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Joining Data with dplyr

BasicSkill Level
4.7+
1,149 reviews
Updated 05/2023
Learn to combine data across multiple tables to answer more complex questions with dplyr.
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RData Manipulation4 hr13 videos49 Exercises4,200 XP81,091Statement of Accomplishment

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Course Description

Often in data science, you'll encounter fascinating data that is spread across multiple tables. This course will teach you the skills you'll need to join multiple tables together to analyze them in combination. You'll practice your skills using a fun dataset about LEGOs from the Rebrickable website. The dataset contains information about the sets, parts, themes, and colors of LEGOs, but is spread across many tables. You'll work with the data throughout the course as you learn a total of six different joins! You'll learn four mutating joins: inner join, left join, right join, and full join, and two filtering joins: semi join and anti join. In the final chapter, you'll apply your new skills to Stack Overflow data, containing each of the almost 300,000 Stack Oveflow questions that are tagged with R, including information about their answers, the date they were asked, and their score. Get ready to take your dplyr skills to the next level!

Prerequisites

Data Manipulation with dplyr
1

Joining Tables

Get started with your first joining verb: inner-join! You'll learn to join tables together to answer questions about the LEGO dataset, which contains information across many tables about the sets, parts, themes, and colors of LEGOs over time.
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2

Left and Right Joins

Learn two more mutating joins, the left and right join, which are mirror images of each other! You'll learn use cases for each type of join as you explore parts and colors of LEGO themes. Then, you'll explore how to join tables to themselves to understand the hierarchy of LEGO themes in the data.
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3

Full, Semi, and Anti Joins

4

Case Study: Joins on Stack Overflow Data

Put together all the types of join you learned in this course to analyze a new dataset: Stack Overflow questions, answers, and tags. This includes calculating and visualizing trends for some notable tags like dplyr and ggplot2. You'll also master one more method for combining tables, the bind_rows verb, which stacks tables on top of each other.
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Joining Data with dplyr
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FAQs

What types of joins does this course teach?

You will learn six joins total: four mutating joins (inner, left, right, and full) and two filtering joins (semi and anti).

What datasets are used in this course?

You work with a LEGO dataset from Rebrickable covering sets, parts, themes, and colors, and with Stack Overflow data on nearly 300,000 R-tagged questions.

What prior R knowledge do I need?

You should be familiar with dplyr for data manipulation and the tidyverse. Prior completion of Data Manipulation with dplyr is recommended.

When would I use filtering joins like semi join and anti join?

Semi joins keep rows that have a match in another table, and anti joins keep rows that do not. They are useful for filtering data without adding extra columns.

How long does this course take to complete?

The course has 4 chapters and 49 exercises. Most learners finish it in about 3.5 hours.

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