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Data Cleaning with R
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Welcome to Data Cleaning with RWhat is Data Cleaning?
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Course Logistics and Materials
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Data OrganizationData Organization Best Practices
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Tidy Data
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Grouping and Indicator Variables
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NA and Empty Values
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Data Sharing Best Practices
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Restructuring DataTidyverse Refresher
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Working with Columns with across()
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Pivoting Data
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coalesce() and fill()
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Regular ExpressionsWhat are Regular Expressions?
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Understanding and Testing Regular Expressions
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Literal Characters and Metacharacters
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Metacharacters: Quantifiers
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Metacharacters: Alternation, Special Sequences, and Escapes
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Combining Metacharacters
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Regex in R
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Regular Expressions and Data Cleaning, Part 1
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Regular Expressions and Data Cleaning, Part 2
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Common IssuesCommon Issues in Data Cleaning
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Unusable Variable Names
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Whitespace
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Letter Case
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Missing, Implicit, or Misplaced Grouping Variables
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Compound Values
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Duplicated Values
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Broken Values
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Empty Rows and Columns
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Parsing Numbers
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Putting Everything Together
Lesson 20 of 31
In Progress
Regular Expressions and Data Cleaning, Part 2
Your Turn
- Download CRAN package descriptions using the
tools
package - Select package name, author, description, and all variables that end in ‘ports’
- Filter rows for packages with names that:
- end in plot
- contain Bayes
- contain digits
- are all UPPER CASE