Type:	Package
Version:	1.0
Date:	2023-12-01
Title:	Data Manipulation using Formula
Description:	A tool for manipulating data using the generic formula. A single formula allows to easily add, replace and remove variables before running the analysis.
Depends:	R (≥ 3.5.0)
Imports:	utils, stats, formula.tools(≥ 1.7.1)
Suggests:	knitr, rmarkdown
VignetteBuilder:	knitr
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Repository:	CRAN
URL:	https://github.com/serafinialessio/dformula
BugReports:	https://github.com/serafinialessio/dformula/issues
NeedsCompilation:	no
Encoding:	UTF-8
LazyData:	true
Packaged:	2023-12-01 09:29:09 UTC; alessioserafini
Author:	Alessio Serafini [aut, cre]
Maintainer:	Alessio Serafini <srf.alessio@gmail.com>
Date/Publication:	2023-12-01 10:10:02 UTC

Add variables

Description

Add new variables by mutating the input variables using a formula.

Usage

add(from, formula, as = NULL,
    position = c("right", "left"),
    na.remove = FALSE, logic_convert = TRUE,...)

Arguments

Details

The formula is composed of two part:

~ new_variables

the right-hand are the new varaible to add starting from the existing varaibles, using the I() function.

For example:

~ I(log(column_names1)) + I(column_names2/100)

the column_names1 and log(column_names1) are added to the data.

If na.remove is set ti TRUE, new variables are created, added to the dataset in input and then the observation with missing are removed.

Value

Returns a data.frame object with the original and the new varaibles.

Author(s)

Alessio Serafini

Examples

data("airquality")
dt <- airquality

head(add(from = dt, formula =   ~ log(Ozone)))
head(add(from = dt, formula =   ~ log(Ozone) +  log(Wind)))
head(add(from = dt, formula =   ~ log(Ozone), as = "Ozone_1"))


head(add(from = dt, formula =  Ozone + Wind ~ log()))
head(add(from = dt, formula =  ~ log()))
head(add(from = dt, formula =  .~ log(), position = "left"))

head(add(from = dt, formula =  .~ log(), na.remove = TRUE))

head(add(from = dt, formula =   ~ I((Ozone>5))))
head(add(from = dt, formula =   ~ I((Ozone>5)), logic_convert = FALSE ))

head(add(from = dt, formula = Ozone + Wind ~ C(Ozone-Ozone)))
head(add(from = dt, formula =  ~ C(log(Ozone))))
head(add(from = dt, formula =  ~ C(5)))
head(add(from = dt, formula = Ozone + Wind ~ C(Ozone-Ozone)))
head(add(from = dt, formula =  Ozone + Wind ~ C(log(Ozone))))



foo <- function(x, a = 100){return(x-x + a)}

head(add(from = dt, formula =  Ozone + Month~ I(foo(a = 100))))
head(add(from = dt, formula =  Ozone + Month~ foo()))
head(add(from = dt, formula =  ~ I(foo(Ozone, a = 100))))

World population

Description

World population and countries are

Usage

data("population_data")

Format

A data frame with 159 observations on the following 3 variables.

Country

a character vector with countries names

Population

a numeric vector with population

Area

a numeric vector with area of the counties

Source

https://www.worldometers.info

Examples

data(population_data)
str(population_data)

Remove a subset

Description

Selects the row and the varaibles to remove by specifing a condition using a formula.

Usage

remove(from, formula = .~., na.remove = FALSE, ...)

Arguments

Details

The formula is composed of two part:

column_names ~ rows_conditions

the left-hand side are the names of the column to remove, and the right-hand the operation to remove the rows, using the I() function.

For example:

column_names1 + column_names2 ~ I(column_names1 == "a") + I(column_names2 > 4)

first the row are selected to be removed if the observation in the column_names1 are equal to a and if the observation in the column_names2 are biggers than 4, then the column_names1 and column_names2 are removed and the other varaibles are returned.

If na.remove is set to TRUE, after the subsetting the observations with missing are removed.

Value

Returns a data.frame object without the selected elements.

