I am developing a Shiny App, where the user can upload data, do some manipulations & create new df from selected rows. I have got till where I can add actionButtons per row in DT but cant make selections work. Selections work as expected if actionButtons are not included in the DT rows. What am I looking for?
1. To be able to toggle between two colors on click within each of the DT row (Orange = not selected; Green = selected, when clicked)
2. Create new data frame from selected rows of the datatable on another actionButton click (Ex: Category 01 or Category 02).
Once any of the Category 01 or Category 02 actionButton is clicked. I get this error Error: incorrect number of dimensions. As shown at the bottom of Image 2.
I have added reproducible code below.
Any help is much appreciated
As in screenshot1, actionbuttons are Orange And in screenshot2 they are Green ,
Data
data <- data.frame(Name = rep(paste("RIS", 1:20, sep = "_")),
Gender = rep(c("Male", "Female"), each = 10),
CDC = rnorm(20),
FDC = rnorm(20),
RDC = rnorm(20),
LDC = rnorm(20)
)
Example Code
library(shiny)
library(DT)
ui <- fluidPage(
titlePanel("simpleApp"),
sidebarLayout(
sidebarPanel(fileInput("file1", "Upload Input file", accept = ".csv"), width = 2,
actionButton("calc", "Calculate"),
hr(style = "border-color: red; height: 5px"),
actionButton("gen1", "Category 01"),
actionButton("gen2", "Category 02")),
mainPanel (
dataTableOutput("table"),
dataTableOutput("table2"),
dataTableOutput("select_table1"),
dataTableOutput("select_table2"))))
server <- function(input, output, session) {
addButtonColumn <- function(df, id, ...) {
f <- function(i) {
as.character(
actionButton(paste(id, i, sep = "_"), class = "btn-warning btn-sm", label = tags$strong("Select"),
onclick = 'Shiny.setInputValue(\"addPressed\", this.id, {priority: "event"})'))
}
addCol <- unlist(lapply(seq_len(nrow(df)), f))
DT::datatable(cbind(Decision = addCol, df),
escape = FALSE, filter = "top", options = list(columnDefs = list(list(targets = 1, sortable = FALSE))))
}
data <- reactive({
df <- input$file1
if(is.null(df))
return(NULL)
df <- read.csv(df$datapath, header = TRUE, sep = ",", row.names = NULL)
return(df)
})
output$table <- DT::renderDataTable(data(), options = list(paging = t, pageLength = 6))
table2 <- eventReactive(input$calc, {
df2 <- input$file1
if(is.null(df2))
return(NULL)
table2 <- data() %>%
mutate("Selection" = CDC * RDC + FDC * LDC) %>%
mutate(across(where(is.numeric), round, 3)) %>%
addButtonColumn("Button")
})
output$table2 <- DT::renderDataTable(table2(), options = list(paging = t, pageLength = 6))
select_table1 <- eventReactive(input$gen1, {
if(is.null(table2)){
return(NULL)
} else {
select_table1 <- table2()[input$table2_rows_selected,]
}
})
select_table2 <- eventReactive(input$gen2, {
if(is.null(table2)){
return(NULL)
} else {
select_table2 <- table2()[input$table2_rows_selected,]
}
})
output$select_table1 <- DT::renderDataTable(select_table1(), options = list(paging = t, pageLength = 6))
output$select_table2 <- DT::renderDataTable(select_table2(), options = list(paging = t, pageLength = 6))
}
shinyApp(ui = ui, server = server)
Some simple CSS can do it.
You called DT::datatable too early in the eventReactive. You need to call it within renderDataTable, otherwise, the render function can't recognize it properly (it can, but table2_rows_selected will not work).
