Spot patterns in strings

Source: R/string_spots.R

Spot patterns in strings.

string_spot(s, pattern, value = TRUE, ...)
string_spoti(s, pattern, ...)
string_spotl(s, pattern, ...)
string_spotm(s, pattern, invert = FALSE, ...)
string_replace(s, search, replace, ...)
string_remove(s, remove, ...)
string_countm(s, pattern, ...)
string_locate(s, pattern, invert = FALSE, ...)

Arguments

s

A string (character) vector.
pattern

A regular expression pattern.
value

Boolean value (TRUE/FALSE) for whether to return the actual values (the former) or the indices (the latter).
...

Parameters to pass to grep(), grepl(), gsub(), or gregexpr().
invert

Boolean value (TRUE/FALSE) for whether to find actual matches (FALSE; default) or non-matches (TRUE).
search

A pattern to search.
replace

The string to replace the searched pattern.
remove

The string to remove.

Value

Character vector for all functions except the string_spotl(), string_spoti(), and string_countm() functions, which produce Boolean, numeric, and numeric vectors respectively.

Details

The function string_spot() subsets a vector to the values matching a given pattern. Optional inputs get passed to grep(). Synonyms are s_spot() and spot().

The function string_spoti() subsets a vector to the indices matching a given pattern. Optional inputs get passed to grep(). Synonyms are s_spoti() and spoti().

The function string_spotl() detects whether a pattern exists in a vector, outputting a Boolean value (TRUE/FALSE). Optional inputs get passed to grepl(). Synonyms are s_spotl() and spotl().

The string_spotm() function spots pattern matches and returns NA if none are found. Optional inputs get passed to grepl(). Synonyms are s_spotm() and spotm().

The string_replace() function acts the same as gsub() with the inputs ordered differently. Optional inputs get passed to gsub(). Synonyms are s_replace(), search_replace(), sr(), find_replace(), and fr().

The string_remove() function blanks out a matching pattern. Optional inputs get passed to gsub(). Synonym is s_remove().

The string_countm() function counts the number of matches in a string. Optional inputs get passed to gregexpr(). Synonyms are s_countm() and countm().

The string_locate() functions produces the character positions at where the pattern match are found--non-matches are produced if invert = TRUE. Optional inputs are passed to gregexpr(). Synonyms are s_locate() and locate().

See also

https://github.com/robertschnitman/stringops

Examples

rn <- rownames(mtcars)

string_spot(rn, "^M")
#>  [1] "Mazda RX4"     "Mazda RX4 Wag" "Merc 240D"     "Merc 230"     
#>  [5] "Merc 280"      "Merc 280C"     "Merc 450SE"    "Merc 450SL"   
#>  [9] "Merc 450SLC"   "Maserati Bora"
string_spot(rn, '^M', invert = TRUE)
#>  [1] "Datsun 710"          "Hornet 4 Drive"      "Hornet Sportabout"  
#>  [4] "Valiant"             "Duster 360"          "Cadillac Fleetwood" 
#>  [7] "Lincoln Continental" "Chrysler Imperial"   "Fiat 128"           
#> [10] "Honda Civic"         "Toyota Corolla"      "Toyota Corona"      
#> [13] "Dodge Challenger"    "AMC Javelin"         "Camaro Z28"         
#> [16] "Pontiac Firebird"    "Fiat X1-9"           "Porsche 914-2"      
#> [19] "Lotus Europa"        "Ford Pantera L"      "Ferrari Dino"       
#> [22] "Volvo 142E"         
string_spoti(rn, "^M")
#>  [1]  1  2  8  9 10 11 12 13 14 31
string_spotl(rn, "^M")
#>  [1]  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE
#> [13]  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#> [25] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE
string_spotm(rn, "^M")
#>  [1] "Mazda RX4"     "Mazda RX4 Wag" NA              NA             
#>  [5] NA              NA              NA              "Merc 240D"    
#>  [9] "Merc 230"      "Merc 280"      "Merc 280C"     "Merc 450SE"   
#> [13] "Merc 450SL"    "Merc 450SLC"   NA              NA             
#> [17] NA              NA              NA              NA             
#> [21] NA              NA              NA              NA             
#> [25] NA              NA              NA              NA             
#> [29] NA              NA              "Maserati Bora" NA             

string_replace(rn, "^M", "Z")
#>  [1] "Zazda RX4"           "Zazda RX4 Wag"       "Datsun 710"         
#>  [4] "Hornet 4 Drive"      "Hornet Sportabout"   "Valiant"            
#>  [7] "Duster 360"          "Zerc 240D"           "Zerc 230"           
#> [10] "Zerc 280"            "Zerc 280C"           "Zerc 450SE"         
#> [13] "Zerc 450SL"          "Zerc 450SLC"         "Cadillac Fleetwood" 
#> [16] "Lincoln Continental" "Chrysler Imperial"   "Fiat 128"           
#> [19] "Honda Civic"         "Toyota Corolla"      "Toyota Corona"      
#> [22] "Dodge Challenger"    "AMC Javelin"         "Camaro Z28"         
#> [25] "Pontiac Firebird"    "Fiat X1-9"           "Porsche 914-2"      
#> [28] "Lotus Europa"        "Ford Pantera L"      "Ferrari Dino"       
#> [31] "Zaserati Bora"       "Volvo 142E"         
string_remove(rn, "^M")
#>  [1] "azda RX4"            "azda RX4 Wag"        "Datsun 710"         
#>  [4] "Hornet 4 Drive"      "Hornet Sportabout"   "Valiant"            
#>  [7] "Duster 360"          "erc 240D"            "erc 230"            
#> [10] "erc 280"             "erc 280C"            "erc 450SE"          
#> [13] "erc 450SL"           "erc 450SLC"          "Cadillac Fleetwood" 
#> [16] "Lincoln Continental" "Chrysler Imperial"   "Fiat 128"           
#> [19] "Honda Civic"         "Toyota Corolla"      "Toyota Corona"      
#> [22] "Dodge Challenger"    "AMC Javelin"         "Camaro Z28"         
#> [25] "Pontiac Firebird"    "Fiat X1-9"           "Porsche 914-2"      
#> [28] "Lotus Europa"        "Ford Pantera L"      "Ferrari Dino"       
#> [31] "aserati Bora"        "Volvo 142E"         
string_countm(rn, 'a')
#>  [1] 2 3 1 0 1 2 0 0 0 0 0 0 0 0 2 1 1 1 1 2 2 1 1 2 1 1 0 1 2 1 3 0

