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Joining Data with dplyr

4.0+
46 reviews
Beginner

Learn to combine data across multiple tables to answer more complex questions with dplyr.

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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!
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In the following Tracks

Certification Available

Data Analyst in R

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Associate Data Scientist in R

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Data Manipulation in R

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  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.

    Play Chapter Now
    The inner_join verb
    50 xp
    What columns would you join on?
    50 xp
    Joining parts and part categories
    100 xp
    Joining with a one-to-many relationship
    50 xp
    Joining parts and inventories
    100 xp
    Joining in either direction
    100 xp
    Joining three or more tables
    50 xp
    Joining three tables
    100 xp
    What's the most common color?
    100 xp
  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.

    Play Chapter Now
  3. 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.

    Play Chapter Now
For Business

Training 2 or more people?

Get your team access to the full DataCamp platform, including all the features.

In the following Tracks

Certification Available

Data Analyst in R

Go To Track
Certification Available

Associate Data Scientist in R

Go To Track

Data Manipulation in R

Go To Track

datasets

setsthemespartspart_categoriesinventoriesinventory_partscolorsquestionstagsquestion_tagsanswers

collaborators

Collaborator's avatar
Amy Peterson
DataCamp Content Creator

Course Instructor

DataCamp offers interactive R, Python, Spreadsheets, SQL and shell courses. All on topics in data science, statistics, and machine learning. Learn from a team of expert teachers in the comfort of your browser with video lessons and fun coding challenges and projects.
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Don’t just take our word for it

*4.0
from 46 reviews
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  • Daniel N.
    2 months

    Dplyr makes it exciting joining data

  • STANISLAV S.
    3 months

    Hi, among my courses, which I have finished, it was the hardest and I think I will return on it in the future.

  • Diana N.
    3 months

    I had an excellent experience learning about the joining functions within the dplyr package and applying this knowledge to Lego datasets. The explanations were clear and the practical exercises were highly beneficial, as is consistently the case with Datacamp. I highly recommend this course to anyone seeking to deepen their understanding of dplyr and R.

  • Kenny O.
    4 months

    This is a challenging chapter but very useful

  • Susana S.
    8 months

    The lesson is very well designer. I found that some of the exercise questions were not clear; both the questions as well as the hint suggestions. Some times there is only um ) or something missing and the hint dies not help to solve that problem . You could add a standard suggestion to review the signaling.

"Dplyr makes it exciting joining data"

Daniel N.

"Hi, among my courses, which I have finished, it was the hardest and I think I will return on it in the future."

STANISLAV S.

"This is a challenging chapter but very useful"

Kenny O.

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