insightsengineering
[Question]: Exploratory data review app module
What is your question?
The teal exploratory data review app code i'm running has the app come up but there is no data. I needed to move the library statements outside of the within statement. Would this cause the data to not be passed to the shiny app?
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Hi @probert7-git2 Please provide screenshot and code so we can reproduce your issue
This code generates a display but it seems that it is instantiated with no incoming data.
# Safety Data Review App from Git Hub Imageengineering
# install.packages("pak")
pak::pak("insightsengineering/teal")
install.packages(“teal.modules.clinical”)
install.packages(“teal.modules.general”)
#install.packages(“random.cdisc.data”)
library(teal.modules.general)
library(teal.modules.clinical)
library(random.cdisc.data)
library(dplyr)
library(tidyr)
library(ggExtra)
library(ggpmisc)
library(ggpp)
library(goftest)
library(gridExtra)
library(htmlwidgets)
library(jsonlite)
library(lattice)
library(MASS)
library(rlang)
library(rtables)
library(nestcolor)
library(broom)
library(colourpicker)
library(sparkline)
options(
shiny.useragg = FALSE,
teal.ggplot2_args = teal.widgets::ggplot2_args(labs = list(caption =
"NEST PROJECT"))
)
ADSL <- radsl(seed = 1)
ADRS <- radrs(ADSL, seed = 1)
ADLB <- radlb(ADSL, seed = 1)
ADLBPCA <- ADLB %>%
dplyr::select(USUBJID, STUDYID, SEX, ARMCD, AVAL, AVISIT, PARAMCD) %>%
tidyr::pivot_wider(
values_from = "AVAL",
names_from = c("PARAMCD", "AVISIT"),
names_sep = " - "
)
# Data reproducible code ----
#data <- teal_data()
#data <- within(data, {
# ADSL <- ADSL
# ADRS <- ADRS
# ADLB <- ADLB
# ADLBPCA <- ADLBPCA
# })
data <- teal_data(
ADSL = ADSL,
ADRS = ADRS,
ADLB = ADLB,
ADLBPCA = ADLBPCA )
#the default_cdisc_join_keys cannot also include ADLBPCA which has no CDISC
metadata
join_keys(data) <- default_cdisc_join_keys[c("ADSL", "ADLB", "ADRS")]
## Reusable Configuration For Modules
ADSL <- data[["ADSL"]]
ADRS <- data[["ADRS"]]
ADLB <- data[["ADLB"]]
ADLBPCA <- data[["ADLBPCA"]]
adsl_extracted_num <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL),
selected = "AGE",
multiple = FALSE,
fixed = FALSE
)
)
adsl_extracted_num2 <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL),
selected = "BMRKR1",
multiple = FALSE,
fixed = FALSE
)
)
adsl_extracted_fct <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL),
selected = "ARMCD",
multiple = FALSE,
fixed = FALSE
)
)
numeric_vars_adsl <- names(Filter(isTRUE, sapply(ADSL, is.numeric)))
adsl_extracted_numeric <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL, subset = numeric_vars_adsl),
selected = "BMRKR1",
multiple = FALSE,
fixed = FALSE
)
)
adsl_extracted_factors <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL, subset = fact_vars_adsl),
selected = NULL,
multiple = FALSE,
fixed = FALSE
)
)
adsl_extracted_multi <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL),
selected = c("AGE", "BMRKR1"),
multiple = TRUE,
fixed = FALSE
)
)
adrs_filters <- filter_spec(
vars = "PARAMCD",
sep = " - ",
choices = value_choices(ADRS, "PARAMCD", "PARAM", c("BESRSPI", "INVET")),
selected = "BESRSPI",
multiple = FALSE,
label = "Choose endpoint"
)
adrs_extracted_response <- data_extract_spec(
dataname = "ADRS",
filter = adrs_filters,
select = select_spec(
choices = variable_choices(ADRS, c("AVALC", "AVAL")),
selected = "AVALC",
multiple = FALSE,
fixed = FALSE
)
)
