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server.R
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library(dplyr)
library(ggplot2)
library(stringr)
library(tidyr)
options(scipen=999) # disable scientific number formatting
shinyServer(function(input, output, session) {
output$country <- renderUI({
country_names <- unique(FAOcountryProfile$FAO_TABLE_NAME)
opts <- selectInput("country_name", "Pick a Country:",choices = country_names, selected=country_names[1])
list(opts)
})
output$group <- renderUI({
groupNames <- groupTable[["groupName"]]
opts <- selectInput("gc_name", "Which Group are you looking for:",choices = groupNames, selected=groupNames[2])
list(opts)
})
output$indicator <- renderUI({
if (input$trade_production %in% "Production"){
fao_meta2 <- fao_meta %>% filter(!(Element %in% c("Export Quantity","Export Value",
"Import Quantity","Import Value")))
items <- unique(fao_meta2$Item)
items <- items[c(-125)]
}
if (input$trade_production %in% "Trade"){
fao_meta2 <- fao_meta %>% filter(Element %in% c("Export Quantity","Export Value",
"Import Quantity","Import Value"))
items <- unique(fao_meta2$Item)
items <- items[c(-76,-287,-390)]
}
opts <- selectInput("indicator_name", "Pick an item:",choices = items, selected = items[2])
list(opts)
})
#item_to_pick <- "Bananas"
data_trade <- reactive({
fao_meta3 <- fao_meta %>% filter(Element %in% c("Export Quantity","Export Value","Import Quantity","Import Value"),
Item %in% input$indicator_name)
file_name <- str_replace_all(unique(fao_meta3$file_name), ".RData", "")
ids <- unique(fao_meta3$id)
dat <- get(file_name)
dat2 <- dat[c("CountryCode","Year",ids)]
dat3 <- gather(dat2, var, value, 3:ncol(dat2))
dat3$var <- as.character(dat3$var)
vars <- as.character(unique(dat3$var))
for (i in vars){
dat3$var[dat3$var %in% i] <- fao_meta[fao_meta$id %in% i,]$Element
}
names(dat3)[names(dat3)=="CountryCode"] <- "FAOST_CODE"
dat3 <- left_join(dat3,FAOcountryProfile[c("FAOST_CODE","FAO_TABLE_NAME","SHORT_NAME")])
dat3[dat3$FAOST_CODE != 41,]
})
data_production <- reactive({
fao_meta3 <- fao_meta %>% filter(!(Element %in% c("Export Quantity","Export Value","Import Quantity","Import Value")),
Item %in% input$indicator_name)
file_name <- str_replace_all(unique(fao_meta3$file_name), ".RData", "")
ids <- unique(fao_meta3$id)
dat <- get(file_name)
dat2 <- dat[c("CountryCode","Year",ids)]
dat3 <- gather(dat2, var, value, 3:ncol(dat2))
dat3$var <- as.character(dat3$var)
vars <- as.character(unique(dat3$var))
for (i in vars){
dat3$var[dat3$var %in% i] <- fao_meta[fao_meta$id %in% i,]$Element
}
names(dat3)[names(dat3)=="CountryCode"] <- "FAOST_CODE"
dat3 <- left_join(dat3,FAOcountryProfile[c("FAOST_CODE","FAO_TABLE_NAME","SHORT_NAME")])
dat3[dat3$FAOST_CODE != 41,]
})
output$yearYear <- renderUI({
if (input$trade_production %in% "Trade") data <- data_trade()
if (input$trade_production %in% "Production") data <- data_production()
maxim <- max(data$Year)
minim <- min(data$Year)
opts <- sliderInput("year_year", "Select year", min = minim, max = maxim, value = maxim, step = 1,animate = TRUE)
list(opts)
})
output$yearRange <- renderUI({
if (input$trade_production %in% "Trade") data <- data_trade()
if (input$trade_production %in% "Production") data <- data_production()
maxim <- max(data$Year)
minim <- min(data$Year)
opts <- sliderInput("year_range", "Select year range", min = minim, max = maxim, value = c(minim,maxim), step = 1)
list(opts)
})
