I tried to do this simple search but couldn't find anything on the percent (%) symbol in R.
What does %in% mean in the following code?
time(x) %in% time(y) where x and y are matrices.
How do I look up help on %in% and similar functions that follow the %stuff% pattern, as I cannot locate the help file?
Related questions:
What does eg %+% do? in R
The R %*% operator
What does %*% mean in R
What does %||% do in R?
What does %>% mean in R
I didn't think GSee's or Sathish's answers went far enough because "%" does have meaning all by itself and not just in the context of the %in% operator. It is the mechanism for defining new infix operators by users. It is a much more general issue than the virtues of the %in% infix operator or its more general prefix ancestor match. It could be as simple as making a pairwise "s"(um) operator:
`%s%` <- function(x,y) x + y
Or it could be more interesting, say making a second derivative operator:
`%DD%` <- function(expr, nam="x") { D(D( bquote(.(expr)), nam), nam) }
expression(x^4) %DD% "x"
# 4 * (3 * x^2)
The %-character also has importance in the parsing of Date, date-time, and C-type format functions like strptime, formatC and sprintf.
Since that was originally written we have seen the emergence of the magrittr package with the dplyr elaboration that demonstrates yet another use for %-flanked operators.
So the most general answer is that % symbols are handled specially by the R parser. Since the parser is used to process plotmath expressions, you will also see extensive options for graphics annotations at the ?plotmath help page.
%op% denotes an infix binary operator. There are several built-in operators using %, and you can also create your own.
(A single % sign isn't a keyword in R. You can see a list of keywords on the ?Reserved help page.)
How do I get help on binary operators?
As with anything that isn't a standard variable name, you have to to enclose the term in quotes or backquotes.
?"%in%"
?`%in%`
Credit: GSee's answer.
What does %in% do?
As described on the ?`%in%` help page (which is actually the ?match help page since %in% is really only an infix version of match.),
[%in%] returns a logical vector indicating if there is a match or not for its left operand
It is most commonly used with categorical variables, though it can be used with numbers as well.
c("a", "A") %in% letters
## [1] TRUE FALSE
1:4 %in% c(2, 3, 5, 7, 11)
## [1] FALSE TRUE TRUE FALSE
Credit: GSee's answer, Ari's answer, Sathish's answer.
How do I create my own infix binary operators?
These are functions, and can be defined in the same way as any other function, with a couple of restrictions.
It's a binary opertor, so the function must take exactly two arguments.
Since the name is non-standard, it must be written with quotes or backquotes.
For example, this defines a matrix power operator.
`%^%` <- function(x, y) matrixcalc::matrix.power(x, y)
matrix(1:4, 2) %^% 3
Credit: BondedDust's answer, Ari's answer.
What other % operators are there?
In base R:
%/% and %% perform integer division and modular division respectively, and are described on the ?Arithmetic help page.
%o% gives the outer product of arrays.
%*% performs matrix multiplication.
%x% performs the Kronecker product of arrays.
In ggplot2:
%+% replaces the data frame in a ggplot.
%+replace% modifies theme elements in a ggplot.
%inside% (internal) checks for values in a range.
%||% (internal) provides a default value in case of NULL values. This function also appears internally in devtools, reshape2, roxygen2 and knitr. (In knitr it is called %n%.)
In magrittr:
%>% pipes the left-hand side into an expression on the right-hand side.
%<>% pipes the left-hand side into an expression on the right-hand side, and then assigns the result back into the left-hand side object.
%T>% pipes the left-hand side into an expression on the right-hand side, which it uses only for its side effects, returning the left-hand side.
%,% builds a functional sequence.
%$% exposes columns of a data.frame or members of a list.
In data.table:
%between% checks for values in a range.
%chin% is like %in%, optimised for character vectors.
%like% checks for regular expression matches.
In Hmisc:
%nin% returns the opposite of %in%.
In devtools:
%:::% (internal) gets a variable from a namespace passed as a string.
In sp:
%over% performs a spatial join (e.g., which polygon corresponds to some points?)
