Tibbles

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1. How can you tell if an object is a tibble? (Hint: try printing mtcars, which is a regular data frame).

When we print mtcars, it prints all the columns.

mtcars

But when we first convert mtcars to a tibble using as_tibble(), it prints on the first ten observations. There are also some other differences in formatting of the printed data frame.

as_tibble(mtcars)

You can use the function is_tibble() to check whether a data frame is a tibble or not. The mtcars data frame is not a tibble.

is_tibble(mtcars)

[1] FALSE

But the diamonds and flights data are tibbles.

is_tibble(ggplot2::diamonds)

[1] TRUE

is_tibble(nycflights13::flights)

[1] TRUE

is_tibble(as_tibble(mtcars))

[1] TRUE

More generally, you can use the class() function to find out the class of an object. Tibbles has the classes c("tbl_df", "tbl", "data.frame"), while old data frames will only have the class "data.frame".

class(mtcars)

[1] "data.frame"

class(ggplot2::diamonds)

[1] "tbl_df"     "tbl"        "data.frame"

class(nycflights13::flights)

[1] "tbl_df"     "tbl"        "data.frame"

If you are interested in reading more on R’s classes, read the chapters on object oriented programming in Advanced R.

2. Compare and contrast the following operations on a data.frame and equivalent tibble. What is different? Why might the default data frame behaviors cause you frustration?

df <- data.frame(abc = 1, xyz = "a")
df$x

[1] a
Levels: a

df[, "xyz"]

[1] a
Levels: a

df[, c("abc", "xyz")]

tbl <- as_tibble(df)
tbl$x

Unknown or uninitialised column: 'x'.

NULL

tbl[, "xyz"]

tbl[, c("abc", "xyz")]

The $ operator will match any column name that starts with the name following it. Since there is a column named xyz, the expression df$x will be expanded to df$xyz. This behavior of the $ operator saves a few keystrokes, but it can result in accidentally using a different column than you thought you were using.

With data.frames, with [ the type of object that is returned differs on the number of columns. If it is one column, it won’t return a data.frame, but instead will return a vector. With more than one column, then it will return a data.frame. This is fine if you know what you are passing in, but suppose you did df[ , vars] where vars was a variable. Then what that code does depends on length(vars) and you’d have to write code to account for those situations or risk bugs.

3. If you have the name of a variable stored in an object, e.g. var <- "mpg", how can you extract the reference variable from a tibble?

You can use the double bracket, like df[[var]]. You cannot use the dollar sign, because df$var would look for a column named var.

4. Practice referring to non-syntactic names in the following data frame by:

1. Extracting the variable called 1.
2. Plotting a scatterplot of 1 vs 2.
3. Creating a new column called 3 which is 2 divided by 1.
4. Renaming the columns to one, two and three.

For this example, I’ll create a dataset called annoying with columns named 1 and 2.

annoying <- tibble(
  `1` = 1:10,
  `2` = `1` * 2 + rnorm(length(`1`))
)

1. To extract the variable named 1:

annoying[["1"]]

 [1]  1  2  3  4  5  6  7  8  9 10

or

annoying$`1`

 [1]  1  2  3  4  5  6  7  8  9 10

2. To create a scatter plot of 1 vs. 2:

ggplot(annoying, aes(x = `1`, y = `2`)) +
  geom_point()

3. To add a new column 3 which is 2 divided by 1:

mutate(annoying, `3` = `2` / `1`)

or

annoying[["3"]] <- annoying$`2` / annoying$`1`

or

annoying[["3"]] <- annoying[["2"]] / annoying[["1"]]

4. To rename the columns to one, two, and three, run:

annoying <- rename(annoying, one = `1`, two = `2`, three = `3`)
glimpse(annoying)

Observations: 10
Variables: 3
$ one   <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
$ two   <dbl> 1.795927, 2.367798, 6.048697, 8.507860, 9.895426, 10.586689, 13.874955, 13....
$ three <dbl> 1.795927, 1.183899, 2.016232, 2.126965, 1.979085, 1.764448, 1.982136, 1.690...

5. What does tibble::enframe() do? When might you use it?

The function tibble::enframe() converts named vectors to a data frame with names and values

enframe(c(a = 1, b = 2, c = 3))

6. What option controls how many additional column names are printed at the footer of a tibble?

The help page for the print() method of tibble objects is discussed in ?print.tbl. The n_extra argument determines the number of extra columns to print information for.