In this video, Mark Niemann-Ross recaps the import and export tools covered in this course. Learn about next steps to take when dealing with a high variety of data.
- [Mark] In this course we've discussed…ways of dealing with a variety of different formats,…starting with the popular world of Excel,…then moving on to flat data files,…SPSS, and DBF,…as well as other formats.…Obtaining and scrubbing data are two important tasks…you'll immediately face when working with data,…so learning how to work with multiple formats…is a useful skill.…I've enjoyed exploring these tools…and hope this has been a useful course…in your work as a data scientist.…
- Name the three types of big data.
- List three considerations used to determine the appropriate R package for Excel.
- Determine the best package used to import entire Excel workbooks.
- Explain how to import standard text files using base R and tidyverse.
- Define the purpose of the foreign language package for R.
- Recognize restrictions when working on SAS files in the foreign language package.
- Identify the problems involved with extracting data from a PDF in R.
Skill Level Intermediate
R Programming in Data Science: High Volume Datawith Mark Niemann-Ross1h 25m Intermediate
1. Use R with Excel
2. Importing Text Files
3. Understanding the Foreign Package
4. Use R with Popular Data Formats
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