This example selects columns from an ore.frame object.
Example 3-1 Selecting Data by Column
This example first creates a temporary database table, with the corresponding proxy ore.frame object iris_of, from the iris data.frame object. It displays the first three rows of iris_of. The example selects two columns from iris_of and creates the ore.frame object iris_projected with them. It then displays the first three rows of iris_projected.
iris_of <- ore.push(iris)
head(iris_of, 3)
iris_projected = iris_of[, c("Petal.Length", "Species")]
head (iris_projected, 3)
Listing for This Example
iris_of <- ore.push(iris)
head(iris_of, 3)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 4.7 3.2 1.3 0.2 setosa
R> iris_projected = iris_of[, c("Petal.Length", "Species")]
R> head (iris_projected, 3)
Petal.Length Species
1 1.4 setosa
2 1.4 setosa
3 1.3 setosa
This example selects rows from an ordered ore.frame object.
Example 3-2 Selecting Data by Row
This example first adds a column to the iris data.frame object for use in creating an ordered ore.frame object. It invokes the ore.drop function to delete the database table IRIS_TABLE, if it exists. It then creates a database table, with the corresponding proxy ore.frame object IRIS_TABLE, from the iris data.frame. The example invokes the ore.exec function to execute a SQL statement that makes the RID column the primary key of the database table. It then invokes the ore.sync function to synchronize the IRIS_TABLE ore.frame object with the table and displays the first three rows of the proxy ore.frame object.
The example next selects 51 rows from IRIS_TABLE by row number and creates the ordered ore.frame object iris_selrows with them. It displays the first six rows of iris_selrows. It then selects 3 rows by row name and displays the result.
# Add a column to the iris data set to use as row identifiers.
iris$RID <- as.integer(1:nrow(iris) + 100)
ore.drop(table = 'IRIS_TABLE')
ore.create(iris, table = 'IRIS_TABLE')
ore.exec("alter table IRIS_TABLE add constraint IRIS_TABLE
primary key (\"RID\")")
ore.sync(table = "IRIS_TABLE")
head(IRIS_TABLE, 3)
# Select rows by row number.
iris_selrows <- IRIS_TABLE[50:100,]
head(iris_selrows)
# Select rows by row name.
IRIS_TABLE[c("101", "151", "201"),]
Listing for This Example
R> # Add a column to the iris data set to use as row identifiers.
R> iris$RID <- as.integer(1:nrow(iris) + 100)
R> ore.drop(table = 'IRIS_TABLE')
R> ore.create(iris, table = 'IRIS_TABLE')
R> ore.exec("alter table IRIS_TABLE add constraint IRIS_TABLE
+ primary key (\"RID\")")
R> ore.sync(table = "IRIS_TABLE")
R> head(IRIS_TABLE, 3)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species RID
101 5.1 3.5 1.4 0.2 setosa 101
102 4.9 3.0 1.4 0.2 setosa 102
103 4.7 3.2 1.3 0.2 setosa 103
R> # Select rows by row number.
R> iris_selrows <- IRIS_TABLE[50:100,]
R> head(iris_selrows)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species RID
150 5.0 3.3 1.4 0.2 setosa 150
151 7.0 3.2 4.7 1.4 versicolor 151
152 6.4 3.2 4.5 1.5 versicolor 152
153 6.9 3.1 4.9 1.5 versicolor 153
154 5.5 2.3 4.0 1.3 versicolor 154
155 6.5 2.8 4.6 1.5 versicolor 155
R> # Select rows by row name.
R> IRIS_TABLE[c("101", "151", "201"),]
Sepal.Length Sepal.Width Petal.Length Petal.Width Species RID
101 5.1 3.5 1.4 0.2 setosa 101
151 7.0 3.2 4.7 1.4 versicolor 151
201 6.3 3.3 6.0 2.5 virginica 201
This example selects portions of a data set.
Example 3-3 Selecting Data by Value
The example pushes the iris data set to the database and gets the ore.frame object iris_of. It filters the data to produce iris_of_filtered, which contains the values from the rows of iris_of that have a petal length of less than 1.5 and that are in the Sepal.Length and Species columns. The example also filters the data using conditions, so that iris_of_filtered contains the values from iris_of that are of the setosa or versicolor species and that have a petal width of less than 2.0.
iris_of <- ore.push(iris)
# Select sepal length and species where petal length is less than 1.5.
iris_of_filtered <- iris_of[iris_of$Petal.Length < 1.5,
c("Sepal.Length", "Species")]
names(iris_of_filtered)
nrow(iris_of_filtered)
head(iris_of_filtered, 3)
# Alternate syntax filtering.
iris_of_filtered <- subset(iris_of, Petal.Length < 1.5)
nrow(iris_of_filtered)
head(iris_of_filtered, 3)
# Using the AND and OR conditions in filtering.
# Select all rows with in which the species is setosa or versicolor.
# and the petal width is less than 2.0.
iris_of_filtered <- iris_of[(iris_of$Species == "setosa" |
iris_of$Species == "versicolor") &
iris_of$Petal.Width < 2.0,]
nrow(iris_of_filtered)
head(iris_of, 3)
Listing for This Example
R> iris_of <- ore.push(iris)
R> # Select sepal length and species where petal length is less than 1.5.
R> iris_of_filtered <- iris_of[iris_of$Petal.Length < 1.5,
+ c("Sepal.Length", "Species")]
R> names(iris_of_filtered)
[1] "Sepal.Length" "Species"
R> nrow(iris_of_filtered)
[1] 24
R> head(iris_of_filtered, 3)
Sepal.Length Species
1 5.1 setosa
2 4.9 setosa
3 4.7 setosa
R> # Alternate syntax filtering.
R> iris_of_filtered <- subset(iris_of, Petal.Length < 1.5)
R> nrow(iris_of_filtered)[1] 24
R> head(iris_of_filtered, 3)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 4.7 3.2 1.3 0.2 setosa
R> # Using the AND and OR conditions in filtering.
R> # Select all rows with in which the species is setosa or versicolor.
R> # and the petal width is less than 2.0.
R> iris_of_filtered <- iris_of[(iris_of$Species == "setosa" |
+ iris_of$Species == "versicolor") &
+ iris_of$Petal.Width < 2.0,]
R> nrow(iris_of_filtered)[1] 100
R> head(iris_of, 3)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 4.7 3.2 1.3 0.2 setosa