In rebus:
%R% concatenates elements of a regex object.
More generally, you can find all the operators in all the packages installed on your machine using:
library(magrittr)
ip <- installed.packages() %>% rownames
(ops <- setNames(ip, ip) %>%
lapply(
function(pkg)
{
rdx_file <- system.file("R", paste0(pkg, ".rdx"), package = pkg)
if(file.exists(rdx_file))
{
rdx <- readRDS(rdx_file)
fn_names <- names(rdx$variables)
fn_names[grepl("^%", fn_names)]
}
}
) %>%
unlist
)
Put quotes around it to find the help page. Either of these work
> help("%in%")
> ?"%in%"
Once you get to the help page, you'll see that
‘%in%’ is currently defined as
‘"%in%" <- function(x, table) match(x, table, nomatch = 0) > 0’
Since time is a generic, I don't know what time(X2) returns without knowing what X2 is. But, %in% tells you which items from the left hand side are also in the right hand side.
> c(1:5) %in% c(3:8)
[1] FALSE FALSE TRUE TRUE TRUE
See also, intersect
> intersect(c(1:5), c(3:8))
[1] 3 4 5
More generally, %foo% is the syntax for a binary operator. Binary operators in R are really just functions in disguise, and take two arguments (the one before and the one after the operator become the first two arguments of the function).
For example:
> `%in%`(1:5,4:6)
[1] FALSE FALSE FALSE TRUE TRUE
While %in% is defined in base R, you can also define your own binary function:
`%hi%` <- function(x,y) cat(x,y,"\n")
> "oh" %hi% "my"
oh my
%in% is an operator used to find and subset multiple occurrences of the same name or value in a matrix or data frame.
For example 1: subsetting with the same name
set.seed(133)
x <- runif(5)
names(x) <- letters[1:5]
x[c("a", "d")]
# a d
# 0.5360112 0.4231022
Now you change the name of "d" to "a"
names(x)[4] <- "a"
If you try to extract the similar names and its values using the previous subscript, it will not work. Notice the result, it does not have the elements of [1] and [4].
x[c("a", "a")]
# a a
# 0.5360112 0.5360112
So, you can extract the two "a"s from different position in a variable by using %in% binary operator.
names(x) %in% "a"
# [1] TRUE FALSE FALSE TRUE FALSE
#assign it to a variable called "vec"
vec <- names(x) %in% "a"
#extract the values of two "a"s
x[vec]
# a a
# 0.5360112 0.4231022
Example 2: Subsetting multiple values from a column
Refer this site for an example
Related
I'm trying to get the output "1*2*4*5" from (function(x) Reduce(paste0(toString("*")),x))(c(1,2,4,5)), but no matter how I manipulate Reduce, paste0, and the asterisks, I'm either getting error messages or the asterisks being treated as multiplication (giving 40). Where am I going wrong?
Reduce uses a function with two arguments to which it applies the previous result and the next element of the vector. Therefore, you need a function of both x and y:
Reduce(function(x,y)paste0(x,"*",y),c(1,2,4,5))
#[1] "1*2*4*5"
As an aside, you can provide an initial value to be applied as x for the first element of the vector with init =.
Reduce(function(x,y)paste0(x,"*",y),c(1,2,4,5), init = 0)
#[1] "0*1*2*4*5"
One thing you may have tried was this:
Reduce(paste0("*"),c(1,2,4,5))
#[1] 40
This applies the multiplication operator to x and y, because paste0("*") evaluates to "*".
