You can use aes_string: f <- function( column ) { … ggplot( rates.by.groups, aes_string(x=”name”, y=”rate”, colour= column, group=column ) ) } as long as you pass the column to the function as a string (f(“majr”) rather than f(majr)). Also note that we changed the other columns, “name” and “rate”, to be strings. If for whatever … Read more
Any ggplots side-by-side (or n plots on a grid) The function grid.arrange() in the gridExtra package will combine multiple plots; this is how you put two side by side. require(gridExtra) plot1 <- qplot(1) plot2 <- qplot(1) grid.arrange(plot1, plot2, ncol=2) This is useful when the two plots are not based on the same data, for example … Read more
From ggplot 2.2.0 labels can easily be stacked by using position = position_stack(vjust = 0.5) in geom_text. ggplot(Data, aes(x = Year, y = Frequency, fill = Category, label = Frequency)) + geom_bar(stat = “identity”) + geom_text(size = 3, position = position_stack(vjust = 0.5)) Also note that “position_stack() and position_fill() now stack values in the reverse … Read more
tl;dr Never use [ or $ inside aes(). Consider this illustrative example where the facetting variable f is purposely in a non-obvious order with respect to x d <- data.frame(x=1:10, f=rev(letters[gl(2,5)])) Now contrast what happens with these two plots, p1 <- ggplot(d) + facet_grid(.~f, labeller = label_both) + geom_text(aes(x, y=0, label=x, colour=f)) + ggtitle(“good mapping”) … Read more
Here is one solution # GET EQUATION AND R-SQUARED AS STRING # SOURCE: https://groups.google.com/forum/#!topic/ggplot2/1TgH-kG5XMA lm_eqn <- function(df){ m <- lm(y ~ x, df); eq <- substitute(italic(y) == a + b %.% italic(x)*”,”~~italic(r)^2~”=”~r2, list(a = format(unname(coef(m)[1]), digits = 2), b = format(unname(coef(m)[2]), digits = 2), r2 = format(summary(m)$r.squared, digits = 3))) as.character(as.expression(eq)); } p1 <- p … Read more
The best way for me was using vector with categories in order I need as limits parameter to scale_x_discrete. I think it is pretty simple and straightforward solution. ggplot(mtcars, aes(factor(cyl))) + geom_bar() + scale_x_discrete(limits=c(8,4,6))
Since @Etienne asked how to do this without melting the data (which in general is the preferred method, but I recognize there may be some cases where that is not possible), I present the following alternative. Start with a subset of the original data: datos <- structure(list(fecha = structure(c(1317452400, 1317538800, 1317625200, 1317711600, 1317798000, 1317884400, 1317970800, … Read more
For a small number of variables, you can build the plot manually yourself: ggplot(test_data, aes(date)) + geom_line(aes(y = var0, colour = “var0”)) + geom_line(aes(y = var1, colour = “var1”))
There are common use-cases dual y axes, e.g., the climatograph showing monthly temperature and precipitation. Here is a simple solution, generalized from Megatron’s solution by allowing you to set the lower limit of the variables to something else than zero: Example data: climate <- tibble( Month = 1:12, Temp = c(-4,-4,0,5,11,15,16,15,11,6,1,-3), Precip = c(49,36,47,41,53,65,81,89,90,84,73,55) ) … Read more
@GavinSimpson: reorder is a powerful and effective solution for this: ggplot(theTable, aes(x=reorder(Position,Position, function(x)-length(x)))) + geom_bar()