Compute entropies of documents or features

textstat_entropy(x, margin = c("documents", "features"), base = 2)

Arguments

x	a `dfm`
margin	character indicating for which margin to compute entropy
base	base for logarithm function

Value

a data.frame of entropies for the given document or feature

Examples

textstat_entropy(data_dfm_lbgexample)
#>   document  entropy
#> 1       R1 3.386943
#> 2       R2 3.386943
#> 3       R3 3.386943
#> 4       R4 3.386943
#> 5       R5 3.386943
#> 6       V1 3.386943
textstat_entropy(data_dfm_lbgexample, "features")
#>    feature   entropy
#> 1        A 0.0000000
#> 2        B 0.0000000
#> 3        C 0.0000000
#> 4        D 0.0000000
#> 5        E 0.0000000
#> 6        F 0.1686609
#> 7        G 0.1708952
#> 8        H 0.4371120
#> 9        I 0.6476138
#> 10       J 1.0338027
#> 11       K 1.4131631
#> 12       L 1.5669101
#> 13       M 1.5996467
#> 14       N 1.5656144
#> 15       O 1.5806321
#> 16       P 1.6267307
#> 17       Q 1.6414915
#> 18       R 1.6034693
#> 19       S 1.5561626
#> 20       T 1.5311306
#> 21       U 1.4979274
#> 22       V 1.3664642
#> 23       W 1.1291805
#> 24       X 1.0439334
#> 25       Y 1.0338027
#> 26       Z 1.0726302
#> 27      ZA 1.0458291
#> 28      ZB 0.7876499
#> 29      ZC 0.5357150
#> 30      ZD 0.3435197
#> 31      ZE 0.1708952
#> 32      ZF 0.1686609
#> 33      ZG 0.0000000
#> 34      ZH 0.0000000
#> 35      ZI 0.0000000
#> 36      ZJ 0.0000000
#> 37      ZK 0.0000000