Governance.Rmd

---
title: "Governance"
author: "Cian Stryker"
date: "5/13/2020"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)

library(readxl)
library(gt)
library(cowplot)
library(janitor)
library(ggthemes)
library(png)
library(countrycode)
library(tidyverse)
```


```{r GDP Cleaning}

GDP <- read_csv("Data/GDP_World_Bank.csv", col_types = cols(
  .default = col_double(),
  `Country Name` = col_character(),
  `Country Code` = col_character(),
  `2019` = col_logical()
)) 

GDP <- GDP[, -c(2, 26)]

GDP <- GDP %>%
  pivot_longer(-`Country Name`,
                names_to = "year",
               values_to = "GDP") %>%
  clean_names() 

GDP$country <- countrycode(GDP$country_name, "country.name", "country.name")

GDP$country_code = GDP$country

GDP$country_code <- countrycode(GDP$country_code, "country.name", "iso2c")

GDP <- GDP[, -1]

GDP<- GDP[c(3, 4, 1, 2)]

GDP <- GDP %>%
  mutate(year = as.integer(as.character(year)))
```

```{r Rule of Law}

RoL <- read_excel("Data/Rule_of_Law_World_Bank.xlsx")

RoL <- RoL[, -2]

RoL <- RoL %>%
  pivot_longer(-"Country/Territory",
               names_to = "year",
               values_to = "score"
                ) 

RoL$country = RoL$`Country/Territory`

RoL <- RoL[, -1]

RoL$country <- countrycode(RoL$country, "country.name", "country.name")

RoL$country_code = RoL$country

RoL$country_code <- countrycode(RoL$country_code, "country.name", "iso2c")

RoL <- RoL[c(3, 4, 1, 2)]
```

```{r Gov Effectivness}

Gov <- read_excel("Data/Government_Effectivness_World_Bank.xlsx")

Gov <- Gov[, -2]

Gov <- Gov %>%
  pivot_longer(-"Country/Territory",
               names_to = "year",
               values_to = "score"
                ) 

Gov$country = Gov$`Country/Territory`

Gov <- Gov[, -1]

Gov$country <- countrycode(Gov$country, "country.name", "country.name")

Gov$country_code = Gov$country

Gov$country_code <- countrycode(Gov$country_code, "country.name", "iso2c")

Gov <- Gov[c(3, 4, 1, 2)]
```

```{r Regime, warning = FALSE}

Freedom_House <- read_excel("Data/Freedom_House.xlsx")

FH <- Freedom_House
FH$year <- FH$Edition

FH$country <- countrycode(FH$`Country/Territory`, "country.name", "country.name")

FH$country_code = FH$country

FH$country_code <- countrycode(FH$country_code, "country.name", "iso2c")

FH <- FH[, -c(1,2, 3)]

FH<- FH[c(3, 4, 2, 1)]

FH_Cleanx <- FH %>%
  drop_na() %>%
  clean_names() %>%
  filter(country %in% c("Ecuador", "Kazakhstan", "Kyrgyzstan", "Tajikistan", "Turkmenistan", "Uzbekistan")) %>%
  mutate(year = as.character(year))
```

```{r Rule of Law Bar Chart CA Comparison}

CA_RoLx <- RoL %>%
  filter(country %in% c("Kazakhstan", "Kyrgyzstan", "Tajikistan", "Turkmenistan", "Uzbekistan")) %>%
  filter(year == 2018)

plot1 <- ggplot(CA_RoLx, aes(x = country, y = score,  fill = country)) +
  geom_col() +
  guides(fill = FALSE) +
  theme_cowplot() +
  labs(
    color = "Country",
    title = "Rule of Law",
    subtitle = "Central Asia 2018",
    x = "Country",
    y = "Index Score",
    caption = " "
  ) +
  expand_limits(y = 100) +
  theme(axis.text.x=element_text(angle = 60, hjust = 1))
```

