Package 'rsgl'

Average

Description

The avg function returns the average of a column within each group.

Function Name

• avg

Arguments

• The name of a numerical column to average (required).

Examples

library(duckdb)
con <- dbConnect(duckdb())
dbWriteTable(con, "cars", cars)

dbGetPlot(con, "
  visualize
    origin as x,
    avg(horsepower) as y
  from cars
  group by
    origin
  using bars
")

---

Bars

Description

Documents the aliases, aesthetics, and qualifiers for the bar geom.

Aliases

• bar

• bars

Aesthetics

• x

• y

• theta

• r

• color

Qualifiers

• horizontal: orients the bars horizontally.

• unstacked: doesn't stack overlapping bars.

• vertical: orients the bars vertically.

Examples

library(duckdb)
con <- dbConnect(duckdb())
dbWriteTable(con, "cars", cars)
dbGetPlot(con, "
  visualize
    bin(miles_per_gallon) as x,
    count(*) as y
  from cars
  group by
    bin(miles_per_gallon)
  using bars
")

dbGetPlot(con, "
  visualize
    bin(miles_per_gallon) as y,
    count(*) as x
  from cars
  group by
    bin(miles_per_gallon)
  using horizontal bars
")

---

Bin

Description

The bin function creates equal-width bins for a column; original values are transformed into bin-center values.

Function Name

• bin

Arguments

• The name of a numerical column to bin (required).

• The number of bins (optional, default 30).

Examples

library(duckdb)
con <- dbConnect(duckdb())
dbWriteTable(con, "cars", cars)

dbGetPlot(con, "
  visualize
    bin(miles_per_gallon) as x,
    count(*) as y
  from cars
  group by
    bin(miles_per_gallon)
  using bars
")

dbGetPlot(con, "
  visualize
    bin(miles_per_gallon, 10) as x,
    count(*) as y
  from cars
  group by
    bin(miles_per_gallon, 10)
  using bars
")

---

Boxes

Description

Documents the aliases, aesthetics, and qualifiers for the box geom.

Aliases

• box

• boxes

Aesthetics

• x

• y

• theta

• r

• color

Qualifiers

• horizontal: orients the boxes horizontally.

• vertical: orients the boxes vertically.

Examples

library(duckdb)
con <- dbConnect(duckdb())
dbWriteTable(con, "cars", cars)
dbGetPlot(con, "
  visualize
    origin as x,
    miles_per_gallon as y
  from cars
  using boxes
")

dbGetPlot(con, "
  visualize
    origin as y,
    miles_per_gallon as x
  from cars
  using horizontal boxes
")

---

Cars dataset

Description

A sample dataset used throughout rsgl documentation and examples containing attributes for a collection of cars. Loading rsgl masks datasets::cars; refer to the built-in version as datasets::cars if you need it.

Usage

cars

Format

A data frame with 406 rows and 5 variables:

car_id

Integer identifier for the car.

horsepower

Engine horsepower.

miles_per_gallon

Fuel economy in miles per US gallon.

origin

Country of origin (USA, Europe, Japan).

year

Model year (1970–1982).

Source

Derived from the cars dataset in the vega-datasets collection (https://github.com/vega/vega-datasets/blob/main/data/cars.json). The Miles_per_Gallon, Horsepower, and Origin columns were kept and renamed, year is the year taken from the original Year date, and car_id is a row identifier.

---

Count

Description

The count function returns the number of rows in each group.

Function Name

• count

Arguments

• * (required).

Examples

library(duckdb)
con <- dbConnect(duckdb())
dbWriteTable(con, "cars", cars)

dbGetPlot(con, "
  visualize
    origin as x,
    count(*) as y
  from cars
  group by
    origin
  using bars
")

---

Generate a plot from a SGL statement

Description

dbGetPlot takes a database connection and a SGL statement and returns the corresponding plot.

Usage

dbGetPlot(con, sgl_stmt)

Arguments

con	A database connection (as returned by DBI::dbConnect())
sgl_stmt	A SGL statement (string)

Value

The plot defined by the SGL statement (a sgl_plot object)

Examples

library(duckdb)
con <- dbConnect(duckdb())
dbWriteTable(con, "cars", cars)
p <- dbGetPlot(con, "
  visualize
    horsepower as x,
    miles_per_gallon as y
  from cars
  using points
")
print(p)

---

Linear

Description

The linear scale linearly maps data values to a visual property. It is the default scale for numerical aesthetic mappings.

