Lea7885
Reputation: 97
Edit filtered reactive data frame in shiny, save user input for use in app
I'm working on an editable table that contains reactive filters for columns AND rows. I implemented the code YBS provided and it looks exactly the way I want and displays correctly. The issue I have is that, I cannot access the updated data frame on the server side. The reason I want a data frame is so that I have information of the changed cells. Each cell value (and references) will serve as an input for a table. I tried to create a different dataframe using observeEvent on my_matrix_cell_edit and rbind but no result
Below is the reprex, when you run it, on the console side I get "NULL'. Is this caused by df <- reactiveValues(data=NULL) that is constantly resetting it?
Thanks all for your help!
country_matrix <- structure(list(industry_group = c("Financial Institutions Group (FIG)",
"Financial Institutions Group (FIG)", "Financial Institutions Group (FIG)",
"Financial Institutions Group (FIG)", "Financial Institutions Group (FIG)",
"Financial Institutions Group (FIG)"), sector = c("Housing Finance",
"Climate Finance", "Climate Finance", "Trade Finance", "Housing Finance",
"Housing Finance"), component = c("Stakeholder", "Stakeholder",
"Environment & Social", "Stakeholder", "Environment & Social",
"Economywide"), subcomponent = c("Access", "Credit: Mitigation",
"Environment", "Environment", "Environment", "Economywide"),
Afghanistan = c(0, 0, 0, 0, 0, 0), Angola = c(0, 0, 0, 0,
0, 0), Albania = c(0, 0, 0, 0, 0, 0), Argentina = c(0, 0,
0, 0, 0, 0), Armenia = c(0, 0, 0, 0, 0, 0), `American Samoa` = c(0,
0, 0, 0, 0, 0), Azerbaijan = c(0, 0, 0, 0, 0, 0), Burundi = c(0,
0, 0, 0, 0, 0), Benin = c(0, 0, 0, 0, 0, 0), `Burkina Faso` = c(0,
0, 0, 0, 0, 0), Bangladesh = c(0, 0, 0, 0, 0, 0), Bulgaria = c(0,
0, 0, 0, 0, 0), `Bosnia and Herzegovina` = c(0, 0, 0, 0,
0, 0), Belarus = c(0, 0, 0, 0, 0, 0), Belize = c(0, 0, 0,
0, 0, 0), Bolivia = c(0, 0, 0, 0, 0, 0), Brazil = c(0, 0,
0, 0, 0, 0), Barbados = c(0, 0, 0, 0, 0, 0), Bhutan = c(0,
0, 0, 0, 0, 0), Botswana = c(0, 0, 0, 0, 0, 0), `Central African Republic` = c(0,
0, 0, 0, 0, 0)
), row.names = c(NA, 6L), class = "data.frame")
###
countrycmx <- names(country_matrix)[5:25]
ui <- fluidPage(
fluidRow(
column(12,
column(
2,
pickerInput(
"sectormx",
'Sector',
selected = "Climate Finance",
choices = unique(country_matrix$sector),
#selected = c('SME Finance', 'Insurance', 'Climate Finance'),
multiple = TRUE)
),
column(
2,
pickerInput(
'componentmx',
'Component',
choices = unique(country_matrix$component),
selected = 'Stakeholder',
multiple = TRUE,
options = pickerOptions(
actionsBox = TRUE,
liveSearch = TRUE,
liveSearchPlaceholder = 'Search...',
liveSearchNormalize = TRUE,
liveSearchStyle = 'contains'
),
width = "100%"
)
),
column(
2,
pickerInput(
'subcomponentmx',
'Subcomponent',
choices = unique(country_matrix$subcomponent),
selected = 'Quality',
multiple = TRUE,
options = pickerOptions(
actionsBox = TRUE,
liveSearch = TRUE,
liveSearchPlaceholder = 'Search...',
liveSearchNormalize = TRUE,
liveSearchStyle = 'contains'
),
width = "100%"
)) ,
column(
2,
pickerInput(
'countrymx',
'Country',
choices = countrycmx,
selected = 'Albania',
multiple = TRUE,
options = pickerOptions(
actionsBox = TRUE,
liveSearch = TRUE,
liveSearchPlaceholder = 'Search...',
liveSearchNormalize = TRUE,
liveSearchStyle = 'contains'
),
width = "100%"
))
#actionButton("update", "Update Data set", class = "btn-primary",style='padding:4px; font-size:120%')
),
# Show a plot of the generated distribution
column(12,
DTOutput("my_matrix")
)
)
)
server <- function(input, output, session) {
matrix <- reactive({
req(input$sectormx, input$componentmx, input$subcomponentmx)
country_matrix %>%
dplyr::filter(
sector %in% input$sectormx#,
) %>%
select(sector,component,subcomponent,input$countrymx)
})
df <- reactiveValues(data=NULL)
observe({df$data <- matrix()})
