In EuropeanForestInstitute/tradeflows: Process forest products trade flow data from COMTRADE and COMEXT

library(knitr)
opts_knit$set(root.dir="../../..") # file paths are relative to the root of the project directory
opts_chunk$set(echo=FALSE)
library(tradeflows)
library(dplyr)
library(ggplot2)
library(reshape2)

# Remove this chunk (or eval=FALSE) when this file is used as a template
# The data frame tfdata will be passed by the report generating function to the template
# Product and reporter information can be extracted back from tfdata 
# in the template this would have to be the country appearing most in the data frame
productcode_ <- c(440799)
reporter_ <- "Cameroon" 
tfdata <- readdbtbl("raw_flow_yearly") %>%
    filter(productcode == productcode_ & (reporter == reporter_ | partner == reporter_)) %>%
    collect

# Only the tfdata variable is passed by the function that creates the report
# Extract product code and reporter from the tfdata.
productcodeinreport <- unique(tfdata$productcode)
reporterinreport <- tfdata %>% group_by(reporter) %>% 
    summarise(nrow = n()) %>% filter(nrow == max(nrow))
reporterinreport <- reporterinreport$reporter
# Calculate discrepancies
tfdata  <- tfdata %>% addpartnerflow %>% calculatediscrepancies 

---

title: "440799 discrepancies sample plots " author: "Paul Rougieux" date: "03/12/2014" output: pdf_document: toc: yes

---

Thailand

Most recent years has poor data, look at the year before last.

Major export partners in weight in max(dtf$year)

dtf <- readdbproduct(440799, "raw_flow_yearly")
reporterinreport <- 764
flowselected <- "Export"
dtf2 <- dtf %>%
    filter(reportercode == reporterinreport)

for (p in unique(dtf$productcode)){
    exp <- dtf2 %>% 
        filter(flow == flowselected & year == max(year) & productcode==p) %>%
        select(partner, weight, discrv) %>%
        arrange(-weight) %>%
        rename(discrepancy = discrv) %>%
        head(10)
    partnerssorted <- unique(exp$partner)
    kable(exp)

        # Order the contries by trade volume
    exp <- exp %>%
        mutate(partner = ordered(partner, levels= partnerssorted)) %>%
        melt(id=c("partner"))

    chart <- ggplot(data=exp)+
        aes(partner, value, fill=variable) +
        geom_bar(position="dodge", stat="identity") +
        scale_fill_manual(values = c("chocolate3","black"))+
        theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
        ggtitle(paste(flowselected, p))
    print(chart)
    cat("\n\n")
}

# write.csv(exp, file="data-raw/export440799_Thailand_mainpartners2013.csv", row.names=FALSE)

Data can be exported to csv, Excel or other formats.

Thailand Export of 440799 to China in recent years

reporterinreport <- 764
# Report could choosedisplay those time series for main partners  only
partnerinreport <- 156 
flowselected <- "Export"
productcodeinreport <- 440799
dtf2 <- dtf %>%
    filter(reportercode == reporterinreport & 
               partnercode==partnerinreport &
               productcode == productcodeinreport&
               flow == flowselected)
kable(select(dtf2, classification, quantity, weight, tradevalue, 
             discrq, discrq, discrv))
dtf2 <- dtf2 %>%
    select(year, weight, discrq, quantity, discrq, tradevalue, discrv) %>%
    melt(id=c("year"))
weight <- dtf2 %>% filter(variable %in% c("weight", "discrv"))
dtf2$v <- dtf2$variable
dtf2$v[dtf2$variable == "discrv"] <- "weight"
dtf2$v[dtf2$variable == "discrq"] <- "quantity"
dtf2$v[dtf2$variable == "discrv"] <- "tradevalue"
# for (v1 in unique(dtf2$v))
ggplot(data=dtf2)+#filter(dtf2,v=="weight"))+
    aes(year, value, fill=variable) +
    geom_bar(position="dodge", stat="identity") +
    scale_fill_manual(values = rep(c("chocolate3","black"),2))+
    theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
    ggtitle(paste(flowselected, p)) +
    facet_grid(v~., scales="free_y")


# csv file for Sergey
# write.csv(dtf2, file="data-raw/export440799_Thailand_to_China.csv", row.names=FALSE) 

Spain

Major import partners in weight in 2012

reporterinreport <- 724
flowselected <- "Import"
# yearselected <-   max(dtf$year)
yearselected <- 2012
dtf2 <- dtf %>%
    filter(reportercode == reporterinreport)

for (p in unique(dtf$productcode)){
    exp <- dtf2 %>% 
        filter(flow == flowselected & year == yearselected & productcode==p) %>%
        select(partner, weight, discrv, tradevalue, discrv, quantity, discrq) %>%
        arrange(-weight) %>%
        head(10)
    partnerssorted <- unique(exp$partner)
    cat("\n\n")
    print(kable(rename(exp, discrepancy_weight = discrv)))
    cat("\n\n")


    exp <- exp %>%
        select(partner, weight, discrv) %>%
        # Order the contries by trade volume
        mutate(partner = ordered(partner, levels= partnerssorted)) %>%
        melt(id=c("partner"))

    chart <- ggplot(data=exp)+
        aes(partner, value, fill=variable) +
        geom_bar(position="dodge", stat="identity") +
        scale_fill_manual(values = c("chocolate3","black"))+
        theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
        ggtitle(paste(flowselected, p))
    cat("\n\n")
    print(chart)
    cat("\n\n")
}
# write.csv(exp, file="data-raw/export440799_Spain_mainpartners2012", 
#           row.names=FALSE)

Cameroon

Cameroon Export of 440799 to Spain in recent years

reporterinreport <- 120 # Cameroon
# Report could choosedisplay those time series for main partners  only
partnerinreport <- 724 # Spain 
flowselected <- "Export"
productcodeinreport <- 440799
dtf2 <- dtf %>%
    filter(reportercode == reporterinreport & 
               partnercode==partnerinreport &
               productcode == productcodeinreport&
               flow == flowselected)
kable(select(dtf2, classification, quantity, weight, tradevalue, 
             discrq, discrv, discrv))
dtf2 <- dtf2 %>%
    select(year, weight, discrv, quantity, discrq, tradevalue, discrv) %>%
    melt(id=c("year"))
weight <- dtf2 %>% filter(variable %in% c("weight", "discrv"))
dtf2$v <- dtf2$variable
dtf2$v[dtf2$variable == "discrv"] <- "weight"
dtf2$v[dtf2$variable == "discrq"] <- "quantity"
dtf2$v[dtf2$variable == "discrv"] <- "tradevalue"
# for (v1 in unique(dtf2$v))
ggplot(data=dtf2)+#filter(dtf2,v=="weight"))+
    aes(year, value, fill=variable) +
    geom_bar(position="dodge", stat="identity") +
    scale_fill_manual(values = rep(c("chocolate3","black"),3))+
    theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
    ggtitle(paste(flowselected, p)) +
    facet_grid(v~., scales="free_y")
# write.csv(dtf2, file="data-raw/export440799_Cameroon_to_Spain.csv", 
#           row.names=FALSE)

EuropeanForestInstitute/tradeflows documentation built on Oct. 7, 2019, 10:57 a.m.