Source: https://www.kaggle.com/strikergene/south-korea-eu-trade-20132018

library(readr)
library(ggplot2)

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library(tidyverse)

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library(dplyr)
library(plotly)

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library(gapminder)

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library(RColorBrewer)
library(reshape)

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library(quantmod)

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library(scales)

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To check out the data set

tradeko <- read_csv(file = "trade_table.csv")

## Warning: Missing column names filled in: 'X1' [1]

## Parsed with column specification:
## cols(
##   X1 = col_double(),
##   year = col_double(),
##   country = col_character(),
##   export_weight = col_double(),
##   import_weight = col_double(),
##   export_amount = col_double(),
##   import_amount = col_double(),
##   trade_balance = col_double(),
##   HS_code = col_double(),
##   description = col_character()
## )

head(tradeko, 4)

## # A tibble: 4 x 10
##      X1  year country export_weight import_weight export_amount
##   <dbl> <dbl> <chr>           <dbl>         <dbl>         <dbl>
## 1     1  2013 Slovak~             0           0               0
## 2     2  2013 Austria             0           0.1             1
## 3     3  2013 Romania             0           0.2             1
## 4     4  2013 Poland              0           0.2             1
## # ... with 4 more variables: import_amount <dbl>, trade_balance <dbl>,
## #   HS_code <dbl>, description <chr>

dim(tradeko)

## [1] 13671    10

str(tradeko)

## Classes 'spec_tbl_df', 'tbl_df', 'tbl' and 'data.frame': 13671 obs. of  10 variables:
##  $ X1           : num  1 2 3 4 5 6 7 8 9 10 ...
##  $ year         : num  2013 2013 2013 2013 2013 ...
##  $ country      : chr  "Slovakia" "Austria" "Romania" "Poland" ...
##  $ export_weight: num  0 0 0 0 1 0 0 0 0 0 ...
##  $ import_weight: num  0 0.1 0.2 0.2 29.4 0 0.4 0 0.2 0.2 ...
##  $ export_amount: num  0 1 1 1 106 0 0 1 0 0 ...
##  $ import_amount: num  0 6 2 5 1511 ...
##  $ trade_balance: num  0 -5 -2 -4 -1404 ...
##  $ HS_code      : num  1 1 1 1 1 1 1 1 1 1 ...
##  $ description  : chr  "LIVE ANIMALS" "LIVE ANIMALS" "LIVE ANIMALS" "LIVE ANIMALS" ...
##  - attr(*, "spec")=
##   .. cols(
##   ..   X1 = col_double(),
##   ..   year = col_double(),
##   ..   country = col_character(),
##   ..   export_weight = col_double(),
##   ..   import_weight = col_double(),
##   ..   export_amount = col_double(),
##   ..   import_amount = col_double(),
##   ..   trade_balance = col_double(),
##   ..   HS_code = col_double(),
##   ..   description = col_character()
##   .. )

To remove the first column that shows row numbers only.

tradeko <- tradeko[-1]
head(tradeko, 3)

## # A tibble: 3 x 9
##    year country export_weight import_weight export_amount import_amount
##   <dbl> <chr>           <dbl>         <dbl>         <dbl>         <dbl>
## 1  2013 Slovak~             0           0               0             0
## 2  2013 Austria             0           0.1             1             6
## 3  2013 Romania             0           0.2             1             2
## # ... with 3 more variables: trade_balance <dbl>, HS_code <dbl>,
## #   description <chr>

To show summary of the sum of export and imprort per year and country by using group_by

tradeko2 <- tradeko %>% group_by(year,country) %>% summarise(export = sum(export_amount), import = sum(import_amount))
exportsum5yr <- summary(tradeko2$export)
importsum5yr <- summary(tradeko2$import)
head(tradeko2)

## # A tibble: 6 x 4
## # Groups:   year [1]
##    year country         export  import
##   <dbl> <chr>            <dbl>   <dbl>
## 1  2013 Austria         606901 1382573
## 2  2013 Belgium        2240762 1585908
## 3  2013 Bulgaria        120364  171894
## 4  2013 Croatia          46307   16603
## 5  2013 Cyprus           66369 1299334
## 6  2013 Czech Republic 1682863  557478

exportsum5yr

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   10705  326406  889878 1653788 2433543 8483848

importsum5yr

##     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
##     7010   112328   598460  1888967  1587345 21298751

Box Plot - Sum of Trade from 2013 to 2018 (with 24 Trade partners in EU)

tradebox <- ggplot(tradeko2, aes(x = country, y = (export/10000), fill = country)) +
                  geom_boxplot(outlier.colour="black", outlier.shape=1, outlier.size=1) +
                  theme(axis.text.x = element_text(angle = 70, hjust = 0.9)) +
                  ggtitle("Sum of Export from 2013 to 2018") +
                  xlab(" ") +
                  ylab("Export: USD $billion") +
                  theme(legend.position = "right")
tradebox <- ggplotly(tradebox)
tradebox

tradebox1 <- ggplot(tradeko2, aes(x = country, y = (import/10000), fill = country)) +
                  geom_boxplot(outlier.colour="black", outlier.shape=1, outlier.size=1) +
                  theme(axis.text.x = element_text(angle = 70, hjust = 0.9)) +
                  ggtitle("Sum of Import from 2013 to 2018") +
                  xlab("Country") +
                  ylab("Import: USD $billion") +
                  theme(legend.position = "right")
tradebox1 <- ggplotly(tradebox1)
tradebox1

tradeko1 <- tradeko %>% group_by(year, country) %>% summarise(balance = mean(trade_balance))
head(tradeko1, 3)

## # A tibble: 3 x 3
## # Groups:   year [1]
##    year country  balance
##   <dbl> <chr>      <dbl>
## 1  2013 Austria   -8431.
## 2  2013 Belgium    6967.
## 3  2013 Bulgaria   -613.

balance5yravg <- summary(tradeko1$balance)
balance5yravg

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
## -153503   -5648     801   -1593    9526   54811

library(ggthemes)

## Warning: package 'ggthemes' was built under R version 3.6.1

library(tibbletime)

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library(gganimate)

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Line Chart

tradeline <- ggplot(tradeko1,
                    aes(x = year, y = (balance/10000), color = country, group = 1)
                    ) +
             theme_economist() + 
             geom_line() +
             geom_point(
                      aes(text = 
                          paste(paste("Rate: ", tradeko1$country, "<br>"),
                                paste("Year: ", tradeko1$year, "<br>"),
                                paste("Trade Balance: ", tradeko1$balance/10000))
                        ),
                       size = 2, 
                       data = tradeko1) +
              scale_x_continuous(breaks=seq(2013, 2018, 1)) +
              scale_color_pander() +
              labs(x="Year", y="USD $billion") +
              ggtitle("Average Trade Balance by Country")

## Warning: Ignoring unknown aesthetics: text

tradeline1 <- ggplotly(tradeline, tooltip =  "text")
tradeline1

Static Plot - Line

tradealine <- ggplot(tradeko1,
                     aes(x = year, y = (balance/10000), color = country)
                     ) +
              geom_line() +
              scale_color_pander() +
#              scale_color_viridis_d() +
              labs(x = "Year", y = "USD $billion") +
              theme(legend.position = "bottom") +
              ggtitle("Average Trade Balance by Country") +
              geom_point() +
              transition_reveal(year)
tradealine