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prepare CRAN release, minor improvements
* If `model.term` does not exist in models, `spread_coef()` now prints the name of non-existing coefficients. * `find_var()` gets a `fuzzy`-argument to enable fuzzy-matching for search pattern. * Argument `part.dist.match` in `str_pos()` caused an error when being larger than 0.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,157 +1,181 @@ | ||
| #' @title Find variable by name or label | ||
| #' @name find_var | ||
| #' | ||
| #' @description This functions finds variables in a data frame, which variable | ||
| #' names or variable (and value) label attribute match a specific | ||
| #' pattern. Regular expression for the pattern is supported. | ||
| #' | ||
| #' @param data A data frame. | ||
| #' @param pattern Character string to be matched in \code{data}. May also be a | ||
| #' character vector of length > 1 (see 'Examples'). \code{pattern} is | ||
| #' searched for in column names and variable label attributes of | ||
| #' \code{data} (see \code{\link{get_label}}). \code{pattern} might also | ||
| #' be a regular-expression object, as returned by \code{\link[stringr]{regex}}, | ||
| #' or any of \pkg{stringr}'s supported \code{\link[stringr]{modifiers}}. | ||
| #' @param ignore.case Logical, whether matching should be case sensitive or not. | ||
| #' @param search Character string, indicating where \code{pattern} is sought. | ||
| #' Use one of following options: | ||
| #' \describe{ | ||
| #' \item{\code{"name_label"}}{The default, searches for \code{pattern} in | ||
| #' variable names and variable labels.} | ||
| #' \item{\code{"name_value"}}{Searches for \code{pattern} in | ||
| #' variable names and value labels.} | ||
| #' \item{\code{"label_value"}}{Searches for \code{pattern} in | ||
| #' variable and value labels.} | ||
| #' \item{\code{"name"}}{Searches for \code{pattern} in | ||
| #' variable names.} | ||
| #' \item{\code{"label"}}{Searches for \code{pattern} in | ||
| #' variable labels} | ||
| #' \item{\code{"value"}}{Searches for \code{pattern} in | ||
| #' value labels.} | ||
| #' \item{\code{"all"}}{Searches for \code{pattern} in | ||
| #' variable names, variable and value labels.} | ||
| #' } | ||
| #' @param as.df Logical, if \code{TRUE}, a data frame with matching variables | ||
| #' is returned (instead of their column indices). | ||
| #' @param as.varlab Logical, if \code{TRUE}, not only column indices, but also | ||
| #' variables labels of matching variables are returned (as | ||
| #' data frame). | ||
| #' | ||
| #' @return A named vector with column indices of found variables (variable names | ||
| #' are used as names-attribute); if \code{as.df = TRUE}, a tibble | ||
| #' with found variables; or, if \code{as.varlab = TRUE}, a tibble | ||
| #' with three columns: column number, variable name and variable label. | ||
| #' | ||
| #' @details This function searches for \code{pattern} in \code{data}'s column names | ||
| #' and - for labelled data - in all variable and value labels of \code{data}'s | ||
| #' variables (see \code{\link{get_label}} for details on variable labels and | ||
| #' labelled data). Search is performed using the | ||
| #' \code{\link[stringr]{str_detect}} functions; hence, regular | ||
| #' expressions are supported as well, by simply using | ||
| #' \code{pattern = stringr::regex(...)}. | ||
| #' | ||
| #' @examples | ||
| #' data(efc) | ||
| #' | ||
| #' # find variables with "cop" in variable name | ||
| #' find_var(efc, "cop") | ||
| #' | ||
