In data science, it is often necessary to get information about a data set to see what is in it. The names of the columns and rows say much about the contents of a data set. Furthermore, it allows the program to make use of this information outside of the data set.

## Dimnames in R

Retrieving the names of the rows and columns from a data set can be tricky in most programming languages. However, dimnames in R does it with a single function. The dimnames() function is in the form of dimnames(data set), and it returns the name of the rows in columns.

```
# dimnames in r
> dimnames(mtcars)
[[1]]
[1] "Mazda RX4" "Mazda RX4 Wag" "Datsun 710"
[4] "Hornet 4 Drive" "Hornet Sportabout" "Valiant"
[7] "Duster 360" "Merc 240D" "Merc 230"
[10] "Merc 280" "Merc 280C" "Merc 450SE"
[13] "Merc 450SL" "Merc 450SLC" "Cadillac Fleetwood"
[16] "Lincoln Continental" "Chrysler Imperial" "Fiat 128"
[19] "Honda Civic" "Toyota Corolla" "Toyota Corona"
[22] "Dodge Challenger" "AMC Javelin" "Camaro Z28"
[25] "Pontiac Firebird" "Fiat X1-9" "Porsche 914-2"
[28] "Lotus Europa" "Ford Pantera L" "Ferrari Dino"
[31] "Maserati Bora" "Volvo 142E"
[[2]]
[1] "mpg" "cyl" "disp" "hp" "drat" "wt" "qsec" "vs" "am" "gear" "carb"
```

Section 1 contains a list of the rows in the mtcars data set. It has a list of thirty-two cars. Section 2 has the eleven columns showing the specifications for these cars.

## Dim in R

One simple way of getting the number of rows and columns in a data set is by dim in R. The dim() function has the form of dim(data set), and it returns the number of rows and columns in that data set.

```
# dim in r
> dim(mtcars)
[1] 32 11
```

The results here are that the mtcars data set has thirty-two rows, each representing a car. Furthermore, it has eleven columns, each representing a specification of these cars.

As can be seen by the example from the mtcars data set, these two functions provide a lot of information about the data set. Having the row and column information tell us a lot about the content of the data set. For example, in this case, the mtcars data set is a list of cars and their specifications. Having two functions to retrieve column and row names as well as numbers of each saves a lot of programming to get this information. It is yet another reason R he’s such an excellent data science tool.