Another base R option is to use paste within gsub, e.g.,
x <- 1:5
gsub("\\s","*",Reduce(paste,x))
which gives
> gsub("\\s","*",Reduce(paste,x))
[1] "1*2*3*4*5"
KISS method:
(with improvements as suggested by #nicola)
bar <- as.character(1:5)
paste0(bar,sep="",collapse='*')
#[1] "1*2*3*4*5"
I'm confused why %in% and '==' give different results here:
day_string <- '2017-07-20'
day_date <- as.Date(day_string)
day_string == day_date #TRUE
day_string %in% day_date #FALSE
From %in% help:
%in% is currently defined as "%in%" <- function(x, table) match(x, table, nomatch = 0) > 0
So if I understand things correctly, since match coerces date to character (but first to numeric),
day_string %in% day_date
is translated to
match(day_string, as.character(as.numeric(day_date)), nomatch = 0) > 0
However '==' help says it also coerces different types. What does '==' actually do in the example above and why it behaves differently than %in%?
From the help of ?== "If the two arguments are atomic vectors of different types, one is coerced to the type of the other"
So I guess while == has two same type vectors to compare, %in% is trying to compare a date with a character.
However, this only happens with date Vs character, i.e.
as.character(5) %in% 5
#[1] TRUE
as.factor('abc') %in% 'abc'
#[1] TRUE
5 %in% 5L
#[1] TRUE
In the case of the OP, as #Cath mentions, df_date is first converted to numeric and then to character so the final comparing is,
as.character(as.numeric(day_date))
#[1] "17367"
as.character(as.numeric(day_date)) %in% day_string
#[1] FALSE
Double Checking,
'17367' %in% as.Date(day_string)
#[1] TRUE
The relational operator "==" is (as noted in ?"==") a generic function that has/can have methods defined either directly ("==.class") or through the Ops generic group (Ops.class). Such functions is highly probable that have methods to account for R's base classes like the "Date" class and could work as expected, as is the case with "==" through ?Ops.Date. We can see if the "Date" class is supported by a generic function by methods(class = "Date").
On the other hand, match (and its wrapper "%in%") is not generic and could not necessarily be expected to account for the "class" attribute of its arguments (even for R's own classes). In cases of classes where it does account for is because it was explicitly designed to account for a specific class and such a fact may be documented in the respective help page. This is the case (has not always been), for example, with the "POSIXlt" class (day_string %in% as.POSIXlt(day_date) works as desired). So, "%in%" ignores the class of "day_date" and all it sees is that it's been passed a typeof(day_date) (unclass(day_date)) and a typeof(day_string) where appropriate coercions are made (say, something like as.character.default(day_date)) according to ?match.
I am quite new to R.
Using the table called SE_CSVLinelist_clean, I want to extract the rows where the Variable called where_case_travelled_1 DOES NOT contain the strings "Outside Canada" OR "Outside province/territory of residence but within Canada". Then create a new table called SE_CSVLinelist_filtered.
SE_CSVLinelist_filtered <- filter(SE_CSVLinelist_clean,
where_case_travelled_1 %in% -c('Outside Canada','Outside province/territory of residence but within Canada'))
The code above works when I just use "c" and not "-c".
So, how do I specify the above when I really want to exclude rows that contains that outside of the country or province?
Note that %in% returns a logical vector of TRUE and FALSE. To negate it, you can use ! in front of the logical statement:
SE_CSVLinelist_filtered <- filter(SE_CSVLinelist_clean,
!where_case_travelled_1 %in%
c('Outside Canada','Outside province/territory of residence but within Canada'))
Regarding your original approach with -c(...), - is a unary operator that "performs arithmetic on numeric or complex vectors (or objects which can be coerced to them)" (from help("-")). Since you are dealing with a character vector that cannot be coerced to numeric or complex, you cannot use -.
Try putting the search condition in a bracket, as shown below. This returns the result of the conditional query inside the bracket. Then test its result to determine if it is negative (i.e. it does not belong to any of the options in the vector), by setting it to FALSE.
SE_CSVLinelist_filtered <- filter(SE_CSVLinelist_clean,
(where_case_travelled_1 %in% c('Outside Canada','Outside province/territory of residence but within Canada')) == FALSE)
Just be careful with the previous solutions since they require to type out EXACTLY the string you are trying to detect.
