Combine a dfm with another dfm, or numeric, or matrix object, returning a dfm with the combined documents or features, respectively.
# S3 method for dfm cbind(...) # S3 method for dfm rbind(...)
... | dfm, numeric, or matrix objects to be joined column-wise
( |
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cbind(x, y, ...)
combines dfm objects by columns, returning a
dfm object with combined features from input dfm objects. Note that this
should be used with extreme caution, as joining dfms with different
documents will result in a new row with the docname(s) of the first dfm,
merging in those from the second. Furthermore, if features are shared
between the dfms being cbinded, then duplicate feature labels will result.
In both instances, warning messages will result.
rbind(x, y, ...)
combines dfm objects by rows, returning a dfm
object with combined features from input dfm objects. Features are matched
between the two dfm objects, so that the order and names of the features
do not need to match. The order of the features in the resulting dfm
is not guaranteed. The attributes and settings of this new dfm are not
currently preserved.
#> Document-feature matrix of: 2 documents, 6 features (33.3% sparse). #> 2 x 6 sparse Matrix of class "dfmSparse" #> features #> docs a b c d e f #> text1 1 1 1 1 0 0 #> text2 0 0 1 1 1 1#> Document-feature matrix of: 2 documents, 5 features (50% sparse). #> 2 x 5 sparse Matrix of class "dfmSparse" #> features #> docs a b x y z #> text1 1 1 0 0 0 #> text2 0 0 1 1 1cbind(dfm1, dfm2)#> Warning: cbinding dfms with overlapping features will result in duplicated features#> Document-feature matrix of: 2 documents, 11 features (40.9% sparse). #> 2 x 11 sparse Matrix of class "dfmSparse" #> features #> docs a b c d e f a b x y z #> text1 1 1 1 1 0 0 1 1 0 0 0 #> text2 0 0 1 1 1 1 0 0 1 1 1cbind(dfm1, 100)#> Document-feature matrix of: 2 documents, 7 features (28.6% sparse). #> 2 x 7 sparse Matrix of class "dfmSparse" #> features #> docs a b c d e f feat #> text1 1 1 1 1 0 0 100 #> text2 0 0 1 1 1 1 100cbind(100, dfm1)#> Document-feature matrix of: 2 documents, 7 features (28.6% sparse). #> 2 x 7 sparse Matrix of class "dfmSparse" #> features #> docs feat a b c d e f #> text1 100 1 1 1 1 0 0 #> text2 100 0 0 1 1 1 1cbind(dfm1, matrix(c(101, 102), ncol = 1))#> Document-feature matrix of: 2 documents, 7 features (28.6% sparse). #> 2 x 7 sparse Matrix of class "dfmSparse" #> features #> docs a b c d e f feat #> text1 1 1 1 1 0 0 101 #> text2 0 0 1 1 1 1 102cbind(matrix(c(101, 102), ncol = 1), dfm1)#> Document-feature matrix of: 2 documents, 7 features (28.6% sparse). #> 2 x 7 sparse Matrix of class "dfmSparse" #> features #> docs feat a b c d e f #> text1 101 1 1 1 1 0 0 #> text2 102 0 0 1 1 1 1# rbind() for dfm objects (dfm1 <- dfm(c(doc1 = "This is one sample text sample."), verbose = FALSE))#> Document-feature matrix of: 1 document, 6 features (0% sparse). #> 1 x 6 sparse Matrix of class "dfmSparse" #> features #> docs this is one sample text . #> doc1 1 1 1 2 1 1#> Document-feature matrix of: 1 document, 5 features (0% sparse). #> 1 x 5 sparse Matrix of class "dfmSparse" #> features #> docs one two three text . #> doc2 1 1 1 2 1#> Document-feature matrix of: 1 document, 7 features (0% sparse). #> 1 x 7 sparse Matrix of class "dfmSparse" #> features #> docs this is the fourth sample text . #> doc3 1 1 1 1 1 1 1rbind(dfm1, dfm2)#>#> Document-feature matrix of: 2 documents, 8 features (31.2% sparse). #> 2 x 8 sparse Matrix of class "dfmSparse" #> features #> docs one text . this is sample two three #> doc1 1 1 1 1 1 2 0 0 #> doc2 1 2 1 0 0 0 1 1rbind(dfm1, dfm2, dfm3)#>#> Document-feature matrix of: 3 documents, 10 features (40% sparse). #> 3 x 10 sparse Matrix of class "dfmSparse" #> features #> docs text . this is sample one two three the fourth #> doc1 1 1 1 1 2 1 0 0 0 0 #> doc2 2 1 0 0 0 1 1 1 0 0 #> doc3 1 1 1 1 1 0 0 0 1 1