When reading in larger datasets with read.table, there are a few things that you can do to make your life easier and prevent R from choking.
- Read the help page for read.table. This contains many hints and tips that can help you to get the most out of the function.
- Make a rough calculation of the memory required to store your dataset. This will help you to determine whether or not your computer has enough RAM to read in the dataset.
- Set comment.char = "" if there are no commented lines in your file. This will prevent R from trying to interpret any lines that start with a # as comments.
- Use the colClasses argument. This will tell R the class of each column in your dataset, which can help to speed up the reading process.
- Set nrows. This will tell R to only read in the first nrows rows of your dataset. This can help to reduce memory usage.
Here is an example of how to use the colClasses argument:
> initial <- read.table("datatable.txt", nrows = 100)
> classes <- sapply(initial, class)
> tabAll <- read.table("datatable.txt", colClasses = classes)
This code will first read in the first 100 rows of the datatable.txt file. Then, it will use the sapply() function to determine the class of each column in the initial data frame. Finally, it will use the read.table() function to read in the entire datatable.txt file, specifying the colClasses argument to be the classes that were determined in the previous step.