fact_vars_adrs <- names(Filter(isTRUE, sapply(ADRS, is.factor)))
adrs_extracted_response_fct <- data_extract_spec(
dataname = "ADRS",
filter = adrs_filters,
select = select_spec(
choices = variable_choices(ADRS, subset = fact_vars_adrs),
selected = "AVALC",
multiple = FALSE,
fixed = FALSE
)
)
adlb_filter_paramcd <- filter_spec(
vars = "PARAMCD",
choices = value_choices(ADLB, "PARAMCD", "PARAM"),
selected = levels(ADLB$PARAMCD)[1],
multiple = FALSE,
label = "Select lab:"
)
adlb_filter_paramcd2 <- filter_spec(
vars = "PARAMCD",
choices = value_choices(ADLB, "PARAMCD", "PARAM"),
selected = levels(ADLB$PARAMCD)[2],
multiple = FALSE,
label = "Select lab:"
)
adlb_filter_visit <- filter_spec(
vars = "AVISIT",
choices = levels(ADLB$AVISIT),
selected = levels(ADLB$AVISIT)[1],
multiple = FALSE,
label = "Select visit:"
)
adlb_extracted_aval <- data_extract_spec(
dataname = "ADLB",
select = select_spec(
choices = variable_choices(ADLB, c("AVAL", "CHG", "PCHG", "ANRIND",
"BASE")),
selected = "AVAL",
multiple = FALSE,
fixed = FALSE
),
filter = list(
adlb_filter_paramcd,
adlb_filter_visit
)
)
numeric_vars_adlbpca <- names(Filter(isTRUE, sapply(ADLBPCA, is.numeric)))
distr_filter_spec <- filter_spec(
vars = choices_selected(
variable_choices(ADSL, fact_vars_adsl),
selected = NULL
),
multiple = TRUE
)
## App header and footer ----
nest_logo <- "
https://raw.githubusercontent.com/insightsengineering/hex-stickers/main/PNG/nest.png
"
app_source <- "
https://github.com/insightsengineering/teal.gallery/tree/main/exploratory"
gh_issues_page <- "
https://github.com/insightsengineering/teal.gallery/issues"
header <- tags$span(
style = "display: flex; align-items: center; justify-content:
space-between; margin: 10px 0 10px 0;",
tags$span("My first teal app", style = "font-size: 30px;"),
tags$span(
style = "display: flex; align-items: center;",
tags$img(src = nest_logo, alt = "NEST logo", height = "45px", style =
"margin-right:10px;"),
tags$span(style = "font-size: 24px;", "NEST @ Roche")
)
)
footer <- tags$p(
"This teal app is brought to you by the NEST Team at Roche/Genentech.
For more information, please visit:",
tags$a(href = app_source, target = "_blank", "Source Code"), ", ",
tags$a(href = gh_issues_page, target = "_blank", "Report Issues")
)
# Add before module definitions
fact_vars_adsl <- names(Filter(is.factor, ADSL))
numeric_vars_adsl <- names(Filter(is.numeric, ADSL))
adsl_extracted_fct2 <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL, subset = fact_vars_adsl),
selected = fact_vars_adsl[1],
multiple = FALSE,
fixed = FALSE
)
)
adsl_extracted_fct3 <- adsl_extracted_fct2 # Replace with proper
definition if needed
app <- init(
data = data,
filter = teal_slices(
count_type = "all",
teal_slice(dataname = "ADSL", varname = "SEX"),
teal_slice(dataname = "ADSL", varname = "AGE")
),
modules = modules(
teal.modules.general::tm_front_page(
label = "App Info",
header_text = c(
"Info about input data source" =
"This app uses CDISC ADaM datasets randomly generated by
`random.cdisc.data` R packages"
),
tables = list(
`NEST packages used in this demo app` = data.frame(Packages =
c("teal.modules.general", "random.cdisc.data"))
)
),
teal.modules.general::tm_file_viewer(
label = "File viewer",
input_path = list(
png = "https://www.r-project.org/logo/Rlogo.png",
Rmd = "
https://raw.githubusercontent.com/tidyverse/dplyr/master/README.Rmd",
pdf = "
https://cran.r-project.org/web/packages/shinyTree/shinyTree.pdf"
)
),
