edit: I realized only changing the mutate to be mutate(y = lubridate::ymd_hms(timestamp)) resolves the issue in both cases. My new question would be why does this resolve the issue in dplyer mutate?

I am having trouble generating a plot after parsing my datetime column, timestamp, into POSIXct format. The plot I want to create is timestamp vs. SOEC_FC_0200_PIDPI_VAL0. The problem is occurring when I perform mutate and when I define aes() in ggplot. If I mutate timestamp and store in a new column i.e. y and use aes(y, SOEC_FC_0200_PIDPI_VAL0), the plot will render as intended. I am confused why parsing into POSIXct format in the same timestamp column does not generate a plot.

I don’t see why mutate to the same column would cause issue, so my best guess is that aes() is referring to a different timestamp than the one I want.

library(shiny)
library(ggplot2)
library(dplyr)
library(DateTimeRangePicker)

ui <- fluidPage(
  DateTimeRangePickerInput('date_range', from = '2024-06-11 14:00:00', to = '2024-06-11 14:00:05'),
  actionButton('run', 'Run'),
  plotOutput('plot')
)

server <- function(input,output){
  
  data_input <- structure(list(timestamp = c("2024-06-11 14:00:00.0076393", "2024-06-11 14:00:01.0134811", 
                                             "2024-06-11 14:00:02.0112244", "2024-06-11 14:00:03.0090309", 
                                             "2024-06-11 14:00:04.0058750"), timestamp_utc = c("2024-06-11 18:00:00.0076393", 
                                                                                               "2024-06-11 18:00:01.0134811", "2024-06-11 18:00:02.0112244", 
                                                                                               "2024-06-11 18:00:03.0090309", "2024-06-11 18:00:04.0058750"), 
                               sequence_number = 56500303:56500307, SOEC_EC_0510_PIDPI_VAL0 = c(151.346252441406, 
                                                                                                151.346252441406, 151.323455810547, 151.351745605469, 151.355331420898
                               ), SOEC_FC_0200_PIDPI_VAL0 = c(3.9853515625, 3.99609375, 
                                                              4.017578125, 4.0068359375, 4.0068359375)), row.names = c(NA, 
                                                                                                                       5L), class = "data.frame")
  
  data_input_0  <- data_input |> mutate(timestamp = lubridate::ymd_hms(timestamp))
  
  data_filtered <- eventReactive(input$run,
                                 filter(data_input_0, as.POSIXct(timestamp) >= as.POSIXct(input$date_range[1]) & as.POSIXct(timestamp) <= as.POSIXct(input$date_range[2]))
  )
  
  output$plot <- renderPlot(
    ggplot(data_filtered(), aes(x = timestamp, y = SOEC_FC_0200_PIDPI_VAL0))+geom_point()
  )
}

shinyApp(ui = ui, server = server)

This problem is related to another issue I am having. When I incorporate fileInput() in the user interface and change data_input to take in the imported .csv file, the same issue occurs. Except now, even when I mutate to a new y column, the plot will still not render even though the .csv file contains the same data as before.

library(shiny)
library(ggplot2)
library(dplyr)
library(DateTimeRangePicker)

ui <- fluidPage(
  fileInput("csv_input", "Select file", accept = ".csv"),
  DateTimeRangePickerInput('date_range', from = '2024-06-11 14:00:00', to = '2024-06-11 14:00:05'),
  actionButton('run', 'Run'),
  plotOutput('plot')
)

server <- function(input,output){
  
  data_input <- reactive({
    req(input$csv_input)
    df <- read.csv(input$csv_input$datapath)
    return(df)
  })
  
  data_input_0 <- reactive({data_input() |> mutate(y = lubridate::ymd_hms(timestamp))
  })
  
  data_filtered <- eventReactive(input$run,{
    filter(data_input_0(), as.POSIXct(timestamp) >= as.POSIXct(input$date_range[1]) & as.POSIXct(timestamp) <= as.POSIXct(input$date_range[2]))
  })
  
  
  output$plot <- renderPlot(
    ggplot(data_filtered(), aes(x = timestamp, y = SOEC_TE_0304_IOPI_VAL0))+geom_point()
  )
}

shinyApp(ui = ui, server = server)