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Visualizations.R
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Visualizations.R
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setwd("C:\\Users") # set working dir
final <- read.csv("Final.csv") # data set containing only the import-adjusted FD components for V4 countries and the Baltics
################################################################
## Required libraries
library(tidyverse)
library(gridExtra)
library(zoo)
################################################################library(zoo)
## pivoting the csv. data
final_pivoted <- pivot_longer(final,
cols = GrowthRate_C:GrowthRate_EX,
names_to = "Categories",
values_to = "Value")
## renaming the import-adjusted growth categories
final_pivoted <- final_pivoted %>%
mutate(Categories = case_when(
Categories == "GrowthRate_C" ~ "Import-adjusted Private Consumption",
Categories == "GrowthRate_I" ~ "Import-adjusted Investment",
Categories == "GrowthRate_G" ~ "Import-adjusted Government Consumption",
Categories == "GrowthRate_EX" ~ "Import-adjusted Exports",
TRUE ~ Categories
))
## Subsetting countries into separate dfs
## Computing 3-year moving averages
Czechia <- final_pivoted %>%
filter(Country == "Czechia") %>%
mutate(moving_avg = ave(Value, Categories, FUN = function(x) rollmean(x, k = 3, align = "right", fill = NA)))
Hungary <- final_pivoted %>%
filter(Country == "Hungary") %>%
mutate(moving_avg = ave(Value, Categories, FUN = function(x) rollmean(x, k = 3, align = "right", fill = NA)))
Poland <- final_pivoted %>%
filter(Country == "Poland") %>%
mutate(moving_avg = ave(Value, Categories, FUN = function(x) rollmean(x, k = 3, align = "right", fill = NA)))
Slovakia <- final_pivoted %>%
filter(Country == "Slovakia") %>%
mutate(moving_avg = ave(Value, Categories, FUN = function(x) rollmean(x, k = 3, align = "right", fill = NA)))
Estonia <- final_pivoted %>%
filter(Country == "Estonia") %>%
mutate(moving_avg = ave(Value, Categories, FUN = function(x) rollmean(x, k = 3, align = "right", fill = NA)))
Latvia <- final_pivoted %>%
filter(Country == "Latvia") %>%
mutate(moving_avg = ave(Value, Categories, FUN = function(x) rollmean(x, k = 3, align = "right", fill = NA)))
Lithuania <- final_pivoted %>%
filter(Country == "Lithuania") %>%
mutate(moving_avg = ave(Value, Categories, FUN = function(x) rollmean(x, k = 3, align = "right", fill = NA)))
## Plotting the moving-averages using stacked barplot
CZ <- ggplot(Czechia, aes(fill = Categories, y = moving_avg, x = Year))+
geom_bar(position = "stack", stat = "identity") +
labs(title = "Czechia", x = "", y = "Growth Contribution in %") +
theme_light() +
theme(panel.grid = element_blank(),
panel.border = element_blank(),
axis.line = element_line(color = "black"))+
scale_fill_manual(
name = "Categories",
values = c("Import-adjusted Private Consumption" = "lightblue",
"Import-adjusted Investment" = "darkolivegreen2",
"Import-adjusted Government Consumption" = "coral",
"Import-adjusted Exports" = "darkgoldenrod1"
)) +
guides(fill = guide_legend(title = NULL))
HU <- ggplot(Hungary, aes(fill = Categories, y = moving_avg, x = Year))+
geom_bar(position = "stack", stat = "identity") +
labs(title = "Hungary", x = "", y = "Growth Contribution in %") +
theme_light() +
theme(panel.grid = element_blank(),
panel.border = element_blank(),
axis.line = element_line(color = "black"))+
scale_fill_manual(
name = "Categories",
values = c("Import-adjusted Private Consumption" = "lightblue",
"Import-adjusted Investment" = "darkolivegreen2",
"Import-adjusted Government Consumption" = "coral",
"Import-adjusted Exports" = "darkgoldenrod1"
))+
guides(fill = guide_legend(title = NULL))
PL <- ggplot(Poland, aes(fill = Categories, y = moving_avg, x = Year))+
geom_bar(position = "stack", stat = "identity") +
labs(title = "Poland", x = "", y = "Growth Contribution in %") +
theme_light() +
theme(panel.grid = element_blank(),
panel.border = element_blank(),
axis.line = element_line(color = "black"))+
scale_fill_manual(
name = "Categories",
values = c("Import-adjusted Private Consumption" = "lightblue",
"Import-adjusted Investment" = "darkolivegreen2",
"Import-adjusted Government Consumption" = "coral",
"Import-adjusted Exports" = "darkgoldenrod1"
))+
guides(fill = guide_legend(title = NULL))
SK <- ggplot(Slovakia, aes(fill = Categories, y = moving_avg, x = Year))+
geom_bar(position = "stack", stat = "identity") +
labs(title = "Slovakia", x = "", y = "Growth Contribution in %") +
theme_light() +
theme(panel.grid = element_blank(),
panel.border = element_blank(),
axis.line = element_line(color = "black"))+
scale_fill_manual(
name = "Categories",
values = c("Import-adjusted Private Consumption" = "lightblue",
"Import-adjusted Investment" = "darkolivegreen2",
"Import-adjusted Government Consumption" = "coral",
"Import-adjusted Exports" = "darkgoldenrod1"
))+
guides(fill = guide_legend(title = NULL))
EE <- ggplot(Estonia, aes(fill = Categories, y = moving_avg, x = Year))+
geom_bar(position = "stack", stat = "identity") +
labs(title = "Estonia", x = "", y = "Growth Contribution in %") +
theme_light() +
theme(panel.grid = element_blank(),
panel.border = element_blank(),
axis.line = element_line(color = "black"))+
scale_fill_manual(
name = "Categories",
values = c("Import-adjusted Private Consumption" = "lightblue",
"Import-adjusted Investment" = "darkolivegreen2",
"Import-adjusted Government Consumption" = "coral",
"Import-adjusted Exports" = "darkgoldenrod1"
))+
guides(fill = guide_legend(title = NULL))
LV <- ggplot(Latvia, aes(fill = Categories, y = moving_avg, x = Year))+
geom_bar(position = "stack", stat = "identity") +
labs(title = "Latvia", x = "", y = "Growth Contribution in %") +
theme_light() +
theme(panel.grid = element_blank(),
panel.border = element_blank(),
axis.line = element_line(color = "black"))+
scale_fill_manual(
name = "Categories",
values = c("Import-adjusted Private Consumption" = "lightblue",
"Import-adjusted Investment" = "darkolivegreen2",
"Import-adjusted Government Consumption" = "coral",
"Import-adjusted Exports" = "darkgoldenrod1"
))+
guides(fill = guide_legend(title = NULL))
LT <- ggplot(Lithuania, aes(fill = Categories, y = moving_avg, x = Year))+
geom_bar(position = "stack", stat = "identity") +
labs(title = "Lithuania", x = "", y = "Growth Contribution in %") +
theme_light() +
theme(panel.grid = element_blank(),
panel.border = element_blank(),
axis.line = element_line(color = "black"))+
scale_fill_manual(
name = "Categories",
values = c("Import-adjusted Private Consumption" = "lightblue",
"Import-adjusted Investment" = "darkolivegreen2",
"Import-adjusted Government Consumption" = "coral",
"Import-adjusted Exports" = "darkgoldenrod1"
))+
guides(fill = guide_legend(title = NULL))
## Putting all together
grid.arrange(CZ, HU, PL, SK, nrow = 2, ncol = 2)
grid.arrange(EE, LV, LT, nrow = 2, ncol = 2)