#' symptom_profile_covid_tested
#'
#' @param data
#' @param start_date
#' @param end_date
#' @param plot_chart
#' @param title
#'
#' @return
#' @export
#'
#' @examples
symptom_profile_covid_tested <- function(data, start_date = as.Date("2020-01-01", format = "%Y-%m-%d"),
end_date = as.Date("2020-02-01", format = "%Y-%m-%d"),
plot_chart = TRUE) {
positive_tested_symptoms <- data %>%
dplyr::select(id, covid_tested, shortness_breath, muscle_ache, cough, loss_smell_taste) %>%
dplyr::filter(covid_tested == "positive")
data_piv <- positive_tested_symptoms %>%
tidyr::pivot_longer(cols=3:6, names_to="Symptom", values_to="Event") %>%
dplyr::group_by(Symptom, Event) %>%
dplyr::summarise(Count=n()) %>%
dplyr::mutate(Percentage=Count/sum(Count) *100)
symptom_levels <- c('Shorthness of breath' = "shortness_breath",
'Muscle ache' = "muscle_ache",
"Cough" = "cough",
"Loss of smell and taste" = "loss_smell_taste")
data_levels <- data_piv %>%
dplyr::mutate(Symptom = forcats::fct_recode(Symptom, !!!symptom_levels)) %>%
dplyr::arrange(desc(Count))
data_level_positive <- data_levels %>%
dplyr::filter(Event == "Yes")
title_stub_freq <- "SARS-COVID-19 positive tested patients, Frequency\n"
start_date_title <- format(as.Date(start_date), format = "%d %B %Y")
end_date_title <- format(as.Date(end_date), format = "%d %B %Y")
chart_title_2 <- paste0(title_stub_freq, start_date_title, " to ", end_date_title)
plot_test <- ggplot2::ggplot(data_level_positive, ggplot2::aes(x = reorder(Symptom, -Percentage), y = Percentage, fill = Percentage)) +
ggplot2::coord_flip() +
ggplot2::geom_bar(stat = "identity", position = "dodge") +
ggplot2::scale_fill_viridis_c(option = "magma", direction = -1) +
ggplot2::scale_x_discrete(limits = unique(data_level_positive$Symptom)) +
#ggplot2::theme(legend.position = "bottom") +
#ggplot2::guides(fill = ggplot2::guide_legend(nrow = 3)) +
ggplot2::theme_minimal() +
ggplot2::labs( title = chart_title_2,
subtitle = "Four main Covid-19 Symptoms in patients tested positive",
y = "Frequency",
x = "Covid-19 Symptoms",
caption = "Source: Dataset - Your.md Dataset") +
ggplot2::theme(
axis.title.y = ggplot2::element_text(margin = ggplot2::margin(
t = 0,
r = 21,
b = 0,
l = 0
)),
plot.title = ggplot2::element_text(size = 10, face = "bold"),
plot.subtitle = ggplot2::element_text(size = 9),
axis.text.x = ggplot2::element_text(angle = 55, hjust = 1)
)
if(plot_chart == TRUE){
plot_test
}else{
data_levels
}
}
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