rfml (version 0.1.0)

[,ml.data.frame-method: Extract subsets of a ml.data.frame

Description

Extract subset of columns and/or rows of a ml.data.frame. When extracting rows a ml.col.def referense can be used or a search text, see ml.data.frame for query string grammar. See details for limitations when using a reference. The row filtering will be used togheter with the existing query of the ml.data.frame

Usage

"["(x, i, j, ..., drop = NA)

Arguments

x

a ml.data.frame from which to extract element(s).

i, j

Indices specifying elements to extract. Indices are 'numeric' or 'character' vectors or empty (missing) or 'NULL'.

...

Not used.

drop

Not used.

Value

A ml.data.frame object is returned

Details

When extracting rows using ml.col.def comparison operators can be used. For the ">" "<" "!=" " <=" ">=" operators there muset exist a element range index on the source field or a error will be raised, element range index can be created using the ml.add.index function. "==" operator will always work since it does not depend of range indexes.

Examples

## Not run: 
#  library(rfml)
#  localConn <- ml.connect()
#  # create a ml.data.frame based on the iris data set
#  mlIris <- as.ml.data.frame(localConn, iris, "iris")
#  # select first three columns
#  mlIris2 <- mlIris[1:3]
#  # same
#  mlIris2 <- mlIris[,1:3]
#  # same
#  mlIris2 <- mlIris[,c("Sepal.Length","Sepal.Width","Petal.Length")]
#  # select first three columns for all rows with Spieces = setosa
#  mlIris2 <- mlIris[mlIris$Species=="setosa", 1:3]
#  # select all columns for all rows with Spieces = setosa
#  mlIris2 <- mlIris[mlIris$Species=="setosa",]
#  # select all columns for all rows with "setosa" in any column
#  mlIris2 <- mlIris["setosa",]
# ## End(Not run)