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  • 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.

  • 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.

  • 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.

  • 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.

Initializing

Exercise

Counting part colors

Sometimes you'll want to do some processing before you do a join, and prioritize keeping the second (right) table's rows instead. In this case, a right join is for you.

In this exercise, we'll count the part_cat_id from parts, before using a right_join to join with part_categories. The reason we do this is because we don't only want to know the count of part_cat_id in parts, but we also want to know if there are any part_cat_ids not present in parts.

Instructions 1/2

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  • Use the count verb to count each part_cat_id in the parts table.
  • Use a right_join to join part_categories. You'll need to use the part_cat_id from the count and the id column from part_categories.