Nothing
#' Date summary for a Numeric Row
#'
#' Summarizes a numeric row using the five-number summary for a date object.
#' @param dt the name of the dataframe object.
#' @param ... Additional arguments supplied within the package row functions.
#' @return A dataframe with summary statistics for a numeric variable.
#' @details This is an internal function of `tangram.pipe`. Additional arguments
#' should be supplied for this function to work properly.
#'
#' `rowlabel` : the label for the table row name, if different from row_var.
#'
#' `missing` : if TRUE, missing data is considered; FALSE only uses complete cases.
#' @seealso Additional prewritten summary functions for numeric data: \link[tangram.pipe]{num_default}, \link[tangram.pipe]{num_mean_sd}, \link[tangram.pipe]{num_medianiqr}, \link[tangram.pipe]{num_minmax}
#' @import dplyr
#' @importFrom stats complete.cases
#' @importFrom stats aggregate
#' @importFrom stats sd
#' @importFrom stats median
#' @importFrom stats quantile
#' @keywords tangram.pipe
#' @export
num_date <- function(dt, ...){
dots <- list(...)
rowlabel <- dots$rowlabel
missing <- dots$missing
nocols <- FALSE
if (is.null(ncol(dt))) {
nocols <- TRUE
dt <- data.frame(x = dt) %>% mutate(y = 1:n()%%2)
}
if (missing == TRUE) {
miss <- dt %>% filter(is.na(dt[, 1]))
miss <- miss[, 2] %>% table() %>% as.data.frame() %>%
t()
miss <- if (dim(miss)[1] >= 2)
as.numeric(miss[2, ])
else 0
}
dt <- dt[complete.cases(dt), ]
dt[,1] <- as.Date(dt[,1])
out <- aggregate(dt[, 1], list(dt[, 2]), median) %>%
t() %>%
as.data.frame()
Q1 <- aggregate(dt[, 1], list(dt[, 2]), quantile, probs = 0.25, type = 1) %>%
t() %>%
as.data.frame()
Q3 <- aggregate(dt[, 1], list(dt[, 2]), quantile, probs = 0.75, type = 1) %>%
t() %>%
as.data.frame()
MIN <- aggregate(dt[, 1], list(dt[, 2]), min) %>% t() %>% as.data.frame()
MAX <- aggregate(dt[, 1], list(dt[, 2]), max) %>% t() %>% as.data.frame()
out["min", ] <- MIN[2, ]
out["Q1", ] <- Q1[2, ]
out["median", ] <- out[2, ]
out["Q3", ] <- Q3[2, ]
out["max", ] <- MAX[2, ]
colnames(out) <- out[1, ]
out$Overall <- ""
out$Overall[3] <- min(dt[, 1]) %>% as.character()
out$Overall[4] <- quantile(dt[, 1], 0.25, type = 1) %>% as.character
out$Overall[5] <- median(dt[, 1]) %>% as.character
out$Overall[6] <- quantile(dt[, 1],0.75, type = 1) %>% as.character
out$Overall[7] <- max(dt[, 1]) %>% as.character
out <- out[(3:nrow(out)), ]
out <- data.frame(Measure = rownames(out), out, check.names = FALSE)
rownames(out) <- NULL
if (missing == TRUE) {
out <- cbind(Variable = "", out)
out[6, ] <- ""
out$Variable[1] <- rowlabel
out$Measure[6] <- "Missing"
for (i in 1:length(miss)) {
out[6, (2 + i)] <- miss[i]
}
out$Overall[6] <- sum(miss)
}
else {
out <- cbind(Variable = "", out)
out$Variable[1] <- rowlabel
}
if (nocols == TRUE) {
out <- out[, -c(3, 4)]
}
out
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.