sandbox/shiny/ComparisonApp.R
In SWS-Methodology/faoswsFisheryStandardization: Package to compute Fishery FBS
# get old SUA
greece=fread("data/SUA_standard/GreeceCleaned.csv" , header = TRUE)
austria=fread("data/SUA_standard/AustriaCleaned.csv" , header = TRUE)
chechia=fread("data/SUA_standard/CzechiaCleaned.csv" , header = TRUE)
sua_old=rbind(greece,austria,chechia)
sua_old=melt( sua_old,
id.vars = colnames(sua_old)[c(1:3)],
measure.vars = colnames(sua_old)[c(4:20)],
variable.name = "timePointYears",
value.name = "Value"
)
sua_old[,Status:="OLD"]
#get new SUA
greece=fread("C:/Users/ROSA/Desktop/Fisheries/batch0_SUA_pilotCounties/300.csv" , header = TRUE)
austria=fread("C:/Users/ROSA/Desktop/Fisheries/batch0_SUA_pilotCounties/40.csv" , header = TRUE)
chechia=fread("C:/Users/ROSA/Desktop/Fisheries/batch0_SUA_pilotCounties/203.csv" , header = TRUE)
sua_new=rbind(greece,austria,chechia)
sua_new[,availability:=NULL]
sua_new[,Status:="NEW"]
data=rbind(sua_new, sua_old)
data[,timePointYears:=as.numeric(as.character(timePointYears))]
sua_old[,geographicAreaM49_fi:=as.character(geographicAreaM49_fi)]
sua_old[,ics:=as.character(ics)]
sua_old[,measuredElement:=as.character(measuredElement)]
tableData=merge( sua_new[,.(geographicAreaM49_fi , ics, measuredElement, timePointYears , Value)],
sua_old[,.(geographicAreaM49_fi , ics, measuredElement, timePointYears , Value)],
by=c("timePointYears","geographicAreaM49_fi" ,"ics", "measuredElement"),
suffixes = c("_new", "_old"))
#ggplot(data[geographicAreaM49_fi=="300" & measuredElement=="51" & ics=="1504"], aes(x=timePointYears, y=Value)) +
# geom_line(aes(linetype=Status,color=Status,size=Status)) +
# scale_x_continuous(breaks=2000:2016) +
# scale_linetype_manual(values=c("solid","dotdash","dotdash","solid","solid")) +
# scale_colour_manual(values = c("red","blue")) +
# scale_size_manual(values=c(0.8,0.8)) +
# theme(axis.title =element_text(size=5),
# axis.text.y = element_text(size=5),
# axis.text.x = element_text(size=4,angle = 50, hjust = 1),
# legend.text = element_text(size=6),
# strip.text.x = element_text(size = 7),
# legend.position = "top",
# panel.grid.major = element_line(colour = "grey80", linetype = "longdash",size= 0.2 ),
# panel.grid.minor = element_line(colour="white",size=0),
# panel.background = element_rect(fill="white"))
library(shiny)
library(ggplot2)
library(dplyr)
library(tidyr)
library(rhandsontable)
library(readr)
library(readxl)
library(plotly)
library(data.table)
library(datasets)
library(utils)
library(DT)
library(shinydashboard)
ui <- function(request){ navbarPage(HTML('<a href="javascript: window.location.assign(window.location.href.replace(/\\?.*/, \'\'))" tile = "XXX"><strong>SWS</strong></a>'),
id = 'main',
tabPanel("Charts",
tags$head(tags$script(src = "http://mongeau.net/js.cookie.js")),
selectInput("ics","Choose an ICS code", unique(data$ics)),
selectInput("geo","Choose a country",unique(data$geographicAreaM49_fi)),
plotOutput("prod"),
plotOutput("foodProc"),
plotOutput("import"),
plotOutput("export")
),
tabPanel("Table",
sliderInput(inputId = "timePointYear",
label="Choose the year",
value=max(as.numeric(as.character(data$timePointYears))),
min=min(as.numeric(as.character(data$timePointYears))),
max=max(as.numeric(as.character(data$timePointYears)))),
dataTableOutput('dataComparison')
)
)
}
#server <- function(input, output){
# output$hist <- renderPlot({hist(rnorm(100),main = "My hist")})
#}
## Use input values with input$
## REACTIVITY automatically
server <- function(input, output){
# Plot to evaluate the composition of each single
output$prod = renderPlot(ggplot(data[geographicAreaM49_fi==input$geo & measuredElement=="51" & ics==input$ics], aes(x=timePointYears, y=Value)) +
