Practical Data Management with R

Format:

Book

Language:

English

Subjects (All):

Social sciences.

Physical Description:

Online course : (30 hr.)

Place of Publication:

London : SAGE Publishing 2020

Summary:

This course teaches learners how to use R to manage data in a wide variety of formats, in a reproducible manner, at scale. This course will help learners to: •An understanding of Basic R commands and data structures for manipulating data. •The ability to read data from multiple formats in and out of R. •Proficiency using loops, conditional statements, and functions to automate common data management tasks. •Familiarity with R’s package system for extending its functionality. •The skills to clean and manage multiple complex datasets. •The ability to clean and manipulate textual data. •An understanding of basic web scraping techniques, for both standard web pages and the Twitter API. •An overview of the techniques and hardware necessary to manage large datasets efficiently. MODULE ONE: INTRODUCTION TO R AND RSTUDIO You will learn about: installing R and RStudio, basic R programming skills and five basic data structures. •How to install R and RStudio. •Basic R programming skills, such as how to write commands in an R script. •How to understand the core data structures you need to manage a huge variety of data. MODULE TWO: R PROGRAMMING FUNDAMENTALS You will learn about: Data I/O and packages, looping and conditional statements, and functions. •Data I/O and packages so you can extend the functionality of R. •Looping and conditional statements so you can automate wildly complex tasks. •Functions so you don’t have to write the same code over and over again for similar tasks. MODULE THREE: DATA MANAGEMENT IN R You will learn how to: manage multiple datasets by example, work with text data, convert long- and wide-format data and deal with messy data. •Manage multiple datasets by example. •Convert long and wide format data. •Deal with poorly formatted data and/or missing data. •Automate tasks using functions Work with and manipulate text data. MODULE FOUR: AUTOMATED DATA COLLECTION You will be given: an overview of web/text scraping and the legal considerations, a basic web scraping example and an understanding of scraping Twitter. •An overview of web/text scraping and the related legal considerations. •A basic web scraping example so you can learn how to treat a webpage as a messy text document. •An understanding of scraping Twitter. MODULE FIVE: PERFORMANCE AND SCALABILITY You will be introduced to High Performance Computing and Big Data and learn about performant programming. •Giving you an overview of big data and high-performance computing (HPC). •Teaching you about performant programming. •Wrapping up with a range of next steps and ways to extend your skills.

ISBN:

1-5297-5426-7

OCLC:

1200116893