m61r: Create m61r object

In m61r: Package About Data Manipulation in Pure Base R

Create m61r object

Description

Create a m61r object that enables to run a sequence of operations on a data.frame.

Usage

m61r(df = NULL)

## S3 method for class 'm61r'
x[i, j, ...]

## S3 replacement method for class 'm61r'
x[i, j] <- value

## S3 method for class 'm61r'
print(x, ...)

## S3 method for class 'm61r'
names(x, ...)

## S3 method for class 'm61r'
dim(x, ...)

## S3 method for class 'm61r'
as.data.frame(x, ...)

## S3 method for class 'm61r'
rbind(x, ...)

## S3 method for class 'm61r'
cbind(x, ...)

Arguments

df	data.frame
x	object of class m61r
i	row
j	column
...	further arguments passed to or from other methods
value	value to be assigned

Value

The function m61r returns an object of type m61r.

Argument df get stored internally to the object m61r. One manipulates the internal data.frame by using internal functions similar to the ones implemented in package m61r for data.frames as arrange, desange, filter, join and its relatives, mutate and transmutate, gather and spread, select, groupe_by, summarise, values and modify. The result of the last action is stored internally to the object m61r until the internal function values get called. It is thus possible to create a readable sequence of actions on a data.frame.

In addition,

• [.m61r returns a subset of the internal data.frame embedded to the object m61r.

• [<-.m61r assigns value to the internal data.frame embedded to the object m61r.

• print.m61r prints the internal data.frame embedded to the object m61r.

• names.m61r provides the names of the column of the internal data.frame embedded to the object m61r.

• dim.m61r provides the dimensions of the internal data.frame embedded to the object m61r.

• as.data.frame.m61r extracts the internal data.frame embedded to the object m61r.

• cbind.m61r combines by _c_olumns two objects m61r.

• rbind.m61r combines by _r_ows two objects m61r.

• left_join, anti_join, full_join, inner_join, right_join, semi_join join two objects m61r.

Finally, it is possible to clone a m61r object into a new one by using the internal function clone.

Examples

  # init
  co2 <- m61r(df=CO2)

  # filter
  co2$filter(~Plant=="Qn1")
  co2

  co2$filter(~Type=="Quebec")
  co2

  # select
  co2$select(~Type)
  co2

  co2$select(~c(Plant,Type))
  co2

  co2$select(~-Type)
  co2

  co2$select(variable=~-(Plant:Treatment))
  co2

  # mutate/transmutate
  co2$mutate(z=~conc/uptake)
  co2

  co2$mutate(mean=~mean(uptake))
  co2

  co2$mutate(z1=~uptake/conc,y=~conc/100)
  co2

  co2$transmutate(z2=~uptake/conc,y2=~conc/100)
  co2

  # summarise
  co2$summarise(mean=~mean(uptake),sd=~sd(uptake))
  co2

  co2$group_by(~c(Type,Treatment))
  co2$summarise(mean=~mean(uptake),sd=~sd(uptake))
  co2

  # arrange/dessange
  co2$arrange(~c(conc))
  co2

  co2$arrange(~c(Treatment,conc,uptake))
  co2

  co2$desange(~c(Treatment,conc,uptake))
  co2

  # join
  authors <- data.frame(
               surname = I(c("Tukey", "Venables", "Tierney", "Ripley", "McNeil")),
               nationality = c("US", "Australia", "US", "UK", "Australia"),
               deceased = c("yes", rep("no", 4)))

  books <- data.frame(
             name = I(c("Tukey", "Venables", "Tierney","Ripley",
                   "Ripley", "McNeil", "R Core")),
            title = c("Exploratory Data Analysis",
                   "Modern Applied Statistics ...",
                   "LISP-STAT",
                   "Spatial Statistics", "Stochastic Simulation",
                   "Interactive Data Analysis",
                   "An Introduction to R"),
         other.author = c(NA, "Ripley", NA, NA, NA, NA,"Venables & Smith"))

  ## inner join
  tmp <- m61r(df=authors)

  tmp$inner_join(books, by.x = "surname", by.y = "name")
  tmp

  ## left join
  tmp$left_join(books, by.x = "surname", by.y = "name")
  tmp

  ## right join
  tmp$right_join(books, by.x = "surname", by.y = "name")
  tmp

  ## full join
  tmp$full_join(books, by.x = "surname", by.y = "name")
  tmp

  ## semi join
  tmp$semi_join(books, by.x = "surname", by.y = "name")
  tmp

  ## anti join #1
  tmp$anti_join(books, by.x = "surname", by.y = "name")
  tmp

  ## anti join #2
  tmp2 <- m61r(df=books)
  tmp2$anti_join(authors, by.x = "name", by.y = "surname")
  tmp2

  ## with two m61r objects
  tmp1 <- m61r(books)
  tmp2 <- m61r(authors)
  tmp3 <- anti_join(tmp1,tmp2, by.x = "name", by.y = "surname")
  tmp3

  # Reshape

  ## gather
  df3 <- data.frame(id = 1:4,
                    age = c(40,50,60,50),
                    dose.a1 = c(1,2,1,2),
                    dose.a2 = c(2,1,2,1),
                    dose.a14 = c(3,3,3,3))

  df4 <- m61r::m61r(df3)
  df4$gather(pivot = c("id","age"))
  df4

  ## spread
  df3 <- data.frame(id = 1:4,
                    age = c(40,50,60,50),
                    dose.a1 = c(1,2,1,2),
                    dose.a2 = c(2,1,2,1),
                    dose.a14 = c(3,3,3,3))

  df4 <- m61r::gather_(df3,pivot = c("id","age"))
  df4 <- rbind(df4,
    data.frame(id=5, age=20,parameters="dose.a14",values=8),
    data.frame(id=6, age=10,parameters="dose.a1",values=5))

  tmp <- m61r::m61r(df4)
  tmp$spread(col_name="parameters",col_values="values",pivot=c("id","age"))
  tmp


  # equivalence
  co2           # is not equivalent to co2[]
  co2[]         # is equivalent to co2$values()
  co2[1,]       # is equivalent to co2$values(1,)
  co2[,2:3]     # is equivalent to co2$values(,2:3)
  co2[1:10,1:3] # is equivalent to co2$values(1:10,2:3)
  co2[1,"Plant"]# is equivalent to co2$values(1,"Plant")

  # modification on m61r object only stay for one step
  co2[1,"conc"] <- 100
  co2[1,] # temporary result
  co2[1,] # back to normal

  # WARNING:
  # Keep the brackets to manipulate the intern data.frame
  co2[] <- co2[-1,]
  co2[1:3,] # temporary result
  co2[1:3,] # back to normal

  # ... OR you will destroy co2, and only keep the data.frame
  # co2 <- co2[-1,]
  # class(co2) # data.frame

  # descriptive manipulation
  names(co2)
  dim(co2)
  str(co2)

  ## cloning
  # The following will only create a second variable that point on
  # the same object (!= cloning)
  foo <- co2
  str(co2)
  str(foo)

  # Instead, cloning into a new environemnt
  foo <- co2$clone()
  str(co2)
  str(foo)

m61r documentation built on May 6, 2022, 5:07 p.m.