R Programming: Advanced Analytics In R For Data Science

R Programming: Advanced Analytics In R For Data Science, available at $109.99, has an average rating of 4.66, with 62 lectures, 3 quizzes, based on 8898 reviews, and has 61674 subscribers.

You will learn about Perform Data Preparation in R Identify missing records in dataframes Locate missing data in your dataframes Apply the Median Imputation method to replace missing records Apply the Factual Analysis method to replace missing records Understand how to use the which() function Know how to reset the dataframe index Work with the gsub() and sub() functions for replacing strings Explain why NA is a third type of logical constant Deal with date-times in R Convert date-times into POSIXct time format Create, use, append, modify, rename, access and subset Lists in R Understand when to use [] and when to use [[]] or the $ sign when working with Lists Create a timeseries plot in R Understand how the Apply family of functions works Recreate an apply statement with a for() loop Use apply() when working with matrices Use lapply() and sapply() when working with lists and vectors Add your own functions into apply statements Nest apply(), lapply() and sapply() functions within each other Use the which.max() and which.min() functions This course is ideal for individuals who are Anybody who has basic R knowledge and would like to take their skills to the next level or Anybody who has already completed the R Programming A-Z course or This course is NOT for complete beginners in R It is particularly useful for Anybody who has basic R knowledge and would like to take their skills to the next level or Anybody who has already completed the R Programming A-Z course or This course is NOT for complete beginners in R.

Enroll now: R Programming: Advanced Analytics In R For Data Science

Summary

Title: R Programming: Advanced Analytics In R For Data Science

Price: $109.99

Average Rating: 4.66

Number of Lectures: 62

Number of Quizzes: 3

Number of Published Lectures: 53

Number of Published Quizzes: 3

Number of Curriculum Items: 65

Number of Published Curriculum Objects: 56

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

• Perform Data Preparation in R
• Identify missing records in dataframes
• Locate missing data in your dataframes
• Apply the Median Imputation method to replace missing records
• Apply the Factual Analysis method to replace missing records
• Understand how to use the which() function
• Know how to reset the dataframe index
• Work with the gsub() and sub() functions for replacing strings
• Explain why NA is a third type of logical constant
• Deal with date-times in R
• Convert date-times into POSIXct time format
• Create, use, append, modify, rename, access and subset Lists in R
• Understand when to use [] and when to use [[]] or the $ sign when working with Lists
• Create a timeseries plot in R
• Understand how the Apply family of functions works
• Recreate an apply statement with a for() loop
• Use apply() when working with matrices
• Use lapply() and sapply() when working with lists and vectors
• Add your own functions into apply statements
• Nest apply(), lapply() and sapply() functions within each other
• Use the which.max() and which.min() functions

Who Should Attend

• Anybody who has basic R knowledge and would like to take their skills to the next level
• Anybody who has already completed the R Programming A-Z course
• This course is NOT for complete beginners in R

Target Audiences

• Anybody who has basic R knowledge and would like to take their skills to the next level
• Anybody who has already completed the R Programming A-Z course
• This course is NOT for complete beginners in R