output$mytable = renderDataTable({
#fao_data()
#d <- data_trade()
d <- data_production()
d %>% filter(Year > input$year_range[1], Year < input$year_range[2])
d %>% filter(Year == input$year_year)
},options = list(pageLength = 100))
# ------------------------------------------------------------
# ------------------------------------------------------------
# ------------------------------------------------------------
# Define the boxes
# ------------------------------------------------------------
# ------------------------------------------------------------
output$page_title <- renderUI({
#paste(input$trade_production,"of",input$item_name)
input$indicator_name
})
output$box_1_1 <- renderValueBox({
if (input$trade_production %in% "Production"){
dd <- data_production()
#dd <- dat3
value <- round(dd[dd$Year == input$year_year & dd$FAOST_CODE == 5000 & dd$var %in% "Production",]$value / 1000000,1)
#value <- round(dd[dd$Year == 2000 & dd$FAOST_CODE == 5000 & dd$var %in% "Production",]$value / 1000000,1)
valueBox(subtitle=paste("Production quantity in",input$year_year),
value=paste0(value," million tonnes"),
icon = icon("th"),
color = "green")
} else {
dd <- data_trade()
value <- round(dd[dd$Year == input$year_year & dd$FAOST_CODE == 5000 & dd$var %in% "Export Value",]$value / 1000000,1)
valueBox(subtitle="Total export value",
value=paste(value,"million US$"),
icon = icon("fa fa-plane"),
color = "red")
}
})
output$box_1_2 <- renderValueBox({
# Define the box
if (input$trade_production %in% "Production"){
dd <- data_production()
value <- round(dd[dd$Year == input$year_year & dd$FAOST_CODE == 5000 & dd$var %in% "Area harvested",]$value / 1000000,1)
valueBox(subtitle=paste("Area harvested in ",input$year_year),
value=paste0(value,"million hectares"),
icon = icon("globe"),
color = "green")
} else {
dd <- data_trade()
value <- round(dd[dd$Year == input$year_year & dd$FAOST_CODE == 5000 & dd$var %in% "Import Value",]$value / 1000000,1)
valueBox(subtitle="Total import value",value=paste(value,"million US$"),
icon = icon("fa fa-plane fa-rotate-180"),
color = "red")
}
})
output$box_1_3 <- renderInfoBox({
if (input$trade_production %in% "Production"){
dd <- data_production()
#dd <- dat3
value <- round(dd[dd$Year == input$year_year & dd$FAOST_CODE == 5000 & dd$var %in% "Yield",]$value,1)
#value <- round(dd[dd$Year == 2000 & dd$FAOST_CODE == 5000 & dd$var %in% "Production",]$value / 1000000,1)
infoBox(title=paste("Yield in",input$year_year),
value=paste0(value," unit here"),
icon = icon("signal"),
color = "aqua")
} else {
dd <- data_trade()
value <- round(dd[dd$Year == input$year_year & dd$FAOST_CODE == 5000 & dd$var %in% "Export Quantity",]$value / 1000000,1)
infoBox(title="Total export quantity",
value=paste(value,"million tonnes"),
icon = icon("fa fa-plane"),
color = "yellow")
}
})
output$box_1_4 <- renderInfoBox({
if (input$trade_production %in% "Production"){
dd <- data_production()
#dd <- dat3
value <- round(dd[dd$Year == input$year_year & dd$FAOST_CODE == 5000 & dd$var %in% "Seed",]$value,1)
infoBox(title=paste("Seed in",input$year_year),value=paste0(value," unit here"),icon = icon("cubes"),color = "aqua",width=6)
} else {
dd <- data_trade()
value <- round(dd[dd$Year == input$year_year & dd$FAOST_CODE == 5000 & dd$var %in% "Import Quantity",]$value / 1000000,1)
infoBox(title="Total import quantity",
value=paste(value,"million tonnes"),
icon = icon("fa fa-plane fa-rotate-180"),
color = "yellow")
}
})
