inst/app/menu/descriptive_ui.R
In bit2r/BitStat: Statistical Analytics using R and Shiny
################################################################################
## 03. 기술통계 > 집계표
################################################################################
##==============================================================================
## 03.01. 기술통계 > 집계표 > 수치 변수 통계표
##==============================================================================
##------------------------------------------------------------------------------
## 03.01.01. 기술통계 > 집계표 > 수치형 변수 UI 정의
##------------------------------------------------------------------------------
output$summary_numeric <- renderUI({
tagList(
fluidRow(
style = "padding-top:10px;padding-bottom:0px",
column(
width = 3,
wellPanel(
style = "padding-top:5px;padding-bottom:10px",
h4(translate("집계표 설정")),
radioButtons(
inputId = "choice_numerical_summary",
label = translate("대상변수 선택 방법:"),
choices = element_method_choose_variables,
selected = "all"),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.choice_numerical_summary == 'user'",
fluidRow(
column(
width = 12,
uiOutput('list_num_var_summary')
)
)
),
selectizeInput(
inputId = "statistics_method",
label = translate("통계량 종류:"),
choices = element_statistics,
selected = c("na", "mean", "sd", "skewness", "kurtosis"),
multiple = TRUE,
width = "250"
),
selectizeInput(
inputId = "quantiles_method",
label = translate("분위수 종류:"),
choices = element_quantiles,
selected = c("p00", "p25", "p50", "p75", "p100"),
multiple = TRUE,
width = "250"
),
checkboxInput(
inputId = "is_group_num_summary",
label = translate("범주별 계산"),
value = FALSE
),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.is_group_num_summary == 1",
fluidRow(
column(
width = 12,
uiOutput('list_cat_var_summary')
)
)
),
numericInput(
inputId = "diglab_num_summary",
label = translate("통계량 소수점 자리수:"),
min = 0, max = 10, value = 3,
width = "250"
),
checkboxInput(
inputId = "viz_num_summary",
label = translate("시각화 여부"),
value = FALSE
),
actionButton(
inputId = "runNumericalSummary",
label = translate("실행"),
icon = icon("cogs"),
style = "background-color: #90CAF9; border: none;"
)
)
),
column(
width = 9,
wellPanel(
style = "padding-top:10px; padding-left:10px; padding-right:10px",
htmlOutput("num_summary", style = "height: 700px;")
)
)
)
)
})
##------------------------------------------------------------------------------
## 03.01.02. 수치형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_num_var_summary <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_num <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("numeric", "integer")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_num_var_summary",
label = translate("수치형 변수 목록(하나이상 선택):"),
choices = list_num,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.01.03. 범주형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_cat_var_summary <- renderUI({
req(input$combo_dataset)
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_cat_var_summary",
label = translate("범주형 변수 목록:"),
choices = list_cat,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.01.04. 수치형 변수선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_num_var_summary, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.01.05. 범주형 변수선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_cat_var_summary, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.01.06. 범주별 계산 체크버튼 선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$is_group_num_summary, {
req(input$combo_dataset)
if (!input$is_group_num_summary) {
return()
}
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull() %>%
as.character()
updateSelectInput(session,
"list_cat_var_summary",
choices = list_cat)
})
##------------------------------------------------------------------------------
## 03.01.07. 실행 버튼 클릭 이벤트
##------------------------------------------------------------------------------
observeEvent(input$runNumericalSummary, {
req(input$combo_dataset)
id_dataset <- input$combo_dataset
if (input$choice_numerical_summary == "user" & length(input$list_num_var_summary) < 1) {
message <- translate("수치변수는 1개 이상을 선택해야 합니다.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
if (input$is_group_num_summary & length(input$list_cat_var_summary) == 0) {
message <- translate("범주별 계산을 체크했으나 범주형 변수는 선택하지 않았습니다. 체크를 해제하거나 변수를 선택하세요.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
if (input$choice_numerical_summary == "user") {
select_variables <- input$list_num_var_summary
} else {
select_variables <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("numeric", "integer")) %>%
select(variable) %>%
pull()
}
rmd_content <- create_summary_numeric(
id_dataset = id_dataset,
variables = select_variables,
statistics = input$statistics_method,
quantiles = input$quantiles_method,
digits = input$diglab_num_summary,
group_flag = input$is_group_num_summary,
group_variable = input$list_cat_var_summary,
plot = input$viz_num_summary
)
output$num_summary <- renderUI({
input$runNumericalSummary
tags$iframe(
seamless = "seamless",
src = "report/num_summary.html",
width = "100%",
height = "100%"
)
})
})
##==============================================================================
