# Load .csv file and rename columns
kickstart_projects <- read.csv("A2_kickstart - Sheet1.csv", stringsAsFactors = FALSE)
names(kickstart_projects) <- c("Projects", "Launched", "Successful", "Money.pledged", "Pledges", "Success.rate", "Average.pledge")
# Sort by success rate and remove rows with NA values
project_success_rate <- kickstart_projects %>%
  mutate(Projects = reorder(Projects, Success.rate)) %>% drop_na()
# Create a new variable Money.pledged for % money pledged for project to total money pledged
project_success_rate$pledge.percent <- (((project_success_rate$Money.pledged) / sum(project_success_rate$Money.pledged)) * 100)
project_success_rate$pledge.percent <- round(project_success_rate$pledge.percent, 1)

Crowdfunded projects on kickstarter in 2012 Visualization

# Horizontal bar chart descending order w/ money pledged %
kickstart_visualization <- ggplot(project_success_rate, aes(x = Projects, y = Success.rate)) +
  geom_bar(stat = "identity", width = 0.5, fill = "#999999") +
  geom_point(data = project_success_rate, aes(x = Projects, 
    y = pledge.percent, color = pledge.percent), size = 2) +
    scale_color_gradient(low = "#FFCC00",
    high = "#CC0000") + ylab("Success Rate (%)") +
  labs(title = "Crowdfunded projects on Kickstarter in 2012",
       subtitle = "Project success rate vs. Money pledged",
       caption = "*Money pledged % = Money pledged per project as % of total",
       color = "% Money pledged") +
  theme_classic() +
  theme(axis.title.y = element_blank(),
        axis.text.y = element_text(vjust = 0.3, size = 10),
        plot.title = element_text(size = 12, face = "bold"),
        plot.subtitle = element_text(size = 9, hjust = 0.1),
        plot.caption = element_text(size = 6, vjust = 1),
        legend.position = c(0.8, 0.4),
        legend.title = element_text(size = 8),
        legend.text = element_text(size = 8)) +
  coord_flip()
kickstart_visualization