labelr (version 0.1.9)

ssort: Safely Sort (Re-order) a Labeled Data Frame

Description

ssort allows one to sort (after the fashion of base::order or dplyr::arrange) the rows of a data.frame based on column values.

Usage

ssort(data, vars, descending = FALSE, na.last = TRUE, fact.to.char = TRUE)

Value

a labelr label attribute-preserving data.frame consisting of the re-sorted data.frame.

Arguments

data

the data.frame to be sorted.

vars

the variables to be sorted on, specified as a quoted character vector of variable names or an integer vector of column position indices.

descending

whether to sort the given variable of vars in descending or ascending order. Default is FALSE, which will be recycled to all vars arguments.

na.last

force NA values to appear last in a variable's sort order if TRUE (default).

fact.to.char

coerce all factor variables to character variables.

Details

This function accepts a data.frame, followed by a quoted vector of column names (or an integer vector of column position indices), followed by an indication of which are to be sorted ascending (default) or descending. If multiple columns are supplied to vars, sorting prioritizes the columns that appear earlier, with values of subsequent columns being sorted within distinct values of earlier columns. Note: ssort is fast enough on small data.frames and very slow on "larger" (>500K records) data.frames, particularly for more complex or demanding sort requests. Other R packages may provide faster sorting while preserving labelr attributes.

Examples

# make toy demographic (gender, raceth, etc.) data set
set.seed(555)
df <- make_demo_data(n = 1000) # another labelr:: function

# let's add variable VALUE labels for variable "raceth"
df <- add_val_labs(df,
  vars = "raceth", vals = c(1:7),
  labs = c("White", "Black", "Hispanic", "Asian", "AIAN", "Multi", "Other"),
  max.unique.vals = 50
)

head(df, 3)
check_labs_att(df, "val.labs.raceth") # "raceth" lab specifically TRUE

dfsort1 <- ssort(df, c("raceth", "gender", "age"), descending = c(TRUE, FALSE, FALSE))

head(dfsort1, 20)

check_labs_att(dfsort1, "val.labs.raceth") # "raceth" lab specifically TRUE

dfsort2 <- ssort(df, c("age", "gender"))

head(dfsort2, 20)

check_labs_att(dfsort2, "val.labs.raceth") # "raceth" lab specifically TRUE

dfsort3 <- ssort(df, c("raceth"))

head(dfsort3, 10)

check_labs_att(dfsort3, "val.labs.raceth") # "raceth" lab specifically TRUE