## 03.02. 기술통계 > 집계표 > 범주형 변수 돗수분포표
##==============================================================================
##------------------------------------------------------------------------------
## 03.02.01. 기술통계 > 집계표 > 범주형 변수 돗수분포표 변수 UI 정의
##------------------------------------------------------------------------------
output$summary_category <- renderUI({
tagList(
fluidRow(
style = "padding-top:10px;padding-bottom:0px",
column(
width = 3,
wellPanel(
style = "padding-top:5px;padding-bottom:10px",
h4(translate("집계표 설정")),
radioButtons(
inputId = "choice_categorical_table",
label = translate("대상변수 선택 방법:"),
choices = element_method_choose_variables,
selected = "all"),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.choice_categorical_table == 'user'",
fluidRow(
column(
width = 12,
uiOutput('list_cat_var_table')
)
)
),
checkboxInput(
inputId = "viz_cat_table",
label = translate("시각화 여부"),
value = FALSE
),
actionButton(
inputId = "runCategoricalSummary",
label = translate("실행"),
icon = icon("cogs"),
style = "background-color: #90CAF9; border: none;"
)
)
),
column(
width = 9,
wellPanel(
style = "padding-top:10px; padding-left:10px; padding-right:10px",
htmlOutput("cat_summary", style = "height: 700px;")
)
)
)
)
})
##------------------------------------------------------------------------------
## 03.02.02. 범주형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_cat_var_table <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_cat_var_table",
label = translate("범주형 변수 목록(하나이상 선택):"),
choices = list_cat,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.02.03. 범주형 변수선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_cat_var_table, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.02.04. 실행 버튼 클릭 이벤트
##------------------------------------------------------------------------------
observeEvent(input$runCategoricalSummary, {
req(input$combo_dataset)
id_dataset <- input$combo_dataset
if (input$choice_categorical_table == "user" & length(input$list_cat_var_table) < 1) {
message <- translate("범주형 변수는 1개 이상을 선택해야 합니다.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
if (input$choice_categorical_table == "user") {
select_variables <- input$list_cat_var_table
} else {
select_variables <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
}
rmd_content <- create_summary_category(
id_dataset = id_dataset,
variables = select_variables,
plot = input$viz_cat_table
)
output$cat_summary <- renderUI({
input$runCategoricalSummary
tags$iframe(
seamless = "seamless",
src = "report/cat_summary.html",
width = "100%",
height = "100%"
)
})
})
##==============================================================================
## 03.03. 기술통계 > 집계표 > 범주형 변수 분할표
##==============================================================================
##------------------------------------------------------------------------------
## 03.02.01. 기술통계 > 집계표 > 범주형 변수 분할표 변수 UI 정의
##------------------------------------------------------------------------------
output$summary_contingency <- renderUI({
tagList(
fluidRow(
style = "padding-top:10px;padding-bottom:0px",
column(
width = 3,
wellPanel(
style = "padding-top:5px;padding-bottom:10px",
h4(translate("집계표 설정")),
fluidRow(
column(
width = 12,
uiOutput('list_row_contingency')
)
),
fluidRow(
column(
width = 12,
uiOutput('list_col_contingency')
)
),
checkboxInput(
inputId = "marginal",
label = translate("주변 합 여부"),
value = FALSE),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.marginal == true",
fluidRow(
column(
width = 12,
uiOutput('list_marginal_type')
)
)
),
checkboxInput(
inputId = "viz_cat_contingency",
label = translate("시각화 여부"),
value = FALSE
),
actionButton(
inputId = "runContingencyTable",
label = translate("실행"),
icon = icon("cogs"),
style = "background-color: #90CAF9; border: none;"
)
)
),
column(
width = 9,
wellPanel(
style = "padding-top:10px; padding-left:10px; padding-right:10px",
htmlOutput("cat_contingency_table", style = "height: 700px;")
)
)
)
)
})
##------------------------------------------------------------------------------
## 03.03.02. 행 변수 목록 생성
##------------------------------------------------------------------------------
output$list_row_contingency <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_row_contingency",
label = translate("행 변수 (한개 선택):"),
choices = list_cat,
multiple = FALSE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.03.03. 열 변수 목록 생성
##------------------------------------------------------------------------------
output$list_col_contingency <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_col_contingency",
label = translate("열 변수 (한개 선택):"),
choices = list_cat,
selected = list_cat[2],
multiple = FALSE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.03.04. 주변 합 목록 생성
##------------------------------------------------------------------------------
output$list_marginal_type <- renderUI({
selectInput(
inputId = "list_marginal_type",
label = translate("주변 합 종류:"),
choices = element_marginal_type,
multiple = FALSE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.03.04. 행 변수 목록 선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_row_contingency, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.03.05. 열 변수 목록 선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_col_contingency, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.03.06. 실행 버튼 클릭 이벤트
