Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

LinkedIn Learning

R Programming in Data Science: High Variety Data

via LinkedIn Learning

Go to class Write review
Udacity Ad

Get 50% Off Udacity Nanodegrees — Code CC50

Learn More → Scrimba Ad

Free courses from frontend to fullstack and AI

Learn More →

Overview

Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
High-variety data can cause a slew of problems for data scientists. In this course, learn what these problems are and how to use the unique capabilities of R to solve them.

Syllabus

Introduction
  • Jumping over the high-variety hurdle
  • Perspectives on high-variety data
1. Use R with Excel
  • Excel packages compared
  • Read a workbook from Excel
  • Write a workbook to Excel
  • Read ranges from Excel
  • Write ranges to Excel
  • Read rows and columns from Excel
  • Write rows and columns to Excel
  • Read individual cells from Excel
  • Write individual cells to Excel
2. Importing Text Files
  • Text files in R
  • CSV files in R
  • Tab-delimited files in R
  • Fixed-width files in R
3. Understanding the Foreign Package
  • What is the R foreign package?
  • Read form and write to DBF
  • Read from and write to SPSS
  • Read from and write to Stata
  • Read from and write to SAS
4. Use R with Popular Data Formats
  • XML in R
  • JSON in R
  • ODS files in R
  • HTML files in R
  • Extracting data from a PDF in R
  • Google Docs with R
  • Working with images in R
Conclusion
  • Next steps

Taught by

Mark Niemann-Ross

Reviews

4.7 rating at LinkedIn Learning based on 55 ratings

Start your review of R Programming in Data Science: High Variety Data

Go to class

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free
Someone learning on their laptop while sitting on the floor.