string_locate(rn, 'a')
#> [[1]]
#> [1] 2 5
#> 
#> [[2]]
#> [1]  2  5 12
#> 
#> [[3]]
#> [1] 2
#> 
#> [[4]]
#> [1] NA
#> 
#> [[5]]
#> [1] 13
#> 
#> [[6]]
#> [1] 2 5
#> 
#> [[7]]
#> [1] NA
#> 
#> [[8]]
#> [1] NA
#> 
#> [[9]]
#> [1] NA
#> 
#> [[10]]
#> [1] NA
#> 
#> [[11]]
#> [1] NA
#> 
#> [[12]]
#> [1] NA
#> 
#> [[13]]
#> [1] NA
#> 
#> [[14]]
#> [1] NA
#> 
#> [[15]]
#> [1] 2 7
#> 
#> [[16]]
#> [1] 18
#> 
#> [[17]]
#> [1] 16
#> 
#> [[18]]
#> [1] 3
#> 
#> [[19]]
#> [1] 5
#> 
#> [[20]]
#> [1]  6 14
#> 
#> [[21]]
#> [1]  6 13
#> 
#> [[22]]
#> [1] 9
#> 
#> [[23]]
#> [1] 6
#> 
#> [[24]]
#> [1] 2 4
#> 
#> [[25]]
#> [1] 6
#> 
#> [[26]]
#> [1] 3
#> 
#> [[27]]
#> [1] NA
#> 
#> [[28]]
#> [1] 12
#> 
#> [[29]]
#> [1]  7 12
#> 
#> [[30]]
#> [1] 5
#> 
#> [[31]]
#> [1]  2  6 13
#> 
#> [[32]]
#> [1] NA
#> 
string_locate(rn, 'a', invert = TRUE)
#> [[1]]
#> [1] 1 3 4 6 7 8 9
#> 
#> [[2]]
#>  [1]  1  3  4  6  7  8  9 10 11 13
#> 
#> [[3]]
#> [1]  1  3  4  5  6  7  8  9 10
#> 
#> [[4]]
#>  [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14
#> 
#> [[5]]
#>  [1]  1  2  3  4  5  6  7  8  9 10 11 12 14 15 16 17
#> 
#> [[6]]
#> [1] 1 3 4 6 7
#> 
#> [[7]]
#>  [1]  1  2  3  4  5  6  7  8  9 10
#> 
#> [[8]]
#> [1] 1 2 3 4 5 6 7 8 9
#> 
#> [[9]]
#> [1] 1 2 3 4 5 6 7 8
#> 
#> [[10]]
#> [1] 1 2 3 4 5 6 7 8
#> 
#> [[11]]
#> [1] 1 2 3 4 5 6 7 8 9
#> 
#> [[12]]
#>  [1]  1  2  3  4  5  6  7  8  9 10
#> 
#> [[13]]
#>  [1]  1  2  3  4  5  6  7  8  9 10
#> 
#> [[14]]
#>  [1]  1  2  3  4  5  6  7  8  9 10 11
#> 
#> [[15]]
#>  [1]  1  3  4  5  6  8  9 10 11 12 13 14 15 16 17 18
#> 
#> [[16]]
#>  [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 19
#> 
#> [[17]]
#>  [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 17
#> 
#> [[18]]
#> [1] 1 2 4 5 6 7 8
#> 
#> [[19]]
#>  [1]  1  2  3  4  6  7  8  9 10 11
#> 
#> [[20]]
#>  [1]  1  2  3  4  5  7  8  9 10 11 12 13
#> 
#> [[21]]
#>  [1]  1  2  3  4  5  7  8  9 10 11 12
#> 
#> [[22]]
#>  [1]  1  2  3  4  5  6  7  8 10 11 12 13 14 15 16
#> 
#> [[23]]
#>  [1]  1  2  3  4  5  7  8  9 10 11
#> 
#> [[24]]
#> [1]  1  3  5  6  7  8  9 10
#> 
#> [[25]]
#>  [1]  1  2  3  4  5  7  8  9 10 11 12 13 14 15 16
#> 
#> [[26]]
#> [1] 1 2 4 5 6 7 8 9
#> 
#> [[27]]
#>  [1]  1  2  3  4  5  6  7  8  9 10 11 12 13
#> 
#> [[28]]
#>  [1]  1  2  3  4  5  6  7  8  9 10 11
#> 
#> [[29]]
#>  [1]  1  2  3  4  5  6  8  9 10 11 13 14
#> 
#> [[30]]
#>  [1]  1  2  3  4  6  7  8  9 10 11 12
#> 
#> [[31]]
#>  [1]  1  3  4  5  7  8  9 10 11 12
#> 
#> [[32]]
#>  [1]  1  2  3  4  5  6  7  8  9 10
#>