##------------------------------------------------------------------------------
observeEvent(input$runContingencyTable, {
req(input$combo_dataset)
id_dataset <- input$combo_dataset
if (input$list_row_contingency == input$list_col_contingency) {
message <- translate("행과 열의 변수가 달라야 합니다.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
rmd_content <- create_summary_contingency(
id_dataset = id_dataset,
variable_row = input$list_row_contingency,
variable_col = input$list_col_contingency,
marginal = input$marginal,
marginal_type = input$list_marginal_type,
plot = input$viz_cat_contingency
)
output$cat_contingency_table <- renderUI({
input$runContingencyTable
tags$iframe(
seamless = "seamless",
src = "report/cat_contingency.html",
width = "100%",
height = "100%"
)
})
})
################################################################################
## 03. 기술통계 > 상관관계
################################################################################
##==============================================================================
## 03.01. 기술통계 > 상관관계 > 상관행렬
##==============================================================================
##------------------------------------------------------------------------------
## 03.01.01. 기술통계 > 상관관계 > 상관행렬 UI 정의
##------------------------------------------------------------------------------
output$correlation_matrix <- renderUI({
tagList(
fluidRow(
style = "padding-top:10px;padding-bottom:0px",
column(
width = 3,
wellPanel(
style = "padding-top:5px;padding-bottom:10px",
h4(translate("상관행렬 설정")),
radioButtons(
inputId = "choice_variable_cmat",
label = translate("대상변수 선택 방법:"),
choices = element_method_choose_variables,
selected = "all"),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.choice_variable_cmat == 'user'",
fluidRow(
column(
width = 12,
uiOutput('list_num_var_corrmat')
)
)
),
selectizeInput(
inputId = "correlation_method",
label = translate("상관계수 종류:"),
choices = element_corr_method,
selected = "pearson",
width = "250"
),
checkboxInput(
inputId = "is_group_corr_mat",
label = translate("범주별 계산"),
value = FALSE
),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.is_group_corr_mat == 1",
fluidRow(
column(
width = 12,
uiOutput('list_cat_var_corrmat')
)
)
),
numericInput(
inputId = "diglab_corr_mat",
label = translate("상관계수 소수점 자리수:"),
min = 0, max = 10, value = 3,
width = "250"
),
checkboxInput(
inputId = "viz_corr_mat",
label = translate("시각화 여부"),
value = FALSE
),
actionButton(
inputId = "runCorrelationMatrix",
label = translate("실행"),
icon = icon("cogs"),
style = "background-color: #90CAF9; border: none;"
)
)
),
column(
width = 9,
wellPanel(
style = "padding-top:10px; padding-left:10px; padding-right:10px",
htmlOutput("mat_correlation", style = "height: 700px;")
)
)
)
)
})
##------------------------------------------------------------------------------
## 03.01.02. 수치형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_num_var_corrmat <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_num <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("numeric", "integer")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_num_var_corrmat",
label = translate("수치형 변수 목록(두개이상 선택):"),
choices = list_num,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.01.03. 범주형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_cat_var_corrmat <- renderUI({
req(input$combo_dataset)
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_cat_var_corrmat",
label = translate("범주형 변수 목록:"),
choices = list_cat,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.01.04. 수치형 변수선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_num_var_corrmat, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.01.05. 범주형 변수선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_cat_var_corrmat, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.01.06. 범주별 계산 체크버튼 선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$is_group_corr_mat, {
req(input$combo_dataset)
if (!input$is_group_corr_mat) {
return()
}
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull() %>%
as.character()
updateSelectInput(session,
"list_cat_var_corrmat",
choices = list_cat)
})
##------------------------------------------------------------------------------
## 03.01.07. 실행 버튼 클릭 이벤트
##------------------------------------------------------------------------------
observeEvent(input$runCorrelationMatrix, {
req(input$combo_dataset)
id_dataset <- input$combo_dataset
if (input$choice_variable_cmat == "user" & length(input$list_num_var_corrmat) < 2) {
message <- translate("수치변수는 2개 이상을 선택해야 합니다.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
if (input$is_group_corr_mat & length(input$list_cat_var_corrmat) == 0) {
message <- translate("범주별 계산을 체크했으나 범주형 변수는 선택하지 않았습니다. 체크를 해제하거나 변수를 선택하세요.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
rmd_content <- create_mat_corr(
id_dataset = id_dataset,
variables = input$list_num_var_corrmat,
method = input$method,
digits = input$diglab_corr_mat,
group_flag = input$is_group_corr_mat,
