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    • Courses
      • Getting Started with R
      • Fundamentals of R
      • Going Deeper with R
      • The Glamour of Graphics
      • Using Git and GitHub with R
      • Mapping with R
      • Data Cleaning with R
      • Package Development with R
      • Inferential Statistics with R
    • R in 3 Months
    • Custom Training
    • Consulting
    • Blog
    • About
    • Contact
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    Data Cleaning with R

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    1. Welcome to Data Cleaning with R
      What is Data Cleaning?
    2. Course Logistics and Materials
    3. Data Organization
      Data Organization Best Practices
    4. Tidy Data
    5. Grouping and Indicator Variables
    6. NA and Empty Values
    7. Data Sharing Best Practices
    8. Restructuring Data
      Tidyverse Refresher
    9. Working with Columns with across()
    10. Pivoting Data
    11. coalesce() and fill()
    12. Regular Expressions
      What are Regular Expressions?
    13. Understanding and Testing Regular Expressions
    14. Literal Characters and Metacharacters
    15. Metacharacters: Quantifiers
    16. Metacharacters: Alternation, Special Sequences, and Escapes
    17. Combining Metacharacters
    18. Regex in R
    19. Regular Expressions and Data Cleaning, Part 1
    20. Regular Expressions and Data Cleaning, Part 2
    21. Common Issues
      Common Issues in Data Cleaning
    22. Unusable Variable Names
    23. Whitespace
    24. Letter Case
    25. Missing, Implicit, or Misplaced Grouping Variables
    26. Compound Values
    27. Duplicated Values
    28. Broken Values
    29. Empty Rows and Columns
    30. Parsing Numbers
    31. Putting Everything Together
    Data Cleaning with R Putting Everything Together
    Lesson 31 of 31
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    Putting Everything Together

    A slightly reorganized version of the the code used in this lesson is below.

    Forum Description

    [muse-video id="pzjjz6x"]

    A slightly reorganized version of the the code used in this lesson is below.