Type: Package
Title: Organizing Data in Hypercubes
Version: 0.2.1
Author: Michael Scholz
Maintainer: Michael Scholz <michael.scholz@th-deg.de>
Description: Provides functions and methods for organizing data in hypercubes (i.e., a multi-dimensional cube). Cubes are generated from molten data frames. Each cube can be manipulated with five operations: rotation (change.dimensionOrder()), dicing and slicing (add.selection(), remove.selection()), drilling down (add.aggregation()), and rolling up (remove.aggregation()).
License: GPL-3
Encoding: UTF-8
Depends: R (≥ 3.3.0), stats, plotly
Imports: methods, stringr, dplyr
LazyData: TRUE
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-02-27 13:57:33 UTC; mScholz
Repository: CRAN
Date/Publication: 2020-02-28 07:10:08 UTC

Provides functions and methods for organizing data in hypercubes

Description

This package provides methods for organizing data in a hypercube Each cube can be manipulated with five operations rotation (changeDimensionOrder), dicing and slicing (add.selection, remove.selection), drilling down (add.aggregation), and rolling up (remove.aggregation).

Details

Package: hypercube
Type: Package
Version: 0.2.1
Date: 2020-02-27
License: GPL-3
Depends: R (>= 3.0), methods

Author(s)

Michael Scholz michael.scholz@th-deg.de

Examples


# Simple example
data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
cube

# More sophisticated example
data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
       location = c("state"), product = "product"), valueColumn = "amount")
cube = add.selection(cube, criteria = list(state = c("AL", "TX")))
cube = add.aggregation(cube, dimensions = c("month", "year"), fun = "sum")
cube
df = as.data.frame(cube)
df

Class "Cube"

Description

Class "Cube"

Slots

data

(array) The data that are represented as hypercube.

structure

(list) The structure of the dimensions of the hypercube.

view

(list) Information about how to build a view for the hypercube. This information is stored in a list of Dimension-class objects.

Objects from the Class

Objects can be created by calls of the form new("Cube", ...). This S4 class describes Cube objects.

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

generateCube

Examples


# show Cube definition
showClass("Cube")

Class "Cube"

Description

Class "Cube"

Slots

name

(character) The name of the dimension.

values

(vector) A vector of selected values for this dimension.

aggregation

(vector) A vector of aggregation functions that will be applied to this dimension.

Objects from the Class

Objects can be created by calls of the form new("Dimension", ...). This S4 class describes Dimension objects.

Author(s)

Michael Scholz michael.scholz@th-deg.de

Examples


# show Dimension definition
showClass("Dimension")

Adds an aggregation to a hypercube

Description

This function adds a further aggregation to a hypercube. The cube itself will not be changed. The aggregation only affect the data that will be shown when printing the cube. Note that selection criteria will be applied before aggregating the data.

Usage

add.aggregation(
  x,
  dimensions,
  fun = c("sum", "min", "max", "prod", "mean", "median", "sd", "count")
)

Arguments

x

Hypercube for which the selection criteria will be defined.

dimensions

A vector of dimensions that are used in the aggregation.

fun

The function that is used for aggregation. Possible functions are sum, prod, min, max, mean, median, sd, and count.

Value

Returns a Cube object with the added aggregation.

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

Cube remove.aggregation add.selection

Examples


data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
cube = add.aggregation(cube, dimensions = c("month", "year"), fun = "sum")
cube

Adds selection criteria to a hypercube

Description

This function adds further selection criteria to a hypercube. The cube itself will not be changed. The selection criteria only affect the data that will be shown when printing the cube. Note that selection criteria will be applied before aggregating the data.

Usage

add.selection(x, criteria)

Arguments

x

Hypercube for which the selection criteria will be defined.

criteria

A list of selection criteria.

Value

Returns a Cube object with the added selection criteria.

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

Cube remove.selection add.aggregation

Examples


data("sales")
print(str(sales))
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
cube = add.selection(cube, criteria = list(state = c("CA", "FL")))
cube
cube = add.selection(cube, criteria = list(state = c("TX")))
cube

Converts the actual view of a cube to a data frame

Description

Converts the actual view of a Cube object to a data frame. All added selections and aggregations will be regarded. Note that selection criteria will be applied before aggregating the data.

Usage

## S3 method for class 'Cube'
as.data.frame(x, row.names = NULL, optional = FALSE, ...)

Arguments

x

The Cube object that will be converted to a data frame.

row.names

A character vector giving the row names for the data frame.

optional

Should setting row names and converting column names be optional?

...

Further parameters that are passed to as.data.frame.table.

Value

A molten data frame

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

add.aggregation add.selection

Examples


data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
cube = change.dimensionOrder(cube, dimensions = c("product", "month", "year", "state"))
df = as.data.frame(cube)
df

Changes the order of the dimensions in a given cube

Description

Changes the order of the dimensions in a given cube

Usage

change.dimensionOrder(x, dimensions)

Arguments

x

Hypercube for which the dimensions should be re-ordered.

dimensions

Vector of dimensions. The order of the dimensions in this vector defines the order of the dimensions in the cube.

Value

Returns a Cube object.

