How to Identify R Object Properties

1. Identify R Object Properties
2. str() Function
3. typeof() Function
4. class() Function
5. is.___() Functions
6. attributes() Function
7. Other Functions

In our data analysis, we may encounter a situation where a function or operator that we use works on some objects but not on others. This happens because the function/operator only works on objects of a certain type.

For example, the $ operator works on a list but not an atomic vector.

Example Code:

# A list.
l = list(one="First", two="Last")
# A vector.
v = c(one="First", two="Last")

l$one # Works.
v$one# Error.

Output:

> l$one # Works.
[1] "First"

> v$one# Error.
Error in v$one : $ operator is invalid for atomic vectors

Identify R Object Properties

This article will look at functions that help us identify various properties of the objects we work with.

This article will only give a brief description and an example for each function. R’s documentation for these functions gives more details and examples.

First, we will create some R objects.

Example Code:

# Vector of numbers.
vn = c(4, 5, 6, 7)

# Vector of Booleans. (A vector of True False values)
vb <- vn%%2 == 0

# Data frame.
dfr = data.frame(Col1=vn, Col2=vb)

str() Function

The str() function displays the object’s internal structure. It works on any R object.

Example Code:

str(vn)
str(vb)
str(dfr)

Output:

> str(vn)
 num [1:4] 4 5 6 7

> str(vb)
 logi [1:4] TRUE FALSE TRUE FALSE

> str(dfr)
'data.frame':	4 obs. of  2 variables:
 $ Col1: num  4 5 6 7
 $ Col2: logi  TRUE FALSE TRUE FALSE

typeof() Function

The typeof() function displays any R object’s type or storage mode.

Example Code:

typeof(vn)
typeof(vb)
typeof(dfr)

Output:

> typeof(vn)
[1] "double"

> typeof(vb)
[1] "logical"

> typeof(dfr)
[1] "list"

class() Function

The class() function displays the class attribute of the R object. It lists the names of the classes from which this object inherits.

Even objects that do not have a class attribute have an implicit class.

Example Code:

class(vb)
class(dfr)

# Create a matrix and check its class.
m = matrix(c(1:6), nrow=3)
class(m)

Output:

> class(vb)
[1] "logical"
> class(dfr)
[1] "data.frame"

> class(m)
[1] "matrix" "array"

is.___() Functions

R has many inbuilt is.___() functions. These functions return Boolean values indicating whether the object is of that type.

For example, we can check whether a given object is a vector, a list, a matrix, an array, a data frame, etc. In the following code, we will see the result of checking a particular object with various is.___() functions.

Example Code:

# We will check whether the object vb we created is of any of the following types of object.
is.list(vb)
is.vector(vb)
is.atomic(vb)
is.numeric(vb)
is.matrix(vb)
is.data.frame(vb)
is.array(vb)

Output:

> is.list(vb)
[1] FALSE
> is.vector(vb)
[1] TRUE
> is.atomic(vb)
[1] TRUE
> is.numeric(vb)
[1] FALSE
> is.matrix(vb)
[1] FALSE
> is.data.frame(vb)
[1] FALSE
> is.array(vb)
[1] FALSE

attributes() Function

The attributes() function displays a list of an object’s attributes.

Example Code:

# For the list object.
attributes(l)

# For the data frame object.
attributes(dfr)

# For the matrix object.
attributes(m)

Output:

> # For the list object.
> attributes(l)
$names
[1] "a" "z"

> # For the data frame object.
> attributes(dfr)
$names
[1] "Col1" "Col2"
$class
[1] "data.frame"
$row.names
[1] 1 2 3 4

> # For the matrix object.
> attributes(m)
$dim
[1] 3 2

Other Functions

Besides the functions described above, R has other functions which give us more information about an object. A few of them are specific to objects of certain types.

Some of the more commonly used functions are:

1. dim(): displays the dimensions of an object.
2. names(): displays the names of the components of an object.
3. summary(): for statistical models, displays a summary of the model.
4. colnames(), rownames() and row.names(): display the column/row names for matrix-like objects. For a data frame, rownames() calls row.names() and colnames() calls names().