Users Online
· Guests Online: 57
· Members Online: 0
· Total Members: 188
· Newest Member: meenachowdary055
· Members Online: 0
· Total Members: 188
· Newest Member: meenachowdary055
Forum Threads
Newest Threads
No Threads created
Hottest Threads
No Threads created
Latest Articles
DEMO - Data Wrangling in R
DEMO - Data Wrangling in R Data Science |
Categories | Most Recent | Top Rated | Popular Courses |
Uploader | Date Added | Views | Rating | |
Superadmin | 01.01.70 | 535 | No Rating | |
Description | ||||
Tidy data is a data format that provides a standardized way of organizing data values within a dataset. By leveraging tidy data principles, statisticians, analysts, and data scientists can spend less time cleaning data and more time tackling the more compelling aspects of data analysis. In this course, learn about the principles of tidy data, and discover how to create and manipulate data tibbles—transforming them from source data into tidy formats. Instructor Mike Chapple uses the R programming language and the tidyverse packages to teach the concept of data wrangling—the data cleaning and data transformation tasks that consume a substantial portion of analysts' time. He wraps up with three hands-on case studies that help to reinforce the data wrangling principles and tactics covered in this course. Topics include: - Whats tidy data? - Using the tidyverse - Working with tibbles - Subsetting and filtering tibbles - Importing data into R - Making wide datasets long with gather() - Making long datasets wide with spread() - Converting data types in R - Detecting outliers - Manipulating strings in R with stringr |
Ratings
Comments
No Comments have been Posted.
Post Comment
Please Login to Post a Comment.