---
title: "Short Introduction to gganimate"
author: "Arno Kimeswenger"
output:
  html_document:
    code_folding: none # no hide/show button in html document
    number_sections: true
    css: "styles.css"
editor_options: 
  markdown: 
    wrap: 72
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(
  warning = TRUE,
  message = TRUE,
  error = TRUE
)
options(warn = 1)
```


# Libraries:

```{r}
library(tidyverse)
library(viridis)
library(plotly)
library(gganimate)
```


# Data:

```{r}
gapminder.coltypes <- cols(
  country = col_factor(),
  continent = col_factor(levels = c("Africa", "Americas", "Asia", "Europe", "Oceania")),
  year = col_integer(),
  lifeExp = col_double(),
  pop = col_integer(),
  gdpPercap = col_double()
)

gapminder <- read_csv("gapminder.csv", col_types = gapminder.coltypes)

gapminder |> head()
```

These are the values used for year:

```{r}
gapminder |>
  distinct(year) |>
  arrange(year) |>
  pull(year)
```

These are the values used for continent:

```{r}
gapminder |>
  pull(continent) |>
  levels()
```


# 2d Plots

2d plot ignoring year:  
This is a little weird, because each country appears several times.

```{r, fig.height=8}
gapminder |>
  ggplot() +
  geom_point(aes(x = gdpPercap, y = lifeExp, fill = continent, size = pop), shape = 21, alpha = 0.8, color = "black") + # shapes 21 - 25 support fill and color
  scale_fill_manual(
    "Continent",
    values = viridis(7)[c(1, 3, 4, 6, 7)],
    guide = guide_legend(override.aes = list(shape = 21, alpha = 1, size = 5, color = "black")) # ensures the legend key shows the fill color, only some shapes support this
  ) +
  scale_size_continuous(
    "Population",
    breaks = c(5e7, 1e8, 5e8, 1e9, 2e9),
    # labels = scales::comma,
    labels = scales::label_number(scale = 1e-6, suffix = "M"),
    range = c(0.1, 15)
  ) +
  labs(x = "GDP per Capita", y = "Life Expectancy") +
  theme(
    legend.text.align = 1
  )
```

2d plot for one year:  
Better, but now we plot year 2007 only.

```{r, fig.height=8}
gapminder |>
  filter(year == 2007) |>
  ggplot() +
  geom_point(aes(x = gdpPercap, y = lifeExp, fill = continent, size = pop), shape = 21, alpha = 0.8, color = "black") + # shapes 21 - 25 support fill and color
  scale_fill_manual(
    "Continent",
    values = viridis(7)[c(1, 3, 4, 6, 7)],
    guide = guide_legend(override.aes = list(shape = 21, alpha = 1, size = 5, color = "black")) # ensures the legend key shows the fill color, only some shapes support this
  ) +
  scale_size_continuous(
    "Population",
    breaks = c(5e7, 1e8, 5e8, 1e9, 2e9),
    # labels = scales::comma,
    labels = scales::label_number(scale = 1e-6, suffix = "M"),
    range = c(0.1, 15)
  ) +
  labs(x = "GDP per Capita", y = "Life Expectancy") +
  theme(
    legend.text.align = 1
  )
```


2d plot:  
We can use shape to distinguish more than one year, but it gets a bit crowded.

```{r, fig.height=8}
gapminder |>
  filter(year %in% c(1997, 2002, 2007)) |>
  ggplot() +
  geom_point(aes(x = gdpPercap, y = lifeExp, fill = continent, shape = factor(year), size = pop), alpha = 0.8, color = "black") + # need factor(year) and not year
  scale_shape_manual(
    "Year",
    values = c(21, 22, 23), # shapes 21–25 support both fill and border color
    guide = guide_legend(override.aes = list(size = 5))
  ) +
  scale_fill_manual(
    "Continent",
    values = viridis(7)[c(1, 3, 4, 6, 7)],
    guide = guide_legend(override.aes = list(shape = 21, alpha = 1, size = 5, color = "black")) # ensures the legend key shows the fill color, only some shapes support this
  ) +
  scale_size_continuous(
    "Population",
    breaks = c(5e7, 1e8, 5e8, 1e9, 2e9),
    # labels = scales::comma,
    labels = scales::label_number(scale = 1e-6, suffix = "M"),
    range = c(0.1, 15)
  ) +
  labs(x = "GDP per Capita", y = "Life Expectancy") +
  theme(
    legend.text.align = 1
  )
```

Can you find India, China, and the USA in the plot above?

Maybe it is okay to look at fewer countries and plot all years using fill

```{r, fig.height=8}
gapminder |>
  filter(country %in% c("China", "India", "United States", "Germany", "Austria")) |>
  ggplot() +
  geom_point(aes(x = gdpPercap, y = lifeExp, fill = year, shape = country, size = pop), alpha = 0.8, color = "black") + # use year and not factor(year) here
  scale_shape_manual(
    "Country",
    values = c(21, 22, 23, 24, 25), # shapes 21 - 25 support fill and color
    guide = guide_legend(override.aes = list(size = 5))
  ) +
  scale_fill_viridis_c("Year") +
  scale_size_continuous(
    "Population",
    breaks = c(5e7, 1e8, 5e8, 1e9, 2e9),
    # labels = scales::comma,
    labels = scales::label_number(scale = 1e-6, suffix = "M"),
    range = c(0.1, 15)
  ) +
  labs(x = "GDP per Capita", y = "Life Expectancy") +
  theme(
    legend.text.align = 1
  )
```


# 3d Plot

In rare cases, it makes sense to build 3d plots.

```{r, fig.height = 8}
plot_ly() |>
  add_markers(data = gapminder, x = ~gdpPercap, y = ~year, z = ~lifeExp)
```


# Animation

A better alternative is to use time directly and create an animation:

```{r}
p <- ggplot(gapminder) +
  geom_point(aes(x = gdpPercap, y = lifeExp, fill = continent, size = pop), shape = 21, alpha = 0.8, color = "black") + # shapes 21 - 25 support fill and color
  scale_fill_manual(
    "Continent",
    values = viridis(7)[c(1, 3, 4, 6, 7)],
    guide = guide_legend(override.aes = list(shape = 21, alpha = 1, size = 5, color = "black")) # ensures the legend key shows the fill color, only some shapes support this
  ) +
  scale_size_continuous(
    "Population",
    breaks = c(5e7, 1e8, 5e8, 1e9, 2e9),
    # labels = scales::comma,
    labels = scales::label_number(scale = 1e-6, suffix = "M"),
    range = c(0.1, 15)
  ) +
  labs(x = "GDP per Capita", y = "Life Expectancy") +
  theme(
    legend.text.align = 1
  ) +
  transition_time(year) +
  ease_aes("linear")

n <- gapminder |>
  distinct(year) |>
  pull(year) |>
  length()

animate(p, nframes = n, fps = 1) # we only plot our 12 time steps. Increasing means interpolating, one frame per second
```

Which country is on the top right?

```{r}
gapminder |>
  filter(gdpPercap > 70000)
```