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https://github.com/wlandau/wildcard
Templating for data frames.
https://github.com/wlandau/wildcard
Last synced: 16 days ago
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Templating for data frames.
- Host: GitHub
- URL: https://github.com/wlandau/wildcard
- Owner: wlandau
- Created: 2017-05-21T13:17:41.000Z (over 7 years ago)
- Default Branch: main
- Last Pushed: 2020-10-27T16:32:29.000Z (about 4 years ago)
- Last Synced: 2023-11-20T10:22:18.160Z (12 months ago)
- Language: R
- Homepage:
- Size: 464 KB
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 8
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
Awesome Lists containing this project
README
[](https://travis-ci.org/wlandau/wildcard)
[](https://codecov.io/github/wlandau/wildcard?branch=master)
[](http://cran.r-project.org/package=wildcard)
# wildcard
The wildcard package is a templating mechanism for data frames in R. Wildcards are placeholders for text, and you can evaluate them to generate new data frames from templates.
```r
library(wildcard)
myths <- data.frame(
myth = c("Bigfoot", "UFO", "Loch Ness Monster"),
claim = c("various", "day", "day"),
note = c("various", "pictures", "reported day"))
myths
## myth claim note
## 1 Bigfoot various various
## 2 UFO day pictures
## 3 Loch Ness Monster day reported day
wildcard(myths, wildcard = "day", values = c("today", "yesterday"))
## myth claim note
## 1 Bigfoot various various
## 2 UFO today pictures
## 3 UFO yesterday pictures
## 4 Loch Ness Monster today reported today
## 5 Loch Ness Monster yesterday reported yesterday
```
# Installation
First, ensure that [R](https://www.r-project.org/) is installed. To install the [latest CRAN release](https://CRAN.R-project.org/package=wildcard), run
```r
install.packages("wildcard")
```
To install the development version, get the [devtools](https://CRAN.R-project.org/package=devtools) package and then run
```r
devtools::install_github("wlandau/wildcard", build = TRUE)
```
If you specify a tag, you can install a GitHub release.
```r
devtools::install_github("wlandau/[email protected]", build = TRUE)
```
# Tutorial
See the package vignette.
```r
vignette(package = "wildcard")
vignette("wildcard")
```
# Troubleshooting
You can submit questions, bug reports, and feature requests to the [issue tracker](https://github.com/wlandau/wildcard/issues). Please take care to search for duplicates first, even among the closed issues.
# Usage
Try out the following or see the [CRAN vignette](https://cran.r-project.org/web/packages/wildcard/vignettes/wildcard.html) for the output.
## `wildcard()`
```r
library(wildcard)
myths <- data.frame(
myth = c("Bigfoot", "UFO", "Loch Ness Monster"),
claim = c("various", "day", "day"),
note = c("various", "pictures", "reported day"))
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()`
```r
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()`
```r
class(iris$Species)
str(iris)
out <- nofactors(iris)
class(out$Species)
str(out)
```
# A cautionary note
Be sure that wildcards and are not also replacement values.
```r
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`.
```