Difference between [] and $ operators for subsetting

Question

I am trying to subset a data frame by using a variable name. I have it working but there is a part which I don't quite understand.

Originally I have this: rownames (mtcars[mtcars$hp >150,]).

Then, rather than hard-coding "hp", I wanted to assign "hp" to a variable: foo <- "hp" and subset with that. I got it working using this: rownames (mtcars[mtcars[foo] >150,]). (Thanks to link which stopped me from playing with the $ operator.)

But, as I was building up this statement, I noticed there was a difference between the two. For mtcars$hp > 150, I get this output:

 [1] FALSE FALSE FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE  TRUE
[13]  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
[25]  TRUE FALSE FALSE FALSE  TRUE  TRUE  TRUE FALSE

For mtcars[foo] > 150, I get this:

                       hp
Mazda RX4           FALSE
Mazda RX4 Wag       FALSE
Datsun 710          FALSE
Hornet 4 Drive      FALSE
Hornet Sportabout    TRUE
...

Are these two of the same "type"? Is there any reason why R displays the first one without rownames and the second one with rownames?

Perhaps I've naively thought that $ and [] were more or less equivalent. I can get the same final result, but I am curious and worried if my assumptions had been wrong. "Fortunately", I ignored this difference and carried on and got the same final result.

Thank you!

Answer 1

Below we will use the one-row data frame in order to provide briefer output:

mtcars1 <- mtcars[1, ]

Note the differences among these. We can use class as in class(mtcars["hp"]) to investigate the class of the return value.

The first two correspond to the code in the question and return a data frame and plain vector respectively. The key differences between [ and $ are that [ (1) can specify multiple columns, (2) allows passing of a variable as the index and (3) returns a data frame (although see examples later on) whereas $ (1) can only specify a single column, (2) the index must be hard coded and (3) it returns a vector.

mtcars1["hp"]  # returns data frame
##            hp
## Mazda RX4 110

mtcars1$hp # returns plain vector
## [1] 110

Other examples where index is a single element. Note that the first and second examples below are actually the same as drop = TRUE is the default.

mtcars1[, "hp"] # returns plain vector
## [1] 110  

mtcars1[, "hp", drop = TRUE] # returns plain vector
## [1] 110

mtcars1[, "hp", drop = FALSE] # returns data frame
##            hp
## Mazda RX4 110

Also there is the [[ operator which is like the $ operator except it can accept a variable as the index whereas $ requires the index to be hard coded:

mtcars1[["hp"]] # returns plain vector
## [1] 110

Others where index specifies multiple elements. $ and [[ cannot be used with multiple elements so these examples only use [:

mtcars1[c("mpg", "hp")] # returns data frame
##           mpg  hp
## Mazda RX4  21 110

mtcars1[, c("mpg", "hp")] # returns data frame
##           mpg  hp
## Mazda RX4  21 110

mtcars1[, c("mpg", "hp"), drop = FALSE] # returns data frame
##           mpg  hp
## Mazda RX4  21 110

mtcars1[, c("mpg", "hp"), drop = TRUE] # returns list
## $mpg
## [1] 21
## 
## $hp
## [1] 110

[

mtcars[foo] can return more than one column if foo is a vector with more than one element, e.g. mtcars[c("hp", "mpg")], and in all cases the return value is a data.frame even if foo has only one element (as it does in the question).

There is also mtcars[, foo, drop = FALSE] which returns the same value as mtcars[foo] so it always returns a data frame. With drop = TRUE it will return a list rather than a data.frame in the case that foo specifies multiple columns and returns the column itself if it specifies a single column.

[[

On the other hand mtcars[[foo]] only works if foo has one element and it returns that column, not a data frame.

$

mtcars$hp also only works for a single column, like [[, and returns the column, not a data frame containing that column.

mtcars$hp is like mtcars[["hp"]]; however, there is no possibility to pass a variable index with $. One can only hard-code the index with $.

subset

Note that this works:

subset(mtcars, hp > 150)

returning a data frame containing those rows where the hp column exceeds 150:

                     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8

other objects

The above pertain to data frames but other objects that can use $, [ and [[ will have their own rules. In particular if m is a matrix, e.g. m <- as.matrix(BOD), then m[, 1] is a vector, not a one column matrix, but m[, 1, drop = FALSE] is a one column matrix. m[[1]] and m[1] are both the first element of m, not the first column. m$a does not work at all.

help

See ?Extract for more information. Also ?"$", ?"[" and ?"[[" all get to the same page, as well.

Answer 2

The main difference lies on the returned object :

• Using the single bracket [] will return a dataframe.
• When using $, you will have the vector of the elements of the dataframe.

You can apply the class(x) function to see it. Basically, in the previous example, mtcars['foo'] is a dataframe, but mtcars[['foo']] is a vector of float