Mastering Data Wrangling with tidyr

Gain expertise in reshaping and tidying data using the tidyr package. This course will equip you with the skills to transform data into a tidy format, manage missing values effectively, and pivot data frames seamlessly. By the end of this course, you will be proficient in preparing data for comprehensive analysis, enabling you to handle real-world data challenges with confidence.

Lessons and practices

Lesson 1: Gather and Spread

Reshape Data with tidyr

Adding More Subjects Data

Fix Data Gathering and Spreading

Fill in the Data Gaps

Master Data Reshaping Techniques

Lesson 2: Separate and Unite

Separate and Combine Columns in R

Change the Separator in Unite

Fix Column Splitting and Combining

Splitting and Combining Superhero Data

Lesson 3: Drop and Replace

Handling Missing Data in R

Replace Missing Values with Medians

Fix Missing Value Handling in R

Handling Missing Values with Median

Fruit Data Cleanup

Lesson 4: Nest and Unnest

Nesting and Unnesting Data Frames

Add a Department Column

Fix Nesting Error in Data

Nesting and Unnesting Superhero Stats

Nesting and Unnesting Data

Lesson 5: Tidying Data for Comprehensive Analysis

Data Tidying in Action

Change Data Unification

Fix the Data Tidying Process

Tidy Up Musician Data

Write a Tidy Superhero Data Frame

Interested in this course? Learn and practice with Cosmo!

Practice is how you turn knowledge into actual skills.