Welcome to the first lesson in our course on "Fundamentals of Text Data Manipulation". This lesson will introduce you to the crucial skill of reading text files in R. Text files are a fundamental data source in programming, commonly used for storing data, configuration files, and logs. Being able to open and read files in R is a foundational skill you'll often rely on when working with data. By the end of this lesson, you will be able to read the entire contents of a text file using the readLines() function, a skill essential for various data manipulation tasks. Let's get started!

A file path is essentially the address of a file in your system's storage. It tells your program where to find or save a file. There are two types of file paths:

• Absolute Path: This is the full path to a file, starting from the root directory. Here are some examples from different operating systems:

  • Linux: /home/user/documents/input.txt
  • Mac: /Users/user/documents/input.txt
  • Windows: C:\Users\user\documents\input.txt

  Note: In R, when specifying file paths on Windows, you need to use either double backslashes (C:\\Users\\user\\documents\\input.txt) or forward slashes (C:/Users/user/documents/input.txt) due to the backslash being used as an escape character.

• Relative Path: This path is relative to the directory you are working in. For example, documents/input.txt assumes your script is running from the user directory in the examples above.

Here's how you can specify a file path in R:

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1file_path <- 'input.txt'  # Relative path

Make sure your R script and the text file are in the same directory if you use a relative path. Otherwise, use the absolute path to ensure that R can find your file. In the CodeSignal environment, your R script will always be in the same directory as a file or a directory where the file is. This means you can always use a relative path in CodeSignal.

When working with relative paths, it's important to understand the structure of your directories. Here are a few examples with file trees:

1. Example 1:

   File Tree:

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   1project/
   2├── script.R
   3└── data/
   4    └── input.txt

   Relative Path:

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   1file_path <- 'data/input.txt'

2. Example 2:

   File Tree:

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   1user/
   2├── documents/
   3│   └── script.R
   4└── input.txt

   Relative Path:

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   1file_path <- '../input.txt'

The .. is used to navigate to the parent directory. It works this way in both macOS/Linux and Windows.

1. Example 3:

   File Tree:

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   1application/
   2├── scripts/
   3│   ├── script1.R
   4│   └── script2.R
   5└── resources/
   6    └── input.txt

   Relative Path:

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   1file_path <- '../resources/input.txt'

These examples illustrate how relative paths depend on the current working directory of your script.

In R, the readLines() function is used to read the contents of a file. This function reads the file line by line and stores the content in a character vector.

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1file_path <- 'input.txt'
2content <- readLines(file_path, warn = FALSE)
3cat("Full file content:\n")
4cat(content, sep = "\n")

Here, content stores the entire contents of the file as a character vector, which you can then process or display. Notice that we use cat() to print the content, ensuring each line is output correctly.

The warn = FALSE argument is used to suppress any warnings that might occur if there is an incomplete final line in the text file being read. By default, readLines() issues a warning if the last line of the file doesn't have a newline character at the end, which is a common occurrence in plain text files. Setting warn = FALSE ensures that these messages do not clutter the output, especially when you're aware that such incomplete lines are not an error in your specific context.

In this lesson, you've learned how to:

• Specify file paths correctly with examples from different operating systems.
• Use R's <- to assign file paths.
• Read the contents of a file in R using the readLines() function.
• Define relative paths correctly with examples and file tree illustrations.

These foundational skills will serve you well in handling data stored in text files. As you move on to the practice exercises, you'll apply these concepts by reading different text files and extracting their content. This hands-on experience will solidify your understanding, preparing you for more advanced file manipulation techniques in the future. Keep up the good work and happy coding!