Indexing and sequences (within a vector)

If we want to extract one or several values from a vector, we must provide one or several indices in square brackets, just as we do in math.

R indexes start at 1. Programming languages like Fortran, MATLAB, and R start counting at 1, because that’s what human beings typically do. Languages in the C family (including C++, Java, Perl, and Python) count from 0 because that’s simpler for computers to do.

Our metadata data frame has rows and columns (it has 2 dimensions), if we want to extract some specific data from it, we need to specify the “coordinates” we want from it. Row numbers come first, followed by column numbers (i.e. [row, column]).

metadata[1, 2]   # first element in the 2nd column of the data frame
metadata[1, 6]   # first element in the 6th column
metadata[1:3, 7] # first three elements in the 7th column
metadata[3, ]    # the 3rd element for all columns
metadata[, 7]    # the entire 7th column
head_meta <- metadata[1:6, ] # metadata[1:6, ] is equivalent to head(metadata)

Indexing and sequences (within a data.frame)

For larger datasets, it can be tricky to remember the column number that corresponds to a particular variable. (Are species names in column 5 or 7? oh, right… they are in column 6). In some cases, in which column the variable will be can change if the script you are using adds or removes columns. It’s therefore often better to use column names to refer to a particular variable, and it makes your code easier to read and your intentions clearer.

You can do operations on a particular column, by selecting it using the $ sign. In this case, the entire column is a vector. You can use names(metadata) or colnames(metadata) to remind yourself of the column names. For instance, to extract all the strain information from our datasets:

metadata$strain

In some cases, you may way to select more than one column. You can do this using the square brackets. Suppose we wanted strain and clade information:

metadata[, c("strain", "clade")]

You can even access columns by column name and select specific rows of interest. For example, if we wanted the strain and clade of just rows 4 through 7, we could do:

metadata[4:7, c("strain", "clade")]