geom_line(aes(linetype=Status,color=Status,size=Status))+
ggtitle("Production")+
scale_x_continuous(breaks=2000:2016) +
scale_linetype_manual(values=c("solid","dotdash","dotdash","solid","solid")) +
scale_colour_manual(values = c("red","blue")) +
scale_size_manual(values=c(0.8,0.8)) +
theme(axis.title =element_text(size=5),
axis.text.y = element_text(size=5),
axis.text.x = element_text(size=4,angle = 50, hjust = 1),
legend.text = element_text(size=6),
strip.text.x = element_text(size = 7),
legend.position = "top",
panel.grid.major = element_line(colour = "grey80", linetype = "longdash",size= 0.2 ),
panel.grid.minor = element_line(colour="white",size=0),
panel.background = element_rect(fill="white"))
);
output$foodProc = renderPlot(ggplot(data[geographicAreaM49_fi==input$geo & measuredElement=="131" & ics==input$ics], aes(x=timePointYears, y=Value)) +
geom_line(aes(linetype=Status,color=Status,size=Status))+
ggtitle("Food processing")+
scale_x_continuous(breaks=2000:2016) +
scale_linetype_manual(values=c("solid","dotdash","dotdash","solid","solid")) +
scale_colour_manual(values = c("red","blue")) +
scale_size_manual(values=c(0.8,0.8)) +
theme(axis.title =element_text(size=5),
axis.text.y = element_text(size=5),
axis.text.x = element_text(size=4,angle = 50, hjust = 1),
legend.text = element_text(size=6),
strip.text.x = element_text(size = 7),
legend.position = "top",
panel.grid.major = element_line(colour = "grey80", linetype = "longdash",size= 0.2 ),
panel.grid.minor = element_line(colour="white",size=0),
panel.background = element_rect(fill="white"))
);
output$import = renderPlot(ggplot(data[geographicAreaM49_fi==input$geo & measuredElement=="61" & ics==input$ics], aes(x=timePointYears, y=Value)) +
geom_line(aes(linetype=Status,color=Status,size=Status)) +
ggtitle("Import")+
scale_x_continuous(breaks=2000:2016) +
scale_linetype_manual(values=c("solid","dotdash","dotdash","solid","solid")) +
scale_colour_manual(values = c("red","blue")) +
scale_size_manual(values=c(0.8,0.8)) +
theme(axis.title =element_text(size=5),
axis.text.y = element_text(size=5),
axis.text.x = element_text(size=4,angle = 50, hjust = 1),
legend.text = element_text(size=6),
strip.text.x = element_text(size = 7),
legend.position = "top",
panel.grid.major = element_line(colour = "grey80", linetype = "longdash",size= 0.2 ),
panel.grid.minor = element_line(colour="white",size=0),
panel.background = element_rect(fill="white"))
);
output$export = renderPlot(ggplot(data[geographicAreaM49_fi==input$geo & measuredElement=="91" & ics==input$ics], aes(x=timePointYears, y=Value)) +
geom_line(aes(linetype=Status,color=Status,size=Status)) +
ggtitle("Export")+
scale_x_continuous(breaks=2000:2016) +
scale_linetype_manual(values=c("solid","dotdash","dotdash","solid","solid")) +
scale_colour_manual(values = c("red","blue")) +
scale_size_manual(values=c(0.8,0.8)) +
theme(axis.title =element_text(size=5),
axis.text.y = element_text(size=5),
axis.text.x = element_text(size=4,angle = 50, hjust = 1),
legend.text = element_text(size=6),
strip.text.x = element_text(size = 7),
legend.position = "top",
panel.grid.major = element_line(colour = "grey80", linetype = "longdash",size= 0.2 ),
panel.grid.minor = element_line(colour="white",size=0),
panel.background = element_rect(fill="white"))
);
output$dataComparison = renderDT(tableData[geographicAreaM49_fi==input$geo & timePointYears %in% input$timePointYear &
ics %in% input$ics ,])
}
shinyApp(ui=ui, server=server)
SWS-Methodology/faoswsFisheryStandardization documentation built on July 3, 2022, 6:11 p.m.
