Data Science & Statistics: Creating a Matrix in R

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What are matrices:

1. When it comes to storing data, matrices are a natural extension to vectors: while vectors are 1-dimensional collections of data, matrices are two-dimensional arrays;
2. Matrices have a fixed number of rows and columns;
3. Matrices, same as vectors, can contain only one basic data type. This makes sense: you create a matrix from a vector. You can think of it as curving the vector into rows or columns, and just as a vector can only store doubles, or characters, or logicals, and so on, so can a matrix.

There are two methods for creating a matrix in R. The matrix() function, and the rbind() and cbind() functions.

matrix() takes at least two arguments: a vector it can structure into a matrix, and an argument specifying the number of rows the new object must have, called nrow. Alternatively, you can pass the number of columns you want your matrix to have, by specifying ncol.

When creating the matrix, R fills out the first column first, then moves on to the second, and so on. To organize your data by rows, use the byrow argument in the matrix() function, and set it to TRUE instead of its default FALSE.

Using rbind and cbind to create a matrix. Rbind stands for row bind, and cbind for column bind.

Naming the components of a matrix is just like naming a vector but instead of the names() function, matrices recognise the colnames() and rownames() functions.

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