output$sub_title1 <- renderUI({
if (input$trade_production %in% "Production") subtitle <- paste("Top 10 countries in",input$year_year)
if (input$trade_production %in% "Trade") subtitle <- paste("Top 10 countries in",input$year_year)
subtitle
})
# RANKS
output$box_2_1 <- renderPlot({
if (input$trade_production %in% "Production"){
dd <- data_production()
dd <- dd[!is.na(dd$SHORT_NAME),]
top10 <- dd %>% filter(Year == input$year_year, FAOST_CODE < 5000, var %in% "Production") %>% arrange(-value) %>% slice(1:10)
p <- ggplot(top10, aes(x=reorder(SHORT_NAME,value),y=value,fill=factor(SHORT_NAME)))
p <- p + geom_bar(stat="identity",position="dodge")
p <- p + labs(title = "Production quantity")
p <- p + theme_minimal()
p <- p + coord_flip()
p <- p + theme(legend.position="none")
p <- p + theme(axis.text.x = element_text(angle=90, color = "dim grey"))
p <- p + theme(axis.text.y = element_text(size=16, family = "Ubuntu", color="dim grey"))
p <- p + theme(title = element_text(size=18, family = "Ubuntu", color="dim grey",hjust = 0))
p <- p + theme(axis.title = element_blank())
p <- p + theme(axis.ticks = element_blank())
}
if (input$trade_production %in% "Trade"){
dd <- data_trade()
dd <- dd[!is.na(dd$SHORT_NAME),]
top10 <- dd %>% filter(Year == input$year_year, FAOST_CODE < 5000, var %in% "Export Value") %>% arrange(-value) %>% slice(1:10)
p <- ggplot(top10, aes(x=reorder(SHORT_NAME,value),y=value,fill=factor(SHORT_NAME)))
p <- p + geom_bar(stat="identity",position="dodge")
p <- p + labs(title = "Export Value")
p <- p + theme_minimal()
p <- p + coord_flip()
p <- p + theme(legend.position="none")
p <- p + theme(axis.text.x = element_text(angle=90, color = "dim grey"))
p <- p + theme(axis.text.y = element_text(size=16, family = "Ubuntu", color="dim grey"))
p <- p + theme(title = element_text(size=18, family = "Ubuntu", color="dim grey",hjust = 0))
p <- p + theme(axis.title = element_blank())
p <- p + theme(axis.ticks = element_blank())
}
p
})
output$box_2_2 <- renderPlot({
if (input$trade_production %in% "Production"){
dd <- data_production()
dd <- dd[!is.na(dd$SHORT_NAME),]
top10 <- dd %>% filter(Year == input$year_year, FAOST_CODE < 5000, var %in% "Area harvested") %>% arrange(-value) %>% slice(1:10)
p <- ggplot(top10, aes(x=reorder(SHORT_NAME,value),y=value,fill=factor(SHORT_NAME)))
p <- p + geom_bar(stat="identity",position="dodge")
p <- p + labs(title = "Area harvested")
p <- p + theme_minimal()
p <- p + coord_flip()
p <- p + theme(legend.position="none")
p <- p + theme(axis.text.x = element_text(angle=90, color = "dim grey"))
p <- p + theme(axis.text.y = element_text(size=16, family = "Ubuntu", color="dim grey" ))
p <- p + theme(title = element_text(size=18, family = "Ubuntu", color="dim grey",hjust = 0))
p <- p + theme(axis.title = element_blank())
p <- p + theme(axis.ticks = element_blank())
p
}
if (input$trade_production %in% "Trade"){
dd <- data_trade()
dd <- dd <- dd[!is.na(dd$SHORT_NAME),]
top10 <- dd %>% filter(Year == input$year_year, FAOST_CODE < 5000, var %in% "Import Value") %>% arrange(-value) %>% slice(1:10)
p <- ggplot(top10, aes(x=reorder(SHORT_NAME,value),y=value,fill=factor(SHORT_NAME)))
p <- p + geom_bar(stat="identity",position="dodge")
p <- p + labs(title = "Import value")
p <- p + theme_minimal()
p <- p + coord_flip()
p <- p + theme(legend.position="none")
p <- p + theme(axis.text.x = element_text(angle=90, color = "dim grey"))
p <- p + theme(axis.text.y = element_text(size=16, family = "Ubuntu", color="dim grey"))