df <- data.frame(Name = rep(paste("RIS", 1:20, sep = "_")),
Gender = rep(c("Male", "Female"), each = 10),
CDC = rnorm(20),
FDC = rnorm(20),
RDC = rnorm(20),
LDC = rnorm(20)
)
library(shiny)
library(DT)
ui <- fluidPage(
titlePanel("simpleApp"),
sidebarLayout(
sidebarPanel(fileInput("file1", "Upload Input file", accept = ".csv"), width = 2,
actionButton("calc", "Calculate"),
hr(style = "border-color: red; height: 5px"),
actionButton("gen1", "Category 01"),
actionButton("gen2", "Category 02")),
mainPanel (
dataTableOutput("table"),
dataTableOutput("table2"),
dataTableOutput("select_table1"),
dataTableOutput("select_table2"))),
tags$style(
'
table.dataTable tr.selected button {
background-color: green;
border-color: green;
}
'
)
)
server <- function(input, output, session) {
addButtonColumn <- function(df, id, ...) {
f <- function(i) {
as.character(
actionButton(paste(id, i, sep = "_"), class = "btn-warning btn-sm", label = tags$strong("Select"),
onclick = 'Shiny.setInputValue(\"addPressed\", this.id, {priority: "event"})'))
}
addCol <- unlist(lapply(seq_len(nrow(df)), f))
cbind(Decision = addCol, df)
}
data <- reactive({
df
})
output$table <- DT::renderDataTable(data(), options = list(paging = t, pageLength = 6))
table2 <- eventReactive(input$calc, {
df2 <- df
if(is.null(df2))
return(NULL)
data() %>%
mutate("Selection" = CDC * RDC + FDC * LDC) %>%
mutate(across(where(is.numeric), round, 3)) %>%
addButtonColumn("Button")
})
output$table2 <- DT::renderDataTable(DT::datatable(
table2(), escape = FALSE, filter = "top",
options = list(columnDefs = list(list(targets = 1, sortable = FALSE, paging = t, pageLength = 6)))
))
select_table1 <- eventReactive(input$gen1, {
if(is.null(table2)){
return(NULL)
} else {
print(input$table2_rows_selected)
select_table1 <- table2()[input$table2_rows_selected,]
}
})
select_table2 <- eventReactive(input$gen2, {
if(is.null(table2)){
return(NULL)
} else {
select_table2 <- table2()[input$table2_rows_selected,]
}
})
output$select_table1 <- DT::renderDataTable(DT::datatable(select_table1(), escape = FALSE, options = list(paging = t, pageLength = 6)))
output$select_table2 <- DT::renderDataTable(select_table2(), escape = FALSE, options = list(paging = t, pageLength = 6))
}
shinyApp(ui = ui, server = server)
Disabled your uploading part. You need to change it back.
I have a shiny app linked to a duckdb. Since I have a very big dataset I just want to load in 10'000 rows. However as soon as the user downloads the dataset it should download the entire dataset and not just the first 10'000 rows. So I guess there should be some kind of if condition where i specify the "LIMIT 10000" which reacts on the download handler. However, I dont know how to change the LIMIT based on the download handler.
BestandeslisteDaten_UI <- function(id3, mydb, data_Vertrag){
ns <- NS(id3)
tagList(
fluidRow(
box(
title = "Daten Bestandesliste", status = "primary", solidHeader = TRUE,
collapsible = TRUE, width=9,
DTOutput(ns("dt31"))
),
box(
title = "Einschränkung des Datenset", status = "primary", solidHeader = TRUE,
collapsible = TRUE, width=3, height = "110em",
downloadButton(ns("download32"),"Download entire Table as csv")
)
)
)
}
BestandeslisteDaten_Server <- function(id3, mydb, data_Vertrag){
moduleServer(
id3,
function(input, output, session){
filter_BestandVertrag_Daten <- reactive({
query <- glue_sql("SELECT * FROM data_Vertrag",
.con = mydb)
add_where <- TRUE
query <- glue_sql(query, " LIMIT 10000", .con = mydb)
print(query)
dt <- as.data.table(dbGetQuery(mydb, query))
print(dt)
dt
})
# Data Table
output$dt31 <- renderDT({
filter_BestandVertrag_Daten() %>%
datatable(
extensions = 'Buttons',
options = list(
server = TRUE,
lengthMenu=c(10, 100),
scrollX = TRUE,
scrollY = "500px",
dom = 'Blfrtip'
))
})
# Download Datatable
output$download32 <- downloadHandler(
filename = function() {
paste("Bestandesliste_", Sys.Date(), ".csv", sep="")
},
content = function(file) {
write.csv(filter_BestandVertrag_Daten(), file)
}
)
}
)
}
Here is my problem, I have a couple of tabs and I'm trying to update a map according to a choice in the selectInput() function.
The select option in inputSelect() is activated and points to Los Angeles which should activate the ObserveEvent() or Observe() function but it doesn't when clicking on the Map tab for the first time.
