The wildcard package is a templating mechanism for data frames. Wildcards are placeholders for text, and you can evaluate them to generate new data frames from templates. The functionality is straightforward.
wildcard()
library(wildcard) myths <- data.frame( myth = c("Bigfoot", "UFO", "Loch Ness Monster"), claim = c("various", "day", "day"), note = c("various", "pictures", "reported day")) myths wildcard(myths, wildcard = "day", values = c("today", "yesterday")) wildcard(myths, wildcard = "day", values = c("today", "yesterday"), expand = FALSE) wildcard(myths, wildcard = "day", values = c("today", "yesterday"), include = "claim") wildcard(myths, wildcard = "day", values = c("today", "yesterday"), exclude = c("claim", "note")) locations <- data.frame( myth = c("Bigfoot", "UFO", "Loch Ness Monster"), origin = "where") rules <- list( where = c("North America", "various", "Scotland"), UFO = c("spaceship", "saucer")) wildcard(locations, rules = rules, expand = c(FALSE, TRUE)) numbers <- data.frame(x = 4, y = 3, z = 4444, w = 4.434) wildcard(numbers, wildcard = 4, values = 7)
expandrows()
df <- data.frame( ID = c("24601", "Javert", "Fantine"), fate = c("fulfillment", "confusion", "misfortune")) expandrows(df, n = 2, type = "each") expandrows(df, n = 2, type = "times")
nofactors()
class(iris$Species) str(iris) out <- nofactors(iris) class(out$Species) str(out)
You can submit questions, bug reports, and feature requests to the issue tracker. Please take care to search for duplicates first, even among the closed issues.
Be sure that wildcards and are not also replacement values.
df <- data.frame(x = "a", y = "b") rules <- list(a = letters[1:3], b = LETTERS[1:3]) wildcard(df, rules = rules)
## x y ## 1 a A ## 2 a B ## 3 a C ## 4 A A ## 5 B B ## 6 C C ## 7 c A ## 8 c B ## c C ## Warning message: ## In check_rules(rules) : ## In `rules`, some wildcards are also replacement values. ## The returned data frame may be different than you expect, ## and it may depend on the order of the wildcards in `rules`.
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