| Type: | Package |
| Title: | Build Your Own Madlibs! |
| Version: | 0.2.0 |
| Maintainer: | Stephanie Kirmer <stephanie@stephaniekirmer.com> |
| Description: | Make your phrase or sentence into something funny! Pass a string with the keywords in, and get out a bit of humor. |
| License: | BSD_3_clause + file LICENSE |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.1.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | data.table, lexicon, stringr (≥ 1.4), utils |
| Suggests: | testthat |
| NeedsCompilation: | no |
| Packaged: | 2020-07-15 16:41:30 UTC; skirmer |
| Author: | Stephanie Kirmer [aut, cre] |
| Repository: | CRAN |
| Date/Publication: | 2020-07-15 16:50:02 UTC |
POSTagger
Description
POSTagger
Usage
POSTagger(wordDF)
Arguments
wordDF |
Dataframe including one column labeled "word" for tagging |
Value
Original dataframe including part of speech columns.
Examples
## Not run: newwords <- data.frame(word = c("cat", "green", "slowly"))
POSTagger(newwords)
## End(Not run)
A list of English words with the "humor ratings" attached.
Description
A dataset compiled by Tomas Englethaler for his research on humor. https://github.com/tomasengelthaler/HumorNorms Please visit his page for more details on the methodology used to score words.
Usage
data(humor_dataset)
Format
A data frame with 4997 rows and 16 variables:
- word
string of the actual word
- mean
mean of humor rating across all audiences
- mean_F
mean of humor rating (women)
- mean_M
mean of humor rating (men)
- mean_old
mean of humor rating (old)
- mean_young
mean of humor rating (young)
- n
audience size
- n_F
audience size (women)
- n_M
audience size (men)
- n_old
audience size (old)
- n_young
audience size (young)
- sd
sd of humor rating across all audiences
- sd_F
sd humor rating (women)
- sd_M
sd of humor rating (men)
- sd_old
sd humor rating (old)
- sd_young
sd of humor rating (young)
Source
https://github.com/tomasengelthaler/HumorNorms
makeRadlibs
Description
makeRadlibs
Usage
makeRadlibs(phrase, wordset = NA)
Arguments
phrase |
String including any number of the words noun, verb, adjective, adverb, plural, or interjection enclosed in curly braces |
wordset |
Data table of your choosing with columns "word" and "pos" at the minimum. Preferably all lowercase. |
Value
New string replacing the keywords with alternatives. Hopefully funny.
Examples
## Not run: makeRadlibs("not sure if i should {verb} or {verb} because it's an {adjective} {noun}")
A list of English proper nouns with the classifications.
Description
A dataset derived from https://www.kaggle.com/vered1986/propernames-categories/version/1. The words are British focused, and I have adjusted some classifications to be easier for users to work with.
Usage
data(proper_nouns)
Format
A data frame with 747 rows and 2 variables:
- word
string of the actual word
- pos
part of speech (aka celebrity, place, etc)
Source
https://www.kaggle.com/vered1986/propernames-categories/version/1