I'm trying to set the default value for a function parameter to a named numeric. Is there a way to create one in a single statement? I checked ?numeric and ?vector but it doesn't seem so. Perhaps I can convert/coerce a matrix or data.frame and achieve the same result in one statement? To be clear, I'm trying to do the following in one shot:
test = c( 1 , 2 )
names( test ) = c( "A" , "B" )
The setNames() function is made for this purpose. As described in Advanced R and ?setNames:
test <- setNames(c(1, 2), c("A", "B"))
How about:
c(A = 1, B = 2)
A B
1 2
...as a side note, the structure function allows you to set ALL attributes, not just names:
structure(1:10, names=letters[1:10], foo="bar", class="myclass")
Which would produce
a b c d e f g h i j
1 2 3 4 5 6 7 8 9 10
attr(,"foo")
[1] "bar"
attr(,"class")
[1] "myclass"
The convention for naming vector elements is the same as with lists:
newfunc <- function(A=1, B=2) { body} # the parameters are an 'alist' with two items
If instead you wanted this to be a parameter that was a named vector (the sort of function that would handle arguments supplied by apply):
newfunc <- function(params =c(A=1, B=2) ) { body} # a vector wtih two elements
If instead you wanted this to be a parameter that was a named list:
newfunc <- function(params =list(A=1, B=2) ) { body}
# a single parameter (with two elements in a list structure
magrittr offers a nice and clean solution.
result = c(1,2) %>% set_names(c("A", "B"))
print(result)
A B
1 2
You can also use it to transform data.frames into vectors.
df = data.frame(value=1:10, label=letters[1:10])
vec = extract2(df, 'value') %>% set_names(df$label)
vec
a b c d e f g h i j
1 2 3 4 5 6 7 8 9 10
df
value label
1 1 a
2 2 b
3 3 c
4 4 d
5 5 e
6 6 f
7 7 g
8 8 h
9 9 i
10 10 j
To expand upon #joran's answer (I couldn't get this to format correctly as a comment): If the named vector is assigned to a variable, the values of A and B are accessed via subsetting using the [ function. Use the names to subset the vector the same way you might use the index number to subset:
my_vector = c(A = 1, B = 2)
my_vector["A"] # subset by name
# A
# 1
my_vector[1] # subset by index
# A
# 1
Related
I have a list where each entry is a vector of named integers, like this.
a = c(1:5)
b = c(2:6)
names(a) = c("a","b","c","d","e")
names(b) = c("b","c","d","e","f")
mylist <- list("0" = a, "1" = b)
The names inside list "mylist" will always start at "0" and increase by 1, but in my real scenario, the list will not always have two entries (can vary from 2 to a few dozen).
What I am trying to do is loop through all names in my list (in this case "0" and "1"), and access the information corresponding to each index. I've tried
for (x in 0:(length(mylist) - 1)) {
print(mylist$x)
}
and
for (x in 0:(length(mylist) - 1)) {
name = as.character(x)
print(mylist$name)
}
which also does not work. I'm aware that I can use normal list indexing such as
mylist[x]
but this includes the names (e.g. "0", "1") which I am trying to provide producing in the output. To clarify, I want my output to look like
print(mylist$"0")
output:
a b c d e
1 2 3 4 5
and not
print(mylist[1])
output:
$`0`
a b c d e
1 2 3 4 5
If we want to show similar to $, use [[
mylist[[1]]
for (x in 0:(length(mylist) - 1)) {
name = as.character(x)
print(mylist[[name]])
}
#a b c d e
#1 2 3 4 5
#b c d e f
#2 3 4 5 6
I am creating a custom object for a package and I want to have a list of two objects, but for one of those elements to be 'hidden'
For example:
l = list(data = data.frame(a = 1:3, b = 4:6), hidden = list(obj1 = 1, obj2 = 2))
When I interact with the list I want to only interact with the data element and the other be only accessed specifically.
So, if i typed l
> l
a b
1 1 4
2 2 5
3 3 6
Which I can manage with a custom print method. But I also want to be able to do
> l[,1]
[1] 1 2 3
Which I don't think is possible with a custom print method.
