Description Usage Arguments Details Value Author(s) See Also Examples

An aggregate function is a function where the values of multiple rows are grouped together as input to calculate a single value of more significant meaning or measurement. The aggregate functions included are mean, sum, count, max, min, standard deviation, and variance. Also included is a function to compute the mean value of each column and a function to compute the sum of each column.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | ```
## S4 method for signature 'db.obj'
mean(x, ...)
## S4 method for signature 'db.obj'
sum(x, ..., na.rm = FALSE)
## S4 method for signature 'db.obj'
count(x)
## S4 method for signature 'db.obj'
max(x, ..., na.rm = FALSE)
## S4 method for signature 'db.obj'
min(x, ..., na.rm = FALSE)
## S4 method for signature 'db.obj'
sd(x)
## S4 method for signature 'db.obj'
var(x)
## S4 method for signature 'db.obj'
colMeans(x, na.rm = FALSE, dims = 1, ...)
## S4 method for signature 'db.obj'
colSums(x, na.rm = FALSE, dims = 1, ...)
colAgg(x)
db.array(x, ...)
``` |

`x` |
A For |

`...` |
further arguments passed to or from other methods This is currently not implemented. |

`na.rm` |
logical. Should missing values (including 'NaN') be removed? This is currently not implemented. |

`dims` |
integer: Which dimensions are regarded as 'rows' or 'columns' to sum over. This is currently not implemented and the default behavior is to sum over columns |

For aggregate functions: `mean`

, `sum`

, `count`

,
`max`

, `min`

, `sd`

, and `var`

, the signature
`x`

must be a reference to a single column in a table.

For aggregate functions: `colMeans`

, `colSums`

, and `colAgg`

the signature
`x`

can be a `db.obj`

referencing to a single column or a single
table, or can be a `db.Rquery`

referencing to multiple columns in a table.

For `mean`

, a `db.Rquery`

which is a SQL query to extract the average of a column of a table. Actually, it can work on multiple columns, so it is the same as `colMeans`

.

For `sum`

, a `db.Rquery`

which is a SQL query to extract the sum of a column of a table. Actually, it can work on multiple columns, so it is the same as `colSums`

.

For `count`

, a `db.Rquery`

which is a SQL query to extract the count of a column of a table.

For `max`

, a `db.Rquery`

which is a SQL query to extract the max of a column of a table.

For `min`

, a `db.Rquery`

which is a SQL query to extract the min of a column of a table.

For `sd`

, a `db.Rquery`

which is a SQL query to extract the standard deviation of a column of a table.

For `var`

, a `db.Rquery`

which is a SQL query to extract the variance of a column of a table.

For `colMeans`

, a `db.Rquery`

which is a SQL query to extract the mean of multiple columns of a table.

For `colSums`

, a `db.Rquery`

which is a SQL query to extract the sum of multiple columns of a table.

For `colAgg`

, a `db.Rquery`

which is a SQL query to retreive
the column values as an array aggregate.

For `db.array`

, a `db.Rquery`

which is a SQL query which
combine all columns into an array.

Author: Predictive Analytics Team at Pivotal Inc.

Maintainer: Frank McQuillan, [email protected]

`by,db.obj-method`

is usually used together with
aggregate functions.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | ```
## Not run:
## get the help for a method
## help("mean,db.obj-method")
## set up the database connection
## Assume that .port is port number and .dbname is the database name
cid <- db.connect(port = .port, dbname = .dbname, verbose = FALSE)
## ----------------------------------------------------------------------
## create a table from the example data.frame "abalone"
delete("abalone", conn.id = cid)
x <- as.db.data.frame(abalone, "abalone", conn.id = cid, verbose = FALSE)
## get the mean of a column
mean(x$diameter)
## get the sum of a column
sum(x$height)
## get the number of entries in a column
count(x$id)
## get the max value of a column
max(x$diameter)
## get the min value of a column
min(x$diameter)
## get the standard deviation of the values in column
sd(x$diameter)
## get the variance of the values in column
var(x$diameter)
## get the mean of all columns in the table
colMeans(x)
## get the sum of all columns in the table
colSums(x)
## get the array aggregate of a specific column in the table
colAgg(x$diameter)
## get the array aggregate of all columns in the table
colAgg(x)
## put everything into an array plus a constant 1 as the first element
db.array(1, x[,3:5], x[,6:7], x[,8:10])
## ----------------------------------------------------------------------
db.disconnect(cid, verbose = FALSE)
## End(Not run)
``` |

PivotalR documentation built on May 30, 2017, 8:18 a.m.

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