NA and Empty Values

1

What is Data Cleaning?

06:07

2

Course Logistics and Materials

03:43

1

Data Organization Best Practices

04:03

2

Tidy Data

08:11

3

Grouping and Indicator Variables

01:05

4

NA and Empty Values

01:19

5

Data Sharing Best Practices

01:27

1

Tidyverse Refresher

14:49

2

Working with Columns with across()

12:05

3

Pivoting Data

09:45

4

coalesce() and fill()

09:06

1

What are Regular Expressions?

03:48

2

Understanding and Testing Regular Expressions

03:51

3

Literal Characters and Metacharacters

06:16

4

Metacharacters: Quantifiers

01:33

5

Metacharacters: Alternation, Special Sequences, and Escapes

02:53

6

Combining Metacharacters

05:18

7

Regex in R

02:58

8

Regular Expressions and Data Cleaning, Part 1

04:15

9

Regular Expressions and Data Cleaning, Part 2

12:00

1

Common Issues in Data Cleaning

03:17

2

Unusable Variable Names

10:11

3

Whitespace

11:10

4

Letter Case

06:52

5

Missing, Implicit, or Misplaced Grouping Variables

11:19

6

Compound Values

10:09

7

Duplicated Values

08:49

8

Broken Values

09:52

9

Empty Rows and Columns

11:30

10

Parsing Numbers

12:02

11

Putting Everything Together

25:50

1

Wrapping Up Data Cleaning with R