Author(s)

Alessio Serafini

Examples

data("airquality")
dt <- airquality

head(remove(from = dt, formula = .~ I(Ozone > 10)))
head(remove(from = dt, formula = .~ I(Ozone > 10), na.remove = TRUE))
head(remove(from = dt, formula = Ozone ~ .))

head(remove(from = dt, formula = Ozone~ I(Ozone > 10)))
head(remove(from = dt, formula = Ozone + Wind~ I(Ozone > 10)))

head(remove(from = dt, formula = Ozone + . ~ I(Ozone > 10)))
head(remove(from = dt, formula = Ozone + NULL ~ I(Ozone > 10)))

Rename variables

Description

Rename variables using formulas

Usage

rename(from, formula, ...)

Arguments

Details

The formula is composed of two part:

column_names ~ new_variables_name

the left-hand side select the columns to change the names, and the right-hand the new names of the selected columns

For example:

column_names1 + column_names2 ~ new_variables_name1 + new_variables_name2

the name of the column 1 and the name of the column 2 are changed in new_variables_name1 and new_variables_name2

Value

The original data.frame with changed column names

Author(s)

Alessio Serafini

Examples

data("airquality")
dt <- airquality

head(rename(from = dt, Ozone ~ Ozone1))
head(rename(from = dt, Ozone + Wind ~ Ozone_new + Wind_new))

Select a subset

Description

Selects the row and the varaibles by specifing a condition using a formula.

Usage

select(from, formula = .~., as = NULL, na.remove = FALSE, na.return = FALSE,...)

Arguments

Details

The formula is composed of two part:

column_names ~ row_conditions

the left-hand side are the names of the column to select, and the right-hand the operations to select the rows, using the I() function.

For example:

column_names1 + column_names2 ~ I(column_names1 == "a") + I(column_names2 > 4)

first the rows are selected if the observation in the column_names1 are equal to a and if the observation in the column_names2 are biggers than 4, then the column_names1 and column_names2 are returned.

If na.remove is set to TRUE, after the subsetting the observations with missing are removed.

Value

Returns a data.frame object containing the selected elements.

Author(s)

Alessio Serafini

Examples

data("airquality")
dt <- airquality

## Selects columns and filter rows

select(from = dt, formula = .~ I(Ozone > 10 & Wind > 10))
select(from = dt, formula = Ozone ~ I(Wind > 10))
select(from = dt, formula = Ozone + Wind~ I(Ozone > 10))

## All rows and filter columns

select(from = dt, formula = Ozone ~ .)
select(from = dt, formula = Ozone + Wind ~ NULL)

Transform varibles

Description

Mutate input variables using a formula.

Usage

transform(from, formula, as = NULL,
          na.remove = FALSE, logic_convert = TRUE, ...)

Arguments

Details

The formula is composed of two part:

column_names ~ trasformed_variables

the left-hand side are the names of the column to transform, and the right-hand the operations applied to the selected columns, using the I() function.

For example:

column_names1 + column_names2 ~ I(log(column_names1)) + I(column_names2/100)

the column_names1 is mutated in log(column_names1) and column_names2 is divided by 100.

If na.remove is set to TRUE, variables are mutaded, and then the observation with missing are removed.

Value

Returns the original data.frame object with mutaded varaibles.

Author(s)

Alessio Serafini

Examples

data("airquality")
dt <- airquality

head(transform(from = dt, Ozone ~ I(Ozone-Ozone)))
head(transform(from = dt, Ozone ~ log(Ozone)))
head(transform(from = dt, Ozone ~ I(Ozone>5)))
head(transform(from = dt, Ozone ~ I(Ozone>5), logic_convert = TRUE))


head(transform(from = dt,  ~ log()))
head(transform(from = dt, . ~ log()))
head(transform(from = dt, NULL ~ log()))

head(transform(from = dt, Ozone + Day ~ log()))
head(transform(from = dt, Ozone + Day ~ log(Ozone/100) + exp(Day)))
head(transform(from = dt, Ozone ~ log()))

head(transform(from = dt,Ozone + Wind ~ C(log(1))))
head(transform(from = dt,Ozone + Wind ~ log(Ozone) + C(10)))


head(transform(from = dt, Ozone + Wind~ C(log(Ozone))))


foo <- function(x, a = 100){return(x-x + a)}
head(transform(from = dt, Ozone + Wind ~ foo(a = 100)))
head(transform(from = dt, . ~ foo(a = 100)))

head(transform(from = dt, Ozone + Wind ~ log(log(1))))