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Courses>Programming Languages>Data Manipulation with data.table in R
Data ScienceData Manipulation with data.table in R
Price:Paid
Length:4 Hours
Language:English
Content type:video
level:advanced
Updated:04 March 2024
Published:13 September 2022
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Courses>Programming Languages>Data Manipulation with data.table in R
Data Manipulation with data.table in R
4 Hours
20265 students
Syllabus
This chapter introduces data.tables as a drop-in replacement for data.frames and shows how to use data.table's i argument to filter rows.
Just as the i argument lets you filter rows, the j argument of data.table lets you select columns and also perform computations. The syntax is far more convenient and flexible when compared to data.frames.
This chapter introduces data.table's by argument that lets you perform computations by groups. By the end of this chapter, you will master the concise DT[i, j, by] syntax of data.table.
You will learn about a unique feature of data.table in this chapter: modifying existing data.tables in place. Modifying data.tables in place makes your operations incredibly fast and is easy to learn.
Not only does the data.table package help you perform incredibly fast computations, it can also help you read and write data to disk with amazing speeds. This chapter focuses on data.table's fread() and fwrite() functions which let you import and export flat files quickly and easily!
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Courses>Programming Languages>Data Manipulation with data.table in R
Data ScienceData Manipulation with data.table in R
Price:Paid
Length:4 Hours
Language:English
Content type:video
level:advanced
Updated:04 March 2024
Published:13 September 2022
Similar courses
Opportunities
Courses>Programming Languages>Data Manipulation with data.table in R
Data Manipulation with data.table in R
4 Hours
20265 students
Syllabus
This chapter introduces data.tables as a drop-in replacement for data.frames and shows how to use data.table's i argument to filter rows.
Just as the i argument lets you filter rows, the j argument of data.table lets you select columns and also perform computations. The syntax is far more convenient and flexible when compared to data.frames.
This chapter introduces data.table's by argument that lets you perform computations by groups. By the end of this chapter, you will master the concise DT[i, j, by] syntax of data.table.
You will learn about a unique feature of data.table in this chapter: modifying existing data.tables in place. Modifying data.tables in place makes your operations incredibly fast and is easy to learn.
Not only does the data.table package help you perform incredibly fast computations, it can also help you read and write data to disk with amazing speeds. This chapter focuses on data.table's fread() and fwrite() functions which let you import and export flat files quickly and easily!
Similar courses
Opportunities
Make the most out of your online education
Careertail
Copyright © 2021 Careertail.
All rights reserved
Quick Links
Get StartedLog InAbout UsCourses
Company
BlogContactsPrivacy PolicyCookie PolicyTerms and Conditions
Stay up to date
Trustpilot