Joining Data with dplyr

Learn to combine data across multiple tables to answer more complex questions with dplyr.
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4 Hours13 Videos49 Exercises18,591 Learners
4200 XP

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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!

  1. 1

    Joining Tables

    Free
    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. 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. 3

    Full, Semi, and Anti Joins

    In this chapter, you'll cover three more joining verbs: full-join, semi-join, and anti-join. You'll then use these verbs to answer questions about the similarities and differences between a variety of LEGO sets.
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  4. 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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In the following tracks
Data Analyst Data Manipulation Data Scientist
Collaborators
Amy Peterson
Chris Cardillo Headshot

Chris Cardillo

Data Scientist
Chris is a Generalist, and actually learned programming for data science on DataCamp prior to joining the company. He is extremely passionate about helping others find the joy of coding to alleviate repetitive and time-consuming tasks. Previously, Chris was the Associate Director of Strategy at M&C Saatchi Mobile, a Data Scientist at DataCamp, and graduated with a B.S./M.B.A. from Drexel University in Philadelphia.
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What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden
Harvard Business School

DataCamp is by far my favorite website to learn from.

Ronald Bowers
Decision Science Analytics, USAA

Join over 7 million learners and start Joining Data with dplyr today!

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