output$bar3 <- renderPlotly({

     s <- CT_Data2 %>% filter(Sector == input$Sector & Airline == input$Airline1)
     d <- group_by(s, Booking.Month, Agency.Group)
     f <- summarize(d,num1 = sum(Bookings), num2 = sum(Pax))
     l = dcast(f, Booking.Month ~ Agency.Group, value.var= "num1")
     print(l)
     print(str(l))
     colNames <- names(l)[-1]
     print(colNames)

     p <- plotly::plot_ly()
     for(trace in colNames)
     {
       p <- p %>% plotly::add_trace(data = l,x = ~Booking.Month, y = ~trace, name = trace)

     }
     p %>% layout(title = "Trend Over Time",
              xaxis = list(title = ""),
              yaxis = list (title = "Value"),type='bar')

})

'data.frame':   5 obs. of  3 variables:
 $ Booking.Month: chr  "Aug" "Jul" "Jun" "Oct" ...
 $ Cleartrip    : num  NA NA NA 10 NA
 $ ROM          : num  32 31 21 25 20

Booking.Month Cleartrip ROM
1           Aug        NA  32
2           Jul        NA  31
3           Jun        NA  21
4           Oct        10  25
5           Sep        NA  20