| #' # return tibble with matching variables | ||
| #' find_var(efc, "cop", as.df = TRUE) | ||
| #' | ||
| #' # or return "summary"-tibble with matching variables | ||
| #' # and their variable labels | ||
| #' find_var(efc, "cop", as.varlab = TRUE) | ||
| #' | ||
| #' # find variables with "dependency" in names and variable labels | ||
| #' find_var(efc, "dependency") | ||
| #' get_label(efc$e42dep) | ||
| #' | ||
| #' # find variables with "level" in names and value labels | ||
| #' res <- find_var(efc, "level", search = "name_value", as.df = TRUE) | ||
| #' res | ||
| #' get_labels(res, attr.only = FALSE) | ||
| #' | ||
| #' # use sjPlot::view_df() to view results | ||
| #' \dontrun{ | ||
| #' library(sjPlot) | ||
| #' view_df(res)} | ||
| #' | ||
| #' @importFrom stringr regex coll | ||
| #' @importFrom tibble as_tibble | ||
| #' @export | ||
| find_var <- function(data, | ||
| pattern, | ||
| ignore.case = TRUE, | ||
| search = c("name_label", "name_value", "label_value", "name", "label", "value", "all"), | ||
| as.df = FALSE, | ||
| as.varlab = FALSE) { | ||
| # check valid args | ||
| if (!is.data.frame(data)) { | ||
| stop("`data` must be a data frame.", call. = F) | ||
| } | ||
|
|
||
| # match args | ||
| search <- match.arg(search) | ||
|
|
||
| pos1 <- pos2 <- pos3 <- c() | ||
|
|
||
| # search for pattern in variable names | ||
| if (search %in% c("name", "name_label", "name_value", "all")) { | ||
| # check variable names | ||
| if (inherits(pattern, "regex")) | ||
| pos1 <- which(stringr::str_detect(colnames(data), pattern)) | ||
| else | ||
| pos1 <- which(stringr::str_detect(colnames(data), stringr::coll(pattern, ignore_case = ignore.case))) | ||
| } | ||
|
|
||
|
|
||
| # search for pattern in variable labels | ||
| if (search %in% c("label", "name_label", "label_value", "all")) { | ||
| # get labels and variable names | ||
| labels <- get_label(data) | ||
|
|
||
| # check labels | ||
| if (inherits(pattern, "regex")) | ||
| pos2 <- which(stringr::str_detect(labels, pattern)) | ||
| else | ||
| pos2 <- which(stringr::str_detect(labels, stringr::coll(pattern, ignore_case = ignore.case))) | ||
| } | ||
|
|
||
| # search for pattern in value labels | ||
| if (search %in% c("value", "name_value", "label_value", "all")) { | ||
| labels <- get_labels(data, attr.only = F) | ||
|
|
||
| # check value labels with regex | ||
| if (inherits(pattern, "regex")) { | ||
| pos3 <- which(unlist(lapply(labels, function(x) { | ||
| any(stringr::str_detect(x, pattern)) | ||
| }))) | ||
| } else { | ||
| pos3 <- which(unlist(lapply(labels, function(x) { | ||
| any(stringr::str_detect(x, stringr::coll(pattern, ignore_case = ignore.case))) | ||
| }))) | ||
| } | ||
| } | ||
|
|
||
| # get unqiue variable indices | ||
| pos <- unique(c(pos1, pos2, pos3)) | ||
|
|
||
| # return data frame? | ||
| if (as.df) { | ||
| return(tibble::as_tibble(data[, pos])) | ||
| } | ||
|
|
||
| # return variable labels? | ||
| if (as.varlab) { | ||
| return(tibble::tibble( | ||
| col.nr = pos, | ||
| var.name = colnames(data)[pos], | ||
| var.label = get_label(data[, pos], def.value = colnames(data)[pos]) | ||
| )) | ||
| } | ||
|
|
||
| # use column names | ||
| names(pos) <- colnames(data)[pos] | ||
| pos | ||
| } | ||
| #' @title Find variable by name or label | ||
| #' @name find_var | ||
| #' | ||
| #' @description This functions finds variables in a data frame, which variable | ||
| #' names or variable (and value) label attribute match a specific | ||
| #' pattern. Regular expression for the pattern is supported. | ||
| #' | ||
| #' @param data A data frame. | ||
