Nothing
require("shiny") || stop("unable to load shiny")
require("shinyjs") || stop("unable to load shinyjs")
require("StepReg") || stop("unable to load StepReg")
require("survival") || stop("unable to load survival")
require("MASS") || stop("unable to load MASS")
require("cowplot") || stop("unable to load cowplot")
require("stringr") || stop("unable to load stringr")
require("DT") || stop("unable to load DT")
require("shinythemes") || stop("unable to load shinythemes")
require("shinycssloaders") || stop("unable to laod shinycssloaders")
require("ggplot2") || stop("unable to load ggplot2")
require("dplyr") || stop("unable to load dplyr")
require("summarytools") || stop("unable to load summarytools")
require("ggcorrplot") || stop("unable to load ggcorrplot")
require("tidyr") || stop("unable to load tidyr")
#require("GGally") || stop("unable to load GGally")
require("ggrepel") || stop("unable to load ggrepel")
require("purrr") || stop("unable to load purrr")
require("rmarkdown") || stop("unable to load rmarkdown")
createPlot <- function(plot_type_value, var_plot_value, data_value) {
plot_type <- switch(
plot_type_value,
"Bar plot" = {
# Create a bar plot for each selected variable
lapply(var_plot_value, function(var) {
data_value %>%
ggplot(aes(x = .data[[var]])) +
geom_bar() +
labs(title = paste("Bar Plot of", var), x = var)
})
},
"Box plot" = {
# Create a box plot for each selected variable
lapply(var_plot_value, function(var) {
data_value %>%
ggplot(aes(y = .data[[var]])) +
geom_boxplot() +
labs(title = paste("Box Plot of", var), x = var) +
scale_y_continuous(labels = NULL)})
},
"Correlation plot" = {
# Create a Correlation plot for each selected variable
corr <- round(cor(select(data_value, all_of(var_plot_value))), 1)
p <- list(corr %>% ggcorrplot::ggcorrplot(hc.order = TRUE, type = "lower", lab = TRUE))
},
"Density plot" = {
# Create a density plot for each selected variable
lapply(var_plot_value, function(var) {
data_value %>%
ggplot(aes(.data[[var]])) +
geom_density() +
labs(title = paste("Density Plot of", var), x = var) +
scale_y_continuous(labels = NULL)
})
},
"Dot plot" = {
# Create a dot plot for each selected variable
lapply(var_plot_value, function(var) {
data_value %>%
ggplot(aes(.data[[var]])) +
geom_dotplot() +
labs(title = paste("Dot Plot of", var), x = var) +
scale_y_continuous(labels = NULL)
})
},
"Histogram" = {
# Create a histogram plot for each selected variable
lapply(var_plot_value, function(var) {
data_value %>%
ggplot(aes(.data[[var]])) +
geom_histogram() +
labs(title = paste("Histogram Plot of", var), x = var) +
scale_y_continuous(labels = NULL)
})
},
"QQ plot" = {
# Create a qq plot for each selected variable
lapply(var_plot_value, function(var) {
data_value %>%
ggplot(aes(sample = .data[[var]])) +
stat_qq() +
stat_qq_line() +
labs(title = paste("QQ Plot of", var), x = var) +
scale_y_continuous(labels = NULL)
})
},
"Scatter and Line plot" = {
# Create a scatter plot for each selected variable
lapply(var_plot_value, function(var) {
data_value %>%
select(all_of(var_plot_value)) %>%
gather(-{{var}}, key = "var", value = "value") %>%
ggplot(aes(x = value, y = .data[[var]])) +
geom_point() +
stat_smooth() +
facet_wrap(~ var, scales = "free") +
theme_bw()
})
}
# "Pairs plot" = {
# # Create a pairs plot
# data_value %>%
# select(all_of(var_plot_value)) %>%
# ggpairs
# }
)
return(plot_type)
}
# prepData <- function(example_dataset, upload_file, header_value, sep_value, quote_value){
# if (example_dataset != " ") {
# # Read the selected example dataset
# data(CreditCard, package = 'AER')
# data(remission,package="StepReg")
# survival::lung %>%
# mutate(sex = factor(sex, levels = c(1,2))) %>% # make sex as factor
# mutate(status = ifelse(status == 1, 0, 1)) %>% # recode status: 0 means cencored, 1 means dead
# na.omit() -> lung# get rid of incomplete records
#
#
# df <- switch(example_dataset,
# "base::mtcars" = mtcars,
# "StepReg::remission" = remission,
# "survival::lung" = lung,
# "AER::CreditCard" = CreditCard)
# }
# if (!is.null(upload_file)) {
# # Read the uploaded file
# df <- read.table(upload_file$datapath,
# header = header_value,
# sep = sep_value,
# quote = quote_value)
# }
# return(df)
# }
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