R Programming in Data Science: High Variety Data

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.

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