#==============================================================================#
# discussion #
#==============================================================================#
#' discussion
#'
#' \code{discussion} Extracts data and renders plots for discussion section.
#'
#' @param analysis Data frame containing the results of analysis and hypothesis tests.
#' @return list containing a data frame of summarized data and a plot.
#'
#' @author John James, \email{jjames@@datasciencesalon.org}
#' @family xmar functions
#' @export
discussion <- function(analysis) {
#---------------------------------------------------------------------------#
# Extract Data #
#---------------------------------------------------------------------------#
d <- data.frame(Scope = analysis$Scope,
p1 = round(analysis$p1, 2),
p2 = round(analysis$p2, 2),
PctChange = round(analysis$Diff / analysis$p1 * 100, 2),
Significant = ifelse(analysis$Decision == "Reject", "Yes", "No"))
d$Scope <- factor(d$Scope, levels = d$Scope[order(d$PctChange)], ordered = TRUE)
d <- d %>% arrange(desc(PctChange))
#---------------------------------------------------------------------------#
# Plot Data #
#---------------------------------------------------------------------------#
# Proportion Bar Plot
plotBar <- ggplot2::ggplot(data = d,
ggplot2::aes(x = Scope, y = PctChange,
fill = Scope)) +
ggplot2::geom_bar(stat = "identity") +
ggplot2::geom_text(data = d,
ggplot2::aes(x = Scope, y = PctChange / 2,
label = paste0(PctChange, "%")),
colour="black", family="Tahoma", size = 8) +
ggplot2::theme_minimal(base_size = 24) +
ggplot2::theme(legend.position="bottom",
text=ggplot2::element_text(family="Open Sans")) +
ggplot2::scale_fill_brewer(palette = 'Greens') +
ggplot2::labs(title = "Percent Change in Traditional Opinion over Periods",
x = "Scope",
y = "Percent Change")
res = list(
data = d,
plot = plotBar
)
return(res)
}
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