Importing Data into R

Introduction

• Focus of today’s session: Importing data correctly into R via RStudio.

Getting Started with RStudio

• Console: Located at the bottom left.
  • Blink cursor: You can type code directly here and hit return.
• Script Editor: Preferred for writing and saving code and notes.
  • Use # to write comments/notes in code.

Setting Your Working Directory

• First step for every session: Specify the working directory.
  • Select folder (e.g., r_examples).
  • Confirm it in the console.

Overview of the Data

• Data file to import: serial.csv
• Contains five columns with both categorical and numerical data.
  • Important: Data must not have special characters or spaces in column names.
    • Example: Use fruit_loops instead of fruit loops to avoid confusions.
• Ensure the dataset is saved in CSV format.

Importing the Data

• Naming the Dataset:
  • Choose a descriptive name (e.g., be_fast).
• Code for Import:
  • Use the read.csv() function:

    be_fast <- read.csv("serial.csv", header = TRUE, sep = ",")
    

  • Parameters:
    • header = TRUE: Indicates the first row contains headers.
    • sep = ",": Confirms data is comma-separated.

Checking Imported Data

• Use be_fast in the console to view the data or double-click in the global environment to confirm data is imported correctly.
• Data structure should resemble an Excel sheet.

Conclusion

• Successful completion of the first part of the session.
• Next session: Basic descriptive statistics and saving scripts.