teal.modules.general::tm_data_table("Data Table"),
teal.modules.general::tm_variable_browser("Variable Browser"),
teal.modules.general::tm_missing_data("Missing Data"),
teal.modules.general::tm_g_distribution(
"Distribution",
dist_var = adsl_extracted_numeric,
strata_var = data_extract_spec(
dataname = "ADSL",
filter = distr_filter_spec
),
group_var = data_extract_spec(
dataname = "ADSL",
filter = distr_filter_spec
)
),
teal.modules.general::tm_outliers(
"Outliers",
outlier_var = data_extract_spec(
dataname = "ADLB",
select = select_spec(
choices = variable_choices(ADLB, c("AVAL", "CHG", "PCHG",
"BASE")),
selected = "AVAL",
multiple = FALSE,
fixed = FALSE
)
),
categorical_var = data_extract_spec(
dataname = "ADLB",
select = select_spec(
choices = variable_choices(ADLB, c("PARAM", "PARAMCD")),
selected = NULL,
multiple = FALSE,
fixed = FALSE
)
)
),
teal.modules.general::tm_g_association(
ref = adsl_extracted_num,
vars = adsl_extracted_fct3
),
teal.modules.general::tm_g_bivariate(
x = adsl_extracted_num,
y = adlb_extracted_aval,
row_facet = adsl_extracted_factors,
col_facet = adsl_extracted_factors,
use_density = FALSE,
plot_height = c(600L, 200L, 2000L),
ggtheme = "gray"
),
teal.modules.general::tm_a_regression(
label = "Regression",
response = adsl_extracted_numeric,
regressor = adrs_extracted_response
),
teal.modules.general::tm_g_response(
response = adrs_extracted_response_fct,
x = adsl_extracted_fct2,
row_facet = adsl_extracted_factors,
col_facet = adsl_extracted_factors,
coord_flip = FALSE
),
teal.modules.general::tm_g_scatterplotmatrix(
label = "Scatterplot matrix",
variables = adsl_extracted_multi
),
teal.modules.general::tm_g_scatterplot(
"Scatterplot",
x = adsl_extracted_num,
y = adsl_extracted_num2,
row_facet = adsl_extracted_factors,
col_facet = adsl_extracted_factors,
color_by = adsl_extracted_factors,
size = 3, alpha = 1,
plot_height = c(600L, 200L, 2000L)
),
teal.modules.general::tm_t_crosstable(
"Table Choices",
x = adsl_extracted_fct2,
y = adsl_extracted_fct
),
teal.modules.general::tm_a_pca(
"Principal Component Analysis",
dat = data_extract_spec(
dataname = "ADLBPCA",
select = select_spec(
choices = variable_choices(ADLBPCA, numeric_vars_adlbpca),
selected = c("ALT - WEEK 5 DAY 36", "CRP - WEEK 5 DAY 36", "IGA -
WEEK 5 DAY 36"),
multiple = TRUE,
fixed = FALSE,
label = "Variable"
),
),
plot_height = c(600L, 200L, 2000L),
plot_width = c(600L, 200L, 2000L)
)
)
) |>
modify_title(
title = "Exploratory Analysis Teal Demo App",
favicon = nest_logo
) |>
modify_header(header) |>
modify_footer(footer)
shinyApp(app$ui, app$server)
On Thu, May 8, 2025 at 4:05 PM Dony Unardi @.***> wrote:
donyunardi left a comment (insightsengineering/teal.gallery#202) https://github.com/insightsengineering/teal.gallery/issues/202#issuecomment-2864644186
Hi @probert7-git2 https://github.com/probert7-git2 Please provide screenshot and code so we can reproduce your issue
— Reply to this email directly, view it on GitHub https://github.com/insightsengineering/teal.gallery/issues/202#issuecomment-2864644186, or unsubscribe https://github.com/notifications/unsubscribe-auth/BQH2MY4RCC6IVZ7Y43RKHYD25PPM7AVCNFSM6AAAAAB37HFFAGVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDQNRUGY2DIMJYGY . You are receiving this because you were mentioned.Message ID: @.***>
You don't need to put the library outside of the within() statement. If you don't see any data, then maybe there's something wrong with how the teal_data() was constructed.