```{r Gov Effectivness CA Comparison}

CA_Gov <- Gov %>%
  filter(country %in% c("Kazakhstan", "Kyrgyzstan", "Tajikistan", "Turkmenistan", "Uzbekistan")) %>%
  filter(year == 2018)

plot2 <- ggplot(CA_Gov, aes(x = country, y = score,  fill = country)) +
  geom_col() +
  guides(fill = FALSE) +
  theme_cowplot() +
  labs(
    color = "Country",
    title = "Government Effectiveness",
    subtitle = "Central Asia 2018",
    x = "Country",
    y = " ",
    caption = "Source: World Bank"
  ) +
  expand_limits(y = 100) +
  theme(axis.text.x=element_text(angle = 60, hjust = 1))

``` 


```{r CA Governance Comparative Plot}

Governance_CA <- plot_grid(plot1, plot2)
```

```{r Rule of Law Bar Chart CA + Ecuador Comparison}

RoL_All <- RoL %>%
  filter(country %in% c("Ecuador", "Kazakhstan", "Kyrgyzstan", "Tajikistan", "Turkmenistan", "Uzbekistan")) %>%
  filter(year == 2018)

plot1x <- ggplot(RoL_All, aes(x = country, y = score,  fill = country)) +
  geom_col() +
  guides(fill = FALSE) +
  theme_cowplot() +
  labs(
    color = "Country",
    title = "Rule of Law",
    subtitle = "Central Asia and Ecuador 2018",
    x = "Country",
    y = "Index Score",
    caption = " "
  ) +
  expand_limits(y = 100) +
  theme(axis.text.x=element_text(angle = 60, hjust = 1))
```

```{r Gov Effectivness CA + Ecuador Comparison}

Gov_All <- Gov %>%
  filter(country %in% c("Ecuador", "Kazakhstan", "Kyrgyzstan", "Tajikistan", "Turkmenistan", "Uzbekistan")) %>%
  filter(year == 2018)

plot2x <- ggplot(Gov_All, aes(x = country, y = score,  fill = country)) +
  geom_col() +
  guides(fill = FALSE) +
  theme_cowplot() +
  labs(
    color = "Country",
    title = "Government Effectiveness",
    subtitle = "Central Asia and Ecuador 2018",
    x = "Country",
    y = " ",
    caption = "Source: World Bank"
  ) +
  expand_limits(y = 100) +
  theme(axis.text.x=element_text(angle = 60, hjust = 1))
``` 


```{r CA + Ecuador Governance Comparative Plot}

Governance_CA_E <- plot_grid(plot1x, plot2x)
```

```{r Governance Data}

Governance <- left_join(RoL, Gov, by = c("country", "year", "country_code"))

Governance$roL <- Governance$score.x
Governance$effect <- Governance$score.y

Governance <- Governance[, c(-4, -5)]

maybe <- full_join(FH_Cleanx, Governance, by = c("country", "year", "country_code"))


Governance_Clean <- maybe %>%
  pivot_longer(-c("country", "country_code", "year"),
               names_to = "index",
               values_to = "score"
                )
```

```{r Governance Kyrgyzstan, warning=FALSE}

Kyrgyzstan_Gov <- Governance_Clean %>%
  filter(country %in% c("Kyrgyzstan")) %>%
  filter(year >= 2002)

Gov_Kyrgyzstan <- ggplot(Kyrgyzstan_Gov, aes(x = year, y = score, group = index)) +
  geom_line(aes(linetype= "dash", color = index)) +
  geom_point(aes(color = index)) +
  theme_economist_white() +
  labs(
    color = "Index",
    title = "Governance in Kyrgyzstan",
    x = "Year",
    y = "Index Score",
    caption = "Source: World Bank and Freedom House"
  ) +
  expand_limits(y = 100, x = "2020") +
  scale_x_discrete(breaks = c(2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018, 2020)) +
  scale_y_continuous(breaks = c(0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
  guides(linetype = FALSE) +
  scale_color_hue(labels = c("Government Effectiveness", "Rule of Law", "Freedom House Index")) +
  theme(axis.title.y = element_text(vjust = 4), axis.title.x = element_text(vjust = -4), plot.title = element_text(hjust = .45))
```


```{r GDP Kyrgyzstan}

Kyrgyzstan_GDP <- GDP %>%
  filter(country %in% c("Kyrgyzstan")) 

