quest (version 0.2.0)

reorders: Reorder Levels of Factor Data

Description

reorders re-orders the levels of factor data. The factors are columns in a data.frame where the same reordering scheme is desired. This is often useful before using factor data in a statistical analysis (e.g., lm) or a graph (e.g., ggplot). It is essentially a vectorized version of reorder.default.

Usage

reorders(data, fct.nm, ord.nm = NULL, fun, ..., suffix = "_r")

Value

data.frame of re-ordered factor columns with colnames =

paste0(fct.nm, suffix).

Arguments

data

data.frame of data.

fct.nm

character vector of colnames in data that specify the factor columns. If any of the columns specified by fct.nm are not factors, then an error is returned.

ord.nm

character vector of length 1 or NULL. If a character vector of length 1, it is a colname in data specifying the column in data that will be used in conjunction with fun to re-order the factor columns. If NULL (default), it is assumed that each factor column itself will be used in conjunction with fun to re-order the factor columns.

fun

function that will be used to re-order the factor columns. The function is expected to input an atomic vector of length = nrow(data) and return an atomic vector of length 1. fun is applied to data[[ord.nm]] if ord.nm is a character vector of length 1 or applied to each column in data[fct.nm] if ord.nm = NULL.

...

additional named arguments used by fun. For example, if fun is mean, the user might specify an argument na.rm = TRUE to set the na.rm argument in the mean function.

suffix

character vector of length 1 specifying the string that will be appended to the end of the colnames in the return object.

See Also

reorder.default

Examples

# factor vector
reorder(x = state.region, X = state.region,
   FUN = length) # least frequent to most frequent
reorder(x = state.region, X = state.region,
   FUN = function(vec) {-1 * length(vec)}) # most frequent to least frequent

# data.frame of factors
infert_fct <- infert
fct_nm <- c("education","parity","induced","case","spontaneous")
infert_fct[fct_nm] <- lapply(X = infert[fct_nm], FUN = as.factor)
x <- reorders(data = infert_fct, fct.nm = fct_nm,
   fun = length) # least frequent to most frequent
lapply(X = x, FUN = levels)
y <- reorders(data = infert_fct, fct.nm = fct_nm,
   fun = function(vec) {-1 * length(vec)}) # most frequent to least frequent
lapply(X = y, FUN = levels)
# ord.nm specified as a different column in data.frame
z <- reorders(data = infert_fct, fct.nm = fct_nm, ord.nm = "pooled.stratum",
   fun = mean) # category with highest mean for pooled.stratum to
   # category with lowest mean for pooled.stratum
lapply(X = z, FUN = levels)