output$my_matrix <- renderDT(df$data, editable = TRUE, rownames = FALSE)
#observeEvent(input$my_matrix_cell_edit, {
observeEvent(input$my_matrix_cell_edit, {
info = input$my_matrix1_cell_edit
str(info)
i = info$row
j = info$col + 1
v = info$value
df$data[i, j] <<- editData(info, df$data[i, j])
})
}
shinyApp(ui = ui, server = server)
Upvotes: 0
Views: 684
Answers (2)
Lea7885
Reputation: 97
Thanks to YBS and some additional help I got a fully working solution :
library(data.table)
library(DT)
library(dplyr)
library(tidyr)
country_matrix <- structure(list(industry_group = c("Financial Institutions Group (FIG)",
"Financial Institutions Group (FIG)", "Financial Institutions Group (FIG)",
"Financial Institutions Group (FIG)", "Financial Institutions Group (FIG)",
"Financial Institutions Group (FIG)"), sector = c("Housing Finance",
"Climate Finance", "Climate Finance", "Trade Finance", "Housing Finance",
"Housing Finance"), component = c("Stakeholder", "Stakeholder",
"Environment & Social", "Stakeholder", "Environment & Social",
"Economywide"), subcomponent = c("Access", "Credit: Mitigation",
"Environment", "Environment", "Environment", "Economywide"),
Afghanistan = c(0, 0, 0, 0, 0, 0), Angola = c(0, 0, 0, 0,
0, 0), Albania = c(0, 0, 0, 0, 0, 0), Argentina = c(0, 0,
0, 0, 0, 0), Armenia = c(0, 0, 0, 0, 0, 0), `American Samoa` = c(0,
0, 0, 0, 0, 0), Azerbaijan = c(0, 0, 0, 0, 0, 0), Burundi = c(0,
0, 0, 0, 0, 0), Benin = c(0, 0, 0, 0, 0, 0), `Burkina Faso` = c(0,
0, 0, 0, 0, 0), Bangladesh = c(0, 0, 0, 0, 0, 0), Bulgaria = c(0,
0, 0, 0, 0, 0), `Bosnia and Herzegovina` = c(0, 0, 0, 0,
0, 0), Belarus = c(0, 0, 0, 0, 0, 0), Belize = c(0, 0, 0,
0, 0, 0), Bolivia = c(0, 0, 0, 0, 0, 0), Brazil = c(0, 0,
0, 0, 0, 0), Barbados = c(0, 0, 0, 0, 0, 0), Bhutan = c(0,
0, 0, 0, 0, 0), Botswana = c(0, 0, 0, 0, 0, 0), `Central African Republic` = c(0,
0, 0, 0, 0, 0)
), row.names = c(NA, 6L), class = "data.frame")
###
countrycmx <- names(country_matrix)[5:25]
ui <- fluidPage(
fluidRow(
column(12,
column(
2,
pickerInput(
"sectormx",
'Sector',
selected = "Climate Finance",
choices = unique(country_matrix$sector),
#selected = c('SME Finance', 'Insurance', 'Climate Finance'),
multiple = TRUE)
),
column(
2,
pickerInput(
'componentmx',
'Component',
choices = unique(country_matrix$component),
selected = 'Stakeholder',
multiple = TRUE,
options = pickerOptions(
actionsBox = TRUE,
liveSearch = TRUE,
liveSearchPlaceholder = 'Search...',
liveSearchNormalize = TRUE,
liveSearchStyle = 'contains'
),
width = "100%"
)
),
column(
2,
pickerInput(
'subcomponentmx',
'Subcomponent',
choices = unique(country_matrix$subcomponent),
selected = 'Quality',
multiple = TRUE,
options = pickerOptions(
actionsBox = TRUE,
liveSearch = TRUE,
liveSearchPlaceholder = 'Search...',
liveSearchNormalize = TRUE,
liveSearchStyle = 'contains'
),
width = "100%"
)) ,
column(
2,
pickerInput(
'countrymx',
'Country',
choices = countrycmx,
selected = 'Albania',
multiple = TRUE,
options = pickerOptions(
actionsBox = TRUE,
liveSearch = TRUE,
liveSearchPlaceholder = 'Search...',
liveSearchNormalize = TRUE,
liveSearchStyle = 'contains'
),
width = "100%"
))
#actionButton("update", "Update Data set", class = "btn-primary",style='padding:4px; font-size:120%')
),
# Show a plot of the generated distribution
column(12,
DTOutput("my_matrix")
)
)
)
server <- function(input, output, session) {
matrix <- reactive({
req(input$sectormx, input$componentmx, input$subcomponentmx)
country_matrix %>%
dplyr::filter(
sector %in% input$sectormx#,
#component %in% input$componentmx,
#subcomponent %in% input$subcomponentmx
) %>%
select(sector,component,subcomponent,input$countrymx)
})
df <- reactiveVal(NULL)
observe({
df(matrix())
})
output$my_matrix <- renderDT(df(), editable = TRUE, rownames = FALSE)
observeEvent(input$my_matrix_cell_edit, {
#browser()
info = input$my_matrix_cell_edit
print(info)
t <- df()
t[info$row, info$col+1] <- as.numeric(info$value)
