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.  


Het inner_join-werkwoord

Op welke kolommen zou je joinen?

Onderdelen en onderdeelcategorieën samenvoegen

Joinen met een één-op-veel-relatie

Onderdelen en inventarissen samenvoegen

In beide richtingen joinen

Drie of meer tabellen joinen

Drie tabellen samenvoegen

Wat is de meest voorkomende kleur?

Joining Tables

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. 

The left_join verb

Left joining two sets by part and color

Left joining two sets by color

Finding an observation that doesn't have a match

The right_join verb

Which join is best?

Counting part colors

Cleaning up your count

Joining tables to themselves

Joining themes to their children

Joining themes to their grandchildren

Left joining a table to itself

Left and Right 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. 

The full_join verb

Differences between Batman and Star Wars

Aggregating each theme

Full joining Batman and Star Wars LEGO parts

Comparing Batman and Star Wars LEGO parts

The semi_join and anti_join verbs

Select the join

Something within one set but not another

What colors are included in at least one set?

Which set is missing version 1?

Visualizing set differences

Aggregating sets to look at their differences

Combining sets

Visualizing the difference: Batman and Star Wars

Full, Semi, and Anti Joins

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.

Stack Overflow questions

Left joining questions and tags

Comparing scores across tags

What tags never appear on R questions?

Joining questions and answers

Finding gaps between questions and answers

Joining question and answer counts

Joining questions, answers, and tags

Average answers by question

The bind_rows verb

Joining questions and answers with tags

Binding and counting posts with tags

Visualizing questions and answers in tags

Congratulations!

Case Study: Joins on Stack Overflow Data

sets

themes

parts

part_categories

inventories

inventory_parts

colors

questions

question_tags

answers

In data science kom je vaak interessante data tegen die over meerdere tabellen is verspreid. In deze cursus leer je de vaardigheden om meerdere tabellen te combineren en zo samen te analyseren. Je oefent met een leuke gegevensset over LEGO van de Rebrickable-website. De gegevensset bevat informatie over de sets, onderdelen, thema’s en kleuren van LEGO, maar is verdeeld over veel tabellen. Je werkt de hele cursus met deze data terwijl je in totaal zes verschillende joins leert! Je leert vier mutating joins: inner join, left join, right join en full join, en twee filtering joins: semi join en anti join. In het laatste hoofdstuk pas je je nieuwe skills toe op Stack Overflow-data, met daarin bijna 300.000 Stack Overflow-vragen die zijn getagd met R, inclusief informatie over hun antwoorden, de datum waarop ze zijn gesteld en hun score. Maak je klaar om je dplyr-skills naar een hoger niveau te tillen!

Data Manipulation with dplyr 

Leer gegevens uit meerdere tabellen te combineren met dplyr. Ontdek 6 joins zoals inner, full, anti.

Data samenvoegen met dplyr

Leer hoe je data uit meerdere tabellen kunt combineren om complexere vragen te beantwoorden met dplyr.

Joinen met een één-op-veel-relatie

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