Ask yourself if the word "Outside", for example, is sufficient. If so, then:
data_filtered <- data %>%
filter(!str_detect(where_case_travelled_1, "Outside")
A reprex version:
iris
iris %>%
filter(!str_detect(Species, "versicolor"))
Quick fix. First define the opposite of %in%:
'%ni%' <- Negate("%in%")
Then apply:
SE_CSVLinelist_filtered <- filter(
SE_CSVLinelist_clean,
where_case_travelled_1 %ni% c('Outside Canada',
'Outside province/territory of residence but within Canada'))
How does R interpret parentheses? Like most other programming languages these are built-in operators, and I normally use them without thinking.
However, I came across this example. Let's say we have a data.table in R, and I would like to apply a function on it's columns. Then I might write:
dt <- data.table(my_data)
important_cols <- c("col1", "col2", "col5")
dt[, (important_cols) := lapply(.SD, my_func), .SDcols = important_cols]
Obviously I can't neglect the parentheses:
dt[, important_cols := lapply(.SD, my_func), .SDcols = important_cols]
as that would introduce a new object called important_cols to my data.table, instead of modifying my existing columns in place.
My question is, why does putting ( ) around the vector "expand" it?
This question can probably better phrased and titled. But then I would have probably found the answer by Googling if I knew the terminology to employ while asking it, hence I'm here.
While we're on that topic, if someone could point out the differences between [ ], { }, etc., and how they should be used, that would be appreciated too :)
A special feature of R (compared to e.g. C++) is that the various parentheses are actually functions. What this means is that (a) and a are different expressions. The second is just a, while the first is the function ( called with an argument a. Here are a few expressions trees for you to compare:
as.list(substitute( a ))
#[[1]]
#a
as.list(substitute( (a) ))
#[[1]]
#`(`
#
#[[2]]
#a
as.list(substitute( sqrt(a) ))
#[[1]]
#sqrt
#
#[[2]]
#a
Notice how similar the last trees are - in one the function is sqrt, in the other it's "(". In most places in R, the "(" function doesn't do anything, it just returns the same expression, but in the particular case of data.table, it is "overridden" (in quotes because that's not exactly how it's done, but in spirit it is) to do a variety of useful operations.
And here's one more demo to hopefully cement the point:
`(` = function(x) x*x
2
#[1] 2
(2)
#[1] 4
((2))
#[1] 16
How can one concisely change a numeric R variable (keeping it numeric) so that, e.g.,
"-0.34" becomes simply "-.34"?
Only when you output a numeric value do you have to choose a concrete representation (i.e., how the number should be formatted). You cannot change a numeric variable from "-0.34" to "-.34"; both are representations for the same number.
However, when you output an expression e, you can choose how it should be formatted. I don't know of any build-in way to leave off the leading "0", but you could always just remove it manually:
> sub("^(-?)0.", "\\1.", sprintf("%.2f", -0.34))
[1] "-.34"
You can define a function for convenience, e.g.,
numformat <- function(val) { sub("^(-?)0.", "\\1.", sprintf("%.2f", val)) }
In addition to the existing answers, I wanted to mention that the package weights has a function rd() which can be used to "round numbers to text with no leading zero". Of course, the result is not numeric but character.
library("weights")
rd(-0.341, digits=2)
[1] "-.34"
I needed to show numbers to 3 decimal places.
If you want to print to an arbitrary number of decimal places and you don't want to have to add another package (i.e., the weights package above), then this function (adapted from #stefan's answer) seems to work:
numformat <- function(x, digits = 2) {
ncode <- paste0("%.", digits, "f")
sub("^(-?)0.", "\\1.", sprintf(ncode, x))
}
So for example:
> numformat(-.232, 2)
[1] "-.23"
> numformat(-.232, 3)
[1] "-.232"
> numformat(-.232, 4)
[1] "-.2320"
In addition to #stefan's nice answer, I stumbled upon the following code which accomplishes the same thing but prints out more decimal places:
f = function(X1)gsub("0\\.","\\.", X1)
If it's for reporting in R Markdown I use the package MOTE with the function apa() and code: apa(-0.34, 2, FALSE) this will return -.34 in my documents.