Datasets in R: Loading & Saving Data

R Programming 4.0+    |    Beginner
  • 14 Videos | 1h 44m 17s
  • Includes Assessment
  • Earns a Badge
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Transforming and manipulating massive amounts of data is crucial for all organizations. The R programming language offers a plethora of packages to load, explore, manipulate, and transform data. R is ideal for data analysis, mutation, and cleaning, making it a choice language for statisticians and data scientists. In this course, you'll learn how to write R script files using the RStudio environment. You'll use different panes to debug and evaluate your R program, import data in various file formats, and access files embedded in an R package and stored on your machine. Additionally, you'll learn how to export data to different file formats. Once you've completed this course, you'll know how to work R using RStudio, import and export data in R, and perform simple data transformation and exploration operations.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    install and set up the R programming language on macOS
    download and set up the RStudio IDE on macOS
    install and set up the R programming language on Windows
    download and set up the RStudio IDE on Windows
    run commands on the RStudio console
    recall the use of the different panes available in RStudio
  • create a new project and a new R script file and execute code
    demonstrate and visualize built-in R datasets
    use vignettes for help on packages
    read in csv files from the file system and built-in packages
    import data from XML, Excel, and JSON files
    export data to various text, CSV, JSON, and Excel files
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 51s
    UP NEXT
  • Playable
    2. 
    Installing R on macOS
    9m 2s
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    3. 
    Installing RStudio on macOS
    5m 7s
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    4. 
    Installing R on Windows
    8m 47s
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    5. 
    Installing RStudio on Windows
    5m 2s
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    6. 
    Running Commands Using the RStudio Console
    9m 20s
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    7. 
    Working with Panes in RStudio
    6m 33s
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    8. 
    Creating a New Project and Examining Datasets
    10m 58s
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    9. 
    Demonstrating and Visualizing Built-in Datasets
    8m 48s
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    10. 
    Browsing Package Vignettes
    6m 53s
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    11. 
    Reading from CSV Files
    11m 10s
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    12. 
    Reading from Text, XML, Excel, and JSON Files
    10m 48s
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    13. 
    Writing Data Out to Different File Formats
    8m 4s
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    14. 
    Course Summary
    1m 55s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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