Beer_states.Rmd

---
title: "Untitled"
author: "Tu"
date: "6/22/2020"
output: html_document
---

```{r include=FALSE}
library(tidyverse)
library(geofacet)
library(ggtext)
library(showtext)
library(ggchicklet)

font_add_google("Indie Flower", "Indie Flower")
theme_set(theme_void(base_family = "Indie Flower", base_size = 15))
showtext_auto()
```
```{r}
beer_plot <- beer %>%
  mutate(
    people_drink = consume_per_capita * adults_pop,
    deficiency = if_else((people_drink - production_sum) > 0, people_drink - production_sum, 0)
  ) %>%
  pivot_longer(
    cols = c(deficiency, production_sum),
    names_to = "type",
    values_to = "amount"
  ) %>%
  mutate(
    uniform_col = "THIS",
    type = factor(type, levels = c("deficiency", "production_sum"))
  )
```

```{r}
set.seed(222)
beer_dot <- beer %>%
  mutate(
    people_drink = consume_per_capita * adults_pop,
    deficiency = people_drink - production_sum
  ) %>%
  group_by(state) %>%
  slice(rep(1, each = floor(consume_per_capita))) %>%
  transmute(
    state = factor(state),
    uniform_col = "THIS",
    dots_brewer = runif(floor(consume_per_capita),
      min = if_else(production_sum > people_drink, people_drink * 0.1, production_sum * 0.1),
      max = if_else(production_sum < people_drink, people_drink * 0.9, production_sum * 0.9)
    ),
    dot_size = runif(floor(consume_per_capita), 0, 1)
  ) %>%
  ungroup()
```

## America
```{r}
US <- beer %>%
  transmute(
    US_prodution = sum(production_sum),
    overflow = sum(production_sum) - sum(consume_per_capita * adults_pop)
  ) %>%
  pivot_longer(
    cols = c(overflow, US_prodution),
    names_to = "type",
    values_to = "amount"
  ) %>%
  mutate(
    uniform_col = "THIS",
    type = factor(type, levels = c("overflow", "US_prodution"))
  ) %>%
  distinct()

US_dot <- US %>%
  slice(rep(1, each = 12)) %>%
  mutate(
    dots_brewer = runif(12,
      min = 2330310745 * 0.1,
      max = 5173564192 * 0.9
    ),
    dot_size = runif(12, 0, 1)
  )
```

```{r fig.height=3, fig.width=3}
# US_p <-
US %>%
  ggplot() +
  geom_chicklet(aes(x = uniform_col, y = amount, fill = fct_rev(type))) +
  scale_fill_manual(values = c("#F2CF77", "#c96e12")) +
  geom_jitter(
    data = US_dot,
    aes(uniform_col, dots_brewer, size = dot_size),
    position = position_jitter(width = 0.5, height = 0.22, seed = 3),
    shape = 21,
    color = colorspace::darken("#f9e556", .45),
    stroke = .3,
    # colorspace::darken("#f9e556", .45)
    alpha = 0.5
  ) +
  theme(legend.position = "none")
```



## geom_col
```{r fig.height=13.5, fig.width=22}
#p <-
  beer_plot %>%
  full_join(us_state_grid2, by = c("state" = "code")) %>%
  ggplot(aes(1000, 1000)) +
  geom_chicklet(aes(x = uniform_col, y = amount, fill = fct_rev(type))) +
  scale_fill_manual(values = c("#F2CF77", "white")) +
  # f4d380/F2CF77
  # bubbles
  geom_jitter(
    data = beer_dot,
    aes(uniform_col, dots_brewer, size = dot_size),
    position = position_jitter(width = 0.5, height = 0.3, seed = 2),
    shape = 21,
    color = colorspace::darken("#f9e556", .45),
    stroke = .3,
    # colorspace::darken("#f9e556", .45)
    alpha = 0.6
  ) +
  geom_text(
    data = beer_plot,
    mapping = aes(x = 0.6, y = -Inf, label = state),
    family = "Indie Flower",
    hjust = 0.01,
    vjust = -1,
    colour = "#1C1259",
    fontface = "bold",
    size = 8
  ) +
  facet_geo(vars(state), grid = "us_state_grid2", scales = "free_y") +
  labs(
    title = "How much <span style='color:white'>beer would be needed</span> if legal drinkers in each state <br>were only allowed to drink <span style='color:#F2CF77'>local beer</span> in 2018?",
    subtitle = "Only 1/3 states' <span style='color:#F2CF77'>total beer production</span> in 2018 can fulfill the local beer crave, but US in total produces more than 30% more <br> beer than US adult citizens drink in 2018.<br><span font-size:15em> Yellow bar is the <span style='color:#F2CF77'>total beer production</span>in that state, and the white bar is the <span style='color:white'>beer in demand</span>.<br>Number of bubbles represents the number of gallons consumed per person in each states. </span>",
    caption = "Source:Datafrom the Alcohol and Tobacco Tax and Trade Bureau (TTB) and National Institute on Alcohol Abuse and Alcoholism (NIAA)"
    # https://pubs.niaaa.nih.gov/publications/surveillance115/pcyr1970-2018.txt"
  ) +
  theme(
    plot.background = element_rect(fill = "#48a4d6"),
    # 1C1259
    legend.position = "none",

  
    plot.title = element_markdown(
      face = "bold",
      size = rel(2.8),
      color = "#1C1259",
      hjust = 0.02,
      margin = margin(t = 6, b = 7)
    ),
    plot.subtitle = element_markdown(
      size = rel(1.6),
      color = "#1C1259",
      # hjust = 0.06,
      margin = margin(t = 5, b = 3)
    ),
    plot.caption = element_text(
      face = "italic",
      # size = rel(1.1),
      color = "#1C1259",
      hjust = 0.47
    ),
    strip.text = element_blank()
  ) +
  coord_cartesian(clip = "off")
```
## geom_rect
```{r fig.height=12, fig.width=18}
beer %>%
  # mutate(state = factor(state)) %>%
  full_join(us_state_grid2, by = c("state" = "code")) %>%
  ggplot() +
  geom_rect(aes(xmin = state, xmax = production_sum / 10e7, ymin = 0, ymax = people_drink), fill = "#EBE1CE") +
  geom_rect(aes(xmin = state, xmax = production_sum / 10e7, ymin = 0, ymax = production_sum), fill = "#f9e556") +

  # bubbles
  geom_jitter(
    data = beer_dot,
    aes(state, dots_brewer, size = dot_size),
    position = position_jitter(width = 0.7),
    shape = 21,
    color = colorspace::darken("#f9e556", .17),
    stroke = .3,
  ) +
  facet_geo(vars(state), grid = "us_state_grid2", label = "code", scales = "free_y") +
  theme_void() +
  theme(
    plot.background = element_rect(fill = "#1C1259"),
    strip.text = element_text(hjust = 0.3, vjust = 0.8),
    legend.position = "none",
    plot.caption = element_text(face = "italic")
  ) +
  labs(
    subtitle = "North Dakota and South Dakota need the least number of people to consume their local beer.",
    caption = "Source: 
    Data is downloaded from NIAA   https://pubs.niaaa.nih.gov/publications/surveillance115/pcyr1970-2018.txt"
  )
```


```{r}
ggsave("p.pdf", p,
  width = 22, height = 13.5, units = "in", device = cairo_pdf
)
```