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44 lines
1.6 KiB
R
44 lines
1.6 KiB
R
#' Easy function for splitting numeric variable in quantiles
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#'
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#' Using base/stats functions cut() and quantile().
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#'
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#' @param x Variable to cut.
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#' @param groups Number of groups.
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#' @param y alternative vector to draw quantile cuts from. Limits has to be within x. Default is NULL.
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#' @param na.rm Remove NA's. Default is TRUE.
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#' @param group.names Names of groups to split to. Default is NULL, giving intervals as names.
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#' @param ordered.f Set resulting vector as ordered. Default is FALSE.
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#' @param detail.list flag to include details or not
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#' @param inc.outs Flag to include min(x) and max(x) as boarders in case of y!=NULL.
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#'
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#' @return vector or list with vector and details (length 2)
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#'
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#' @keywords quantile
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#' @export
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#' @examples
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#' aa <- as.numeric(sample(1:1000,2000,replace = TRUE))
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#' x <- 1:450
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#' y <- 6:750
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#' summary(quantile_cut(aa,groups=4,detail.list=FALSE)) ## Cuts quartiles
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quantile_cut<-function (x, groups, y=NULL, na.rm = TRUE,
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group.names = NULL, ordered.f = FALSE, inc.outs=FALSE,
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detail.list=FALSE){
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if (!is.null(y)){
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q<-quantile(y, probs = seq(0, 1, 1/groups), na.rm = na.rm,
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names = TRUE, type = 7)
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if (inc.outs){ # Setting cut borders to include outliers in x compared to y.
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q[1]<-min(x,na.rm = TRUE)
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q[length(q)]<-max(x,na.rm = TRUE)
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}
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}
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if (is.null(y)){
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q<-quantile(x, probs = seq(0, 1, 1/groups), na.rm = na.rm,
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names = TRUE, type = 7)
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}
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d<-cut(x, q, include.lowest = TRUE, labels = group.names,
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ordered_result = ordered.f)
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if (detail.list) list(d,q) else d
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}
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