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Importing Data with R

Authors: Justin Flett, Jason Browning

In order to work with data in R, you need to know how to get data into R. This Skill defines data import recipes for common data import problems you’ll encounter using R.

What You Will Learn

  • This skill conveys the most common techniques for getting data from a data source into R for further processing and analysis.

Pre-requisites

  • Data Literacy
  • R for Data Analysts

Beginner

Import text, flat, delimited, and JSON files to enable processing of data as well as loading data from Excel and proprietary data files.

Importing Formatted Text Files: R Playbook

by Justin Flett

Aug 29, 2019 / 1h 17m

1h 17m

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Description

R is a widely used programming language for statistical computing. In this course, you will learn foundational knowledge importing formatted text files R. First, you will learn the basics of importing text files using default R functions. Next, you will learn how to import CSV and tab delimited files. You will learn how to import JSON files using the rjson package. Finally, you will learn how to import XML files within R. When you’re finished with this course, you will have the skills and knowledge of importing some of the most commonly used data files into R.

Table of contents
  1. Course Overview
  2. Importing Text Files in R
  3. Importing CSV Files in R
  4. Importing Delimited Files in R
  5. Importing JSON Files in R
  6. Importing XML Files in R

Importing Common Data File Formats: R Playbook

by Jason Browning

Jan 24, 2020 / 1h 16m

1h 16m

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Description

To effectively analyze and manipulate data, it is important to have the ability to access data stored in various formats. In this course, Importing Common Data File Formats: R Playbook, you will gain the ability to import data from various sources into R. First, you will learn how to import data from CSV and delimited text files. Next, you will discover how to import and format data from Microsoft Excel. Then, you will explore how to import data from specialized statistical applications, including SAS, Stata, and Minitab. Finally, you'll learn about the ability to create, save, and reuse objects in R itself. When you are finished with this course, you will have the knowledge of base R functions and various packages to easily work with data from a variety of sources.

Table of contents
  1. Course Overview
  2. Importing Data from Diverse Sources
  3. Importing Data from Microsoft Excel
  4. Refining the Microsoft Excel Import
  5. Formatting the Microsoft Excel Import
  6. Importing Data from SAS
  7. Importing Data from Other Statistical Software
  8. Importing Data from R