Matrix

Suppose, we also have the prices of these three items for the month of June as follows:

june_price = c(20, 25, 33)

Now if we want to stack all these three months in a single variable, we can't use vectors anymore; we need a new data structure. One of the data structures to rescue in this case is the matrix. A matrix is basically a two-dimensional array of data elements with a number of rows and columns fixed. Like a vector, a matrix can also contain just one type of element; a mix of two types is not allowed. To combine these three vectors with every row corresponding to a particular month's prices of different items and every column corresponding to prices of different items in a particular month, what we can do is first combine these three vectors inside a matrix() command, followed by a comma and nrow = 3, indicating the fact that there are three different items (for example, items are arranged row-wise and months are arranged column-wise).

all_prices = matrix(c(jan_price, mar_price, june_price), nrow= 3)
all_prices

The all_prices data frame will look like the following:

[,1] [,2] [,3]
 [1,] 10 11 20
 [2,] 20 22 25
 [3,] 30 33 33

Now suppose we change our mind and want to arrange this with the items displayed column-wise and the prices displayed row-wise; that is, the first row corresponds to the prices of different items in a particular month and the first column corresponds to the first month's (January's) prices of different items, with that arrangement continuing for every other row and column. We can do so very easily by mentioning byrow = TRUE inside the matrix. byrow = TRUE arranges the values of vectors row-wise. It arranges the matrix by aligning all the elements row-wise allowing for its dimensions:

all_prices2 = matrix(c(jan_price, mar_price, june_price), nrow= 3, byrow = TRUE)  
all_prices2

The output will look like the following:

[,1] [,2] [,3]
 [1,] 10 20 30
 [2,] 11 22 33
 [3,] 20 25 33

We can see that here jan_price is considered as the first row, mar_price as the second row, and june_price as the third row in all_prices2.