Get the features from a document-feature matrix, which are stored as the column names of the dfm object.

featnames(x)

Arguments

x

the dfm whose features will be extracted

Value

character vector of the feature labels

Examples

dfmat <- dfm(data_corpus_inaugural)
#> Warning: 'dfm.corpus()' is deprecated. Use 'tokens()' first.

# first 50 features (in original text order)
head(featnames(dfmat), 50)
#>  [1] "fellow-citizens" "of"              "the"             "senate"         
#>  [5] "and"             "house"           "representatives" ":"              
#>  [9] "among"           "vicissitudes"    "incident"        "to"             
#> [13] "life"            "no"              "event"           "could"          
#> [17] "have"            "filled"          "me"              "with"           
#> [21] "greater"         "anxieties"       "than"            "that"           
#> [25] "which"           "notification"    "was"             "transmitted"    
#> [29] "by"              "your"            "order"           ","              
#> [33] "received"        "on"              "14th"            "day"            
#> [37] "present"         "month"           "."               "one"            
#> [41] "hand"            "i"               "summoned"        "my"             
#> [45] "country"         "whose"           "voice"           "can"            
#> [49] "never"           "hear"           

# first 50 features alphabetically
head(sort(featnames(dfmat)), 50)
#>  [1] "-"           ","           ";"           ":"           "!"          
#>  [6] "?"           "."           "…"           "'"           "\""         
#> [11] "("           ")"           "["           "]"           "/"          
#> [16] "\\"          "$"           "1"           "1,000"       "100"        
#> [21] "100,000,000" "108"         "11"          "120,000,000" "125"        
#> [26] "13"          "14th"        "15th"        "16"          "1774"       
#> [31] "1776"        "1778"        "1780"        "1787"        "1789"       
#> [36] "1790"        "1800"        "1801"        "1812"        "1815"       
#> [41] "1816"        "1817"        "1818"        "1826"        "1850"       
#> [46] "1861"        "1863"        "1868"        "1873"        "1880"       

# contrast with descending total frequency order from topfeatures()
names(topfeatures(dfmat, 50))
#>  [1] "the"        "of"         ","          "and"        "."         
#>  [6] "to"         "in"         "a"          "our"        "we"        
#> [11] "that"       "be"         "is"         "it"         "for"       
#> [16] "by"         "have"       "which"      "not"        "with"      
#> [21] "as"         "will"       "this"       "i"          "all"       
#> [26] "are"        "their"      "but"        "has"        "people"    
#> [31] "from"       "its"        ";"          "government" "or"        
#> [36] "on"         "my"         "us"         "been"       "can"       
#> [41] "no"         "they"       "-"          "so"         "an"        
#> [46] "who"        "must"       "upon"       "at"         "great"