The code that you provided is very similar with the exploratory app code from teal.gallery, with a little update. However, I can't reproduce your issue because I ran into this error message: "Error: object 'fact_vars_adsl' not found". It appears that you moved the creation of this object later in the code when it's needed in the beginning. Can you please check this? I need reproducible code so I can understand your problem. Also, please provide screenshot and sessionInfo() so we can help you better.
@donyunardi I think you can run
fact_vars_adsl <- names(Filter(is.factor, ADSL))
just after data creation
Thanks,
Then I can see the data just fine. @probert7-git2 please follow @m7pr suggestion.
Code
# Safety Data Review App from Git Hub Imageengineering
# install.packages("pak")
# pak::pak("insightsengineering/teal")
#
#
#
# install.packages(“teal.modules.clinical”)
#
# install.packages(“teal.modules.general”)
#install.packages(“random.cdisc.data”)
library(teal.modules.general)
library(teal.modules.clinical)
library(random.cdisc.data)
library(dplyr)
library(tidyr)
library(ggExtra)
library(ggpmisc)
library(ggpp)
library(goftest)
library(gridExtra)
library(htmlwidgets)
library(jsonlite)
library(lattice)
library(MASS)
library(rlang)
library(rtables)
library(nestcolor)
library(broom)
library(colourpicker)
library(sparkline)
options(
shiny.useragg = FALSE,
teal.ggplot2_args = teal.widgets::ggplot2_args(labs = list(caption =
"NEST PROJECT"))
)
ADSL <- radsl(seed = 1)
ADRS <- radrs(ADSL, seed = 1)
ADLB <- radlb(ADSL, seed = 1)
ADLBPCA <- ADLB %>%
dplyr::select(USUBJID, STUDYID, SEX, ARMCD, AVAL, AVISIT, PARAMCD) %>%
tidyr::pivot_wider(
values_from = "AVAL",
names_from = c("PARAMCD", "AVISIT"),
names_sep = " - "
)
# Data reproducible code ----
#data <- teal_data()
#data <- within(data, {
# ADSL <- ADSL
# ADRS <- ADRS
# ADLB <- ADLB
# ADLBPCA <- ADLBPCA
# })
data <- teal_data(
ADSL = ADSL,
ADRS = ADRS,
ADLB = ADLB,
ADLBPCA = ADLBPCA )
#the default_cdisc_join_keys cannot also include ADLBPCA which has no CDISC
# metadata
join_keys(data) <- default_cdisc_join_keys[c("ADSL", "ADLB", "ADRS")]
## Reusable Configuration For Modules
ADSL <- data[["ADSL"]]
ADRS <- data[["ADRS"]]
ADLB <- data[["ADLB"]]
ADLBPCA <- data[["ADLBPCA"]]
adsl_extracted_num <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL),
selected = "AGE",
multiple = FALSE,
fixed = FALSE
)
)
adsl_extracted_num2 <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL),
selected = "BMRKR1",
multiple = FALSE,
fixed = FALSE
)
)
adsl_extracted_fct <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL),
selected = "ARMCD",
multiple = FALSE,
fixed = FALSE
)
)
fact_vars_adsl <- names(Filter(is.factor, ADSL))
# numeric_vars_adsl <- names(Filter(is.numeric, ADSL))
numeric_vars_adsl <- names(Filter(isTRUE, sapply(ADSL, is.numeric)))
adsl_extracted_numeric <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL, subset = numeric_vars_adsl),
selected = "BMRKR1",
multiple = FALSE,
fixed = FALSE
)
)
adsl_extracted_factors <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL, subset = fact_vars_adsl),
selected = NULL,
multiple = FALSE,
fixed = FALSE
)
)
adsl_extracted_multi <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL),
selected = c("AGE", "BMRKR1"),
multiple = TRUE,
fixed = FALSE
)
)
adrs_filters <- filter_spec(
vars = "PARAMCD",
sep = " - ",