| #' @param pattern Character string to be matched in \code{data}. May also be a | ||
| #' character vector of length > 1 (see 'Examples'). \code{pattern} is | ||
| #' searched for in column names and variable label attributes of | ||
| #' \code{data} (see \code{\link{get_label}}). \code{pattern} might also | ||
| #' be a regular-expression object, as returned by \code{\link[stringr]{regex}}, | ||
| #' or any of \pkg{stringr}'s supported \code{\link[stringr]{modifiers}}. | ||
| #' @param ignore.case Logical, whether matching should be case sensitive or not. | ||
| #' @param search Character string, indicating where \code{pattern} is sought. | ||
| #' Use one of following options: | ||
| #' \describe{ | ||
| #' \item{\code{"name_label"}}{The default, searches for \code{pattern} in | ||
| #' variable names and variable labels.} | ||
| #' \item{\code{"name_value"}}{Searches for \code{pattern} in | ||
| #' variable names and value labels.} | ||
| #' \item{\code{"label_value"}}{Searches for \code{pattern} in | ||
| #' variable and value labels.} | ||
| #' \item{\code{"name"}}{Searches for \code{pattern} in | ||
| #' variable names.} | ||
| #' \item{\code{"label"}}{Searches for \code{pattern} in | ||
| #' variable labels} | ||
| #' \item{\code{"value"}}{Searches for \code{pattern} in | ||
| #' value labels.} | ||
| #' \item{\code{"all"}}{Searches for \code{pattern} in | ||
| #' variable names, variable and value labels.} | ||
| #' } | ||
| #' @param as.df Logical, if \code{TRUE}, a data frame with matching variables | ||
| #' is returned (instead of their column indices). | ||
| #' @param as.varlab Logical, if \code{TRUE}, not only column indices, but also | ||
| #' variables labels of matching variables are returned (as | ||
| #' data frame). | ||
| #' @param fuzzy Logical, if \code{TRUE}, "fuzzy matching" (partial and | ||
| #' close distance matching) will be used to find \code{pattern} | ||
| #' in \code{data} if no exact match was found. \code{\link{str_pos}} | ||
| #' is used for fuzzy matching. | ||
| #' | ||
| #' @return A named vector with column indices of found variables (variable names | ||
| #' are used as names-attribute); if \code{as.df = TRUE}, a tibble | ||
| #' with found variables; or, if \code{as.varlab = TRUE}, a tibble | ||
| #' with three columns: column number, variable name and variable label. | ||
| #' | ||
| #' @details This function searches for \code{pattern} in \code{data}'s column names | ||
| #' and - for labelled data - in all variable and value labels of \code{data}'s | ||
| #' variables (see \code{\link{get_label}} for details on variable labels and | ||
| #' labelled data). Search is performed using the | ||
| #' \code{\link[stringr]{str_detect}} functions; hence, regular | ||
| #' expressions are supported as well, by simply using | ||
| #' \code{pattern = stringr::regex(...)}. | ||
| #' | ||
| #' @examples | ||
| #' data(efc) | ||
| #' | ||
| #' # find variables with "cop" in variable name | ||
| #' find_var(efc, "cop") | ||
| #' | ||
| #' # return tibble with matching variables | ||
| #' find_var(efc, "cop", as.df = TRUE) | ||
| #' | ||
| #' # or return "summary"-tibble with matching variables | ||
| #' # and their variable labels | ||
| #' find_var(efc, "cop", as.varlab = TRUE) | ||
| #' | ||
| #' # find variables with "dependency" in names and variable labels | ||
| #' find_var(efc, "dependency") | ||
| #' get_label(efc$e42dep) | ||
| #' | ||
| #' # find variables with "level" in names and value labels | ||
| #' res <- find_var(efc, "level", search = "name_value", as.df = TRUE) | ||