group_variable = input$list_cat_var_corrmat,
plot = input$viz_corr_mat
)
output$mat_correlation <- renderUI({
input$runCorrelationMatrix
tags$iframe(
seamless = "seamless",
src = "report/corr_mat.html",
width = "100%",
height = "100%"
)
})
})
##==============================================================================
## 03.02. 기술통계 > 상관관계 > 상관검정
##==============================================================================
##------------------------------------------------------------------------------
## 03.02.01. 기술통계 > 상관관계 > 상관검정 UI 정의
##------------------------------------------------------------------------------
output$correlation_test <- renderUI({
tagList(
fluidRow(
style = "padding-top:10px;padding-bottom:0px",
column(
width = 3,
wellPanel(
style = "padding-top:5px;padding-bottom:10px",
h4(translate("상관검정 설정")),
uiOutput("list_varriable_corrtest"),
selectizeInput(
inputId = "correlation_method_test",
label = translate("상관계수 종류:"),
choices = element_corr_method,
selected = "pearson",
width = "250"
),
selectizeInput(
inputId = "alternative",
label = translate("대립가설:"),
choices = element_alternative_test,
selected = "two.sided",
width = "250"
),
checkboxInput(
inputId = "is_group_corr_test",
label = translate("범주별 계산"),
value = FALSE
),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.is_group_corr_test == 1",
fluidRow(
column(
width = 12,
uiOutput('list_cat_var_corrtest')
)
)
),
checkboxInput(
inputId = "viz_corr_test",
label = translate("시각화 여부"),
value = FALSE
),
actionButton(
inputId = "runCorrelationTest",
label = translate("실행"),
icon = icon("cogs"),
style = "background-color: #90CAF9; border: none;"
)
)
),
column(
width = 9,
wellPanel(
style = "padding-top:10px; padding-left:10px; padding-right:10px",
htmlOutput("test_correlation", style = "height: 700px;")
)
)
)
)
})
##------------------------------------------------------------------------------
## 03.02.02. 수치형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_varriable_corrtest <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_num <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("numeric", "integer")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_varriable_corrtest",
label = translate("수치형 변수 목록(두개 선택):"),
choices = list_num,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.02.03. 범주형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_cat_var_corrtest <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_cat_var_corrtest",
label = translate("범주형 변수 목록:"),
choices = list_cat,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.02.04. 변수선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_varriable_corrtest, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.02.05. 범주별 계산 체크버튼 체크 이벤트
##------------------------------------------------------------------------------
observeEvent(input$is_group_corr_test, {
req(input$combo_dataset)
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
if (!input$is_group_corr_test) {
return()
}
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull() %>%
as.character()
updateSelectInput(session,
"list_cat_var_corrtest",
choices = list_cat)
})
##------------------------------------------------------------------------------
## 03.02.06. 실행 버튼 클릭
##------------------------------------------------------------------------------
observeEvent(input$runCorrelationTest, {
req(input$combo_dataset)
id_dataset <- input$combo_dataset
if (length(input$list_varriable_corrtest) != 2) {
message <- translate("수치변수는 2개를 선택해야 합니다.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
if (input$is_group_corr_test & length(input$list_cat_var_corrtest) == 0) {
message <- translate("범주별 계산을 체크했으나 범주형 변수는 선택하지 않았습니다. 체크를 해제하거나 변수를 선택하세요.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
rmd_content <- create_mat_test(
id_dataset = id_dataset,
variables = input$list_varriable_corrtest,
method = input$correlation_method_test,
alternative = input$alternative,
group_flag = input$is_group_corr_test,
group_variable = input$list_cat_var_corrtest,
plot = input$viz_corr_test
)
output$test_correlation <- renderUI({
input$runCorrelationTest
tags$iframe(
seamless = "seamless",
src = "report/corr_test.html",
width = "100%",
height = "100%"
)
})
})
################################################################################
## 04. 기술통계 메뉴 정의
################################################################################
output$ui_desc_data <- renderUI({
tagList(
tabBox(
width = 12,
tabPanel(
title = translate("집계표"),
tabsetPanel(
tabPanel(
title = translate("수치형 변수 통계표"),
uiOutput("summary_numeric"),
icon = shiny::icon("calculator")
),
tabPanel(
title = translate("범주형 변수 돗수분포표"),
uiOutput("summary_category"),
icon = shiny::icon("list-alt")
),
tabPanel(
title = translate("범주형 변수 분할표"),
uiOutput("summary_contingency"),
icon = shiny::icon("table")
)
)
),
tabPanel(
title = translate("상관관계"),
tabsetPanel(
tabPanel(
title = translate("상관행렬"),
uiOutput("correlation_matrix"),
icon = shiny::icon("cubes")
),
tabPanel(
title = translate("상관검정"),
uiOutput("correlation_test"),
icon = shiny::icon("stethoscope")
)
)
)
)
)
})
bit2r/BitStat documentation built on Nov. 8, 2022, 4:17 p.m.