choices = value_choices(ADRS, "PARAMCD", "PARAM", c("BESRSPI", "INVET")),
selected = "BESRSPI",
multiple = FALSE,
label = "Choose endpoint"
)
adrs_extracted_response <- data_extract_spec(
dataname = "ADRS",
filter = adrs_filters,
select = select_spec(
choices = variable_choices(ADRS, c("AVALC", "AVAL")),
selected = "AVALC",
multiple = FALSE,
fixed = FALSE
)
)
fact_vars_adrs <- names(Filter(isTRUE, sapply(ADRS, is.factor)))
adrs_extracted_response_fct <- data_extract_spec(
dataname = "ADRS",
filter = adrs_filters,
select = select_spec(
choices = variable_choices(ADRS, subset = fact_vars_adrs),
selected = "AVALC",
multiple = FALSE,
fixed = FALSE
)
)
adlb_filter_paramcd <- filter_spec(
vars = "PARAMCD",
choices = value_choices(ADLB, "PARAMCD", "PARAM"),
selected = levels(ADLB$PARAMCD)[1],
multiple = FALSE,
label = "Select lab:"
)
adlb_filter_paramcd2 <- filter_spec(
vars = "PARAMCD",
choices = value_choices(ADLB, "PARAMCD", "PARAM"),
selected = levels(ADLB$PARAMCD)[2],
multiple = FALSE,
label = "Select lab:"
)
adlb_filter_visit <- filter_spec(
vars = "AVISIT",
choices = levels(ADLB$AVISIT),
selected = levels(ADLB$AVISIT)[1],
multiple = FALSE,
label = "Select visit:"
)
adlb_extracted_aval <- data_extract_spec(
dataname = "ADLB",
select = select_spec(
choices = variable_choices(ADLB, c("AVAL", "CHG", "PCHG", "ANRIND",
"BASE")),
selected = "AVAL",
multiple = FALSE,
fixed = FALSE
),
filter = list(
adlb_filter_paramcd,
adlb_filter_visit
)
)
numeric_vars_adlbpca <- names(Filter(isTRUE, sapply(ADLBPCA, is.numeric)))
distr_filter_spec <- filter_spec(
vars = choices_selected(
variable_choices(ADSL, fact_vars_adsl),
selected = NULL
),
multiple = TRUE
)
## App header and footer ----
nest_logo <- "
https://raw.githubusercontent.com/insightsengineering/hex-stickers/main/PNG/nest.png
"
app_source <- "
https://github.com/insightsengineering/teal.gallery/tree/main/exploratory"
gh_issues_page <- "
https://github.com/insightsengineering/teal.gallery/issues"
header <- tags$span(
style = "display: flex; align-items: center; justify-content:
space-between; margin: 10px 0 10px 0;",
tags$span("My first teal app", style = "font-size: 30px;"),
tags$span(
style = "display: flex; align-items: center;",
tags$img(src = nest_logo, alt = "NEST logo", height = "45px", style =
"margin-right:10px;"),
tags$span(style = "font-size: 24px;", "NEST @ Roche")
)
)
footer <- tags$p(
"This teal app is brought to you by the NEST Team at Roche/Genentech.
For more information, please visit:",
tags$a(href = app_source, target = "_blank", "Source Code"), ", ",
tags$a(href = gh_issues_page, target = "_blank", "Report Issues")
)
# Add before module definitions
fact_vars_adsl <- names(Filter(is.factor, ADSL))
numeric_vars_adsl <- names(Filter(is.numeric, ADSL))
adsl_extracted_fct2 <- data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(ADSL, subset = fact_vars_adsl),
selected = fact_vars_adsl[1],
multiple = FALSE,
fixed = FALSE
)
)
adsl_extracted_fct3 <- adsl_extracted_fct2 # Replace with proper
# definition if needed
app <- init(
data = data,
filter = teal_slices(
count_type = "all",
teal_slice(dataname = "ADSL", varname = "SEX"),
teal_slice(dataname = "ADSL", varname = "AGE")
),
modules = modules(
teal.modules.general::tm_front_page(
label = "App Info",
header_text = c(
"Info about input data source" =
"This app uses CDISC ADaM datasets randomly generated by
`random.cdisc.data` R packages"
),