Function Name

• linear

Arguments

• The name of an aesthetic to scale (required).

Examples

library(duckdb)
con <- dbConnect(duckdb())
dbWriteTable(con, "cars", cars)

# explicit linear scales
dbGetPlot(con, "
  visualize
    horsepower as x,
    miles_per_gallon as y
  from cars
  using points
  scale by
    linear(x),
    linear(y)
")

# default linear scales
dbGetPlot(con, "
  visualize
    horsepower as x,
    miles_per_gallon as y
  from cars
  using points
")

---

Lines

Description

Documents the aliases, aesthetics, and qualifiers for the line geom.

Aliases

• line

• lines

Aesthetics

• x

• y

• theta

• r

• color

Qualifiers

• horizontal: orients the line horizontally; points are connected in order of increasing x/theta values.

• regression: fits a linear regression line to the data.

• vertical: orients the line vertically; points are connected in order of increasing y/r values.

Examples

library(duckdb)
con <- dbConnect(duckdb())
dbWriteTable(con, "trees", trees)
dbGetPlot(con, "
  visualize
    age as x,
    circumference as y
  from trees
  collect by
    tree_id
  using lines
")

dbWriteTable(con, "cars", cars)
dbGetPlot(con, "
  visualize
    horsepower as x,
    miles_per_gallon as y
  from cars
  using (
     points
     layer
     regression line
  )
   scale by
     log(x),
     log(y)
")

---

Natural Log

Description

The ln scale maps data values to a visual property through a natural logarithm transformation.

Function Name

• ln

Arguments

• The name of an aesthetic to scale (required).

Examples

library(duckdb)
con <- dbConnect(duckdb())
dbWriteTable(con, "cars", cars)

dbGetPlot(con, "
  visualize
    horsepower as x,
    miles_per_gallon as y
  from cars
  using points
  scale by
    ln(x),
    ln(y)
")

---

Log

Description

The log scale maps data values to a visual property through a base-10 logarithm transformation.

Function Name

• log

Arguments

• The name of an aesthetic to scale (required).

Examples

library(duckdb)
con <- dbConnect(duckdb())
dbWriteTable(con, "cars", cars)

dbGetPlot(con, "
  visualize
    horsepower as x,
    miles_per_gallon as y
  from cars
  using points
  scale by
    log(x),
    log(y)
")

---

Points

Description

Documents the aliases, aesthetics, and qualifiers for the point geom.

Aliases

• point

• points

Aesthetics

• x

• y

• theta

• r

• color

• size

Qualifiers

• jittered: adds a small amount of random noise to each point's position.

Examples

library(duckdb)
con <- dbConnect(duckdb())
dbWriteTable(con, "cars", cars)
dbGetPlot(con, "
  visualize
    horsepower as x,
    miles_per_gallon as y
  from cars
  using points
")

set.seed(0)
dbGetPlot(con, "
  visualize
    origin as x,
    miles_per_gallon as y
  from cars
  using jittered points
")

---

Trees dataset

Description

A dataset used throughout rsgl documentation and examples containing repeated measurements of tree growth over time. Loading rsgl masks datasets::trees; refer to the built-in version as datasets::trees if you need it.

Usage

trees

Format

A data frame with 35 rows and 3 variables:

tree_id

Integer identifier for the tree.

age

Age of the tree at the time of measurement.

circumference

Trunk circumference at the time of measurement.

Source

Derived from datasets::Orange (R Core Team), with the Tree column renamed to tree_id.

---

Get SGL type classifications for columns in a table

Description

type_classifications takes a database connection and a table name and returns the SGL type classifications (numerical, categorical, or temporal) of the table's columns.

Usage

type_classifications(con, table_name)

Arguments

con	A database connection (as returned by DBI::dbConnect())
table_name	The name of a table

Value

A dataframe listing the SGL type classification of each column.

Examples

library(duckdb)
con <- dbConnect(duckdb())
dbWriteTable(con, "iris", iris)
type_classifications(con, "iris")

---