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################################################################################
## 03. 기술통계 > 집계표
################################################################################
##==============================================================================
## 03.01. 기술통계 > 집계표 > 수치 변수 통계표
##==============================================================================
##------------------------------------------------------------------------------
## 03.01.01. 기술통계 > 집계표 > 수치형 변수 UI 정의
##------------------------------------------------------------------------------
output$summary_numeric <- renderUI({
tagList(
fluidRow(
style = "padding-top:10px;padding-bottom:0px",
column(
width = 3,
wellPanel(
style = "padding-top:5px;padding-bottom:10px",
h4(translate("집계표 설정")),
radioButtons(
inputId = "choice_numerical_summary",
label = translate("대상변수 선택 방법:"),
choices = element_method_choose_variables,
selected = "all"),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.choice_numerical_summary == 'user'",
fluidRow(
column(
width = 12,
uiOutput('list_num_var_summary')
)
)
),
selectizeInput(
inputId = "statistics_method",
label = translate("통계량 종류:"),
choices = element_statistics,
selected = c("na", "mean", "sd", "skewness", "kurtosis"),
multiple = TRUE,
width = "250"
),
selectizeInput(
inputId = "quantiles_method",
label = translate("분위수 종류:"),
choices = element_quantiles,
selected = c("p00", "p25", "p50", "p75", "p100"),
multiple = TRUE,
width = "250"
),
checkboxInput(
inputId = "is_group_num_summary",
label = translate("범주별 계산"),
value = FALSE
),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.is_group_num_summary == 1",
fluidRow(
column(
width = 12,
uiOutput('list_cat_var_summary')
)
)
),
numericInput(
inputId = "diglab_num_summary",
label = translate("통계량 소수점 자리수:"),
min = 0, max = 10, value = 3,
width = "250"
),
checkboxInput(
inputId = "viz_num_summary",
label = translate("시각화 여부"),
value = FALSE
),
actionButton(
inputId = "runNumericalSummary",
label = translate("실행"),
icon = icon("cogs"),
style = "background-color: #90CAF9; border: none;"
)
)
),
column(
width = 9,
wellPanel(
style = "padding-top:10px; padding-left:10px; padding-right:10px",
htmlOutput("num_summary", style = "height: 700px;")
)
)
)
)
})
##------------------------------------------------------------------------------
## 03.01.02. 수치형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_num_var_summary <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_num <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("numeric", "integer")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_num_var_summary",
label = translate("수치형 변수 목록(하나이상 선택):"),
choices = list_num,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.01.03. 범주형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_cat_var_summary <- renderUI({
req(input$combo_dataset)
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_cat_var_summary",
label = translate("범주형 변수 목록:"),
choices = list_cat,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.01.04. 수치형 변수선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_num_var_summary, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.01.05. 범주형 변수선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_cat_var_summary, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.01.06. 범주별 계산 체크버튼 선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$is_group_num_summary, {
req(input$combo_dataset)
if (!input$is_group_num_summary) {
return()
}
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull() %>%
as.character()
updateSelectInput(session,
"list_cat_var_summary",
choices = list_cat)
})
##------------------------------------------------------------------------------
## 03.01.07. 실행 버튼 클릭 이벤트
##------------------------------------------------------------------------------
observeEvent(input$runNumericalSummary, {
req(input$combo_dataset)
id_dataset <- input$combo_dataset
if (input$choice_numerical_summary == "user" & length(input$list_num_var_summary) < 1) {
message <- translate("수치변수는 1개 이상을 선택해야 합니다.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
if (input$is_group_num_summary & length(input$list_cat_var_summary) == 0) {
message <- translate("범주별 계산을 체크했으나 범주형 변수는 선택하지 않았습니다. 체크를 해제하거나 변수를 선택하세요.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
if (input$choice_numerical_summary == "user") {
select_variables <- input$list_num_var_summary
} else {
select_variables <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("numeric", "integer")) %>%
select(variable) %>%
pull()
}
rmd_content <- create_summary_numeric(
id_dataset = id_dataset,
variables = select_variables,
statistics = input$statistics_method,
quantiles = input$quantiles_method,
digits = input$diglab_num_summary,
group_flag = input$is_group_num_summary,
group_variable = input$list_cat_var_summary,
plot = input$viz_num_summary
)
output$num_summary <- renderUI({
input$runNumericalSummary
tags$iframe(
seamless = "seamless",
src = "report/num_summary.html",
width = "100%",
height = "100%"
)
})
})
##==============================================================================
## 03.02. 기술통계 > 집계표 > 범주형 변수 돗수분포표
##==============================================================================
