R Programming in Data Science: High Variety Data

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Free Online Course: R Programming in Data Science: High Variety Data provided by LinkedIn Learning is a comprehensive online course, which lasts for 1-2 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from LinkedIn Learning. R Programming in Data Science: High Variety Data is taught by Mark Niemann-Ross.

Overview
  • 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