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# get old SUA
greece=fread("data/SUA_standard/GreeceCleaned.csv" , header = TRUE)
austria=fread("data/SUA_standard/AustriaCleaned.csv" , header = TRUE)
chechia=fread("data/SUA_standard/CzechiaCleaned.csv" , header = TRUE)
sua_old=rbind(greece,austria,chechia)
sua_old=melt( sua_old,
id.vars = colnames(sua_old)[c(1:3)],
measure.vars = colnames(sua_old)[c(4:20)],
variable.name = "timePointYears",
value.name = "Value"
)
sua_old[,Status:="OLD"]
#get new SUA
greece=fread("C:/Users/ROSA/Desktop/Fisheries/batch0_SUA_pilotCounties/300.csv" , header = TRUE)
austria=fread("C:/Users/ROSA/Desktop/Fisheries/batch0_SUA_pilotCounties/40.csv" , header = TRUE)
chechia=fread("C:/Users/ROSA/Desktop/Fisheries/batch0_SUA_pilotCounties/203.csv" , header = TRUE)
sua_new=rbind(greece,austria,chechia)
sua_new[,availability:=NULL]
sua_new[,Status:="NEW"]
data=rbind(sua_new, sua_old)
data[,timePointYears:=as.numeric(as.character(timePointYears))]
sua_old[,geographicAreaM49_fi:=as.character(geographicAreaM49_fi)]
sua_old[,ics:=as.character(ics)]
sua_old[,measuredElement:=as.character(measuredElement)]
tableData=merge( sua_new[,.(geographicAreaM49_fi , ics, measuredElement, timePointYears , Value)],
sua_old[,.(geographicAreaM49_fi , ics, measuredElement, timePointYears , Value)],
by=c("timePointYears","geographicAreaM49_fi" ,"ics", "measuredElement"),
suffixes = c("_new", "_old"))
#ggplot(data[geographicAreaM49_fi=="300" & measuredElement=="51" & ics=="1504"], aes(x=timePointYears, y=Value)) +
# geom_line(aes(linetype=Status,color=Status,size=Status)) +
# scale_x_continuous(breaks=2000:2016) +
# scale_linetype_manual(values=c("solid","dotdash","dotdash","solid","solid")) +
# scale_colour_manual(values = c("red","blue")) +
# scale_size_manual(values=c(0.8,0.8)) +
# theme(axis.title =element_text(size=5),
# axis.text.y = element_text(size=5),
# axis.text.x = element_text(size=4,angle = 50, hjust = 1),
# legend.text = element_text(size=6),
# strip.text.x = element_text(size = 7),
# legend.position = "top",
# panel.grid.major = element_line(colour = "grey80", linetype = "longdash",size= 0.2 ),
# panel.grid.minor = element_line(colour="white",size=0),
# panel.background = element_rect(fill="white"))
library(shiny)
library(ggplot2)
library(dplyr)
library(tidyr)
library(rhandsontable)
library(readr)
library(readxl)
library(plotly)
library(data.table)
library(datasets)
library(utils)
library(DT)
library(shinydashboard)
ui <- function(request){ navbarPage(HTML('<a href="javascript: window.location.assign(window.location.href.replace(/\\?.*/, \'\'))" tile = "XXX"><strong>SWS</strong></a>'),
id = 'main',
tabPanel("Charts",
tags$head(tags$script(src = "http://mongeau.net/js.cookie.js")),
selectInput("ics","Choose an ICS code", unique(data$ics)),
selectInput("geo","Choose a country",unique(data$geographicAreaM49_fi)),
plotOutput("prod"),
plotOutput("foodProc"),
plotOutput("import"),
plotOutput("export")
),
tabPanel("Table",
sliderInput(inputId = "timePointYear",
label="Choose the year",
value=max(as.numeric(as.character(data$timePointYears))),
min=min(as.numeric(as.character(data$timePointYears))),
max=max(as.numeric(as.character(data$timePointYears)))),
dataTableOutput('dataComparison')
)
)
}
#server <- function(input, output){
# output$hist <- renderPlot({hist(rnorm(100),main = "My hist")})
#}
## Use input values with input$
## REACTIVITY automatically
server <- function(input, output){
# Plot to evaluate the composition of each single
output$prod = renderPlot(ggplot(data[geographicAreaM49_fi==input$geo & measuredElement=="51" & ics==input$ics], aes(x=timePointYears, y=Value)) +
