#' @title make_trade_network
#'
#' @description This function takes (import) trade data and cleans it and transforms it into a network.
#' This function can be applied to trade data downloaded from UN Comtrade (download csv and read into R as a dataframe), or any other trade data. You just make sure it has the following column names:
#' reporter_iso, partner_iso and edge_weight. Some dataformats may have different names. Also - it is important to note that this function is for import data.
#' @param DF Dataframe of trade data downloaded (potentially using the comtradr package)
#' @param threshold Apply a threshold - TRUE, Extract the backbone - FALSE
#' @param cutoff Threshold - cutoff level, Backbone - significance level
#' @export
#' @return International Trade Network - igraph object
make_trade_network<-function(DF,threshold,cutoff){
H<-stats::aggregate(edge_weight~reporter_iso+partner_iso, DF, sum)
Sender<-as.vector(H[,"partner_iso"])
Sender<- gsub('SER', 'SRB', Sender)
Sender<- gsub('TMP', 'TLS', Sender)
Sender<- gsub('ZAR', 'COD', Sender)
Sender<- gsub('ROM', 'ROU', Sender)
Sender<- gsub('SUD', 'SDN', Sender)
Sender<- gsub('MNT', 'MNE', Sender)
Receiver<-as.vector(H[,"reporter_iso"])
Receiver<- gsub('SER', 'SRB', Receiver)
Receiver<- gsub('TMP', 'TLS', Receiver)
Receiver<- gsub('ZAR', 'COD', Receiver)
Receiver<- gsub('ROM', 'ROU', Receiver)
Receiver<- gsub('SUD', 'SDN', Receiver)
Receiver<- gsub('MNT', 'MNE', Receiver)
VAL<-H[,"edge_weight"]
VAL<-as.numeric(VAL)
FULLel<-as.data.frame(cbind(Sender,Receiver,VAL),stringsAsFactors = FALSE)
FULLel$VAL<-as.numeric(FULLel$VAL)
WDIDataSeries<-WDI::WDI_data
WDICountryInfo<-WDIDataSeries$country
WD<-as.data.frame(WDICountryInfo)
COUNTRYlist<-WDICountryInfo[,"iso3c"]
REGIONlist<-WDICountryInfo[,"region"]
INCOMElist<-WDICountryInfo[,"income"]
CountryRegion<-cbind(COUNTRYlist,REGIONlist)
CountryIncome<-cbind(COUNTRYlist,INCOMElist)
AggReg<-c("All","EUN","UNS","OAS","FRE","BAT",
"SPE","VAT","UMI","ATA","PCN","AIA","COK",
"SHN","MSR","NIU",
"BES","BLM","BUN","BVT","CCK","CXR","FLK",#Small regions
"HMD","IOT","NFK","SGS","TKL", #small regions
"ESH","SPM","ATF"
)
AggRegMat<-matrix("Aggregates",length(AggReg),2)
AggRegMat[,1]<-AggReg
CountryRegion<-rbind(CountryRegion,AggRegMat)
CountryIncome<-rbind(CountryIncome,AggRegMat)
AggregatesList<-subset(CountryRegion, REGIONlist %in% "Aggregates")
TotalCountryExports<-subset(FULLel,Receiver %in% "All")
AllAllTotal<-as.matrix(subset(TotalCountryExports,Sender %in% "All"))
GrandTotal<-as.numeric(AllAllTotal[,3])
if (is.numeric(isEmpty(GrandTotal))==FALSE){
GrandTotal<-sum(VAL)
}else GrandTotal<-GrandTotal
Share<-list()
for (i in 1:length(VAL)){
Share[[i]]<-(VAL[i]/GrandTotal)*100
}
Share <-plyr::ldply(Share, data.frame)
Share<-dplyr::as_tibble(Share)
colnames(Share)<-"Share"
FULLel<-cbind(FULLel,Share)
G1<-igraph::graph_from_data_frame(FULLel,direct=TRUE)
igraph::E(G1)$weight<-FULLel[,4]
igraph::V(G1)$id<-igraph::V(G1)$name
CountryNames<-igraph::V(G1)$name
NotCovered<-subset(CountryNames,!(CountryNames %in% CountryRegion[,1]))
mm<-matrix("NA",length(NotCovered),2)
mm[,1]<-NotCovered
CountryRegion2<-rbind(CountryRegion,mm)
CountryIncome2<-rbind(CountryIncome,mm)
RegionListAttr<-list()
IncomeListAttr<-list()
for (i in 1:length(CountryNames)){
RegionListAttr[[i]]<-subset(CountryRegion2,COUNTRYlist %in% CountryNames[i])
IncomeListAttr[[i]]<-subset(CountryIncome2,COUNTRYlist %in% CountryNames[i])
}
dfREG<-plyr::ldply(RegionListAttr, data.frame)
dfREG<-dplyr::as_tibble(dfREG)
dfINC<-plyr::ldply(IncomeListAttr,data.frame)
dfINC<-dplyr::as_tibble(dfINC)
target<-CountryNames
dfREG<-dfREG[match(target,dfREG$COUNTRYlist),]
#
RR<-unlist(dfREG[,2])
RR2 <- as.factor(RR)
H<-as.character(dfREG$REGIONlist)
dfINC<-dfINC[match(target,dfINC$COUNTRYlist),]
KK<-unlist(dfINC[,2])
KK2<-as.factor(KK)
U<-as.character(dfINC$INCOMElist)
A<-levels(RR2)
B<-1:length(A)
KEY<-cbind(A,B)
Ainc<-levels(KK2)
Binc<-1:length(Ainc)
IH<-fastmatch::fmatch(KK,Ainc)
CH<-fastmatch::fmatch(RR, A)
igraph::V(G1)$regionNAME<-H
igraph::V(G1)$region<-CH
igraph::V(G1)$income<-IH
#Delete Aggregated Vertices etc
KEY2<-as.data.frame(KEY)
NAcheck<-"NA" %in% KEY2$A
Aggrow<-as.data.frame(KEY2[KEY2$A=="Aggregates", ])
AggNumber<-as.numeric(as.vector(Aggrow$B))
if (NAcheck==TRUE){
NArow<-as.data.frame(KEY2[KEY2$A=="NA", ])
NANumber<-as.numeric(as.vector(NArow$B))
G2<-igraph::delete.vertices(G1, which(igraph::V(G1)$region==NANumber))
G3<-igraph::delete.vertices(G2, which(igraph::V(G2)$region==AggNumber))
} else G3<-G1
#Apply the threshold/backbone
if(threshold==TRUE){
G4<-igraph::delete.edges(G3,which(igraph::E(G3)$weight<cutoff))
} else {
G4<-get.backbone(G3,cutoff,TRUE)
}
G5<-igraph::delete.vertices(G4, which(igraph::degree(G4)==0))
return(G5)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.