I don't have any specific requirements for how the other element should be accessed, but something 'R friendly' I guess.
Is there a different class I should be using or creating a new class? Any advice would be appreciated.
You could indeed define a custom class for your object. Let
class(l) <- "myclass"
Then you may define custom-specific methods for your functions of interest. For instance, in the case of l[, 1] we have
`[.myclass` <- function(x, ...) `[`(x[[1]], ...)
which takes this double list and then calls the usual [ function on the first list element:
l[, 1]
# [1] 1 2 3
The same can be done with other functions, such as print:
fun.myclass <- function(x, ...) fun(x[[1]], ...)
And you still can always access the second object in the usual way,
l$hidden
# $obj1
# [1] 1
#
# $obj2
# [1] 2
I think it would be cleaner for you to use attributes :
l <- list(data = data.frame(a = 1:3, b = 4:6),
hidden = list(obj1 = 1, obj2 = 2))
foo <- function(x){
attr(x$data,"hidden") <- x$hidden
x$data
}
l <- foo(l)
l
# a b
# 1 1 4
# 2 2 5
# 3 3 6
l[,1]
# [1] 1 2 3
attr(l,"hidden")
#
# [1] 1
#
#
# [1] 2
#
Edit
This question seems to be a duplicate of the question How to group a vector into a list of vectors?, and the answer split(df$b, df$id) was suggested. First happy with the solution, I realized that the given answers do not fully address my question. In the below question, I would like to obtain a list in which the vector elements are assigned to the value of a third column (in my example df$a). This is important, as otherwise the order of df$b plays a role. I mean obviously I can arrange by df$a and then call split(), but maybe there is another way of doing that.
My sample df:
df <- data_frame(id = paste0('id',rep(1:2, each = 5)), a = rep(letters[1:5],2),b=c(1:5,5:1))
Df should be grouped by ID (in df$id). I would like to create a list of vectors for each group (id) element that contains the values of df$b. My approach
require(tidyr)
spread_df <- df %>% spread(id,b) #makes new columns for each id
#loop over spread_df
for (i in 1:length(spread_df)) {
list_group_elements [i]<- list(spread_df[[i]])
#I want each vector to be identified by the identifier of column df$a
#therefore:
names(list_group_elements[[i]]) <- list_group_elements[[1]]
}
This results in :
list_group_elements
[[1]]
a b c d e
"a" "b" "c" "d" "e"
[[2]]
a b c d e
1 2 3 4 5
[[3]]
a b c d e
5 4 3 2 1
I don't need the first element of the list, but the rest is basically what I need. I have the peculiar impression that my approach is somewhat not ideal and if someone has an idea to improve this, (e.g., with dplyr?) this would be highly appreciated. Why do I want this: I made a function that uses vectors as arguments and I would like to run this function over certain columns from dataframes - but only using the grouped values as arguments and not the entire column.
You may make df$b a named vector using setNames, and then split it into a list:
split(setNames(df$b, df$a), df$id)
# $id1
# a b c d e
# 1 2 3 4 5
#
# $id2
# a b c d e
# 5 4 3 2 1
One way is
lapply(levels(df$id), function(L) df$b[df$id == L])
[[1]]
[1] 1 2 3 4 5
[[2]]
[1] 5 4 3 2 1
Consider by, object-oriented wrapper of tapply, designed to split dataframe by factor(s):
by(df, df$id, FUN=function(i) i$b)
I am trying to construct a function which shouldn't be hard in terms of programming but I am having some difficulties to conceptualize it. Hope you'll be able to understand my problem better than me!
I'd like a function that takes a single list of vectors as argument. Something like
arg1 = list(c(1,2), c(2,3), c(5,6), c(1,3), c(4,6), c(6,7), c(7,5), c(5,8))
The function should output a matrix with two columns (or a list of two vectors or something like that) where one column contains letters and the other numbers. One can think of the argument as a list of the positions/values that should be placed in the same group. If in the list there is the vector c(5,6), then the output should contain somewhere the same letters next to the values 5 and 6 in the number column. If there are the three following vectors c(1,2), c(2,3) and c(1,3), then the output should contain somewhere the same letters next to the value 1, 2 and 3 in the number column.
