Using the following data:
> str(attribute)
'data.frame': 431 obs. of 2 variables:
$ pos: int 1 2 3 4 5 6 7 8 9 10 ...
$ att: num 0.652 0.733 0.815 1.079 0.885 ... *[between 0 and 3]
and:
ggplot(attribute, aes(x=pos, y=att)) + geom_line() + geom_smooth()
I did:
I would like to progressively smooth the black curve, not "as much as" geom_smooth default did. I've tried n
, level
options, but didn't do what I want. Which would be the best way to increase smoothing progressively? (e.g. average 2 values in one, then try 3 in one, and so on). I guess it's something really easy or achievable without using geom_smooth
, but I don't know what to search/look for. Thanks.
stat_smooth() and geom_smooth() both are aliases. Both of them have the same arguments and both of them are used to plot a smooth line. We can plot a smooth line using the “loess” method of stat_smooth() function.
geom_smooth() and stat_smooth() are effectively aliases: they both use the same arguments. Use stat_smooth() if you want to display the results with a non-standard geom.
Geom_line creates a single line for both panels and distributes the colors according to the colour variable, while geom_smooth does not draw the smooth line in the 2nd panel.
By default, geom_smooth will inherit the dataset that you specify with the top-line call to ggplot() .
This is documented in stat_smooth
. The default smoother is loess
, and additional arguments are passed on to it, as specified for the description of the ...
argument. So what you want is span
:
ggplot(mtcars,aes(x = wt,y = mpg)) +
geom_point() +
geom_smooth(span = 0.4)
Additionally, loess
accepts a degree
argument for more control over the amount of smoothing.
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