df(t)
})
}
shinyApp(ui = ui, server = server)
Upvotes: 0
YBS
Reputation: 21349
Try this
country_matrix <- structure(list(industry_group = c("Financial Institutions Group (FIG)",
"Financial Institutions Group (FIG)", "Financial Institutions Group (FIG)",
"Financial Institutions Group (FIG)", "Financial Institutions Group (FIG)",
"Financial Institutions Group (FIG)"), sector = c("Housing Finance",
"Climate Finance", "Climate Finance", "Trade Finance", "Housing Finance",
"Housing Finance"), component = c("Stakeholder", "Stakeholder",
"Environment & Social", "Stakeholder", "Environment & Social",
"Economywide"), subcomponent = c("Access", "Credit: Mitigation",
"Environment", "Environment", "Environment", "Economywide"),
Afghanistan = c(1, 1, 1, 1, 1, 1), Angola = c(1, 1, 1, 1,
1, 1), Albania = c(1, 1, 1, 1, 1, 1), Argentina = c(1, 1,
1, 1, 1, 1), Armenia = c(1, 1, 1, 1, 1, 1), `American Samoa` = c(1,
1, 1, 1, 1, 1), Azerbaijan = c(1, 1, 1, 1, 1, 1), Burundi = c(1,
1, 1, 1, 1, 1), Benin = c(1, 1, 1, 1, 1, 1), `Burkina Faso` = c(1,
1, 1, 1, 1, 1), Bangladesh = c(1, 1, 1, 1, 1, 1), Bulgaria = c(1,
1, 1, 1, 1, 1), `Bosnia and Herzegovina` = c(1, 1, 1, 1,
1, 1), Belarus = c(1, 1, 1, 1, 1, 1), Belize = c(1, 1, 1,
1, 1, 1), Bolivia = c(1, 1, 1, 1, 1, 1), Brazil = c(1, 1,
1, 1, 1, 1), Barbados = c(1, 1, 1, 1, 1, 1), Bhutan = c(1,
1, 1, 1, 1, 1), Botswana = c(1, 1, 1, 1, 1, 1), `Central African Republic` = c(1,
1, 1, 1, 1, 1)
), row.names = c(NA, 6L), class = "data.frame")
###
countrycmx <- names(country_matrix)[5:25]
ui <- fluidPage(
# Application title
#titlePanel("Old Faithful Geyser Data"),
# Sidebar with a slider input for number of bins
fluidRow(
column(12,
column(
2,
pickerInput(
"sectormx",
'Sector',
selected = "Climate Finance",
choices = unique(country_matrix$sector),
#selected = c('SME Finance', 'Insurance', 'Climate Finance'),
multiple = TRUE)
),
column(
2,
pickerInput(
'componentmx',
'Component',
choices = unique(country_matrix$component),
selected = 'Stakeholder',
multiple = TRUE,
options = pickerOptions(
actionsBox = TRUE,
liveSearch = TRUE,
liveSearchPlaceholder = 'Search...',
liveSearchNormalize = TRUE,
liveSearchStyle = 'contains'
),
width = "100%"
)
),
column(
2,
pickerInput(
'subcomponentmx',
'Subcomponent',
choices = unique(country_matrix$subcomponent),
selected = 'Quality',
multiple = TRUE,
options = pickerOptions(
actionsBox = TRUE,
liveSearch = TRUE,
liveSearchPlaceholder = 'Search...',
liveSearchNormalize = TRUE,
liveSearchStyle = 'contains'
),
width = "100%"
)) ,
column(
2,
pickerInput(
'countrymx',
'Country',
choices = countrycmx,
selected = 'Albania',
multiple = TRUE,
options = pickerOptions(
actionsBox = TRUE,
liveSearch = TRUE,
liveSearchPlaceholder = 'Search...',
liveSearchNormalize = TRUE,
liveSearchStyle = 'contains'
),
width = "100%"
))
#selectInput("select", "Select country", c('col1', 'col2'), multiple = TRUE),
#actionButton("update", "Update Data set", class = "btn-primary",style='padding:4px; font-size:120%')
),
# Show a plot of the generated distribution
column(12,
DTOutput("my_matrix")
#DTOutput("table")
)
)
)
server <- function(input, output, session) {
matrix <- reactive({
req(input$sectormx, input$componentmx, input$subcomponentmx)
country_matrix %>%
dplyr::filter(
sector %in% input$sectormx#,
#component %in% input$componentmx,
#subcomponent %in% input$subcomponentmx
) %>%
select(sector,component,subcomponent,input$countrymx)
})
df <- reactiveValues(data=NULL)
observe({df$data <- matrix()})
output$my_matrix <- renderDT(df$data, editable = TRUE, rownames = FALSE)
observeEvent(input$my_matrix_cell_edit, {
info = input$my_matrix1_cell_edit
str(info)
i = info$row
j = info$col + 1
v = info$value
df$data[i, j] <<- DT:::coerceValue(v, df$data[i, j])
#replaceData(proxy, x, resetPaging = FALSE, rownames = FALSE)
})
}
shinyApp(ui = ui, server = server)
Upvotes: 1
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