Wrangling Data in the Tidyverse
Data never arrive in the condition that you need them in order to do effective data analysis. Data need to be re-shaped, re-arranged, and re-formatted, so that they can be visualized or be inputted into a machine learning algorithm. This course addresses the problem of wrangling your data so that you can bring them under control and analyze them effectively. The key goal in data wrangling is transforming non-tidy data into tidy data.This course covers many of the critical details about handling tidy and non-tidy data in R such as converting from wide to long formats, manipulating tables with the dplyr package, understanding different R data types, processing text data with regular expressions, and conducting basic exploratory data analyses. Investing the time to learn these data wrangling techniques will make your analyses more efficient, more reproducible, and more understandable to your data science team.
In this specialization we assume familiarity with the R programming language. If you are not yet familiar with R, we suggest you first complete R Programming before returning to complete this course.
Apply Tidyverse functions to transform non-tidy data to tidy data
Conduct basic exploratory data analysis
Conduct analyses of text data
Syllabus
Syllabus - What you will learn from this course
Week 1
Wrangling Data in the Tidyverse
Week 2
Working With Factors, Dates, and Times
Week 3
Working With Strings and Text and Functional Programming
Exploratory Data Analysis
Week 4
Case Studies
Project: Wrangling data in the Tidyverse
FAQ
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Reviews
Excellent course! I've learned so many useful R techniques/codes!
Great course to get yourself acquanted with data wrangling in Tidyverse.
