day24_monochrome.Rmd

---
title: 'Day 24: time series - Monochrome'
author: "Christophe Nicault"
date: "26/04/2021"
output: html_document
---

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

```{r load_packages}

library(tidyverse)
#devtools::install_github("davidsjoberg/ggsankey", ref = "main", force= TRUE)
library(ggsankey)
library(ggimage)
library(ggtext)
library(showtext)

font_add_google("Roboto Condensed", "roboto condensed")
font_add_google("Oswald", "oswald")
font_add_google("Share Tech Mono", "techmono")

showtext_opts(dpi = 320)
showtext_auto(enable = TRUE)

```

Link to the data :
https://ourworldindata.org/co2/country/united-states?country=~USA


```{r load_data}
co2 <- read_csv(here::here("input", "CO2-by-source.csv"))
chimney <- here::here("day24", "img", "chimney_fullgrey.png")
earth <- here::here("day24", "img", "earth_transparent.png")

```

```{r data_prep}

country_stat <-  co2 %>%
  filter(Year == 2019) %>%
  filter(!is.na(Code), Entity != "World") %>%
  pivot_longer(cols = c(4:9)) %>%
  group_by(Entity, Code) %>%
  summarise(total = sum(value, na.rm = TRUE)) %>%
  ungroup() %>%
  arrange(desc(total)) %>%
  mutate(world_total = sum(total),
         percent = total / world_total,
         cumperc = cumsum(percent)) 

country_text <-country_stat %>%
  head(5) %>%
  arrange(total) %>%
  mutate(high = cumsum(total),
         prev = lag(high, default = 0),
         posy = prev + (high-prev)/2,
         size = total)  %>%
  mutate(Entity = ifelse(Code == "USA", "USA", Entity))

country_text <- country_text %>%
  bind_cols(fsize = c(4, 5, 6, 20, 50))


top5 <- country_stat %>%
  head(5) %>%
  arrange(total) %>%
  pull(Code)

pal <- c("#D9D9D9", "#A6A6A6", "#737373", "#404040", "#0D0D0D")
color_pal <- c()
color_pal[top5] <- pal

legend <- country_stat %>%
  mutate(label = glue::glue("{Entity}: {round(total / 1e9, 1)} Bt / {scales::percent(round(percent,4), accuracy = 0.01)} of world emission")) %>%
  head(5) %>%
  arrange(total) %>%
  mutate(posy = 8e9 + row_number() * 1e9) %>%
  select(Entity, posy, label)

co2_prep <- co2 %>%
  filter(Code %in% top5) %>%
  filter(Year > 1938) %>%
  pivot_longer(cols = c(4:9)) %>%
  group_by(Year, Entity, Code) %>%
  summarise(total = sum(value, na.rm = TRUE)) %>%
  ungroup()

init <- co2_prep %>% 
  filter(Year == 2019) %>%
  mutate(Year = 1930,
         total = 0)

co2_prep <- init %>%
  bind_rows(co2_prep)

years <- tibble(year = seq(1940,2020, 20))

```

```{r final_plot}

final <- co2_prep %>%
  ggplot() +
  geom_image(aes(x = 1932, y = -0.5e9, image = chimney), size = 0.1, asp = 2)+
  geom_sankey_bump(aes(x = Year, value = total, fill = Code, node = Entity), space = 1e8, type = "alluvial", color = "transparent", smooth = 6) +
  geom_text(data = country_text, aes(x = 2020, y = posy, label = Entity, size = fsize, color = Code), hjust = 0, lineheight = 0.6, family = "oswald") +
  geom_text(data = years, aes(x = year, y = -5e8, label = year), family = "roboto condensed", size = 3, color = "#404040") +
  geom_text(data = legend, aes(x = 1920, y = posy, label = label), family = "roboto condensed", size = 4, color = "#404040", hjust = 0) +
  geom_image(aes(x = 1929, y = -6e9, image = earth), size = 0.12, asp = 2) +
  annotate("richtext", x = 1920, y = 20e9, label = "Ranking of the top 5 CO<sub>2</sub> emitters from burning fuels.",family = "oswald", size = 7, fontface = "bold", label.color = NA, hjust = 0) +
  annotate("richtext", x = 1920, y = 17e9, label = "The 5 top emitters account for 59.3% of the world CO<sub>2</sub> emission.<br> Burning fuels include fossils (coal, oil, gas, flaring) and industry materials such as cement.", family = "oswald", size = 5, lineheight = 1.5, hjust = 0, label.color = NA) +  
  scale_x_continuous(limits = c(1919, 2060)) +
  scale_y_continuous(limits = c(-9e9, 22e9)) +
  scale_fill_manual(values = color_pal) +
  scale_color_manual(values = color_pal) +
  scale_size(range = c(4, 50), breaks = c(4, 5, 6, 20, 50), trans = "identity")+
  labs(
       caption = "#30DayChartChallenge Day 24 | Viz: Christophe Nicault | Data: Our World in Data") +
  guides(color = FALSE, fill = FALSE, size = FALSE) +
  theme_void() +
  theme(plot.caption = element_text(family = "techmono", color = "#404040",size = 11, hjust = 0.98))

ragg::agg_png(here::here("render", paste0("30DayChartChallenge_day24_", format(Sys.time(), "%Y%m%d_%H%M%S"), ".png")), res = 320, width = 16, height = 8, units = "in")

final
  
dev.off()

```