| #' res | ||
| #' get_labels(res, attr.only = FALSE) | ||
| #' | ||
| #' # use sjPlot::view_df() to view results | ||
| #' \dontrun{ | ||
| #' library(sjPlot) | ||
| #' view_df(res)} | ||
| #' | ||
| #' @importFrom stringr regex coll | ||
| #' @importFrom tibble as_tibble | ||
| #' @export | ||
| find_var <- function(data, | ||
| pattern, | ||
| ignore.case = TRUE, | ||
| search = c("name_label", "name_value", "label_value", "name", "label", "value", "all"), | ||
| as.df = FALSE, | ||
| as.varlab = FALSE, | ||
| fuzzy = FALSE) { | ||
| # check valid args | ||
| if (!is.data.frame(data)) { | ||
| stop("`data` must be a data frame.", call. = F) | ||
| } | ||
|
|
||
| # match args | ||
| search <- match.arg(search) | ||
|
|
||
| pos1 <- pos2 <- pos3 <- c() | ||
|
|
||
| # search for pattern in variable names | ||
| if (search %in% c("name", "name_label", "name_value", "all")) { | ||
| # check variable names | ||
| if (inherits(pattern, "regex")) | ||
| pos1 <- which(stringr::str_detect(colnames(data), pattern)) | ||
| else | ||
| pos1 <- which(stringr::str_detect(colnames(data), stringr::coll(pattern, ignore_case = ignore.case))) | ||
|
|
||
| # if nothing found, find in near distance | ||
| if (sjmisc::is_empty(pos1) && fuzzy && !inherits(pattern, "regex")) { | ||
| pos1 <- str_pos(search.string = colnames(data), find.term = pattern, part.dist.match = 1) | ||
| } | ||
| } | ||
|
|
||
|
|
||
| # search for pattern in variable labels | ||
| if (search %in% c("label", "name_label", "label_value", "all")) { | ||
| # get labels and variable names | ||
| labels <- get_label(data) | ||
|
|
||
| # check labels | ||
| if (inherits(pattern, "regex")) | ||
| pos2 <- which(stringr::str_detect(labels, pattern)) | ||
| else | ||
| pos2 <- which(stringr::str_detect(labels, stringr::coll(pattern, ignore_case = ignore.case))) | ||
|
|
||
| # if nothing found, find in near distance | ||
| if (sjmisc::is_empty(pos2) && fuzzy && !inherits(pattern, "regex")) { | ||
| pos2 <- str_pos(search.string = labels, find.term = pattern, part.dist.match = 1) | ||
| } | ||
| } | ||
|
|
||
| # search for pattern in value labels | ||
| if (search %in% c("value", "name_value", "label_value", "all")) { | ||
| labels <- get_labels(data, attr.only = F) | ||
|
|
||
| # check value labels with regex | ||
| if (inherits(pattern, "regex")) { | ||
| pos3 <- which(unlist(lapply(labels, function(x) { | ||
| any(stringr::str_detect(x, pattern)) | ||
| }))) | ||
| } else { | ||
| pos3 <- which(unlist(lapply(labels, function(x) { | ||
| any(stringr::str_detect(x, stringr::coll(pattern, ignore_case = ignore.case))) | ||
| }))) | ||
| } | ||
|
|
||
| # if nothing found, find in near distance | ||
| if (sjmisc::is_empty(pos3) && fuzzy && !inherits(pattern, "regex")) { | ||
| pos3 <- which(unlist(lapply(labels, function(x) { | ||
| str_pos(search.string = x, find.term = pattern, part.dist.match = 1) | ||
| }))) | ||
| } | ||
| } | ||
|
|
||
| # get unique variable indices | ||
| pos <- unique(c(pos1, pos2, pos3)) | ||
| # remove -1 | ||
| pos <- pos[which(pos != -1)] | ||
|
|
||
| # return data frame? | ||
| if (as.df) { | ||
| return(tibble::as_tibble(data[, pos])) | ||
| } | ||
|
|
||
| # return variable labels? | ||
| if (as.varlab) { | ||
| return(tibble::tibble( | ||
| col.nr = pos, | ||
| var.name = colnames(data)[pos], | ||
| var.label = get_label(data[, pos], def.value = colnames(data)[pos]) | ||
| )) | ||
| } | ||
|
|
||
| # use column names | ||
| names(pos) <- colnames(data)[pos] | ||
| pos | ||
| } |
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