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#' Basic summary of the data
#'
#' Takes in a data and returns summary of the data
#' @param data a data.frame or data.table
#' @details
#' This function helps when one wants to get a quick snapshot of the data such as class,
#' distinct values, missing values and sample value of the variables.
#'
#' It works for both 'data.frame' and 'data.table' but the output will be a 'data.frame' only.
#' @return a data.frame that contains variable, class, distinct values,
#' missing values, percentage of missing value and sample value
#' @author Akash Jain
#' @seealso \code{\link{dqcontinuous}}, \code{\link{dqcategorical}}, \code{\link{dqdate}}
#' @examples
#' # A data frame
#' df <- data.frame(x = c(1, 2, 3, 4, NA),
#' y = c('a', 'b', 'c', 'd', 'e'),
#' z = c(1, 1, 0, 0, 1))
#'
#' # Summary of the data
#' dfContents <- contents(data = df)
#' @export
contents <- function(data) {
if(class(data)[1] != 'data.frame' && class(data)[1] != 'data.table') {
stop('Invalid input: data should be either data.frame or data.table')
} else {
variable <- names(data)
class <- sapply(data, class)
distinctValues <- sapply(data, function(var) length(unique(var)))
missingValues <- sapply(data, function(var) sum(is.na(var)))
perMissingValues <- sapply(missingValues, function(value) round(value/nrow(data), digits = 4)*100)
sampleValue <- sapply(data, function(var) sample(var, size = 1))
contents <- data.frame(variable,
class,
distinctValues,
missingValues,
perMissingValues,
sampleValue,
row.names = NULL)
return(contents)
}
}
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