Introduction to R String Functions
R language or R String Functions is majorly implied for graphical representation of the data, statistical analysis on the data, and reporting. it is an open-source language. the naming convention of this language was derived from the first letters of the founders of this language they are Ross Ihaka and Robert Gentleman. It is an interpreted programming language. It has the ability to integrate with various other language procedures namely C++, Python, etc. Currently, R stands to be the world’s most largely used programming language.
Features of R String Functions
The key features of R language are as below,
- A finely developed and very simple statistical language.
- Storage and data handling are very efficiently embedded in R.
- It offers a large set of classified tools which helps in data analysis
- R also offers libraries to attain graphical representations of the data
R String Functions Manipulation
Below given is the list of R string manipulation functions.
1. Grep() in R String Functions
Used to match a pattern in the data and replace the pattern with a different string. The grep function can be expressed in multiple ways in R language’s are regexpr, gregexpr grep, grepl, and regexec.
Ex : grep( pattern, x, ignore. Case = FALSE, perl = FALSE, value = FALSE, fixed = FALSE, use Bytes = FALSE, invert = FALSE)
Arguments:
- Pattern – Character string holding a usual expression that is supposed to equal the given character vector.
- X, Text – An object which can be limited as a character to a character vector.
- Ignore. Case – (False – Pattern matching works case insensitive, True – Pattern matching works case sensitive)
- Perl – To determine Perl-compatible expressions especially regexprns be used.
- Value – If a match found returns true else false,
- Use Bytes – If TRUE after that the matching will be done byte-by-byte instead of character-by-character.
- Invert – Returns indices if True,
- Replacement – The replacement string,
2. Nchar()
Used to count the number of characters in a vector. Takes a vector in string format as an argument and returns another numeric vector that holds the count of the string.
Ex : nchar( x, type = “chars”, allowNA = FALSE, keepNA = NA)
4.5 (9,568 ratings)
View Course
Arguments:
- X – Vector string.
- Type – Type, of the character string, used the three common ones mentioned are (“bytes”, “chars”, “width”).
- AllowNA – Represents whether the ‘Not applicable’ can be returned as output.
- KeepNA – Should ‘Not applicable’ be returned when X is not found.
3. Substr()
Used to pick the substring value of the character vector.
Ex : substr(x, start, stop)
Arguments:
- X, text – The vector charterer string.
- Start, First – integer. Start of the element which is expected to be replaced
- Stop, Last – integer. here replacement is done at the end of the string
4. strsplit() in R String Functions
Used to split an existing vector string into multiple substrings according to the substring matches found within them
Ex : strsplit(x, split, fixed = FALSE, perl = FALSE, useBytes = FALSE)
Arguments:
- X – Character vector which is going to be spited.
- Split – Character vector which acts as the separator.
- Fixed – Makes an equal split when it is passed as true
- Perl – Should Perl-compatible regexps be used?
- UseBytes – When passed as true it triggers byte by byte matching instead of character by character matching
5. Regexpr()
More than grep the regexpr gives the index where a valid match starts and matching string length when no match is found -1 value is returned.
Ex : regexpr(pattern, text, ignore.case=FALSE, perl=FALSE, fixed=FALSE, useBytes=FALSE)
Arguments:
- Pattern – Character string holding a usual expression that is supposed to equal the given character vector.
- X – Character Vector
- Ignore.case – (False – Pattern matching works case insensitive, True – Patter matching works case sensitive)
- Perl – To determine Perl-compatible expressions especially regexprns be used
- Value – If a match found returns true else false
- UseBytes – If TRUE after that the matching will be done byte-by-byte instead of character-by-character.
- Invert – Returns indices if True
6. Gregexpr() in R String Functions
The gregexpr provide returns a list of a similar length as a text every element of which is of a similar form as the return value for regexpr, except that the preliminary positions of every (disjoint) match are given.
Syntax: gregexpr(pattern, text, ignore.case=FALSE, perl=FALSE, fixed=FALSE, useBytes=FALSE, extract=FALSE)
Arguments:
- Pattern – Character string holding a usual expression that be supposed to equal the given character vector.
- X – Character Vector
- Ignore.case – (False – Pattern matching works case insensitive, True – Pattern matching works case sensitive)
- Perl – To determine Perl-compatible expressions especially regexprns be used
- Value – If a match found returns true else false
- UseBytes – If TRUE after that the matching will be done byte-by-byte instead of character-by-character.
- Invert – Returns indices if True
- Extract – When a logical indication is matched then an extract of the substring is made and returned
7. Regexec()
The regexec() in R String Functions is very similar to regexpr() except here the indices parenthesized the corresponding sub-expressions is returned
Syntax : regexec(pattern, text, ignore.case=FALSE, perl=FALSE, fixed=FALSE, useBytes=FALSE)
Arguments:
- Pattern – Character string holding a usual expression that can be supposed to equal the given character vector.
- X – Character Vector
- Ignore.case – (False – Pattern matching works case insensitive, True – Patter matching works case sensitive)
- Perl – To determine Perl compatible expressions especially regexprns be used
- Value – If a match found returns true else false
- UseBytes – If TRUE after that the matching will be done byte-by-byte instead of character-by-character.
- Invert – Returns indices if True
Recommended Articles
This has been a guide to R String Functions. Here we discussed the basic concept, Features, Manipulation of R String Functions with Example and Arguments. You can also go through our other Suggested Articles to learn more –
