Cleaning Bad Data in R

Focused View

Mike Chapple

1:55:31

105 View

01 - Introduction

01 - Data is messy.mp4

01:10

02 - What you need to know.mp4

01:09

02 - 1. Missing Data

01 - Types of missing data.mp4

03:38

02 - Missing values.mp4

11:25

03 - Missing rows.mp4

05:58

04 - Aggregations and missing values.mp4

05:08

03 - 2. Duplicated Data

01 - Duplicated rows and values.mp4

04:50

02 - Aggregations in the data set.mp4

03:42

04 - 3. Formatting Data

01 - Converting dates.mp4

05:54

02 - Unit conversions.mp4

03:50

03 - Numbers stored as text.mp4

03:32

04 - Text improperly converted to numbers.mp4

03:17

05 - Inconsistent spellings.mp4

06:51

05 - 4. Outliers

01 - Screening for outliers.mp4

04:53

02 - Handling outliers.mp4

02:46

03 - Outliers use case.mp4

03:34

04 - Outliers in subgroups.mp4

03:33

05 - Detecting illogical values.mp4

03:14

06 - 5. Tidy Data

01 - What is tidy data.mp4

03:59

02 - Variables, observations, and values.mp4

05:11

03 - Common data problems.mp4

07:57

04 - Wide vs. long data sets.mp4

03:23

05 - Making wide data sets long.mp4

04:37

06 - Making long data sets wide.mp4

03:41

07 - 6. Red Flags

01 - Suspicious values.mp4

04:49

02 - Suspicious multiples.mp4

02:25

08 - Conclusion

01 - Whats next.mp4

01:05

Description

Data integrity is the new focal point of the data science revolution. Now that everybody is onboard with the role of data in people's lives and business, it's not an unfair question to ask, "Can you prove that your data is accurate?" In this course, you can learn how to identify and address many of the data integrity issues facing modern data scientists, using R and the tidyverse. Discover how to handle missing values and duplicated data. Find out how to convert data between different units and tackle poorly formatted text. Plus, learn how to detect outliers, address structural issues, and identify red flags that indicate potential data quality issues.

Where possible, instructor Mike Chapple shows how to correct the issues using R, but the same principles can be applied to any statistical programing language.

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R Programming

Mike Chapple

Instructor's Courses

Cybersecurity and analytics educator and leader with over 20 years of experience in government, the private sector and higher education. Author of over 30 books, including best-selling study guides from Wiley covering the CISSP, Security+, CISM, CySA+, CIPP/US, and PenTest+ exams. Creator of over 100 cybersecurity and business analytics video courses on LinkedIn Learning.

Linkedin Learning

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.