Therefore if we enter the object arg1 in the function it should return:
myFun(arg1)
number_column letters_column
1 A
2 A
3 A
5 B
6 B
7 B
4 C
6 C
5 D
8 D
(the order is not important. The letters E should not be present before the letter D has been used)
Therefore the function has constructed 2 groups of 3 (A:[1,2,3] and B:[5,6,7]) and 2 groups of 2 (C:[4,6] and D:[5,8]). Note one position or number can be in several group.
Please let me know if something is unclear in my question! Thanks!
As I wrote in the comments, it appears that you want a data frame that lists the maximal cliques of a graph given a list of vectors that define the edges.
require(igraph)
## create a matrix where each row is an edge
argmatrix <- do.call(rbind, arg1)
## create an igraph object from the matrix of edges
gph <- graph.edgelist(argmatrix, directed = FALSE)
## returns a list of the maximal cliques of the graph
mxc <- maximal.cliques(gph)
## creates a data frame of the output
dat <- data.frame(number_column = unlist(mxc),
group_column = rep.int(seq_along(mxc),times = sapply(mxc,length)))
## converts group numbers to letters
## ONLY USE if max(dat$group_column) <= 26
dat$group_column <- LETTERS[dat$group_column]
# number_column group_column
# 1 5 A
# 2 8 A
# 3 5 B
# 4 6 B
# 5 7 B
# 6 4 C
# 7 6 C
# 8 3 D
# 9 1 D
# 10 2 D
I'm trying to set the default value for a function parameter to a named numeric. Is there a way to create one in a single statement? I checked ?numeric and ?vector but it doesn't seem so. Perhaps I can convert/coerce a matrix or data.frame and achieve the same result in one statement? To be clear, I'm trying to do the following in one shot:
test = c( 1 , 2 )
names( test ) = c( "A" , "B" )
The setNames() function is made for this purpose. As described in Advanced R and ?setNames:
test <- setNames(c(1, 2), c("A", "B"))
How about:
c(A = 1, B = 2)
A B
1 2
...as a side note, the structure function allows you to set ALL attributes, not just names:
structure(1:10, names=letters[1:10], foo="bar", class="myclass")
Which would produce
a b c d e f g h i j
1 2 3 4 5 6 7 8 9 10
attr(,"foo")
[1] "bar"
attr(,"class")
[1] "myclass"
The convention for naming vector elements is the same as with lists:
newfunc <- function(A=1, B=2) { body} # the parameters are an 'alist' with two items
If instead you wanted this to be a parameter that was a named vector (the sort of function that would handle arguments supplied by apply):
newfunc <- function(params =c(A=1, B=2) ) { body} # a vector wtih two elements
If instead you wanted this to be a parameter that was a named list:
newfunc <- function(params =list(A=1, B=2) ) { body}
# a single parameter (with two elements in a list structure
magrittr offers a nice and clean solution.
result = c(1,2) %>% set_names(c("A", "B"))
print(result)
A B
1 2
You can also use it to transform data.frames into vectors.
df = data.frame(value=1:10, label=letters[1:10])
vec = extract2(df, 'value') %>% set_names(df$label)
vec
a b c d e f g h i j
1 2 3 4 5 6 7 8 9 10
df
value label
1 1 a
2 2 b
3 3 c
4 4 d
5 5 e
6 6 f
7 7 g
8 8 h
9 9 i
10 10 j
To expand upon #joran's answer (I couldn't get this to format correctly as a comment): If the named vector is assigned to a variable, the values of A and B are accessed via subsetting using the [ function. Use the names to subset the vector the same way you might use the index number to subset:
my_vector = c(A = 1, B = 2)
my_vector["A"] # subset by name
# A
# 1
my_vector[1] # subset by index
# A
# 1