However, I realized that the setView() function doesn't update itself when clicking on the second tab even if I have the selected option set in selectInput().
I want a setView() that reacts to the selected option on the first click on the tab.
The selectize option doesn't bring any difference.
Here is an example of what I would like to replicate.
library(shiny)
library(leaflet)
ui = bs4DashPage(
h1('Exemple'),
br(),
bs4TabSetPanel(id = 'tabs',
side = 'left',
bs4TabPanel(tabName = 'First tab',
active = TRUE,
'Here is some text'),
bs4TabPanel(tabName = 'Second tab',
active = FALSE,
fluidRow(bs4Card(title = 'Inputs',
solidHeader = TRUE,
width = 2,
closable = FALSE,
selectInput(inputId = 'city',
label = 'Select a city',
choices = c('New York','Los Angeles','Seattle'),
selected = 'Los Angeles',
selectize = TRUE)),
bs4Card(title = "Map",
width = 10,
leafletOutput('map'))
)))
)
server <- function(input, output, session) {
output$map <- renderLeaflet({
leaflet() %>%
addTiles() %>%
setView(lng = -95.7129,lat = 37.0902, zoom = 3)
})
observeEvent(input$city, {
if(input$city == 'New York'){
lon <- -74.0060
lat <- 40.7128
} else if(input$city == 'Los Angeles'){
lon <- -118.2437
lat <- 34.0522
} else{
lon <- -122.3321
lat <- 47.6062
}
leafletProxy('map') %>%
setView(lng = lon, lat = lat, zoom = 5)
})
}
shinyApp(ui, server)
Thank you for your help.
I am trying to build a rhandsontable, but this time using dq_render_handsontable as it gives additional functionality to put nice filters and pagination.
In my app i am filtering the data twice based on picker input, this creating two reactive data frames... filter_tbl_1() after first fitering and filter_tbl_2() after 2nd.
The dq_render_handsontable function works fine with filter_tbl_1() data and provides correct filtering. But with filter_tbl_2(), it throws an error. My guess is that it is not able to recognize the filter_tbl_2(). More than that there is no information shown in Error. Will appreciate if someone can help
The minimum reproducible code:
library(dqshiny)
library(rhandsontable)
library(tibble)
library(dplyr)
ui <- fluidPage(
column(
width = 4,
pickerInput(inputId = "carb_input",
label = "Pick carb",
choices = mtcars %>% pull(carb) %>% unique(),
selected = mtcars %>% pull(carb) %>% unique(),
multiple = TRUE,
options = pickerOptions(
actionsBox = TRUE,
liveSearch = TRUE,
size = 10
)),
pickerInput(inputId = "gear_input",
label = "Pick Gear",
choices = NULL,
multiple = TRUE,
options = pickerOptions(
actionsBox = TRUE,
liveSearch = TRUE,
size = 10
))
),
column(
width = 8,
dq_handsontable_output("review_table", 8L),
rHandsontableOutput("test")
)
)
server <- function(input,output,session){
filter_tbl_1 <- reactive({
mtcars %>% rowid_to_column() %>% filter(carb %in% input$carb_input)
})
observeEvent(filter_tbl_1(),{
choices <- filter_tbl_1() %>% pull(gear) %>% unique()
updatePickerInput(session, "gear_input", choices = choices, selected = choices)
})
filter_tbl_2 <- reactive({
req(input$gear_input)
filter_tbl_1() %>% filter(gear %in% input$gear_input)
})
dq_render_handsontable("review_table",
data = reactive(filter_tbl_1()))
output$test <- renderRHandsontable(rhandsontable(filter_tbl_2()))
}
shinyApp(ui,server)
In line dq_render_handsontable("review_table",
data = reactive(filter_tbl_1())), if you replace filter_tbl_1() with filter_tbl_2(), you will see the error.
I have seen that this problem has happened to other people, but their solutions have not worked for me. I have my app.R file and a .RData file with the required inputs in the same ECWA_Strategic_Planning_Tool directory. When I run:
library(rsconnect)
rsconnect::deployApp('C:/Users/mikialynn/Documents/Duke/Spring2017/MP/GISTool/Final/ECWA_Strategic_Planning_Tool')
I get the following error on the web page that opens up:
ERROR: An error has occurred. Check your logs or contact the app author for clarification.