tables = list(
`NEST packages used in this demo app` = data.frame(Packages =
c("teal.modules.general", "random.cdisc.data"))
)
),
teal.modules.general::tm_file_viewer(
label = "File viewer",
input_path = list(
png = "https://www.r-project.org/logo/Rlogo.png",
Rmd = "
https://raw.githubusercontent.com/tidyverse/dplyr/master/README.Rmd",
pdf = "
https://cran.r-project.org/web/packages/shinyTree/shinyTree.pdf"
)
),
teal.modules.general::tm_data_table("Data Table"),
teal.modules.general::tm_variable_browser("Variable Browser"),
teal.modules.general::tm_missing_data("Missing Data"),
teal.modules.general::tm_g_distribution(
"Distribution",
dist_var = adsl_extracted_numeric,
strata_var = data_extract_spec(
dataname = "ADSL",
filter = distr_filter_spec
),
group_var = data_extract_spec(
dataname = "ADSL",
filter = distr_filter_spec
)
),
teal.modules.general::tm_outliers(
"Outliers",
outlier_var = data_extract_spec(
dataname = "ADLB",
select = select_spec(
choices = variable_choices(ADLB, c("AVAL", "CHG", "PCHG",
"BASE")),
selected = "AVAL",
multiple = FALSE,
fixed = FALSE
)
),
categorical_var = data_extract_spec(
dataname = "ADLB",
select = select_spec(
choices = variable_choices(ADLB, c("PARAM", "PARAMCD")),
selected = NULL,
multiple = FALSE,
fixed = FALSE
)
)
),
teal.modules.general::tm_g_association(
ref = adsl_extracted_num,
vars = adsl_extracted_fct3
),
teal.modules.general::tm_g_bivariate(
x = adsl_extracted_num,
y = adlb_extracted_aval,
row_facet = adsl_extracted_factors,
col_facet = adsl_extracted_factors,
use_density = FALSE,
plot_height = c(600L, 200L, 2000L),
ggtheme = "gray"
),
teal.modules.general::tm_a_regression(
label = "Regression",
response = adsl_extracted_numeric,
regressor = adrs_extracted_response
),
teal.modules.general::tm_g_response(
response = adrs_extracted_response_fct,
x = adsl_extracted_fct2,
row_facet = adsl_extracted_factors,
col_facet = adsl_extracted_factors,
coord_flip = FALSE
),
teal.modules.general::tm_g_scatterplotmatrix(
label = "Scatterplot matrix",
variables = adsl_extracted_multi
),
teal.modules.general::tm_g_scatterplot(
"Scatterplot",
x = adsl_extracted_num,
y = adsl_extracted_num2,
row_facet = adsl_extracted_factors,
col_facet = adsl_extracted_factors,
color_by = adsl_extracted_factors,
size = 3, alpha = 1,
plot_height = c(600L, 200L, 2000L)
),
teal.modules.general::tm_t_crosstable(
"Table Choices",
x = adsl_extracted_fct2,
y = adsl_extracted_fct
),
#
teal.modules.general::tm_a_pca(
"Principal Component Analysis",
dat = data_extract_spec(
dataname = "ADLBPCA",
select = select_spec(
choices = variable_choices(ADLBPCA, numeric_vars_adlbpca),
selected = c("ALT - WEEK 5 DAY 36", "CRP - WEEK 5 DAY 36", "IGA - WEEK 5 DAY 36"),
multiple = TRUE,
fixed = FALSE,
label = "Variable"
),
),
plot_height = c(600L, 200L, 2000L),
plot_width = c(600L, 200L, 2000L)
)
)
) |>
modify_title(
title = "Exploratory Analysis Teal Demo App",
favicon = nest_logo
) |>
modify_header(header) |>
modify_footer(footer)
shinyApp(app$ui, app$server)
Closing
I ran this code and the same issue occurs. The display object appears with all the analysis type options but when I click on any of them there is no data that are displayed. I would have tried to debug with a browse() function in the server function but the TEAL modules shelter the user from the server function. So, I can't look inside the module to see what data were selected.