##------------------------------------------------------------------------------
## 03.02.01. 기술통계 > 집계표 > 범주형 변수 돗수분포표 변수 UI 정의
##------------------------------------------------------------------------------
output$summary_category <- renderUI({
tagList(
fluidRow(
style = "padding-top:10px;padding-bottom:0px",
column(
width = 3,
wellPanel(
style = "padding-top:5px;padding-bottom:10px",
h4(translate("집계표 설정")),
radioButtons(
inputId = "choice_categorical_table",
label = translate("대상변수 선택 방법:"),
choices = element_method_choose_variables,
selected = "all"),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.choice_categorical_table == 'user'",
fluidRow(
column(
width = 12,
uiOutput('list_cat_var_table')
)
)
),
checkboxInput(
inputId = "viz_cat_table",
label = translate("시각화 여부"),
value = FALSE
),
actionButton(
inputId = "runCategoricalSummary",
label = translate("실행"),
icon = icon("cogs"),
style = "background-color: #90CAF9; border: none;"
)
)
),
column(
width = 9,
wellPanel(
style = "padding-top:10px; padding-left:10px; padding-right:10px",
htmlOutput("cat_summary", style = "height: 700px;")
)
)
)
)
})
##------------------------------------------------------------------------------
## 03.02.02. 범주형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_cat_var_table <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_cat_var_table",
label = translate("범주형 변수 목록(하나이상 선택):"),
choices = list_cat,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.02.03. 범주형 변수선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_cat_var_table, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.02.04. 실행 버튼 클릭 이벤트
##------------------------------------------------------------------------------
observeEvent(input$runCategoricalSummary, {
req(input$combo_dataset)
id_dataset <- input$combo_dataset
if (input$choice_categorical_table == "user" & length(input$list_cat_var_table) < 1) {
message <- translate("범주형 변수는 1개 이상을 선택해야 합니다.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
if (input$choice_categorical_table == "user") {
select_variables <- input$list_cat_var_table
} else {
select_variables <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
}
rmd_content <- create_summary_category(
id_dataset = id_dataset,
variables = select_variables,
plot = input$viz_cat_table
)
output$cat_summary <- renderUI({
input$runCategoricalSummary
tags$iframe(
seamless = "seamless",
src = "report/cat_summary.html",
width = "100%",
height = "100%"
)
})
})
##==============================================================================
## 03.03. 기술통계 > 집계표 > 범주형 변수 분할표
##==============================================================================
##------------------------------------------------------------------------------
## 03.02.01. 기술통계 > 집계표 > 범주형 변수 분할표 변수 UI 정의
##------------------------------------------------------------------------------
output$summary_contingency <- renderUI({
tagList(
fluidRow(
style = "padding-top:10px;padding-bottom:0px",
column(
width = 3,
wellPanel(
style = "padding-top:5px;padding-bottom:10px",
h4(translate("집계표 설정")),
fluidRow(
column(
width = 12,
uiOutput('list_row_contingency')
)
),
fluidRow(
column(
width = 12,
uiOutput('list_col_contingency')
)
),
checkboxInput(
inputId = "marginal",
label = translate("주변 합 여부"),
value = FALSE),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.marginal == true",
fluidRow(
column(
width = 12,
uiOutput('list_marginal_type')
)
)
),
checkboxInput(
inputId = "viz_cat_contingency",
label = translate("시각화 여부"),
value = FALSE
),
actionButton(
inputId = "runContingencyTable",
label = translate("실행"),
icon = icon("cogs"),
style = "background-color: #90CAF9; border: none;"
)
)
),
column(
width = 9,
wellPanel(
style = "padding-top:10px; padding-left:10px; padding-right:10px",
htmlOutput("cat_contingency_table", style = "height: 700px;")
)
)
)
)
})
##------------------------------------------------------------------------------
## 03.03.02. 행 변수 목록 생성
##------------------------------------------------------------------------------
output$list_row_contingency <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_row_contingency",
label = translate("행 변수 (한개 선택):"),
choices = list_cat,
multiple = FALSE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.03.03. 열 변수 목록 생성
##------------------------------------------------------------------------------
output$list_col_contingency <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_col_contingency",
label = translate("열 변수 (한개 선택):"),
choices = list_cat,
selected = list_cat[2],
multiple = FALSE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.03.04. 주변 합 목록 생성
##------------------------------------------------------------------------------
output$list_marginal_type <- renderUI({
selectInput(
inputId = "list_marginal_type",
label = translate("주변 합 종류:"),
choices = element_marginal_type,
multiple = FALSE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.03.04. 행 변수 목록 선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_row_contingency, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.03.05. 열 변수 목록 선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_col_contingency, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.03.06. 실행 버튼 클릭 이벤트
##------------------------------------------------------------------------------
observeEvent(input$runContingencyTable, {