However, I cannot find anything wrong. I install all of my packages, I use relative pathways etc. I am pasting all of the code from my app below. If anyone can spot what I'm doing wrong, I would greatly appreciate it!
library(shiny)
library(leaflet)
library(sp)
library(rgdal)
library(rstudioapi) # For working directory
library(raster)
library(RColorBrewer)
library(rgeos) #Maybe use gSimplify to simplify polygon
library(DT) #To make interactive DataTable
library(plotly) #For pie chart
library(ggplot2) # for layout
# Set Working Directory
setwd(dirname(rstudioapi::getActiveDocumentContext()$path))
# Load R Workspace
load('Shiny.Strategies.RData')
# UI variables
neigh.names <- levels(merge.proj$View)
neigh.default <- c("Urban7")
dt.names <- c('PARCEL_ID', 'PIN', 'OWNER_NAME', 'SITE_ADDRE', 'OWNER_ADDR',
'SUM_ACRE', 'LANDUSE_DE', 'LAND_VALUE', 'TOTAL_VALU', 'SALE_PRICE',
'Pluvial_WtScore', 'Rest_WtScore', 'GI_WtScore', 'SC_WtScore',
'UNCWI_WtScore', 'Total_Score', 'View')
dt.default <- c('PARCEL_ID', 'Pluvial_WtScore', 'Rest_WtScore',
'GI_WtScore', 'SC_WtScore', 'UNCWI_WtScore', 'Total_Score', 'View')
# Build UI
ui <- fluidPage(
titlePanel("ECWA Strategic Planning Tool"),
HTML('<br>'),
column(2,
HTML("<strong>Instructions:</strong><br/><br/>"),
HTML("<p>1) Select weights for parameters and click 'Run' to
initiate tool.<br/><br/>
2) Use rightside panel to adjust Table and Map Settings.<br/>
<br/>
3) Use search/sort functions of Table to identify parcels.
Select row to display Total Score Chart.<br/><br/>
4) Input View and Parcel ID from Table to Map settings to
identify parcel in Map.<br/><br/>
5) When satisfied with weights, click 'Export Shapefile' to
save shapefile of all parcels.<p/><br/>"),
HTML("<strong>Calculate Parcel Scores: </strong><br/>"),
helpText('The sum of the weights must equal to 1.'),
sliderInput(inputId = "weightPluvial", label = "Weight for Pluvial
Flooding",
value = 0.20, min = 0, max = 1),
sliderInput(inputId = "weightRest", label = "Weight for
Restoration",
value = 0.20, min = 0, max = 1),
sliderInput(inputId = "weightGI", label = "Weight for Green
Infrastructure",
value = 0.20, min = 0, max = 1),
sliderInput(inputId = "weightSC", label = "Weight for City
Stormwater Controls",
value = 0.20, min = 0, max = 1),
sliderInput(inputId = "weightUNCWI", label = "Weight for UNCWI",
value = 0.20, min = 0, max = 1),
actionButton("run", "Run"),
actionButton("export", "Export Shapefile")),
column(8,
HTML("<h3><strong>Table Summary</strong></h3>"),
HTML("<br>"),
dataTableOutput("table")),
column(2,
HTML("<p><br><br></p>"),
HTML("<h4>Table Settings:</h4>"),
checkboxGroupInput(inputId = 'show_vars', label = 'Select column(s)
to display in Table:', choices = dt.names, selected = dt.default),
HTML("<strong>Total Score Chart:</strong>"),
helpText("Please select Table row to display pie chart."),
plotlyOutput("pie")
),
fluidRow(
column(8, offset = 2,
HTML("<br>"),
HTML("<h3><strong>Map Display</strong></h3>"),
leafletOutput("map", height = 800),
HTML("<br><br>")),
column(2,
HTML("<p><br><br><br></p>"),
HTML("<h4>Map Settings:</h4>"),
checkboxGroupInput(inputId = 'show_neigh', label = 'Select
View(s) to display in Map:', choices = neigh.names,
selected = neigh.default),
HTML("<br>"),
sliderInput("range", "Select score range to display in Map:", min
= 0.0, max= 10.0, value = as.numeric(c("0.0", "10.0")), step = 0.1),
HTML("<br>"),
HTML("<strong>Parcel Zoom:</strong>"),
helpText("The View and Score Range must contain the parcel of
interest to execute zoom."),
