rm_versatile: Versatile Function for Removing Objects
In MaaniBeigy/DescObs: Versatile Exploration of Data

Versatile function to remove objects.

`save.objects`	an optional list naming objects to be saved (i.e., not to be removed).
`save.patterns`	an optional list of string patterns or regular expressions which specifies the objects to be saved (i.e., not to be removed) .
`rm.objects`	a list naming objects to be removed.
`rm.patterns`	an optional list of string patterns or regular expressions which specifies the objects to be removed.
`modes`	a list to set the type or storage mode of the save.patterns and/or rm.patterns. For example "logical", "integer", "double", "complex", "raw", "character", "list", "expression", "name", "symbol" and "function".
`envir`	the environment to use. Default is set to .GlobalEnv
`inherits`	should the enclosing frames of the environment be inspected?

The traditional rm function from base is not a versatile function because it cannot handle exceptional objects or string patterns to skip or remove. Moreover, rm gives no warning before removing the objects and is not interactive. Also, the pattern argument of ls function cannot handle multiple patterns or multiple regular expressions. This function has been developed for sake of versatility, where you can determine exceptional objects and patterns for saving and/or removing objects. Also, you receive proper message regarding the final approval of removing objects. The search strategy of rm_versatile is based upon apropos function, which enables you to determine the type or storage mode of the objects (e.g., double, integer, character, etc.).

# First let us making some objects
a <- 1
b <- "female"
c <- FALSE
d <- 4:10
e <- 5
f <- 6
g <- 7
df1 <- 8
df2 <- 9
dfcol <- 10
dff1 <- 11
dfff3 <- 12
mydata1 <- 13
mymydata <- 14
dataframe1 <- data.frame(
    gender = c("F", "M", "M", "F"),
    score = c(10, 12, 14, 18)
)
matrix.a <- matrix(1:10, nrow = 2, ncol = 5)
matrix2 <- matrix(1:100, ncol = 2)
x <- c("a", "b", "c", "d")
y <- c("d", "e", "f")
# Remove objects by rm.versatile
rm_versatile(
    save.objects = list("a", "b", "c"),
    save.patterns = list("df", "data"),
    rm.objects = list("x", "y"),
    rm.patterns = list("matrix")
)
# List objects
ls()