R version 4.4.1 (2024-06-14 ucrt) Platform: x86_64-w64-mingw32/x64 Running under: Windows 11 x64 (build 22631)
Matrix products: default
locale: [1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8 LC_MONETARY=English_United States.utf8 [4] LC_NUMERIC=C LC_TIME=English_United States.utf8
time zone: America/Los_Angeles tzcode source: internal
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages: [1] colourpicker_1.3.0 broom_1.0.6 rlang_1.1.4 MASS_7.3-60.2 [5] lattice_0.22-6 jsonlite_1.8.9 htmlwidgets_1.6.4 gridExtra_2.3 [9] goftest_1.2-3 ggpmisc_0.6.1 ggpp_0.5.8-1 ggExtra_0.10.1 [13] sparkline_2.0 nestcolor_0.1.3 teal.modules.clinical_0.10.0 tern_0.9.8 [17] rtables_0.6.12 magrittr_2.0.3 formatters_0.5.11 logger_0.4.0 [21] teal.logger_0.3.2 tidyr_1.3.1 dplyr_1.1.4 random.cdisc.data_0.3.16 [25] teal.modules.general_0.4.1 teal.transform_0.6.0 ggmosaic_0.3.3 ggplot2_3.5.2 [29] teal_0.16.0 teal.slice_0.6.0 teal.data_0.7.0 teal.code_0.6.1 [33] shiny_1.9.1
loaded via a namespace (and not attached): [1] Rdpack_2.6.4 polynom_1.4-1 bsicons_0.1.2 tern.gee_0.1.5 sandwich_3.1-1 [6] multcomp_1.4-28 compiler_4.4.1 vctrs_0.6.5 quantreg_6.1 stringr_1.5.1 [11] pkgconfig_2.0.3 fastmap_1.2.0 backports_1.5.0 fontawesome_0.5.3 utf8_1.2.4 [16] promises_1.3.2 rmarkdown_2.29 MatrixModels_0.5-4 purrr_1.0.2 xfun_0.52 [21] cachem_1.1.0 teal.reporter_0.4.0 later_1.4.1 R6_2.6.1 bslib_0.9.0 [26] stringi_1.8.4 lubridate_1.9.3 jquerylib_0.1.4 estimability_1.5.1 Rcpp_1.0.13-1 [31] knitr_1.50 zoo_1.8-14 httpuv_1.6.15 Matrix_1.7-0 splines_4.4.1 [36] timechange_0.3.0 tidyselect_1.2.1 rstudioapi_0.16.0 yaml_2.3.10 codetools_0.2-20 [41] miniUI_0.1.1.1 teal.widgets_0.4.3.9002 tibble_3.2.1 withr_3.0.2 evaluate_1.0.3 [46] survival_3.8-3 pillar_1.10.2 checkmate_2.3.2 renv_1.1.4 DT_0.33 [51] shinyjs_2.1.0 plotly_4.10.4 generics_0.1.3 mirai_2.2.0 munsell_0.5.1 [56] scales_1.3.0 xtable_1.8-4 glue_1.7.0 emmeans_1.11.0 lazyeval_0.2.2 [61] tools_4.4.1 shinyTree_0.3.1 data.table_1.16.0 SparseM_1.84-2 fs_1.6.4 [66] mvtnorm_1.3-3 grid_4.4.1 rbibutils_2.3 crosstalk_1.2.1 colorspace_2.1-1 [71] nlme_3.1-164 cli_3.6.3 viridisLite_0.4.2 geepack_1.3.12 gtable_0.3.6 [76] sass_0.4.10 digest_0.6.37 ggrepel_0.9.6 TH.data_1.1-3 nanonext_1.5.2 [81] memoise_2.0.1 htmltools_0.5.8.1 lifecycle_1.0.4 httr_1.4.7 shinyWidgets_0.9.0 [86] mime_0.12
On Mon, May 26, 2025 at 4:13 PM Vedha Viyash @.***> wrote:
vedhav left a comment (insightsengineering/teal.gallery#202) https://github.com/insightsengineering/teal.gallery/issues/202#issuecomment-2910747587
@probert7-git2 https://github.com/probert7-git2 Could you share your sessionInfo()?
— Reply to this email directly, view it on GitHub https://github.com/insightsengineering/teal.gallery/issues/202#issuecomment-2910747587, or unsubscribe https://github.com/notifications/unsubscribe-auth/BQH2MY22QSKXJND2U3ICEE33AON2RAVCNFSM6AAAAAB37HFFAGVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDSMJQG42DONJYG4 . You are receiving this because you were mentioned.Message ID: @.***>