numericInput('parcel','Enter Parcel ID',0)
)
))
# SERVER
server <- function(input, output) {
defaultData <-
eventReactive(input$run, {
# Multiply by Weights
merge.proj#data$Pluvial_WtScore <-
round(merge.proj#data$Pluvial_Score*input$weightPluvial, digits = 1)
merge.proj#data$Rest_WtScore <-
round(merge.proj#data$Rest_Score*input$weightRest, digits = 1)
merge.proj#data$GI_WtScore <-
round(merge.proj#data$GI_Score*input$weightGI, digits = 1)
merge.proj#data$SC_WtScore <-
round(merge.proj#data$SC_Score*input$weightSC, digits = 1)
merge.proj#data$UNCWI_WtScore <-
round(merge.proj#data$UNCWI_Score*input$weightUNCWI, digits = 1)
# Find Total Score
merge.proj#data$Total_Score <- merge.proj#data$Pluvial_WtScore +
merge.proj#data$Rest_WtScore + merge.proj#data$GI_WtScore +
merge.proj#data$SC_WtScore + merge.proj#data$UNCWI_WtScore
return(merge.proj)
})
# Subset by neighborhood
neighData <- reactive ({
merge.proj <- defaultData()
merge.proj[merge.proj$View%in%input$show_neigh,]
})
# Plot with leaflet
# Palette for map
colorpal <- reactive({
merge.proj <- neighData()
colorNumeric(palette = "YlOrRd",
domain = merge.proj$Total_Score)
})
# Pop Up Option for map
# popup <- paste0("<strong>Parcel ID: </strong>",
# merge.proj#data$PARCEL_ID,
# "<br><strong>Total Score: </strong>",
# merge.proj#data$Total_Score)
# Label Option for map
labels <- reactive({
merge.proj <- neighData()
sprintf("<strong>Parcel ID: </strong>%s<br/><strong>Total Score:
</strong>%g",
merge.proj$PARCEL_ID,
merge.proj$Total_Score) %>% lapply(htmltools::HTML)
})
# Render Default Map
output$map <- renderLeaflet ({
merge.proj <- neighData()
pal <- colorpal()
lab <- labels()
leaflet() %>%
#addProviderTiles(provider='Esri.WorldImagery') %>%
# setView(zoom =) %>%
addTiles() %>%
addPolygons(
#data = merge.proj[input$show_neigh,, drop = FALSE],
data=merge.proj,
fillColor = ~pal(Total_Score),
weight = 1,
opacity = 1,
color = "white",
dashArray = "3",
fillOpacity = 0.7,
highlight = highlightOptions(
weight = 3,
color = "#666",
dashArray = "",
fillOpacity = 0.7,
bringToFront = TRUE),
# popup= popup) %>%
label = lab,
labelOptions = labelOptions(
style = list("font-weight" = "normal", padding = "3px 8px"),
textsize = "15px",
direction = "auto")) %>%
addLegend(position = "bottomleft",pal = pal, opacity = 0.7, values =
merge.proj$Total_Score, title = "<strong>Total Score</strong>")
})
# Build Data Table
output$table <- renderDataTable({
merge.proj <- defaultData()
table.dat <- merge.proj[, c('PARCEL_ID', 'PIN', 'OWNER_NAME',
'SITE_ADDRE', 'OWNER_ADDR', 'SUM_ACRE', 'LANDUSE_DE', 'LAND_VALUE',
'TOTAL_VALU', 'SALE_PRICE', 'Pluvial_WtScore', 'Rest_WtScore', 'GI_WtScore',
'SC_WtScore', 'UNCWI_WtScore', 'Total_Score', 'View')]
datatable(data = table.dat#data[, input$show_vars, drop = FALSE],
options = list(lengthMenu = c(5, 10, 20, 30), pageLength = 20), rownames =
FALSE)
})
# Plot-ly
output$pie <- renderPlotly({
merge.proj <- defaultData()
names <- c('Pluvial', 'Rest', 'GI', 'SC', 'UNCWI')
colors <- c('rgb(128,133,133)', 'rgb(211,94,96)', 'rgb(144,103,167)',
'rgb(114,147,203)', 'rgb(171,104,87)')
selectedrowindex <-
input$table_rows_selected[length(input$table_rows_selected)]
selectedrowindex <- as.numeric(selectedrowindex)
df <- data.frame(merge.proj[selectedrowindex, c('Pluvial_WtScore',
'Rest_WtScore', 'GI_WtScore', 'SC_WtScore', 'UNCWI_WtScore')])
vector <- unname(unlist(df[1,]))
if (!is.null(input$table_rows_selected)) {
par(mar = c(4, 4, 1, .1))
plot_ly(labels = names, values = vector, type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
