The code is the same as the last one I showed, except I used geom_violin()
instead.
pp <- ggplot(dat1, aes(x = condition, y = t, color = gender, linetype =
direction)) +
geom_violin() +
facet_wrap(~ location) +
scale_color_manual(values = c("blue", "darkorange"))+
theme_bw()+
scale_y_con
Again, I come to think about violin plots which is more informative than
the error bars. But for some reason, the violin in the *west* became way
too slimmer than the *east* one, though the density plot tells me that is
not necessarily the case. I am still trying to figure that out, and that
would
Thanks so much, John and Dennis (who did not respond in the mailing list
for some reason). I feel quite obliged to keep you thinking about this.
I do agree that not using the bar chart with error bars is a better option.
And since *condition* is an important ordinal factor for me, it would be
much
I think maybe it is possible to first produce a blank axis, and then
splitting the data frame by the value of *direction. *Then add the goem_bar
and goem_errorbar for the blank axis for the first split, then add them for
the second half split. This is actually a slit-apply-combine strategy. It
woul
I did not know the SVG file did not come through. I thought SVG should be
able to pass through the filter. Here is a PDF file along with an PNG.
Guess one of them should be able to pass.
祝好，
He who is worthy to receive his days and nights is worthy to receive* all
else* fr
You are most likely simply not running the whole lines of code: note that
the first line is:
N = 32
Best
，
He who is worthy to receive his days and nights is worthy to receive* all
else* from you (and me).
The Prophet, Gibr
Hi all,
I have four factors for a continuous time variable along with its
confidence interval. I would like to produce a publication quality error
bar chart that is clear to understand. For now, I used colors, x axis
position, facets and alpha level to distinguish them.
I would like to overlap ea
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