ssubset {labelr}

Safely Subset a Labeled Data Frame

Description

ssubset allows one to simultaneously filter-select rows that satisfy conditions AND return only selected columns as a data.frame that preserves the labelr attributes attached to the inputted data.frame.

Usage

ssubset(data, condition, ...)

Arguments

data

the data.frame from which columns rows will be filtered (and, possibly, columns selected).

condition

row-filtering conditions along the lines of base::subset() and/or dplyr::select(). Note: Row-filtering conditions (to include condition==NULL) must be supplied.

...

Optionally supply one or more unquoted, comma-separated column names that identify columns to be retained (Note: If no columns are listed, all columns will be retained). Note: While row-filtering conditions may leverage standard operators (e.g., &, |, ==, !=), the column-selection portion of call may not incorporate special characters or symbols, such as quotes, parentheses, colons, minus signs, exclamation points, or other operators.

Details

Combining sfilter and sselect functionality (along the lines of base::subset(), this function accepts a data.frame, followed by conditional filtering instructions (required) and (optional) comma-separated unquoted column names to be selected (see examples), returning the selected rows and columns as a data.frame that preserves the labelr attribute information of the originally supplied data.frame. See ssubset for a variant that combines sfilter row-filtering and sselect column selection in a single function. See also sbrac for a labelr attribute-preserving approach to row-and/or- column indexing. See also sdrop, ssort, srename, slab and flab.

Value

a labelr label attribute-preserving data.frame consisting of the selected rows that meet the filtering condition(s).

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

dfsub1 <- ssubset(df, raceth == 2 & age > 70, id, raceth, gender)
head(dfsub1, 3)
check_labs_att(dfsub1, "val.labs.raceth") # "raceth" lab specifically TRUE

dfsub2 <- ssubset(df, raceth %in% c(2:4), age, raceth)
head(dfsub2, 3)
check_labs_att(dfsub2, "val.labs.raceth") # "raceth" lab specifically TRUE
# even if NULL, must supply explicit condition argument
head(ssubset(df, condition = NULL, age, raceth), 3) # better to just use sselect()
head(ssubset(df, age == 60), 3) # skip column selection (will return all cols)