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Data Cleaning with R

31 steps

Welcome to Data Cleaning with R
What is Data Cleaning?
Course Logistics and Materials
Data Organization
Data Organization Best Practices
Tidy Data
Grouping and Indicator Variables
NA and Empty Values
Data Sharing Best Practices
Restructuring Data
Tidyverse Refresher
Working with Columns with across()
Pivoting Data
coalesce() and fill()
Regular Expressions
What are Regular Expressions?
Understanding and Testing Regular Expressions
Literal Characters and Metacharacters
Metacharacters: Quantifiers
Metacharacters: Alternation, Special Sequences, and Escapes
Combining Metacharacters
Regex in R
Regular Expressions and Data Cleaning, Part 1
Regular Expressions and Data Cleaning, Part 2
Common Issues
Common Issues in Data Cleaning
Unusable Variable Names
Whitespace
Letter Case
Missing, Implicit, or Misplaced Grouping Variables
Compound Values
Duplicated Values
Broken Values
Empty Rows and Columns
Parsing Numbers
Putting Everything Together

Data Cleaning with R

Pivoting Data

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This lesson is called Pivoting Data, part of the Data Cleaning with R course. This lesson is called Pivoting Data, part of the Data Cleaning with R course.

Transcript

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Your Turn

Solution

wp:coblocks/gist {"url":"
          ## %######################################################%##
          #                                                          #
          ####             Pivoting Data - Your Turn              ####
          #                                                          #      
          ## %######################################################%##
        
          # Load the dog ranks data ("dogranks_your.csv")
          # Pivot the data (wide to long and back to wide)
          # load packages -----------------------------------------------------------
        
          library(readr)
          library(tidyr)
        
          # import data -------------------------------------------------------------
          dogranks <- read_csv("data/dogranks-your.csv")
          # pivoting ----------------------------------------------------------------
          # longer
        
          dogranks_long <- dogranks %>% pivot_longer(
            cols = -c(Breed, Size),
            names_to = "Year",
            values_to = "Popularity.Rank"
          )
        
          # back to wide
          dogranks_wide <- dogranks_long %>%
            pivot_wider(names_from = "Year", values_from = "Popularity.Rank")
        ","file":""} /--></div>
</details>
</div>
<p>

Load the dog ranks data ("dogranks_your.csv")
Pivot the data (wide to long and back to wide)

Learn More

The tidyr pivoting vignette is a great place to start to learn more about pivoting your data. Two other sources that have information on pivoting are cmdlinetips.com and Storybench.

Have any questions? Put them below and we will help you out!

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Data Cleaning with R

Welcome to Data Cleaning with R

Data Organization

Restructuring Data

Regular Expressions

Common Issues

Data Cleaning with R

Pivoting Data

This lesson is locked

Transcript

Your Turn

Solution

Learn More

Have any questions? Put them below and we will help you out!