cut,NumericVariable-method {crunch} | R Documentation |
crunch::cut()
is equivalent to base::cut()
except that it operates on
Crunch variables instead of in-memory R objects. The function takes a numeric
variable and derives a new categorical variable from it based on the breaks
argument. You can either break the variable into evenly spaced categories by
specifying the number of breaks, or specify a numeric vector identifying
the start and end point of each category. For example, specifying
breaks = 5
will break the numeric data into five evenly spaced portions
while breaks = c(1, 5, 10)
will recode the data into two groups based on
whether the numeric vector falls between 1 and 5 or 5 and 10.
## S4 method for signature 'NumericVariable'
cut(
x,
breaks,
labels = NULL,
name,
include.lowest = FALSE,
right = TRUE,
dig.lab = 3,
ordered_result = FALSE,
...
)
x |
A Crunch |
breaks |
Either a numeric vector of two or more unique cut points
or a single number giving the number of intervals into which |
labels |
A character vector representing the labels for the levels of
the resulting categories. The length of the labels argument should be the
same as the number of categories, which is one fewer than the number of
breaks. If not specified, labels are constructed using interval notation.
For example, |
name |
The name of the resulting Crunch variable as a character string. |
include.lowest |
logical, indicating if an |
right |
logical, indicating if the intervals should be closed on the right (and open on the left) or vice versa. |
dig.lab |
integer which is used when labels are not given. It determines the number of digits used in formatting the break numbers. |
ordered_result |
Ignored. |
... |
further arguments passed to makeCaseVariable |
a Crunch VariableDefinition
. Assign it into the dataset to create
it as a derived variable on the server.
## Not run:
ds <- loadDataset("mtcars")
ds$cat_var <- cut(ds$mpg,
breaks = c(10, 15, 20),
labels = c("small", "medium"), name = "Fuel efficiency"
)
ds$age <- sample(1:100, 32)
ds$age4 <- cut(df$age, c(0, 30, 45, 65, 200),
c("Youth", "Adult", "Middle-aged", "Elderly"),
name = "Age (4 category)"
)
## End(Not run)