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

Cube

Examples


data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
cube = change.dimensionOrder(cube, dimensions = c("product", "month", "year", "state"))
cube

Generates a hypercube from a given dataframe

Description

This function generates a hypercube from a given dataframe. The dimensions of the hypercube correspond to a set of selected columns from the dataframe.

Usage

generateCube(
  data,
  columns,
  valueColumn,
  fun = c("sum", "min", "max", "prod", "mean", "median", "sd", "count")
)

Arguments

data

A dataframe that is used as source for the hypercube.

columns

A vector of column names that will form the dimensions of the hypercube.

valueColumn

The name of the column that provides the values for the cells of the hypercube.

fun

Aggregation function for aggregating over those columns that do not correspond with any dimension of the hypercube.

Value

Returns a Cube object.

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

Cube

Examples


data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")

Calculates the dimension importances of a given cube.

Description

Calculates the importance values for all dimensions of the actual view of a Cube object. All added selections and aggregations will be regarded. Note that selection criteria will be applied before aggregating the data.

Usage

importance(x)

Arguments

x

The Cube object for which the importance values will be computed.

Value

Sparsity value

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

sparsity

Examples


data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
importance(cube)

Visualizes a Cube object as parallel coordinate plot

Description

Generates a parallel coordinate plot for a given Cube object. All added selections and aggregations will be regarded.

Usage

## S4 method for signature 'Cube'
plot(x, color = NA, colorscale = "RdBu", ...)

Arguments

x

The Cube object that should be plotted.

color

The color of the lines in the parallel coordinate plot. If this parameter is NA or NULL, a colorscale rather than a unique color will be used.

colorscale

The colorscale for the lines in the parallel coordinate plot. Default is RdBu. All plotly colorscales (e.g., Blackbody, Earth, Jet) are possible.

...

Further plot_ly parameters.

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

Cube

Examples


data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
plot(cube)

Prints an Importances object.

Description

Prints an Importances object.

Usage

## S3 method for class 'Importances'
print(x, ...)

Arguments

x

The Importances object that will be printed.

...

Ignored parameters.

Value

Sparsity value

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

importance

Examples


data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
importances = importance(cube)
print(importances)

Removes aggregations from a hypercube

Description

This function removes aggregations from a hypercube. The cube itself will not be changed. The aggregation only affect the data that will be shown when printing the cube.

Usage

remove.aggregation(x, dimensions = NA, last = FALSE)

Arguments

x

Hypercube from which the aggregation will be removed.

dimensions

A vector of dimensions for which the aggregations will be removed.

last

Should the last aggregation be removed? If this parameter is set TRUE, the dimension vector will be ignored.

Value

Returns a Cube object with the added aggregation.

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

Cube add.aggregation remove.selection

Examples


data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
cube = add.aggregation(cube, dimensions = c("month", "year"), fun = "sum")
cube
cube = add.aggregation(cube, dimensions = "year", fun = "sum")
cube
cube = remove.aggregation(cube, dimensions = "year")
cube

Removes selection criteria from a hypercube

Description

This function removes all selection criteria for the given dimensions. The cube itself will not be changed. The selection criteria only affect the data that will be shown when printing the cube.

Usage

remove.selection(x, dimensions)

Arguments

x

Hypercube for which the selection criteria will be defined.

dimensions

A vector of dimension names for which all selection criteria will be removed.

Value

Returns a Cube object with removed selection criteria.

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

Cube add.selection remove.aggregation

Examples


data("sales")
print(str(sales))
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
cube = add.selection(cube, criteria = list(state = c("CA", "FL")))
cube
cube = remove.selection(cube, dimensions = c("state"))
cube

Sales of books

Description

A dataset containing 2,500 sales of 4 books in different states and countries.

Usage

sales

Format

A data fram with 2500 rows and 7 variables:

month

month as number

year

year as number

state

abbreviation of the state as character

country

country as character

product

name of the product as character

unit

number of sold products

amount

amount of sales

Source

Synthetic dataset

Shows a Cube object

Description

Shows the actual view of a Cube object. All added selections and aggregations will be regarded. Note that selection criteria will be applied before aggregating the data.

Usage

## S4 method for signature 'Cube'
show(object)

Arguments

object

The Cube object

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

Cube

Examples


data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
cube

Shows a Dimension object

Description

Shows a Dimension object

Usage

## S4 method for signature 'Dimension'
show(object)

Arguments

object

The Dimension object

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

Cube

Examples


data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
cube@view[[1]]

Calculates the sparsity of a given cube.

Description

Calculates the sparsity of the actual view of a Cube object. All added selections and aggregations will be regarded. Note that selection criteria will be applied before aggregating the data.

Usage

sparsity(x)

Arguments

x

The Cube object for which the sparsity will be computed.

Value

Sparsity value

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

importance

Examples


data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
sparsity(cube)

Shows a summary for the given cube

Description

Shows the dimensions and the number of levels per dimension of the given cube. All added selections and aggregations will be regarded.

Usage

summary(x)

Arguments

x

The Cube object for which the summary is shown.

Author(s)

Michael Scholz michael.scholz@th-deg.de

See Also

Cube

Examples


data("sales")
cube = generateCube(sales, columns = list(time = c("month", "year"),
      location = c("state"), product = "product"), valueColumn = "amount")
summary(cube)