Iris_data <- readLines(paste(path, "/iris.csv", sep = ""), Iris_data <- readLines (paste (path, "/iris.csv", sep = "" ), So, let’s first store the directory, where we want to store and load our example data… In case you want to reproduce the example, simply copy and paste the following code. The readLines function is perfect for such text files, since it reads the text line by line and creates character objects for each of the lines.įor the first example, I’m going to create a simple txt file that we can use for the application of readLines. When you have to do text mining / text analysis of larger texts, you will typically be provided with relatively unstructured. In order to get a bit more concrete, let’s move on to the examples…Įxample 1: Read Lines of txt File via readLines R Function The readline function interactively reads a line from the terminal. The n.readLines function of the reader package provides additional functionalities for reading lines, such as skipping ahead in a file or ignoring comments and headers. The readLines function reads text lines from an input file. N.readLines("path/filename.txt", n = 5, skip = 2) readLines ( "path/filename.txt", n = 5, skip = 2 )
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