req(input$combo_dataset)
id_dataset <- input$combo_dataset
if (input$list_row_contingency == input$list_col_contingency) {
message <- translate("행과 열의 변수가 달라야 합니다.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
rmd_content <- create_summary_contingency(
id_dataset = id_dataset,
variable_row = input$list_row_contingency,
variable_col = input$list_col_contingency,
marginal = input$marginal,
marginal_type = input$list_marginal_type,
plot = input$viz_cat_contingency
)
output$cat_contingency_table <- renderUI({
input$runContingencyTable
tags$iframe(
seamless = "seamless",
src = "report/cat_contingency.html",
width = "100%",
height = "100%"
)
})
})
################################################################################
## 03. 기술통계 > 상관관계
################################################################################
##==============================================================================
## 03.01. 기술통계 > 상관관계 > 상관행렬
##==============================================================================
##------------------------------------------------------------------------------
## 03.01.01. 기술통계 > 상관관계 > 상관행렬 UI 정의
##------------------------------------------------------------------------------
output$correlation_matrix <- renderUI({
tagList(
fluidRow(
style = "padding-top:10px;padding-bottom:0px",
column(
width = 3,
wellPanel(
style = "padding-top:5px;padding-bottom:10px",
h4(translate("상관행렬 설정")),
radioButtons(
inputId = "choice_variable_cmat",
label = translate("대상변수 선택 방법:"),
choices = element_method_choose_variables,
selected = "all"),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.choice_variable_cmat == 'user'",
fluidRow(
column(
width = 12,
uiOutput('list_num_var_corrmat')
)
)
),
selectizeInput(
inputId = "correlation_method",
label = translate("상관계수 종류:"),
choices = element_corr_method,
selected = "pearson",
width = "250"
),
checkboxInput(
inputId = "is_group_corr_mat",
label = translate("범주별 계산"),
value = FALSE
),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.is_group_corr_mat == 1",
fluidRow(
column(
width = 12,
uiOutput('list_cat_var_corrmat')
)
)
),
numericInput(
inputId = "diglab_corr_mat",
label = translate("상관계수 소수점 자리수:"),
min = 0, max = 10, value = 3,
width = "250"
),
checkboxInput(
inputId = "viz_corr_mat",
label = translate("시각화 여부"),
value = FALSE
),
actionButton(
inputId = "runCorrelationMatrix",
label = translate("실행"),
icon = icon("cogs"),
style = "background-color: #90CAF9; border: none;"
)
)
),
column(
width = 9,
wellPanel(
style = "padding-top:10px; padding-left:10px; padding-right:10px",
htmlOutput("mat_correlation", style = "height: 700px;")
)
)
)
)
})
##------------------------------------------------------------------------------
## 03.01.02. 수치형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_num_var_corrmat <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_num <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("numeric", "integer")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_num_var_corrmat",
label = translate("수치형 변수 목록(두개이상 선택):"),
choices = list_num,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.01.03. 범주형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_cat_var_corrmat <- renderUI({
req(input$combo_dataset)
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_cat_var_corrmat",
label = translate("범주형 변수 목록:"),
choices = list_cat,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.01.04. 수치형 변수선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_num_var_corrmat, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.01.05. 범주형 변수선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_cat_var_corrmat, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.01.06. 범주별 계산 체크버튼 선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$is_group_corr_mat, {
req(input$combo_dataset)
if (!input$is_group_corr_mat) {
return()
}
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull() %>%
as.character()
updateSelectInput(session,
"list_cat_var_corrmat",
choices = list_cat)
})
##------------------------------------------------------------------------------
## 03.01.07. 실행 버튼 클릭 이벤트
##------------------------------------------------------------------------------
observeEvent(input$runCorrelationMatrix, {
req(input$combo_dataset)
id_dataset <- input$combo_dataset
if (input$choice_variable_cmat == "user" & length(input$list_num_var_corrmat) < 2) {
message <- translate("수치변수는 2개 이상을 선택해야 합니다.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
if (input$is_group_corr_mat & length(input$list_cat_var_corrmat) == 0) {
message <- translate("범주별 계산을 체크했으나 범주형 변수는 선택하지 않았습니다. 체크를 해제하거나 변수를 선택하세요.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
rmd_content <- create_mat_corr(
id_dataset = id_dataset,
variables = input$list_num_var_corrmat,
method = input$method,
digits = input$diglab_corr_mat,
group_flag = input$is_group_corr_mat,
group_variable = input$list_cat_var_corrmat,
plot = input$viz_corr_mat
)
output$mat_correlation <- renderUI({
input$runCorrelationMatrix
tags$iframe(
seamless = "seamless",
src = "report/corr_mat.html",
width = "100%",
height = "100%"
)
})
})
##==============================================================================
## 03.02. 기술통계 > 상관관계 > 상관검정
##==============================================================================
