.c(...)                       # Non-standard concatenation i.e. .c(a, b) == c("a", "b")
vlabels(X, attrn = "label")   # Get labels of variables in X, in attr(X[[i]], attrn)
vlabels(X, attrn = "label") <- value      # Set labels of variables in X
vclasses(X)                   # Get classes of variables in X
vtypes(X)                     # Get data storage types of variables in X (calling typeof)
namlab(X, class = FALSE,      # Return data frame of names, labels and classes
          attrn = "label")
add_stub(X, stub, pre = TRUE) # Add a stub (i.e. prefix or postfix) to column names
rm_stub(X, stub, pre = TRUE)  # Remove stub from column names
x %!in% table                 # The opposite of %in%
ckmatch(x, table,             # Check-match: throws an informative error if non-matched
     e = "Unknown columns:")
fnlevels(x)                   # Faster version of nlevels(x) (for factors)
fnrow(X)                      # Faster nrow for data frames (not faster for matrices)
fncol(X)                      # Faster ncol for data frames (not faster for matrices)
fdim(X)                       # Faster dim for data frames (not faster for matrices)
allNA(x)                      # Check for all missing cases in a vector
missing_cases(X, cols = NULL) # Find missing cases in a matrix / data framme
na_rm(x)                      # Remove missing values from vector and return vector
na_omit(X, cols = NULL,       # Faster na.omit for matrices and data frames
        na.attr = FALSE)
na_insert(X, prop = 0.1)      # Insert missing values at random in vectors, matrices DF's
cinv(X)                       # Choleski (fast) inverse of symmetric, positive def. matrix
all_identical(...)            # Check exact equality of multiple objects or list-elements
all_obj_equal(...)            # Check near equality of multiple objects or list-elements
seq_row(X)                    # Fast integer sequences along rows of X
seq_col(X)                    # Fast integer sequences along columns of X
setRownames(object,
 nm = if(is.atomic(object))   # Set rownames of object and return object
 seq_row(object) else NULL)
setColnames(object, nm)       # Set colnames of object and return object
setDimnames(object, dn,
            which = NULL)     # Set dimension names of object and return object
unattrib(object)              # Remove all attributes from object
setAttrib(object, a)          # Replace all attributes with list of attributes 'a'
copyAttrib(to, from)          # Copy all attributes from object 'from' to object 'to'
copyMostAttrib(to, from)      # Copy most attributes from object 'from' to object 'to'
is.categorical(x)             # The opposite of is.numeric
is.Date(x)                    # Check if object is of class "Date", "POSIXlt" or "POSIXct"

## Non-standard concatenation
.c(a, b, "c d", e == f)

## Variable labels
namlab(wlddev, class = TRUE)
vlabels(wlddev)
vlabels(wlddev) <- vlabels(wlddev)

## Stub-renaming
log_mtc <- add_stub(log(mtcars), "log.")
head(log_mtc)
head(rm_stub(log_mtc, "log."))
rm(log_mtc)

## Setting dimension names of an object
head(setRownames(mtcars))
ar <- array(1:9, c(3,3,3))
setRownames(ar)
setColnames(ar, c("a","b","c"))
setDimnames(ar, c("a","b","c"), which = 3)
setDimnames(ar, list(c("d","e","f"), c("a","b","c")), which = 2:3)
setDimnames(ar, list(c("g","h","i"), c("d","e","f"), c("a","b","c")))

## Checking exact equality of multiple objects
all_identical(iris, iris, iris, iris)
l <- replicate(100, fmean(num_vars(iris), iris$Species), simplify = FALSE)
all_identical(l)
rm(l)

## Missing values
mtc_na <- na_insert(mtcars, 0.15)    # Set 15% of values missing at random
fNobs(mtc_na)                        # See observation count
na_omit(mtc_na)                      # 12x faster than na.omit(mtc_na)
na_omit(mtc_na, na.attr = TRUE)      # Adds attribute with removed cases, like na.omit
na_omit(mtc_na, cols = c("vs","am")) # Removes only cases missing vs or am
na_omit(qM(mtc_na))                  # Also works for matrices
na_omit(mtc_na$vs, na.attr = TRUE)   # Also works with vectors
na_rm(mtc_na$vs)                     # For vectors na_rm is faster ...
rm(mtc_na)