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17270053
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2013-06-24T07:24:57.007
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2013-06-25T06:48:33.747
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2013-06-25T06:48:33.747
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To create a data.frame, you can do it crudely like this: <pre><code>df <- data.frame(values=unlist(FHM_CS, use.names=FALSE), tag=rep(names(FHM_CS), times=sapply(FHM_CS, length)) </code></pre> But for usage with <code>ggplot2</code>, we should merge everything into a single dataframe: <pre><code>df.CS <- data.frame(values=unlist(FHM_CS, use.names=FALSE), tag=rep(names(FHM_CS), times=sapply(FHM_CS, length)), class='CS', stringsAsFactors=TRUE) df.CD <- data.frame(values=unlist(FHM_CD, use.names=FALSE), tag=rep(names(FHM_CD), times=sapply(FHM_CD, length)), class='CD', stringsAsFactors=TRUE) my.data <- rbind(df.CS, df.CD) </code></pre> Edit Alternatively, as seen what Michele found, use <code>melt</code>: <pre><code>library(reshape2) df.CD <- data.frame(melt(FHM_CD), class='CD') df.CS <- data.frame(melt(FHM_CS), class='CS') ## Except now, instead of `tag`, we have `L1`. my.data <- rbind(df.CD, df.CS) my.data$tag <- my.data$L1 </code></pre> End of edit Then to plot, as you want (I was lazy and didn't enter much data): <pre><code>library(ggplot2) ggplot(my.data, aes(x=interaction(tag, class), y=values)) + geom_point(position=position_jitter()) </code></pre> <img src="https://i.stack.imgur.com/YJC73.png" alt="enter image description here"> But lets try to add the horizontal bars. But, I would use facetting so we will get the following: <pre><code>ggplot(my.data, aes(x=tag, y=values)) + geom_point(position=position_jitter()) + stat_summary(fun.y='mean', geom='errorbarh', aes(xmin=as.integer(tag)-0.3, xmax=as.integer(tag)+0.3), height=0) + facet_grid(.~class) </code></pre> <img src="https://i.stack.imgur.com/WqL2s.png" alt="enter image description here"> Edit 2 First manually create the interaction vector: <pre><code>my.data$it <- with(my.data, interaction(tag, class, sep=' - ', lex.order=TRUE)) </code></pre> Then we plot as previously. <pre><code>ggplot(my.data, aes(x=it, y=values)) + geom_point(position=position_jitter()) + stat_summary(fun.y='mean', geom='errorbarh', aes(xmin=as.integer(it)-0.3, xmax=as.integer(it)+0.3, height=0, colour=class)) </code></pre> <img src="https://i.stack.imgur.com/FYSFX.png" alt="enter image description here"> Of course, you might want to edit the arguments to <code>position_jitter()</code> to squeeze the points more closer.
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1. COok very nice that's what I needed but do you know how to do the same thing but clustered like in excel ? I mean X3 from FHM_CS and X3 from FHM_CD should be right by each other and one should be blue and the other red and same would be for X5 X7 X9 XAS and XPW
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