# R – Data Structure

Data Types

Unlike SAS and SPSS, R has several different data types (structures) including vectors, factors, data frames, matrices, arrays, and lists. The data frame is most like a dataset in SAS.

1. Vectors

A vector is an object that contains a set of values called its elements.

Numeric vector

x <- c(1,2,3,4,5,6)

The operator <–  is equivalent to “=” sign.

Character vector

State <- c(“DL”, “MU”, “NY”, “DL”, “NY”, “MU”)

To calculate frequency for State vector, you can use table function.

To calculate mean for a vector, you can use mean function.

Since the above vector contains a NA (not available) value, the mean function returns NA.To calculate mean for a vector excluding NA values, you can include na.rm = TRUE parameter in mean function.

You can use subscripts to refer elements of a vector.

Convert a column “x” to numeric

data\$x = as.numeric(data\$x)

2. Factors

R has a special data structure to store categorical variables. It tells R that a variable is nominal or ordinal by making it a factor.
Simplest form of the factor function :

Ideal form of the factor function :

The factor function has three parameters:

1. Vector Name
2. Values (Optional)
3. Value labels (Optional)

Convert a column “x” to factor

data\$x = as.factor(data\$x)

3. Matrices

All values in columns in a matrix must have the same mode (numeric, character, etc.) and the same length.

The cbind function joins columns together into a matrix. See the usage below

The numbers to the left side in brackets are the row numbers. The form [1, ] means that it is row number one and the blank following the comma means that R has displayed all the columns.

To see dimension of the matrix, you can use dim function.

To see correlation of the matrix, you can use cor function.

You can use subscripts to identify rows or columns.

4. Arrays

Arrays are similar to matrices but can have more than two dimensions.

5. Data Frames

A data frame is similar to SAS and SPSS datasets. It contains variables and records.
It is more general than a matrix, in that different columns can have different modes (numeric, character, factor, etc.

The data.frame function is used to combine variables (vectors and factors) into a data frame.

6. Lists

A list allows you to store a variety of  objects.

You can use subscripts to select the specific component of the list.

How to know data type of a column

1. ‘class’ is a property assigned to an object that determines how generic functions operate with it.  It is not a mutually exclusive classification.

2. ‘mode’ is a mutually exclusive classification of objects according to their basic structure.  The ‘atomic’ modes are numeric, complex, charcter and logical.

> x <- 1:16
> x <- factor(x)

> class(x)
[1] “factor”

> mode(x)
[1] “numeric”

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