GDP_Kyrgyzstan <- ggplot(Kyrgyzstan_GDP, aes(x = year, y = gdp, color = "red")) +
  geom_point() +
  geom_line() +
  labs(
    title = "Kyryzstan's Economic Climate",
    x = "Year",
    y = "GDP in USD",
    caption = "Source: World Bank"
  ) +
  scale_x_continuous(breaks = c(1996, 1998, 2000, 2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018)) +
  guides(linetype = FALSE, color = FALSE) +
  theme_economist_white() +
  theme(axis.title.y = element_text(vjust = 4), axis.title.x = element_text(vjust = -4), plot.title = element_text(hjust = .45, vjust = 3))
```

```{r Governance Kazakhstan, warning=FALSE}

Kazakhstan_Gov <- Governance_Clean %>%
  filter(country %in% c("Kazakhstan")) %>%
  filter(year >= 2002)


Gov_Kazakhstan <-ggplot(Kazakhstan_Gov, aes(x = year, y = score, group = index)) +
  geom_line(aes(linetype= "dash", color = index)) +
  geom_point(aes(color = index)) +
  labs(
    color = "Index",
    title = "Governance in Kazakhstan",
    x = "Year",
    y = "Index Score",
    caption = "Source: World Bank and Freedom House"
  ) +
  expand_limits(y = 100, x = "2020") +
  scale_x_discrete(breaks = c(2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018, 2020)) +
  scale_y_continuous(breaks = c(0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
  guides(linetype = FALSE) +
  scale_color_hue(labels = c("Government Effectiveness", "Rule of Law", "Freedom House Index")) +
  theme_economist_white() +
  theme(axis.title.y = element_text(vjust = 4), axis.title.x = element_text(vjust = -4), plot.title = element_text(hjust = .45))
```


```{r GDP Kazakhstan}

Kazakhstan_GDP <- GDP %>%
  filter(country %in% c("Kazakhstan")) 

GDP_Kazakhstan <- ggplot(Kazakhstan_GDP, aes(x = year, y = gdp, color = "red")) +
  geom_point() +
  geom_line() +
  labs(
    title = "Kazakhstan's Economic Climate",
    x = "Year",
    y = "GDP in USD",
    caption = "Source: World Bank"
  ) +
  scale_x_continuous(breaks = c(1996, 1998, 2000, 2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018)) +
  guides(linetype = FALSE, color = FALSE) +
  theme_economist_white() +
  theme(axis.title.y = element_text(vjust = 4), axis.title.x = element_text(vjust = -4), plot.title = element_text(hjust = .45, vjust = 3))
```

```{r Governance Tajikistan, warning=FALSE}

Tajikistan_Gov <- Governance_Clean %>%
  filter(country %in% c("Tajikistan")) %>%
  filter(year >= 2002)


Gov_Tajikistan <-ggplot(Tajikistan_Gov, aes(x = year, y = score, group = index)) +
  geom_line(aes(linetype= "dash", color = index)) +
  geom_point(aes(color = index)) +
  labs(
    color = "Index",
    title = "Governance in Tajikistan",
    x = "Year",
    y = "Index Score",
    caption = "Source: World Bank and Freedom House"
  ) +
  expand_limits(y = 100, x = "2020") +
  scale_x_discrete(breaks = c(2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018, 2020)) +
  scale_y_continuous(breaks = c(0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
  guides(linetype = FALSE) +
  scale_color_hue(labels = c("Government Effectiveness", "Rule of Law", "Freedom House Index")) +
  theme_economist_white() +
  theme(axis.title.y = element_text(vjust = 4), axis.title.x = element_text(vjust = -4), plot.title = element_text(hjust = .45))
```


```{r GDP Tajikistan}

Tajikistan_GDP <- GDP %>%
  filter(country %in% c("Tajikistan")) 

