Data is not seen by the Shiny app

[sik]

Hello,

I am a beginner in R, building my first Shiny app. I ran into a problem: when I run the app, it doesn't display any data - all valueboxes and plots are empty, the datatable is empty. No error shows up though. This happened after I modified the dataset and broke down the datetime column in day, month, year, dayofweek, hour, minute (I did the modification in a separate Rmd file and saved the dataframe successfully). The new dataframe imports successfully in Rstudio. Could someone please point me to what I'm doing wrong? Here is my code:

if(!require(plotly)){install.packages(c("plotly"))}
library(tidyverse)
library(shiny)
library(shinydashboard)
library(DT)
library(lubridate)
library(fontawesome)
library(scales)
library(readxl)
library(tmap) 
library(maps)       
library(sf)         
library(mapsf)       
library(viridis)
library(leaflet)


load("ufo_my_project1.RData")


ui <- dashboardPage(    
  dashboardHeader(title = "UFO Sightings - USA"),                   
  dashboardSidebar(                                            
    sliderInput("years", h4("Years"),                        
                min = 1950, max = 2010,                      
                value = c(1950, 2010), step = 5, sep = ""),                                           
    selectInput("state", h4("State"),
                choices = c("All states", as.character(unique(ufo$state)) %>% sort()),
                selected = "All states", multiple = TRUE)
  ),
  
  dashboardBody(
    tabBox(
      height='920px', width = 12,
      tabPanel('Welcome', valueBoxOutput('box1'), valueBoxOutput('box2'), valueBoxOutput('box3'),
               'INSERT WELCOME TEXT HERE'),
      tabPanel('States Analysis', "INSERT WELCOME TEXT HERE", plotOutput('plot1', height = "510px"), plotOutput('plot2', height = "510px")),
      tabPanel('Shapes Exploration', plotOutput('plot3')),
      tabPanel('Time & Date', plotOutput('plot4')),
      tabPanel('Map of Occurences', plotOutput('plot5')),
      tabPanel('Sentiment Analysis', plotOutput('plot6')),
      tabPanel('Data', DT::dataTableOutput ("table_1"))
    )
  )
)



server <- function(input, output){ 
  data <- reactive({  
    if(input$state == "All states"){
      ufo %>%                  
        filter(year >= input$years[1],
               year <= input$years[2])
    } else {
      ufo %>%                  
        filter(year >= input$years[1],
               year <= input$years[2],
               state %in% input$state)
    }
  })




output$table_1  <- DT::renderDataTable({data()}, 
                                       options = list(   
                                         lengthMenu = list(c(10, 12, 19), c('10 lines', '12 rows', '19 items')),   
                                         pageLength = 10
                                         ))

output$box1 <- renderValueBox({
  ufo <- data()
  valueBox(
    value = nrow(ufo),
    subtitle =  "Total UFO Sightings", 
    icon = icon("satellite", lib = "font-awesome"),
    color = "olive"
  )
})

output$box2 <- renderValueBox({
  ufo <- data()
  valueBox(
    value = n_distinct(ufo$ufo_shape),
    subtitle =  "Different UFO Shapes Observed", 
    icon = icon("shapes", lib = "font-awesome"),
    color = "olive"
  )
})

output$box3 <- renderValueBox({
  ufo <- data()
  valueBox(
    value = n_distinct(ufo$city),
    subtitle =  "US Cities Where UFOs Were Seen", 
    icon = icon("city", lib = "font-awesome"),
    color = "olive"
  )
})

output$plot1 <- renderPlot(
  data() %>%
    group_by(state) %>%
    na.omit()%>%
    summarize(nb_occurences=n()) %>%
    ggplot(aes(nb_occurences, reorder(state, nb_occurences))) + geom_col(stat ='identity') + geom_col(fill = "#A4B9C2",  alpha = 0.5)
)


output$plot2 <- renderPlot(
  data() %>%
    group_by(city) %>%
    na.omit()%>%
    summarize(nb_occurences=n()) %>%
    top_n(20, nb_occurences) %>%
    ggplot(aes(nb_occurences, reorder(city, nb_occurences))) + geom_col(stat ='identity') + geom_col(fill = "#A4B9C2",  alpha = 0.5)
)

output$plot3 <- renderPlot(
  data() %>%
    group_by(ufo_shape) %>%
    na.omit()%>%
    summarize(nb_occurences=n()) %>%
    ggplot(aes(x=ufo_shape, y=nb_occurences)) + 
    geom_point(size=3) + 
    geom_segment(aes(x=ufo_shape, 
                     xend=ufo_shape, 
                     y=0, 
                     yend=nb_occurences)) + 
    labs(title="Lollipop Chart", 
         subtitle="Make Vs Avg. Mileage", 
         caption="source: mpg") + 
    theme(axis.text.x = element_text(angle=30, vjust=0.6)))


output$plot4 <- renderPlot(
  data() %>%
    group_by(ufo_shape, state) %>%
    summarise(count = n()) %>%
    top_n(n = 5, wt = count) %>%
    ggplot(aes(x = state, y = count) + geom_col(stat ='identity') + facet_grid()
    ))

output$plot5 <- renderPlot(
  data() %>%
    group_by(year) %>%
    na.omit()%>%
    summarize(nb_occurences=n()) %>%
    ggplot(aes(nb_occurences, reorder(year), nb_occurences))) + geom_col(stat ='identity') + geom_col(fill = "#A4B9C2",  alpha = 0.5)

}

# Run the app ----
shinyApp(ui = ui, server = server)