My Shiny App - UK Fisheries Activity Explorer dashboard

Data for the dashboard's Charts section were sourced from UK Government website. Fishing ports were geolocated using geocode() function from ggmap package, thus producing the map in Map of Ports section. Let's take a look at the master dataset fisheriesData.

head(fisheriesData,2)

        Date Port.of.Landing           Port.NUTS.2.area Port.Nationality
1 2014-01-01       Aberdaran West Wales and the Valleys            Wales
2 2014-01-01       Aberdaran West Wales and the Valleys            Wales
  Vessel.Nationality Length.Group  Species Species.Group
1                 UK    10m&Under    Crabs     Shellfish
2                 UK    10m&Under Lobsters     Shellfish
  Live.weight..tonnes. Landed.weight..tonnes. Value..000s.       Lon
1               0.2826                 0.2826      0.33912 -4.711515
2               0.0030                 0.0030      0.04300 -4.711515
       Lat
1 52.80473
2 52.80473

The App was designed using shiny's flexdashboard package and deployed on shinyapps.io website. Plotly package is applied to all charts to enhance interactivity. Below are sample codes where ggplotly responds to user input to radio button Criteria.

string <- reactive(substring(input$Criteria,1,5))

output$plot1 <- renderPlotly ({ 
        if (string() == "Live ") { 
   p1 <-   ggplot(fisheries_trim, aes(x = Month.number, y = Live.Weight, fill = Year, colour = Year)) + geom_point(size = 6, shape = 18) + scale_x_continuous(name="Month of the Year", breaks=seq(1,12,1),labels= c("Jan", "Feb", "Mar", "Apr", "May", "Jun","Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) + scale_y_continuous(name="Live Weight in '000 tonnes") + ggtitle("Fisheries activity over 12 months (Live Weight)") + theme(plot.title = element_text(size=12, face="bold")) 

   ggplotly(p1)%>%layout(margin=list(l=70, b=120))
        }  

Full codes can be found in my github repository here - please open the link in a new tab.