p <- p + theme(title = element_text(size=18, family = "Ubuntu", color="dim grey",hjust = 0))
p <- p + theme(axis.title = element_blank())
p <- p + theme(axis.ticks = element_blank())
}
p
})
output$sub_title2 <- renderUI({
if (input$trade_production %in% "Production") subtitle <- "Growth"
if (input$trade_production %in% "Trade") subtitle <- "Growth"
subtitle
})
output$box_3_1 <- renderPlot({
if (input$trade_production %in% "Production"){
dd <- data_production()
top10 <- dd %>% filter(Year == input$year_range[2], FAOST_CODE < 5000, var %in% "Production") %>% arrange(-value) %>% slice(1:10)
dat_plot <- dd[dd$FAOST_CODE %in% top10$FAOST_CODE,]
dat_plot <- dat_plot %>% filter(var %in% "Production", Year >= input$year_range[1], Year <= input$year_range[2])
p <- ggplot(dat_plot, aes(x=Year,y=value,color=factor(SHORT_NAME)))
p <- p + geom_text(data=dat_plot[dat_plot$Year == input$year_range[2],],
aes(x=Year,y=value,label=SHORT_NAME,color=SHORT_NAME),
size=4, hjust=-0.2, family="Ubuntu")
p <- p + geom_point() + geom_line()
p <- p + labs(title = "Production quantity")
p <- p + theme_minimal()
#p <- p + coord_flip()
p <- p + theme(legend.position="none")
p <- p + theme(axis.text.y = element_text(color = "dim grey"))
#p <- p + theme(axis.text.y = element_text(size=16, family = "Ubuntu", color="dim grey" ))
p <- p + theme(title = element_text(size=18, family = "Ubuntu", color="dim grey",hjust = .5))
p <- p + theme(axis.title = element_blank())
p <- p + theme(axis.ticks = element_blank())
p <- p + coord_cartesian(xlim=c(input$year_range[1],input$year_range[2]+((input$year_range[2]-input$year_range[1])*.2)))
p <- p + scale_x_continuous(breaks=c(input$year_range[1]:input$year_range[2]))
p <- p + theme(axis.text.x = element_text(angle = 90, color = "dim grey"))
}
if (input$trade_production %in% "Trade"){
dd <- data_trade()
top10 <- dd %>% filter(Year == input$year_range[2], FAOST_CODE < 5000, var %in% "Import Value") %>% arrange(-value) %>% slice(1:10)
dat_plot <- dd[dd$FAOST_CODE %in% top10$FAOST_CODE,]
dat_plot <- dat_plot %>% filter(var %in% "Import Value", Year >= input$year_range[1], Year <= input$year_range[2])
p <- ggplot(dat_plot, aes(x=Year,y=value,color=factor(SHORT_NAME), group=factor(SHORT_NAME)))
p <- p + geom_text(data=dat_plot[dat_plot$Year == input$year_range[2],],
aes(x=Year,y=value,label=SHORT_NAME,color=SHORT_NAME),
size=4, hjust=-0.2, family="Ubuntu")
#p <- p + geom_bar(stat="identity",position="dodge")
p <- p + geom_line()
p <- p + labs(title = "Import value")
p <- p + theme_minimal()
#p <- p + coord_flip()
p <- p + theme(legend.position="none")
p <- p + theme(axis.text.y = element_text(color = "dim grey"))
#p <- p + theme(axis.text.y = element_text(size=16, family = "Ubuntu", color="dim grey" ))
p <- p + theme(title = element_text(size=18, family = "Ubuntu", color="dim grey",hjust = .5))
p <- p + theme(axis.title = element_blank())
p <- p + theme(axis.ticks = element_blank())
p <- p + coord_cartesian(xlim=c(input$year_range[1],input$year_range[2]+((input$year_range[2]-input$year_range[1])*.2)))
p <- p + scale_x_continuous(breaks=c(input$year_range[1]:input$year_range[2]))
p <- p + theme(axis.text.x = element_text(angle = 90, color = "dim grey"))
#p <- p + coord_cartesian(xlim=c(min(dat_plot$Year),max(dat_plot$Year*1.1)))
}
p
})
output$box_3_2 <- renderTable({
mtcars$names <- rownames(mtcars)
mtcars %>% slice(1:11) %>% select(names,disp)
})
})