##------------------------------------------------------------------------------
## 03.02.01. 기술통계 > 상관관계 > 상관검정 UI 정의
##------------------------------------------------------------------------------
output$correlation_test <- renderUI({
tagList(
fluidRow(
style = "padding-top:10px;padding-bottom:0px",
column(
width = 3,
wellPanel(
style = "padding-top:5px;padding-bottom:10px",
h4(translate("상관검정 설정")),
uiOutput("list_varriable_corrtest"),
selectizeInput(
inputId = "correlation_method_test",
label = translate("상관계수 종류:"),
choices = element_corr_method,
selected = "pearson",
width = "250"
),
selectizeInput(
inputId = "alternative",
label = translate("대립가설:"),
choices = element_alternative_test,
selected = "two.sided",
width = "250"
),
checkboxInput(
inputId = "is_group_corr_test",
label = translate("범주별 계산"),
value = FALSE
),
conditionalPanel(
style = "padding-top:0px;",
condition = "input.is_group_corr_test == 1",
fluidRow(
column(
width = 12,
uiOutput('list_cat_var_corrtest')
)
)
),
checkboxInput(
inputId = "viz_corr_test",
label = translate("시각화 여부"),
value = FALSE
),
actionButton(
inputId = "runCorrelationTest",
label = translate("실행"),
icon = icon("cogs"),
style = "background-color: #90CAF9; border: none;"
)
)
),
column(
width = 9,
wellPanel(
style = "padding-top:10px; padding-left:10px; padding-right:10px",
htmlOutput("test_correlation", style = "height: 700px;")
)
)
)
)
})
##------------------------------------------------------------------------------
## 03.02.02. 수치형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_varriable_corrtest <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_num <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("numeric", "integer")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_varriable_corrtest",
label = translate("수치형 변수 목록(두개 선택):"),
choices = list_num,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.02.03. 범주형 변수 목록 생성
##------------------------------------------------------------------------------
output$list_cat_var_corrtest <- renderUI({
req(input$combo_dataset)
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull()
selectInput(
inputId = "list_cat_var_corrtest",
label = translate("범주형 변수 목록:"),
choices = list_cat,
multiple = TRUE,
width = "250"
)
})
##------------------------------------------------------------------------------
## 03.02.04. 변수선택 이벤트
##------------------------------------------------------------------------------
observeEvent(input$list_varriable_corrtest, {
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
})
##------------------------------------------------------------------------------
## 03.02.05. 범주별 계산 체크버튼 체크 이벤트
##------------------------------------------------------------------------------
observeEvent(input$is_group_corr_test, {
req(input$combo_dataset)
if (!is.null(notice_id))
removeNotification(notice_id)
notice_id <<- NULL
if (!input$is_group_corr_test) {
return()
}
id_dataset <- input$combo_dataset
list_cat <- dslists()[[id_dataset]]$dataset %>%
get_class() %>%
filter(class %in% c("factor", "ordered")) %>%
select(variable) %>%
pull() %>%
as.character()
updateSelectInput(session,
"list_cat_var_corrtest",
choices = list_cat)
})
##------------------------------------------------------------------------------
## 03.02.06. 실행 버튼 클릭
##------------------------------------------------------------------------------
observeEvent(input$runCorrelationTest, {
req(input$combo_dataset)
id_dataset <- input$combo_dataset
if (length(input$list_varriable_corrtest) != 2) {
message <- translate("수치변수는 2개를 선택해야 합니다.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
if (input$is_group_corr_test & length(input$list_cat_var_corrtest) == 0) {
message <- translate("범주별 계산을 체크했으나 범주형 변수는 선택하지 않았습니다. 체크를 해제하거나 변수를 선택하세요.")
# Save the ID for removal later
notice_id <<- showNotification(message, duration = 0, type = "error")
return()
}
rmd_content <- create_mat_test(
id_dataset = id_dataset,
variables = input$list_varriable_corrtest,
method = input$correlation_method_test,
alternative = input$alternative,
group_flag = input$is_group_corr_test,
group_variable = input$list_cat_var_corrtest,
plot = input$viz_corr_test
)
output$test_correlation <- renderUI({
input$runCorrelationTest
tags$iframe(
seamless = "seamless",
src = "report/corr_test.html",
width = "100%",
height = "100%"
)
})
})
################################################################################
## 04. 기술통계 메뉴 정의
################################################################################
output$ui_desc_data <- renderUI({
tagList(
tabBox(
width = 12,
tabPanel(
title = translate("집계표"),
tabsetPanel(
tabPanel(
title = translate("수치형 변수 통계표"),
uiOutput("summary_numeric"),
icon = shiny::icon("calculator")
),
tabPanel(
title = translate("범주형 변수 돗수분포표"),
uiOutput("summary_category"),
icon = shiny::icon("list-alt")
),
tabPanel(
title = translate("범주형 변수 분할표"),
uiOutput("summary_contingency"),
icon = shiny::icon("table")
)
)
),
tabPanel(
title = translate("상관관계"),
tabsetPanel(
tabPanel(
title = translate("상관행렬"),
uiOutput("correlation_matrix"),
icon = shiny::icon("cubes")
),
tabPanel(
title = translate("상관검정"),
uiOutput("correlation_test"),
icon = shiny::icon("stethoscope")
)
)
)
)
)
})
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