plastic_charts.R

library(tidyverse)

plastics <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-01-26/plastics.csv')

bar_chart <- 
  plastics %>%
  group_by(parent_company) %>%
  summarize(total = sum(grand_total, na.rm = TRUE)) %>%
  arrange(desc(total)) %>%
  slice(4:14) %>%
  mutate(parent_company = ifelse(parent_company == "NULL", "Unknown", parent_company)) %>%
  ggplot() +
    geom_col(aes(x = total, y = reorder(parent_company, total)), fill = "orchid4") +
    theme_light() +
    labs(title = "Top brands") +
    theme(axis.title = element_blank(), panel.border = element_blank(),
          panel.grid.minor.x = element_blank(),
          panel.grid.major.y = element_blank(),
          plot.title.position = "plot")

pie_chart <- 
  plastics %>%
  group_by(year) %>%
  summarize(total = sum(grand_total, na.rm = TRUE)) %>%
  ggplot() +
  geom_bar(aes(x = "", y = total, fill = as.character(year)), stat = "identity", width = 1) +
  coord_polar("y", start = 0) +
  theme_minimal() +
  labs(title = "Plastic pollution by year", fill = "") +
  theme(axis.title = element_blank(), panel.grid = element_blank(),
        axis.text = element_blank())

bar_chart_2 <- 
  plastics %>%
  select(hdpe:pvc) %>%
  pivot_longer(cols = 1:7) %>%
  group_by(name) %>%
  summarize(total = sum(value, na.rm = TRUE)) %>%
  ggplot() +
  geom_col(aes(x = total, y = reorder(name, total)), fill = "goldenrod") +
  theme_light() +
  labs(title = "By plastic type") +
  theme(axis.title = element_blank(), panel.border = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.y = element_blank(), 
        plot.title.position = "plot")