dbNBins: Determine number of distinct values of variables in a...

In heike/dbData: Database Access for Sufficient Statistics of Data Graphics

Description

For margin = TRUE the function return the number of distinct levels each variable has. For numeric variables this number will be identical to the number of rows in case there are no ties. If margin = FALSE, the function returns the number of distinct tuples. If binwidth is specified, the number of distinct tuples of the binned data is returned. As the number of variables increases, the number of tuples will grow to at most the product of the marginal number of categories, but not beyond the number of records in the data table.

Usage

  dbNBins(data, vars = list(), binwidth = -1,
    margin = TRUE)

Arguments

data	dataDB object
vars	list of variable names
binwidth	vector of bin sizes for each variable. -1 for minimal binwidth
margin	logical value: should marginal distributions be considered or joint distribution?

Examples

connect <- dbConnect(dbDriver("MySQL"), user="2009Expo",
password="R R0cks", port=3306, dbname="baseball",
host="headnode.stat.iastate.edu")
pitch <- new("dataDB", co=connect, table="Pitching")
dbNBins(pitch, vars=list("G", "SO", "yearID"))
dbNBins(pitch, vars=list("G", "SO", "yearID"), binwidth=c(10,10,1))
dbNBins(pitch, vars=list("G", "SO", "yearID"), binwidth=c(10,10,1), margin=FALSE)
dbNBins(pitch, vars=list("yearID", "playerID"), margin=FALSE)

heike/dbData documentation built on May 17, 2019, 3:23 p.m.