GDP_Tajikistan <- ggplot(Tajikistan_GDP, aes(x = year, y = gdp, color = "red")) +
  geom_point() +
  geom_line() +
  labs(
    title = "Tajikistan's Economic Climate",
    x = "Year",
    y = "GDP in USD",
    caption = "Source: World Bank"
  ) +
  scale_x_continuous(breaks = c(1996, 1998, 2000, 2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018)) +
  guides(linetype = FALSE, color = FALSE) +
  theme_economist_white() +
  theme(axis.title.y = element_text(vjust = 4), axis.title.x = element_text(vjust = -4), plot.title = element_text(hjust = .45))
```


```{r Governance Uzbekistan, warning=FALSE}

Uzbekistan_Gov <- Governance_Clean %>%
  filter(country %in% c("Uzbekistan")) %>%
  filter(year >= 2002)


Gov_Uzbekistan <- ggplot(Uzbekistan_Gov, aes(x = year, y = score, group = index)) +
  geom_line(aes(linetype= "dash", color = index)) +
  geom_point(aes(color = index)) +
  labs(
    color = "Index",
    title = "Governance in Uzbekistan and Freedom House",
    x = "Year",
    y = "Index Score",
    caption = "Source: World Bank"
  ) +
  expand_limits(y = 100, x = "2020") +
  scale_x_discrete(breaks = c(2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018, 2020)) +
  scale_y_continuous(breaks = c(0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
  guides(linetype = FALSE) +
  scale_color_hue(labels = c("Government Effectiveness", "Rule of Law", "Freedom House Index"))+
  theme_economist_white() +
  theme(axis.title.y = element_text(vjust = 4), axis.title.x = element_text(vjust = -4), plot.title = element_text(hjust = .45))
```


```{r GDP Uzbekistan}

Uzbekistan_GDP <- GDP %>%
  filter(country %in% c("Uzbekistan")) 

GDP_Uzbekistan <- ggplot(Uzbekistan_GDP, aes(x = year, y = gdp, color = "red")) +
  geom_point() +
  geom_line() +
  labs(
    title = "Uzbekistan's Economic Climate",
    x = "Year",
    y = "GDP in USD",
    caption = "Source: World Bank"
  ) +
  scale_x_continuous(breaks = c(1996, 1998, 2000, 2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018)) +
  guides(linetype = FALSE, color = FALSE) +
  theme_economist_white() +
  theme(axis.title.y = element_text(vjust = 4), axis.title.x = element_text(vjust = -4), plot.title = element_text(hjust = .45, vjust = 3))
```


```{r Governance Ecuador, warning=FALSE}

Ecuador_Gov <- Governance_Clean %>%
  filter(country %in% c("Ecuador")) %>%
  filter(year >= 2002)


Gov_Ecuador <- ggplot(Ecuador_Gov, aes(x = year, y = score, group = index)) +
  geom_line(aes(linetype= "dash", color = index)) +
  geom_point(aes(color = index)) +
  labs(
    color = "Index",
    title = "Governance in Ecuador",
    x = "Year",
    y = "Index Score",
    caption = "Source: World Bank and Freedom House"
  ) +
  expand_limits(y = 100, x = "2020") +
  scale_x_discrete(breaks = c(2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018, 2020)) +
  scale_y_continuous(breaks = c(0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
  guides(linetype = FALSE) +
  scale_color_hue(labels = c("Government Effectiveness", "Rule of Law", "Freedom House Index"))+
  theme_economist_white() +
  theme(axis.title.y = element_text(vjust = 4), axis.title.x = element_text(vjust = -4), plot.title = element_text(hjust = .45))
```


```{r GDP Ecuador}

Ecuador_GDP <- GDP %>%
  filter(country %in% c("Ecuador")) 

GDP_Ecuador <- ggplot(Ecuador_GDP, aes(x = year, y = gdp, color = "red")) +
  geom_point() +
  geom_line() +
  labs(
    title = "Ecuador's Economic Climate",
    x = "Year",
    y = "GDP in USD",
    caption = "Source: World Bank"
  ) +
  scale_x_continuous(breaks = c(1996, 1998, 2000, 2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018)) +
  guides(linetype = FALSE, color = FALSE) +
  theme_economist_white() +
  theme(axis.title.y = element_text(vjust = 4), axis.title.x = element_text(vjust = -4), plot.title = element_text(hjust = .45, vjust = 3))
```