Data Science</a> course, it's time to supercharge your queries using joins and relational set theory. In this course, you'll learn all about the power of joining tables while exploring interesting features of countries and their cities throughout the world. You will master inner and outer joins, as well as self joins, semi joins, anti joins and cross joins—fundamental tools in any PostgreSQL wizard's toolbox. Never fear set theory again after learning all about unions, intersections, and except clauses through easy-to-understand diagrams and examples. Lastly, you'll be introduced to the challenging topic of subqueries. You will be able to visually grasp these ideas by using Venn diagrams and other linking illustrations.
- 1
Introduction to joins
FreeIn this chapter, you'll be introduced to the concept of joining tables, and will explore the different ways you can enrich your queries using inner joins and self joins. You'll also see how to use the case statement to split up a field into different categories. - 2
Outer joins and cross joins
In this chapter, you'll come to grips with different kinds of outer joins. You'll learn how to gain further insights into your data through left joins, right joins, and full joins. In addition to outer joins, you'll also work with cross joins. - 3
Set theory clauses
In this chapter, you'll learn more about set theory using Venn diagrams and get an introduction to union, union all, intersect, and except clauses. You'll finish by investigating semi joins and anti joins, which provide a nice introduction to subqueries. - 4
Subqueries
In this closing chapter, you'll learn how to use nested queries and you'll use what you’ve learned in this course to solve three challenge problems.
Filip Schouwenaars
Colin RicardoPrerequisites
Introduction to SQL
Chester Ismay
Data Science Evangelist at DataRobot
Chester leads data science, machine learning, and data engineering in-person workshops for DataRobot University with DataRobot. He built (and helped instructors build) R, Python, SQL, and Spreadsheets courses for DataCamp first as a Curriculum Lead and then as Head of Content Development. He obtained a PhD in Statistics from Arizona State University and has taught courses and led workshops in mathematics, computer science, statistics, data science, and sociology. He is co-author of the fivethirtyeight R package and author of the thesisdown R package. He is also a co-author of ModernDive, an open-source textbook for introductory statistics and data science students using R.
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