insidetextfont = list(color = '#FFFFFF'),
hoverinfo = 'text',
text = ~paste('Score:', vector),
marker = list(colors = colors,
line = list(color = '#FFFFFF', width = 1)),
#The 'pull' attribute can also be used to create space between the sectors
showlegend = FALSE) %>%
layout(#title = '% Total Score',
xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
}
else {return(NULL)}
})
# Update map to parcel score slider
# Subset data
filteredData <- reactive({
merge.proj <- neighData()
merge.proj[merge.proj#data$Total_Score >= input$range[1] &
merge.proj#data$Total_Score <= input$range[2],]
})
# New Palette
colorpal2 <- reactive({
merge.proj <- filteredData()
colorNumeric(palette = "YlOrRd",
domain = merge.proj$Total_Score)
})
# Pop Up Option
# popup <- paste0("<strong>Parcel ID: </strong>",
# merge.proj#data$PARCEL_ID,
# "<br><strong>Total Score: </strong>",
# merge.proj#data$Total_Score)
# Label Option
labels2 <- reactive({
merge.proj <- filteredData()
sprintf("<strong>Parcel ID: </strong>%s<br/><strong>Total Score:
</strong>%g",
merge.proj$PARCEL_ID,
merge.proj$Total_Score) %>% lapply(htmltools::HTML)
})
#Leaflet Proxy
observe({
merge.proj <- filteredData()
pal2 <- colorpal2()
lab2 <- labels2()
leaf <- leafletProxy("map", data = filteredData()) %>%
clearShapes() %>%
addPolygons(
fillColor = ~pal2(Total_Score),
weight = 1,
opacity = 1,
color = "white",
dashArray = "3",
fillOpacity = 0.7,
highlight = highlightOptions(
weight = 3,
color = "#666",
dashArray = "",
fillOpacity = 0.7,
bringToFront = TRUE),
# popup= popup) %>%
label = lab2,
labelOptions = labelOptions(
style = list("font-weight" = "normal", padding = "3px 8px"),
textsize = "15px",
direction = "auto"))
if(input$parcel>0){
sub.dat <- merge.proj[merge.proj$PARCEL_ID==input$parcel,]
zx <- mean(extent(sub.dat)[1:2])
zy <- mean(extent(sub.dat)[3:4])
leaf <- leaf %>%
setView(lng=zx,lat=zy,zoom=16)
}
leaf
})
#Update Legend
observe({
proxy <- leafletProxy("map", data = filteredData())
pal2 <- colorpal2()
proxy %>% clearControls()
proxy %>% addLegend(position = "bottomleft",pal = pal2, opacity = 0.7,
values = ~Total_Score, title = "<strong>Total Score</strong>")
})
# Export new shapefile
#make so that user can choose name and allow overwrite
observeEvent(input$export, {
merge.proj <- defaultData()
writeOGR(merge.proj, dsn = "Data", layer = "Strategies_Output", driver =
"ESRI Shapefile")
})
}
shinyApp(ui = ui, server = server)
Issue resolved! My initial suspicion was correct; it had to do with the .rdata file. It also relates to shinyapp.io's servers which run on a Linux based server. From my reading, Linux only handles lowercase file paths and extensions. The reason why it worked for the .csv file is because it's pretty common to have the file extension saved in all lowercase. This was not the case for the .RData file. Using the RStudio IDE and the physical "Save Workspace" button, the default file extension is .RData (case sensitive). I couldn't rename the file extension (for some reason, I'm not the most tech-savvy person). Similar to the load() function, there's the save() function. Previously, I used the save() file as follows (note the capitalized .RData at the end):
save(df_training_separated_with_models, file = "sample_data_with_models.RData")
However, using the same function in all lowercase fixes the issue:
save(df_training_separated_with_models, file = "sample_data_with_models.rdata")
Hope this helps any other poor soul with the same issue that is scouring the internet and other forums.
Cheers!