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copied!<p>This is what I do. A darker colour indicates a more important combination of A and B.</p> <pre><code>dataset <- data.frame(A = sample(LETTERS[1:5], 200, prob = runif(5), replace = TRUE), B = sample(LETTERS[1:5], 200, prob = runif(5), replace = TRUE)) Counts <- as.data.frame(with(dataset, table(A, B))) library(ggplot2) ggplot(Counts, aes(x = A, y = B, fill = Freq)) + geom_tile() + scale_fill_gradient(low = "white", high = "black") </code></pre> <p>Or if you prefer lines</p> <pre><code>library(ggplot2) dataset <- data.frame(A = sample(letters[1:5], 200, prob = runif(5), replace = TRUE), B = sample(letters[1:5], 200, prob = runif(5), replace = TRUE)) Counts <- as.data.frame(with(dataset, table(A, B))) Counts$X <- 0 Counts$Xend <- 1 Counts$Y <- as.numeric(Counts$A) Counts$Yend <- as.numeric(Counts$B) ggplot(Counts, aes(x = X, xend = Xend, y = Y, yend = Yend, size = Freq)) + geom_segment() + scale_x_continuous(breaks = 0:1, labels = c("A", "B")) + scale_y_continuous(breaks = 1:5, labels = letters[1:5]) </code></pre> <p>This third options add labels to the data points using geom_text().</p> <pre><code>library(ggplot2) dataset <- data.frame( A = sample(letters[1:5], 200, prob = runif(5), replace = TRUE), B = sample(LETTERS[20:26], 200, prob = runif(7), replace = TRUE) ) Counts <- as.data.frame(with(dataset, table(A, B))) Counts$X <- 0 Counts$Xend <- 1 Counts$Y <- as.numeric(Counts$A) Counts$Yend <- as.numeric(Counts$B) ggplot(Counts, aes(x = X, xend = Xend, y = Y, yend = Yend)) + geom_segment(aes(size = Freq)) + scale_x_continuous(breaks = 0:1, labels = c("A", "B")) + scale_y_continuous(breaks = -1) + geom_text(aes(x = X, y = Y, label = A), colour = "red", size = 7, hjust = 1, vjust = 1) + geom_text(aes(x = Xend, y = Yend, label = B), colour = "red", size = 7, hjust = 0, vjust = 0) </code></pre>

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