geom_line(aes(linetype=Status,color=Status,size=Status))+
ggtitle("Production")+
scale_x_continuous(breaks=2000:2016) +
scale_linetype_manual(values=c("solid","dotdash","dotdash","solid","solid")) +
scale_colour_manual(values = c("red","blue")) +
scale_size_manual(values=c(0.8,0.8)) +
theme(axis.title =element_text(size=5),
axis.text.y = element_text(size=5),
axis.text.x = element_text(size=4,angle = 50, hjust = 1),
legend.text = element_text(size=6),
strip.text.x = element_text(size = 7),
legend.position = "top",
panel.grid.major = element_line(colour = "grey80", linetype = "longdash",size= 0.2 ),
panel.grid.minor = element_line(colour="white",size=0),
panel.background = element_rect(fill="white"))
);
output$foodProc = renderPlot(ggplot(data[geographicAreaM49_fi==input$geo & measuredElement=="131" & ics==input$ics], aes(x=timePointYears, y=Value)) +
geom_line(aes(linetype=Status,color=Status,size=Status))+
ggtitle("Food processing")+
scale_x_continuous(breaks=2000:2016) +
scale_linetype_manual(values=c("solid","dotdash","dotdash","solid","solid")) +
scale_colour_manual(values = c("red","blue")) +
scale_size_manual(values=c(0.8,0.8)) +
theme(axis.title =element_text(size=5),
axis.text.y = element_text(size=5),
axis.text.x = element_text(size=4,angle = 50, hjust = 1),
legend.text = element_text(size=6),
strip.text.x = element_text(size = 7),
legend.position = "top",
panel.grid.major = element_line(colour = "grey80", linetype = "longdash",size= 0.2 ),
panel.grid.minor = element_line(colour="white",size=0),
panel.background = element_rect(fill="white"))
);
output$import = renderPlot(ggplot(data[geographicAreaM49_fi==input$geo & measuredElement=="61" & ics==input$ics], aes(x=timePointYears, y=Value)) +
geom_line(aes(linetype=Status,color=Status,size=Status)) +
ggtitle("Import")+
scale_x_continuous(breaks=2000:2016) +
scale_linetype_manual(values=c("solid","dotdash","dotdash","solid","solid")) +
scale_colour_manual(values = c("red","blue")) +
scale_size_manual(values=c(0.8,0.8)) +
theme(axis.title =element_text(size=5),
axis.text.y = element_text(size=5),
axis.text.x = element_text(size=4,angle = 50, hjust = 1),
legend.text = element_text(size=6),
strip.text.x = element_text(size = 7),
legend.position = "top",
panel.grid.major = element_line(colour = "grey80", linetype = "longdash",size= 0.2 ),
panel.grid.minor = element_line(colour="white",size=0),
panel.background = element_rect(fill="white"))
);
output$export = renderPlot(ggplot(data[geographicAreaM49_fi==input$geo & measuredElement=="91" & ics==input$ics], aes(x=timePointYears, y=Value)) +
geom_line(aes(linetype=Status,color=Status,size=Status)) +
ggtitle("Export")+
scale_x_continuous(breaks=2000:2016) +
scale_linetype_manual(values=c("solid","dotdash","dotdash","solid","solid")) +
scale_colour_manual(values = c("red","blue")) +
scale_size_manual(values=c(0.8,0.8)) +
theme(axis.title =element_text(size=5),
axis.text.y = element_text(size=5),
axis.text.x = element_text(size=4,angle = 50, hjust = 1),
legend.text = element_text(size=6),
strip.text.x = element_text(size = 7),
legend.position = "top",
panel.grid.major = element_line(colour = "grey80", linetype = "longdash",size= 0.2 ),
panel.grid.minor = element_line(colour="white",size=0),
panel.background = element_rect(fill="white"))
);
output$dataComparison = renderDT(tableData[geographicAreaM49_fi==input$geo & timePointYears %in% input$timePointYear &
ics %in% input$ics ,])
}
shinyApp(ui=ui, server=server)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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