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| library(ggplot2) | |
| library(dplyr) | |
| library(scales) | |
| df_foo = data_frame( | |
| var1 = sample(LETTERS[1:4], size = 100, replace = TRUE), | |
| var2 = sample(letters[1:4], size = 100, replace = TRUE) | |
| ) | |
| # stacked absolute bar chart | |
| df_foo %>% | |
| ggplot(aes(x = var1, group = var2, fill = var2)) + | |
| geom_bar(stat = "count", position = "stack") + | |
| theme_minimal() + | |
| ggtitle("Stacked absolute bar chart") | |
| # save the plot | |
| ggsave("results/stacked bar chart.png") | |
| # spineplot (stacked relative bar chart + width) | |
| ## compute the contingency table | |
| df_foo = df_foo %>% | |
| group_by(var1, var2) %>% | |
| summarise(cell_freq = n()) %>% | |
| mutate( | |
| var1_total = sum(cell_freq), | |
| cell_prop = cell_freq/var1_total | |
| ) | |
| # compute the marginal distribution of var1 | |
| df_foo_var1 = df_foo %>% | |
| ungroup() %>% | |
| distinct(var1, .keep_all = TRUE) %>% | |
| select(var1, var1_total) %>% | |
| mutate( | |
| position = 0.5*(cumsum(var1_total) + cumsum(lag(var1_total, default = 0))) | |
| ) | |
| # put the two datasets together | |
| df_foo = df_foo %>% | |
| inner_join(df_foo_var1) | |
| # plot the data | |
| df_foo %>% | |
| ggplot(aes(x = position, y = cell_prop, fill = var2, width = var1_total)) + | |
| geom_bar(stat = "identity") + | |
| scale_y_continuous(labels = percent) + | |
| scale_x_continuous(labels = df_foo_var1$var1, breaks = df_foo_var1$position) + | |
| theme_minimal() + | |
| ggtitle("Spineplot") | |
| # save the plot | |
| ggsave("results/spineplot.png") |
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