---
title: "UN Votes"
author: "YOUR NAME HERE"
format: 
  html:
    self-contained: true
    toc: true
    toc_float: true
    number_section: false
    highlight: "tango"
    theme: "cosmo"
    df-print: paged
editor: visual
editor_options: 
  chunk_output_type: console
---

# Introduction

How do various countries vote in the United Nations General Assembly, how have their voting patterns evolved throughout time, and how similarly or differently do they view certain issues? Answering these questions (at a high level) is the focus of this analysis.

## Packages

We will use the **tidyverse**, **lubridate**, and **scales** packages for data wrangling and visualization, and the **unvotes** package for the data.

```{r}
#| label: load-packages
#| warning: false
#| message: false

library(tidyverse)
library(lubridate)
library(scales)
library(unvotes)
```

## Data

The data we're using originally come from the **unvotes** package. In the chunk below we modify the data by joining the various data frames provided in the package to help you get started with the analysis.

```{r}
#| warning: false
#| message: false
unvotes <- un_votes |>
  inner_join(un_roll_calls, by = "rcid") |>
  inner_join(un_roll_call_issues, by = "rcid")
```

# UN voting patterns

Let's create a data visualisation that displays how the voting record of the UK & NI changed over time on a variety of issues, and compares it to two other countries: US and Turkey.

We can easily change which countries are being plotted by changing which countries the code above `filter`s for. Note that the country name should be spelled and capitalized exactly the same way as it appears in the data. See the [Appendix](#appendix) for a list of the countries in the data.

```{r}
#| label: plot-yearly-yes-issue
#| fig.width: 10
#| fig.height: 6
#| message: false
unvotes |>
  filter(country %in% c("United Kingdom", "United States", "China")) |>
  mutate(year = year(date)) |>
  group_by(country, year, issue) |>
  summarize(percent_yes = mean(vote == "yes")) |>
  ggplot(mapping = aes(x = year, y = percent_yes, color = country)) +
  geom_point(alpha = 0.4) +
  geom_smooth(method = "loess", se = FALSE) +
  facet_wrap(~issue) +
  scale_y_continuous(labels = percent) +
  labs(
    title = "Percentage of 'Yes' votes in the UN General Assembly",
    subtitle = "1946 to 2019",
    y = "% Yes",
    x = "Year",
    color = "Country"
  )
```

# Try it out!

1.  Change the author name to your name

2.  Change the countries being plotted

3.  Render to see your changes in the .html

## References

1.  David Robinson (2017). [unvotes](https://CRAN.R-project.org/package=unvotes): United Nations General Assembly Voting Data. R package version 0.2.0.
2.  Erik Voeten "Data and Analyses of Voting in the UN General Assembly" Routledge Handbook of International Organization, edited by Bob Reinalda (published May 27, 2013).
3.  Much of the analysis has been modeled on the examples presented in the [unvotes package vignette](https://cran.r-project.org/web/packages/unvotes/vignettes/unvotes.html).

## Appendix {#appendix}

Below is a list of countries in the dataset:

```{r list-countries, echo=FALSE}
unvotes |> 
  select(country) |>
  arrange(country) |> 
  distinct()
```
